From ac2e8d760e2359ca5d26a8ce7dabf370873b0a6c Mon Sep 17 00:00:00 2001
From: rzrymiak <106121613+rzrymiak@users.noreply.github.com>
Date: Tue, 19 Jul 2022 14:24:44 -0700
Subject: [PATCH 001/132] Added description heading to README.md

---
 README.md | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 881895c9a..828a3d1f9 100644
--- a/README.md
+++ b/README.md
@@ -5,6 +5,8 @@
 [![Documentation](https://readthedocs.org/projects/freqtrade/badge/)](https://www.freqtrade.io)
 [![Maintainability](https://api.codeclimate.com/v1/badges/5737e6d668200b7518ff/maintainability)](https://codeclimate.com/github/freqtrade/freqtrade/maintainability)
 
+## Description
+
 Freqtrade is a free and open source crypto trading bot written in Python. It is designed to support all major exchanges and be controlled via Telegram or webUI. It contains backtesting, plotting and money management tools as well as strategy optimization by machine learning.
 
 ![freqtrade](https://raw.githubusercontent.com/freqtrade/freqtrade/develop/docs/assets/freqtrade-screenshot.png)
@@ -193,7 +195,7 @@ Issues labeled [good first issue](https://github.com/freqtrade/freqtrade/labels/
 
 The clock must be accurate, synchronized to a NTP server very frequently to avoid problems with communication to the exchanges.
 
-### Min hardware required
+### Minimum hardware required
 
 To run this bot we recommend you a cloud instance with a minimum of:
 

From 229e8864bbeb33bbd0b4c3bc525131939e276ad2 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Tue, 26 Jul 2022 20:15:49 +0200
Subject: [PATCH 002/132] Add send_msg capability to dataprovider

---
 freqtrade/data/dataprovider.py    | 21 +++++++++++++++++++++
 freqtrade/enums/rpcmessagetype.py |  2 ++
 freqtrade/freqtradebot.py         |  1 +
 freqtrade/rpc/rpc_manager.py      | 12 ++++++++++++
 freqtrade/rpc/telegram.py         |  3 ++-
 5 files changed, 38 insertions(+), 1 deletion(-)

diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py
index b9b118c00..800254533 100644
--- a/freqtrade/data/dataprovider.py
+++ b/freqtrade/data/dataprovider.py
@@ -5,12 +5,14 @@ including ticker and orderbook data, live and historical candle (OHLCV) data
 Common Interface for bot and strategy to access data.
 """
 import logging
+from collections import deque
 from datetime import datetime, timezone
 from typing import Any, Dict, List, Optional, Tuple
 
 from pandas import DataFrame
 
 from freqtrade.configuration import TimeRange
+from freqtrade.configuration.PeriodicCache import PeriodicCache
 from freqtrade.constants import ListPairsWithTimeframes, PairWithTimeframe
 from freqtrade.data.history import load_pair_history
 from freqtrade.enums import CandleType, RunMode
@@ -33,6 +35,9 @@ class DataProvider:
         self.__cached_pairs: Dict[PairWithTimeframe, Tuple[DataFrame, datetime]] = {}
         self.__slice_index: Optional[int] = None
         self.__cached_pairs_backtesting: Dict[PairWithTimeframe, DataFrame] = {}
+        self._msg_queue: deque = deque()
+        self.__msg_cache = PeriodicCache(
+            maxsize=1000, ttl=timeframe_to_seconds(self._config['timeframe']))
 
     def _set_dataframe_max_index(self, limit_index: int):
         """
@@ -265,3 +270,19 @@ class DataProvider:
         if self._exchange is None:
             raise OperationalException(NO_EXCHANGE_EXCEPTION)
         return self._exchange.fetch_l2_order_book(pair, maximum)
+
+    def send_msg(self, message: str, always_send: bool = False) -> None:
+        """
+        TODO: Document me
+        :param message: Message to be sent. Must be below 4096.
+        :param always_send: If False, will send the message only once per candle, and surpress
+                            identical messages.
+                            Careful as this can end up spaming your chat.
+                            Defaults to False
+        """
+        if self.runmode not in (RunMode.DRY_RUN, RunMode.LIVE):
+            return
+
+        if always_send or message not in self.__msg_cache:
+            self._msg_queue.append(message)
+        self.__msg_cache[message] = True
diff --git a/freqtrade/enums/rpcmessagetype.py b/freqtrade/enums/rpcmessagetype.py
index 584a011c2..415d8f18c 100644
--- a/freqtrade/enums/rpcmessagetype.py
+++ b/freqtrade/enums/rpcmessagetype.py
@@ -17,6 +17,8 @@ class RPCMessageType(Enum):
     PROTECTION_TRIGGER = 'protection_trigger'
     PROTECTION_TRIGGER_GLOBAL = 'protection_trigger_global'
 
+    STRATEGY_MSG = 'strategy_msg'
+
     def __repr__(self):
         return self.value
 
diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py
index 43608cae7..9ea195c45 100644
--- a/freqtrade/freqtradebot.py
+++ b/freqtrade/freqtradebot.py
@@ -214,6 +214,7 @@ class FreqtradeBot(LoggingMixin):
         if self.trading_mode == TradingMode.FUTURES:
             self._schedule.run_pending()
         Trade.commit()
+        self.rpc.process_msg_queue(self.dataprovider._msg_queue)
         self.last_process = datetime.now(timezone.utc)
 
     def process_stopped(self) -> None:
diff --git a/freqtrade/rpc/rpc_manager.py b/freqtrade/rpc/rpc_manager.py
index 66e84029f..3ccf23228 100644
--- a/freqtrade/rpc/rpc_manager.py
+++ b/freqtrade/rpc/rpc_manager.py
@@ -2,6 +2,7 @@
 This module contains class to manage RPC communications (Telegram, API, ...)
 """
 import logging
+from collections import deque
 from typing import Any, Dict, List
 
 from freqtrade.enums import RPCMessageType
@@ -77,6 +78,17 @@ class RPCManager:
             except NotImplementedError:
                 logger.error(f"Message type '{msg['type']}' not implemented by handler {mod.name}.")
 
+    def process_msg_queue(self, queue: deque) -> None:
+        """
+        Process all messages in the queue.
+        """
+        while queue:
+            msg = queue.popleft()
+            self.send_msg({
+                'type': RPCMessageType.STRATEGY_MSG,
+                'msg': msg,
+            })
+
     def startup_messages(self, config: Dict[str, Any], pairlist, protections) -> None:
         if config['dry_run']:
             self.send_msg({
diff --git a/freqtrade/rpc/telegram.py b/freqtrade/rpc/telegram.py
index 2aff1d210..121324d90 100644
--- a/freqtrade/rpc/telegram.py
+++ b/freqtrade/rpc/telegram.py
@@ -376,7 +376,8 @@ class Telegram(RPCHandler):
 
         elif msg_type == RPCMessageType.STARTUP:
             message = f"{msg['status']}"
-
+        elif msg_type == RPCMessageType.STRATEGY_MSG:
+            message = f"{msg['msg']}"
         else:
             raise NotImplementedError(f"Unknown message type: {msg_type}")
         return message

From 7bac0546681e770d3156db987620a666e4e1a489 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Tue, 26 Jul 2022 20:24:52 +0200
Subject: [PATCH 003/132] Add documentation and clarity for send_msg

---
 docs/strategy-customization.md | 17 +++++++++++++++++
 docs/telegram-usage.md         |  4 +++-
 freqtrade/constants.py         |  4 ++++
 freqtrade/data/dataprovider.py |  8 +++++---
 4 files changed, 29 insertions(+), 4 deletions(-)

diff --git a/docs/strategy-customization.md b/docs/strategy-customization.md
index 6947380dd..38d34d51b 100644
--- a/docs/strategy-customization.md
+++ b/docs/strategy-customization.md
@@ -731,6 +731,23 @@ if self.dp:
 !!! Warning "Warning about backtesting"
     This method will always return up-to-date values - so usage during backtesting / hyperopt will lead to wrong results.
 
+### Send Notification
+
+The dataprovider `.send_msg()` function allows you to send custom notifications from your strategy.
+Identical notifications will only be sent once per candle, unless the 2nd argument (`always_send`) is set to True.
+
+``` python
+    self.dp.send_msg(f"{metadata['pair']} just got hot!")
+
+    # Force send this notification, avoid caching (Please read warning below!)
+    self.dp.send_msg(f"{metadata['pair']} just got hot!", always_send=True)
+```
+
+Notifications will only be sent in trading modes (Live/Dry-run) - so this method can be called without conditions for backtesting.
+
+!!! Warning "Spamming"
+    You can spam yourself pretty good by setting `always_send=True` in this method. Use this with great care and only in conditions you know will not happen throughout a candle to avoid a message every 5 seconds.
+
 ### Complete Data-provider sample
 
 ```python
diff --git a/docs/telegram-usage.md b/docs/telegram-usage.md
index 9853e15c6..a690e18b9 100644
--- a/docs/telegram-usage.md
+++ b/docs/telegram-usage.md
@@ -98,6 +98,7 @@ Example configuration showing the different settings:
         "exit_fill": "off",
         "protection_trigger": "off",
         "protection_trigger_global": "on",
+        "strategy_msg": "off",
         "show_candle": "off"
     },
     "reload": true,
@@ -109,7 +110,8 @@ Example configuration showing the different settings:
 `exit` notifications are sent when the order is placed, while `exit_fill` notifications are sent when the order is filled on the exchange.
 `*_fill` notifications are off by default and must be explicitly enabled.
 `protection_trigger` notifications are sent when a protection triggers and `protection_trigger_global` notifications trigger when global protections are triggered.
-`show_candle` - show candle values as part of entry/exit messages. Only possible value is "ohlc".
+`strategy_msg` - Receive notifications from the strategy, sent via `self.dp.send_msg()` from the strategy [more details](strategy-customization.md#send-notification).
+`show_candle` - show candle values as part of entry/exit messages. Only possible values are `"ohlc"` or `"off"`.
 
 `balance_dust_level` will define what the `/balance` command takes as "dust" - Currencies with a balance below this will be shown.
 `reload` allows you to disable reload-buttons on selected messages.
diff --git a/freqtrade/constants.py b/freqtrade/constants.py
index 6d74ceafd..1d83d21a0 100644
--- a/freqtrade/constants.py
+++ b/freqtrade/constants.py
@@ -317,6 +317,10 @@ CONF_SCHEMA = {
                             'type': 'string',
                             'enum': ['off', 'ohlc'],
                         },
+                        'strategy_msg': {
+                            'type': 'string',
+                            'enum': TELEGRAM_SETTING_OPTIONS,
+                        },
                     }
                 },
                 'reload': {'type': 'boolean'},
diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py
index 800254533..e21f10193 100644
--- a/freqtrade/data/dataprovider.py
+++ b/freqtrade/data/dataprovider.py
@@ -36,8 +36,9 @@ class DataProvider:
         self.__slice_index: Optional[int] = None
         self.__cached_pairs_backtesting: Dict[PairWithTimeframe, DataFrame] = {}
         self._msg_queue: deque = deque()
+
         self.__msg_cache = PeriodicCache(
-            maxsize=1000, ttl=timeframe_to_seconds(self._config['timeframe']))
+            maxsize=1000, ttl=timeframe_to_seconds(self._config.get('timeframe', '1h')))
 
     def _set_dataframe_max_index(self, limit_index: int):
         """
@@ -271,9 +272,10 @@ class DataProvider:
             raise OperationalException(NO_EXCHANGE_EXCEPTION)
         return self._exchange.fetch_l2_order_book(pair, maximum)
 
-    def send_msg(self, message: str, always_send: bool = False) -> None:
+    def send_msg(self, message: str, *, always_send: bool = False) -> None:
         """
-        TODO: Document me
+        Send custom RPC Notifications from your bot.
+        Will not send any bot in modes other than Dry-run or Live.
         :param message: Message to be sent. Must be below 4096.
         :param always_send: If False, will send the message only once per candle, and surpress
                             identical messages.

From 0adfa4d9efe26d9423d769ca8829e723569c0545 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Wed, 27 Jul 2022 06:32:23 +0200
Subject: [PATCH 004/132] Add tests for dataprovider send-message methods

---
 tests/data/test_dataprovider.py | 19 +++++++++++++++++++
 tests/rpc/test_rpc_manager.py   | 21 +++++++++++++++++++--
 tests/rpc/test_rpc_telegram.py  | 10 ++++++++++
 tests/test_freqtradebot.py      |  6 ++++++
 4 files changed, 54 insertions(+), 2 deletions(-)

diff --git a/tests/data/test_dataprovider.py b/tests/data/test_dataprovider.py
index 93f82de5d..843d60786 100644
--- a/tests/data/test_dataprovider.py
+++ b/tests/data/test_dataprovider.py
@@ -311,3 +311,22 @@ def test_no_exchange_mode(default_conf):
 
     with pytest.raises(OperationalException, match=message):
         dp.available_pairs()
+
+
+def test_dp_send_msg(default_conf):
+
+    default_conf["runmode"] = RunMode.DRY_RUN
+
+    default_conf["timeframe"] = '1h'
+    dp = DataProvider(default_conf, None)
+    msg = 'Test message'
+    dp.send_msg(msg)
+
+    assert msg in dp._msg_queue
+    dp._msg_queue.pop()
+    assert msg not in dp._msg_queue
+    # Message is not resent due to caching
+    dp.send_msg(msg)
+    assert msg not in dp._msg_queue
+    dp.send_msg(msg, always_send=True)
+    assert msg in dp._msg_queue
diff --git a/tests/rpc/test_rpc_manager.py b/tests/rpc/test_rpc_manager.py
index 596b5ae20..b9ae16a20 100644
--- a/tests/rpc/test_rpc_manager.py
+++ b/tests/rpc/test_rpc_manager.py
@@ -1,6 +1,7 @@
 # pragma pylint: disable=missing-docstring, C0103
 import logging
 import time
+from collections import deque
 from unittest.mock import MagicMock
 
 from freqtrade.enums import RPCMessageType
@@ -81,9 +82,25 @@ def test_send_msg_telegram_disabled(mocker, default_conf, caplog) -> None:
     assert telegram_mock.call_count == 0
 
 
+def test_process_msg_queue(mocker, default_conf, caplog) -> None:
+    telegram_mock = mocker.patch('freqtrade.rpc.telegram.Telegram.send_msg')
+    mocker.patch('freqtrade.rpc.telegram.Telegram._init')
+
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+    rpc_manager = RPCManager(freqtradebot)
+    queue = deque()
+    queue.append('Test message')
+    queue.append('Test message 2')
+    rpc_manager.process_msg_queue(queue)
+
+    assert log_has("Sending rpc message: {'type': strategy_msg, 'msg': 'Test message'}", caplog)
+    assert log_has("Sending rpc message: {'type': strategy_msg, 'msg': 'Test message 2'}", caplog)
+    assert telegram_mock.call_count == 2
+
+
 def test_send_msg_telegram_enabled(mocker, default_conf, caplog) -> None:
-    telegram_mock = mocker.patch('freqtrade.rpc.telegram.Telegram.send_msg', MagicMock())
-    mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
+    telegram_mock = mocker.patch('freqtrade.rpc.telegram.Telegram.send_msg')
+    mocker.patch('freqtrade.rpc.telegram.Telegram._init')
 
     freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     rpc_manager = RPCManager(freqtradebot)
diff --git a/tests/rpc/test_rpc_telegram.py b/tests/rpc/test_rpc_telegram.py
index f69b7e878..8d244f3fd 100644
--- a/tests/rpc/test_rpc_telegram.py
+++ b/tests/rpc/test_rpc_telegram.py
@@ -1994,6 +1994,16 @@ def test_startup_notification(default_conf, mocker) -> None:
     assert msg_mock.call_args[0][0] == '*Custom:* `Hello World`'
 
 
+def test_send_msg_strategy_msg_notification(default_conf, mocker) -> None:
+
+    telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
+    telegram.send_msg({
+        'type': RPCMessageType.STRATEGY_MSG,
+        'msg': 'hello world, Test msg'
+    })
+    assert msg_mock.call_args[0][0] == 'hello world, Test msg'
+
+
 def test_send_msg_unknown_type(default_conf, mocker) -> None:
     telegram, _, _ = get_telegram_testobject(mocker, default_conf)
     with pytest.raises(NotImplementedError, match=r'Unknown message type: None'):
diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py
index 66cbd7d9b..438a2704c 100644
--- a/tests/test_freqtradebot.py
+++ b/tests/test_freqtradebot.py
@@ -68,6 +68,12 @@ def test_process_stopped(mocker, default_conf_usdt) -> None:
     assert coo_mock.call_count == 1
 
 
+def test_process_calls_sendmsg(mocker, default_conf_usdt) -> None:
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
+    freqtrade.process()
+    assert freqtrade.rpc.process_msg_queue.call_count == 1
+
+
 def test_bot_cleanup(mocker, default_conf_usdt, caplog) -> None:
     mock_cleanup = mocker.patch('freqtrade.freqtradebot.cleanup_db')
     coo_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.cancel_all_open_orders')

From 31ddec834816d980d2802810868b62f44df787d1 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Wed, 27 Jul 2022 06:51:56 +0200
Subject: [PATCH 005/132] Add missing test to confirm backtesting won't send
 messages

---
 tests/data/test_dataprovider.py | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/tests/data/test_dataprovider.py b/tests/data/test_dataprovider.py
index 843d60786..49603feac 100644
--- a/tests/data/test_dataprovider.py
+++ b/tests/data/test_dataprovider.py
@@ -330,3 +330,8 @@ def test_dp_send_msg(default_conf):
     assert msg not in dp._msg_queue
     dp.send_msg(msg, always_send=True)
     assert msg in dp._msg_queue
+
+    default_conf["runmode"] = RunMode.BACKTEST
+    dp = DataProvider(default_conf, None)
+    dp.send_msg(msg, always_send=True)
+    assert msg not in dp._msg_queue

From c84d54b35ec455e02818bca592ce80c98a89d756 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Fri, 29 Jul 2022 08:12:50 +0200
Subject: [PATCH 006/132] Fix typing issue, avoid using .get() when
 unnecessary, convert to fstrings

---
 freqtrade/freqai/data_drawer.py               | 45 ++++++++++---------
 freqtrade/freqai/data_kitchen.py              | 28 ++++++------
 freqtrade/freqai/freqai_interface.py          | 34 +++++++-------
 .../prediction_models/BaseRegressionModel.py  |  4 +-
 .../CatboostPredictionModel.py                |  3 +-
 5 files changed, 57 insertions(+), 57 deletions(-)

diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py
index 4d37ef8c1..97cf7607a 100644
--- a/freqtrade/freqai/data_drawer.py
+++ b/freqtrade/freqai/data_drawer.py
@@ -11,7 +11,7 @@ import numpy as np
 import pandas as pd
 from joblib import dump, load
 from joblib.externals import cloudpickle
-from numpy.typing import ArrayLike
+from numpy.typing import ArrayLike, NDArray
 from pandas import DataFrame
 
 from freqtrade.configuration import TimeRange
@@ -233,12 +233,13 @@ class FreqaiDataDrawer:
             mrv_df[f"{label}_mean"] = dk.data["labels_mean"][label]
             mrv_df[f"{label}_std"] = dk.data["labels_std"][label]
 
-        if self.freqai_info.get("feature_parameters", {}).get("DI_threshold", 0) > 0:
+        if self.freqai_info["feature_parameters"].get("DI_threshold", 0) > 0:
             mrv_df["DI_values"] = dk.DI_values
 
         mrv_df["do_predict"] = do_preds
 
-    def append_model_predictions(self, pair: str, predictions: DataFrame, do_preds: ArrayLike,
+    def append_model_predictions(self, pair: str, predictions: DataFrame,
+                                 do_preds: NDArray[np.int_],
                                  dk: FreqaiDataKitchen, len_df: int) -> None:
 
         # strat seems to feed us variable sized dataframes - and since we are trying to build our
@@ -266,10 +267,10 @@ class FreqaiDataDrawer:
             df[label].iloc[-1] = predictions[label].iloc[-1]
             df[f"{label}_mean"].iloc[-1] = dk.data["labels_mean"][label]
             df[f"{label}_std"].iloc[-1] = dk.data["labels_std"][label]
-        # df['prediction'].iloc[-1] = predictions[-1]
+
         df["do_predict"].iloc[-1] = do_preds[-1]
 
-        if self.freqai_info.get("feature_parameters", {}).get("DI_threshold", 0) > 0:
+        if self.freqai_info["feature_parameters"].get("DI_threshold", 0) > 0:
             df["DI_values"].iloc[-1] = dk.DI_values[-1]
 
         # append the new predictions to persistent storage
@@ -309,7 +310,7 @@ class FreqaiDataDrawer:
         # dataframe['prediction'] = 0
         dataframe["do_predict"] = 0
 
-        if self.freqai_info.get("feature_parameters", {}).get("DI_threshold", 0) > 0:
+        if self.freqai_info["feature_parameters"].get("DI_threshold", 0) > 0:
             dataframe["DI_value"] = 0
 
         dk.return_dataframe = dataframe
@@ -379,24 +380,24 @@ class FreqaiDataDrawer:
             model.save(save_path / f"{dk.model_filename}_model.h5")
 
         if dk.svm_model is not None:
-            dump(dk.svm_model, save_path / str(dk.model_filename + "_svm_model.joblib"))
+            dump(dk.svm_model, save_path / f"{dk.model_filename}_svm_model.joblib")
 
         dk.data["data_path"] = str(dk.data_path)
         dk.data["model_filename"] = str(dk.model_filename)
         dk.data["training_features_list"] = list(dk.data_dictionary["train_features"].columns)
         dk.data["label_list"] = dk.label_list
         # store the metadata
-        with open(save_path / str(dk.model_filename + "_metadata.json"), "w") as fp:
+        with open(save_path / f"{dk.model_filename}_metadata.json", "w") as fp:
             json.dump(dk.data, fp, default=dk.np_encoder)
 
         # save the train data to file so we can check preds for area of applicability later
         dk.data_dictionary["train_features"].to_pickle(
-            save_path / str(dk.model_filename + "_trained_df.pkl")
+            save_path / f"{dk.model_filename}_trained_df.pkl"
         )
 
-        if self.freqai_info.get("feature_parameters", {}).get("principal_component_analysis"):
+        if self.freqai_info["feature_parameters"].get("principal_component_analysis"):
             cloudpickle.dump(
-                dk.pca, open(dk.data_path / str(dk.model_filename + "_pca_object.pkl"), "wb")
+                dk.pca, open(dk.data_path / f"{dk.model_filename}_pca_object.pkl", "wb")
             )
 
         # if self.live:
@@ -429,27 +430,27 @@ class FreqaiDataDrawer:
                     / dk.data_path.parts[-1]
                 )
 
-        with open(dk.data_path / str(dk.model_filename + "_metadata.json"), "r") as fp:
+        with open(dk.data_path / f"{dk.model_filename}_metadata.json", "r") as fp:
             dk.data = json.load(fp)
             dk.training_features_list = dk.data["training_features_list"]
             dk.label_list = dk.data["label_list"]
 
         dk.data_dictionary["train_features"] = pd.read_pickle(
-            dk.data_path / str(dk.model_filename + "_trained_df.pkl")
+            dk.data_path / f"{dk.model_filename}_trained_df.pkl"
         )
 
         # try to access model in memory instead of loading object from disk to save time
         if dk.live and dk.model_filename in self.model_dictionary:
             model = self.model_dictionary[dk.model_filename]
         elif not dk.keras:
-            model = load(dk.data_path / str(dk.model_filename + "_model.joblib"))
+            model = load(dk.data_path / f"{dk.model_filename}_model.joblib")
         else:
             from tensorflow import keras
 
-            model = keras.models.load_model(dk.data_path / str(dk.model_filename + "_model.h5"))
+            model = keras.models.load_model(dk.data_path / f"{dk.model_filename}_model.h5")
 
-        if Path(dk.data_path / str(dk.model_filename + "_svm_model.joblib")).resolve().exists():
-            dk.svm_model = load(dk.data_path / str(dk.model_filename + "_svm_model.joblib"))
+        if Path(dk.data_path / f"{dk.model_filename}_svm_model.joblib").is_file():
+            dk.svm_model = load(dk.data_path / f"{dk.model_filename}_svm_model.joblib")
 
         if not model:
             raise OperationalException(
@@ -458,7 +459,7 @@ class FreqaiDataDrawer:
 
         if self.config["freqai"]["feature_parameters"]["principal_component_analysis"]:
             dk.pca = cloudpickle.load(
-                open(dk.data_path / str(dk.model_filename + "_pca_object.pkl"), "rb")
+                open(dk.data_path / f"{dk.model_filename}_pca_object.pkl", "rb")
             )
 
         return model
@@ -471,7 +472,7 @@ class FreqaiDataDrawer:
         :params:
         dataframe: DataFrame = strategy provided dataframe
         """
-        feat_params = self.freqai_info.get("feature_parameters", {})
+        feat_params = self.freqai_info["feature_parameters"]
         with self.history_lock:
             history_data = self.historic_data
 
@@ -524,7 +525,7 @@ class FreqaiDataDrawer:
         for pair in dk.all_pairs:
             if pair not in history_data:
                 history_data[pair] = {}
-            for tf in self.freqai_info.get("feature_parameters", {}).get("include_timeframes"):
+            for tf in self.freqai_info["feature_parameters"].get("include_timeframes"):
                 history_data[pair][tf] = load_pair_history(
                     datadir=self.config["datadir"],
                     timeframe=tf,
@@ -550,11 +551,11 @@ class FreqaiDataDrawer:
             corr_dataframes: Dict[Any, Any] = {}
             base_dataframes: Dict[Any, Any] = {}
             historic_data = self.historic_data
-            pairs = self.freqai_info.get("feature_parameters", {}).get(
+            pairs = self.freqai_info["feature_parameters"].get(
                 "include_corr_pairlist", []
             )
 
-            for tf in self.freqai_info.get("feature_parameters", {}).get("include_timeframes"):
+            for tf in self.freqai_info["feature_parameters"].get("include_timeframes"):
                 base_dataframes[tf] = dk.slice_dataframe(timerange, historic_data[pair][tf])
                 if pairs:
                     for p in pairs:
diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index f16e169b9..b5a3295b5 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -116,7 +116,7 @@ class FreqaiDataKitchen:
         :filtered_dataframe: cleaned dataframe ready to be split.
         :labels: cleaned labels ready to be split.
         """
-        feat_dict = self.freqai_config.get("feature_parameters", {})
+        feat_dict = self.freqai_config["feature_parameters"]
 
         weights: npt.ArrayLike
         if feat_dict.get("weight_factor", 0) > 0:
@@ -515,7 +515,9 @@ class FreqaiDataKitchen:
             return
 
         if predict:
-            assert self.svm_model, "No svm model available for outlier removal"
+            if not self.svm_model:
+                logger.warning("No svm model available for outlier removal")
+                return
             y_pred = self.svm_model.predict(self.data_dictionary["prediction_features"])
             do_predict = np.where(y_pred == -1, 0, y_pred)
 
@@ -528,7 +530,7 @@ class FreqaiDataKitchen:
 
         else:
             # use SGDOneClassSVM to increase speed?
-            nu = self.freqai_config.get("feature_parameters", {}).get("svm_nu", 0.2)
+            nu = self.freqai_config["feature_parameters"].get("svm_nu", 0.2)
             self.svm_model = linear_model.SGDOneClassSVM(nu=nu).fit(
                 self.data_dictionary["train_features"]
             )
@@ -551,7 +553,7 @@ class FreqaiDataKitchen:
             )
 
             # same for test data
-            if self.freqai_config.get('data_split_parameters', {}).get('test_size', 0.1) != 0:
+            if self.freqai_config['data_split_parameters'].get('test_size', 0.1) != 0:
                 y_pred = self.svm_model.predict(self.data_dictionary["test_features"])
                 dropped_points = np.where(y_pred == -1, 0, y_pred)
                 self.data_dictionary["test_features"] = self.data_dictionary["test_features"][
@@ -605,7 +607,7 @@ class FreqaiDataKitchen:
         self.DI_values = distance.min(axis=0) / self.data["avg_mean_dist"]
 
         do_predict = np.where(
-            self.DI_values < self.freqai_config.get("feature_parameters", {}).get("DI_threshold"),
+            self.DI_values < self.freqai_config["feature_parameters"]["DI_threshold"],
             1,
             0,
         )
@@ -640,7 +642,7 @@ class FreqaiDataKitchen:
             self.append_df[f"{label}_std"] = self.data["labels_std"][label]
 
         self.append_df["do_predict"] = do_predict
-        if self.freqai_config.get("feature_parameters", {}).get("DI_threshold", 0) > 0:
+        if self.freqai_config["feature_parameters"].get("DI_threshold", 0) > 0:
             self.append_df["DI_values"] = self.DI_values
 
         if self.full_df.empty:
@@ -701,7 +703,7 @@ class FreqaiDataKitchen:
         full_timerange = start.strftime("%Y%m%d") + "-" + stop.strftime("%Y%m%d")
 
         self.full_path = Path(
-            self.config["user_data_dir"] / "models" / str(self.freqai_config.get("identifier"))
+            self.config["user_data_dir"] / "models" / f"{self.freqai_config['identifier']}"
         )
 
         config_path = Path(self.config["config_files"][0])
@@ -741,10 +743,10 @@ class FreqaiDataKitchen:
         data_load_timerange = TimeRange()
 
         # find the max indicator length required
-        max_timeframe_chars = self.freqai_config.get("feature_parameters", {}).get(
+        max_timeframe_chars = self.freqai_config["feature_parameters"].get(
             "include_timeframes"
         )[-1]
-        max_period = self.freqai_config.get("feature_parameters", {}).get(
+        max_period = self.freqai_config["feature_parameters"].get(
             "indicator_max_period_candles", 50
         )
         additional_seconds = 0
@@ -832,7 +834,7 @@ class FreqaiDataKitchen:
         refresh_backtest_ohlcv_data(
             exchange,
             pairs=self.all_pairs,
-            timeframes=self.freqai_config.get("feature_parameters", {}).get("include_timeframes"),
+            timeframes=self.freqai_config["feature_parameters"].get("include_timeframes"),
             datadir=self.config["datadir"],
             timerange=timerange,
             new_pairs_days=new_pairs_days,
@@ -845,7 +847,7 @@ class FreqaiDataKitchen:
     def set_all_pairs(self) -> None:
 
         self.all_pairs = copy.deepcopy(
-            self.freqai_config.get("feature_parameters", {}).get("include_corr_pairlist", [])
+            self.freqai_config["feature_parameters"].get("include_corr_pairlist", [])
         )
         for pair in self.config.get("exchange", "").get("pair_whitelist"):
             if pair not in self.all_pairs:
@@ -876,8 +878,8 @@ class FreqaiDataKitchen:
         # for prediction dataframe creation, we let dataprovider handle everything in the strategy
         # so we create empty dictionaries, which allows us to pass None to
         # `populate_any_indicators()`. Signaling we want the dp to give us the live dataframe.
-        tfs = self.freqai_config.get("feature_parameters", {}).get("include_timeframes")
-        pairs = self.freqai_config.get("feature_parameters", {}).get("include_corr_pairlist", [])
+        tfs = self.freqai_config["feature_parameters"].get("include_timeframes")
+        pairs = self.freqai_config["feature_parameters"].get("include_corr_pairlist", [])
         if not prediction_dataframe.empty:
             dataframe = prediction_dataframe.copy()
             for tf in tfs:
diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py
index ec69a78c4..47aeb32e4 100644
--- a/freqtrade/freqai/freqai_interface.py
+++ b/freqtrade/freqai/freqai_interface.py
@@ -12,7 +12,7 @@ from typing import Any, Dict, Tuple
 
 import numpy as np
 import pandas as pd
-from numpy.typing import ArrayLike
+from numpy.typing import NDArray
 from pandas import DataFrame
 
 from freqtrade.configuration import TimeRange
@@ -204,14 +204,9 @@ class IFreqaiModel(ABC):
 
             dk.data_path = Path(
                 dk.full_path
-                / str(
-                    "sub-train"
-                    + "-"
-                    + metadata["pair"].split("/")[0]
-                    + "_"
-                    + str(int(trained_timestamp.stopts))
+                /
+                f"sub-train-{metadata['pair'].split('/')[0]}_{int(trained_timestamp.stopts)}"
                 )
-            )
             if not self.model_exists(
                 metadata["pair"], dk, trained_timestamp=int(trained_timestamp.stopts)
             ):
@@ -331,7 +326,8 @@ class IFreqaiModel(ABC):
             return
         elif self.dk.check_if_model_expired(trained_timestamp):
             pred_df = DataFrame(np.zeros((2, len(dk.label_list))), columns=dk.label_list)
-            do_preds, dk.DI_values = np.ones(2) * 2, np.zeros(2)
+            do_preds = np.ones(2, dtype=np.int_) * 2
+            dk.DI_values = np.zeros(2)
             logger.warning(
                 f"Model expired for {pair}, returning null values to strategy. Strategy "
                 "construction should take care to consider this event with "
@@ -379,15 +375,15 @@ class IFreqaiModel(ABC):
         example of how outlier data points are dropped from the dataframe used for training.
         """
 
-        if self.freqai_info.get("feature_parameters", {}).get(
+        if self.freqai_info["feature_parameters"].get(
             "principal_component_analysis", False
         ):
             dk.principal_component_analysis()
 
-        if self.freqai_info.get("feature_parameters", {}).get("use_SVM_to_remove_outliers", False):
+        if self.freqai_info["feature_parameters"].get("use_SVM_to_remove_outliers", False):
             dk.use_SVM_to_remove_outliers(predict=False)
 
-        if self.freqai_info.get("feature_parameters", {}).get("DI_threshold", 0):
+        if self.freqai_info["feature_parameters"].get("DI_threshold", 0):
             dk.data["avg_mean_dist"] = dk.compute_distances()
 
     def data_cleaning_predict(self, dk: FreqaiDataKitchen, dataframe: DataFrame) -> None:
@@ -401,15 +397,15 @@ class IFreqaiModel(ABC):
         of how the do_predict vector is modified. do_predict is ultimately passed back to strategy
         for buy signals.
         """
-        if self.freqai_info.get("feature_parameters", {}).get(
+        if self.freqai_info["feature_parameters"].get(
             "principal_component_analysis", False
         ):
             dk.pca_transform(dataframe)
 
-        if self.freqai_info.get("feature_parameters", {}).get("use_SVM_to_remove_outliers", False):
+        if self.freqai_info["feature_parameters"].get("use_SVM_to_remove_outliers", False):
             dk.use_SVM_to_remove_outliers(predict=True)
 
-        if self.freqai_info.get("feature_parameters", {}).get("DI_threshold", 0):
+        if self.freqai_info["feature_parameters"].get("DI_threshold", 0):
             dk.check_if_pred_in_training_spaces()
 
     def model_exists(
@@ -430,9 +426,9 @@ class IFreqaiModel(ABC):
         coin, _ = pair.split("/")
 
         if not self.live:
-            dk.model_filename = model_filename = "cb_" + coin.lower() + "_" + str(trained_timestamp)
+            dk.model_filename = model_filename = f"cb_{coin.lower()}_{trained_timestamp}"
 
-        path_to_modelfile = Path(dk.data_path / str(model_filename + "_model.joblib"))
+        path_to_modelfile = Path(dk.data_path / f"{model_filename}_model.joblib")
         file_exists = path_to_modelfile.is_file()
         if file_exists and not scanning:
             logger.info("Found model at %s", dk.data_path / dk.model_filename)
@@ -442,7 +438,7 @@ class IFreqaiModel(ABC):
 
     def set_full_path(self) -> None:
         self.full_path = Path(
-            self.config["user_data_dir"] / "models" / str(self.freqai_info.get("identifier"))
+            self.config["user_data_dir"] / "models" / f"{self.freqai_info['identifier']}"
         )
         self.full_path.mkdir(parents=True, exist_ok=True)
         shutil.copy(
@@ -550,7 +546,7 @@ class IFreqaiModel(ABC):
     @abstractmethod
     def predict(
         self, dataframe: DataFrame, dk: FreqaiDataKitchen, first: bool = True
-    ) -> Tuple[DataFrame, ArrayLike]:
+    ) -> Tuple[DataFrame, NDArray[np.int_]]:
         """
         Filter the prediction features data and predict with it.
         :param unfiltered_dataframe: Full dataframe for the current backtest period.
diff --git a/freqtrade/freqai/prediction_models/BaseRegressionModel.py b/freqtrade/freqai/prediction_models/BaseRegressionModel.py
index 2baec9fc3..85d7ae1ee 100644
--- a/freqtrade/freqai/prediction_models/BaseRegressionModel.py
+++ b/freqtrade/freqai/prediction_models/BaseRegressionModel.py
@@ -3,7 +3,7 @@ from typing import Any, Tuple
 
 import numpy.typing as npt
 from pandas import DataFrame
-
+import numpy as np
 from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
 from freqtrade.freqai.freqai_interface import IFreqaiModel
 
@@ -85,7 +85,7 @@ class BaseRegressionModel(IFreqaiModel):
 
     def predict(
         self, unfiltered_dataframe: DataFrame, dk: FreqaiDataKitchen, first: bool = False
-    ) -> Tuple[DataFrame, npt.ArrayLike]:
+    ) -> Tuple[DataFrame, npt.NDArray[np.int_]]:
         """
         Filter the prediction features data and predict with it.
         :param: unfiltered_dataframe: Full dataframe for the current backtest period.
diff --git a/freqtrade/freqai/prediction_models/CatboostPredictionModel.py b/freqtrade/freqai/prediction_models/CatboostPredictionModel.py
index 884933803..9731e0c01 100644
--- a/freqtrade/freqai/prediction_models/CatboostPredictionModel.py
+++ b/freqtrade/freqai/prediction_models/CatboostPredictionModel.py
@@ -1,6 +1,7 @@
+import gc
 import logging
 from typing import Any, Dict
-import gc
+
 from catboost import CatBoostRegressor, Pool
 
 from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel

From 59624181bd1005feb93e822e0fffddf0644fec44 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Fri, 29 Jul 2022 08:23:44 +0200
Subject: [PATCH 007/132] isort BaseRegressionModel imports

---
 freqtrade/freqai/prediction_models/BaseRegressionModel.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/freqtrade/freqai/prediction_models/BaseRegressionModel.py b/freqtrade/freqai/prediction_models/BaseRegressionModel.py
index 85d7ae1ee..1901c18fe 100644
--- a/freqtrade/freqai/prediction_models/BaseRegressionModel.py
+++ b/freqtrade/freqai/prediction_models/BaseRegressionModel.py
@@ -1,9 +1,10 @@
 import logging
 from typing import Any, Tuple
 
+import numpy as np
 import numpy.typing as npt
 from pandas import DataFrame
-import numpy as np
+
 from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
 from freqtrade.freqai.freqai_interface import IFreqaiModel
 

From 08d3ac7ef821e42e428d8250c279fb00c8da553e Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Fri, 29 Jul 2022 08:49:35 +0200
Subject: [PATCH 008/132] add keras and conv_width to schema and documentation

---
 docs/freqai.md         | 3 +++
 freqtrade/constants.py | 2 ++
 2 files changed, 5 insertions(+)

diff --git a/docs/freqai.md b/docs/freqai.md
index 4060b5394..3c04d5b31 100644
--- a/docs/freqai.md
+++ b/docs/freqai.md
@@ -110,6 +110,9 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `n_estimators` | A common parameter among regressors which sets the number of boosted trees to fit <br> **Datatype:** integer.
 | `learning_rate` | A common parameter among regressors which sets the boosting learning rate. <br> **Datatype:** float.
 | `n_jobs`, `thread_count`, `task_type` | Different libraries use different parameter names to control the number of threads used for parallel processing or whether or not it is a `task_type` of `gpu` or `cpu`. <br> **Datatype:** float.
+|  |  **Extraneous parameters**
+| `keras` | If your model makes use of keras (typical of Tensorflow based prediction models), activate this flag so that the model save/loading follows keras standards. Default value `false`  <br> **Datatype:** boolean.
+| `conv_width` | The width of a convolutional neural network input tensor. This replaces the need for `shift` by feeding in historical data points as the second dimension of the tensor. Technically, this parameter can also be used for regressors, but it only adds computational overhead and does not change the model training/prediction. Default value, 2 <br> **Datatype:** integer.
 
 
 ### Important FreqAI dataframe key patterns
diff --git a/freqtrade/constants.py b/freqtrade/constants.py
index 90c87809b..0134dafc0 100644
--- a/freqtrade/constants.py
+++ b/freqtrade/constants.py
@@ -481,6 +481,8 @@ CONF_SCHEMA = {
         "freqai": {
             "type": "object",
             "properties": {
+                "keras": {"type": "boolean", "default": False},
+                "conv_width": {"type": "integer", "default": 2},
                 "train_period_days": {"type": "integer", "default": 0},
                 "backtest_period_days": {"type": "float", "default": 7},
                 "identifier": {"type": "str", "default": "example"},

From f22b14078259aea39ba6731091538dc307fccc30 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Fri, 29 Jul 2022 17:27:35 +0200
Subject: [PATCH 009/132] fix backtesting bug, undo move of label stat calc,
 fix example strat exit logic

---
 freqtrade/freqai/data_kitchen.py               | 18 +++++++++---------
 freqtrade/freqai/freqai_interface.py           |  3 ---
 .../prediction_models/BaseRegressionModel.py   |  4 ++--
 freqtrade/templates/FreqaiExampleStrategy.py   |  2 +-
 4 files changed, 12 insertions(+), 15 deletions(-)

diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index b5a3295b5..788572ba6 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -635,20 +635,20 @@ class FreqaiDataKitchen:
         Append backtest prediction from current backtest period to all previous periods
         """
 
-        self.append_df = DataFrame()
+        append_df = DataFrame()
         for label in self.label_list:
-            self.append_df[label] = predictions[label]
-            self.append_df[f"{label}_mean"] = self.data["labels_mean"][label]
-            self.append_df[f"{label}_std"] = self.data["labels_std"][label]
+            append_df[label] = predictions[label]
+            append_df[f"{label}_mean"] = self.data["labels_mean"][label]
+            append_df[f"{label}_std"] = self.data["labels_std"][label]
 
-        self.append_df["do_predict"] = do_predict
+        append_df["do_predict"] = do_predict
         if self.freqai_config["feature_parameters"].get("DI_threshold", 0) > 0:
-            self.append_df["DI_values"] = self.DI_values
+            append_df["DI_values"] = self.DI_values
 
         if self.full_df.empty:
-            self.full_df = self.append_df
+            self.full_df = append_df
         else:
-            self.full_df = pd.concat([self.full_df, self.append_df], axis=0)
+            self.full_df = pd.concat([self.full_df, append_df], axis=0)
 
         return
 
@@ -668,7 +668,7 @@ class FreqaiDataKitchen:
         to_keep = [col for col in dataframe.columns if not col.startswith("&")]
         self.return_dataframe = pd.concat([dataframe[to_keep], self.full_df], axis=1)
 
-        self.append_df = DataFrame()
+        # self.append_df = DataFrame()
         self.full_df = DataFrame()
 
         return
diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py
index 47aeb32e4..3b97637a8 100644
--- a/freqtrade/freqai/freqai_interface.py
+++ b/freqtrade/freqai/freqai_interface.py
@@ -1,7 +1,6 @@
 # import contextlib
 import copy
 import datetime
-import gc
 import logging
 import shutil
 import threading
@@ -183,8 +182,6 @@ class IFreqaiModel(ABC):
             (_, _, _) = self.dd.get_pair_dict_info(metadata["pair"])
             train_it += 1
             total_trains = len(dk.backtesting_timeranges)
-            gc.collect()
-            dk.data = {}  # clean the pair specific data between training window sliding
             self.training_timerange = tr_train
             dataframe_train = dk.slice_dataframe(tr_train, dataframe)
             dataframe_backtest = dk.slice_dataframe(tr_backtest, dataframe)
diff --git a/freqtrade/freqai/prediction_models/BaseRegressionModel.py b/freqtrade/freqai/prediction_models/BaseRegressionModel.py
index 1901c18fe..112e48183 100644
--- a/freqtrade/freqai/prediction_models/BaseRegressionModel.py
+++ b/freqtrade/freqai/prediction_models/BaseRegressionModel.py
@@ -56,6 +56,8 @@ class BaseRegressionModel(IFreqaiModel):
                     f"{end_date}--------------------")
         # split data into train/test data.
         data_dictionary = dk.make_train_test_datasets(features_filtered, labels_filtered)
+        if not self.freqai_info.get('fit_live_predictions', 0) or not self.live:
+            dk.fit_labels()
         # normalize all data based on train_dataset only
         data_dictionary = dk.normalize_data(data_dictionary)
 
@@ -75,8 +77,6 @@ class BaseRegressionModel(IFreqaiModel):
 
         if self.freqai_info.get('fit_live_predictions_candles', 0) and self.live:
             self.fit_live_predictions(dk)
-        else:
-            dk.fit_labels()
 
         self.dd.save_historic_predictions_to_disk()
 
diff --git a/freqtrade/templates/FreqaiExampleStrategy.py b/freqtrade/templates/FreqaiExampleStrategy.py
index 58eb47532..1196405ab 100644
--- a/freqtrade/templates/FreqaiExampleStrategy.py
+++ b/freqtrade/templates/FreqaiExampleStrategy.py
@@ -235,7 +235,7 @@ class FreqaiExampleStrategy(IStrategy):
 
         if (
             "prediction" + entry_tag not in pair_dict[pair]
-            or pair_dict[pair]["prediction" + entry_tag] > 0
+            or pair_dict[pair]["prediction" + entry_tag] == 0
         ):
             with self.freqai.lock:
                 pair_dict[pair]["prediction" + entry_tag] = abs(trade_candle["&-s_close"])

From d70650b074e023c649a04ce15ca84946b3409eb6 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 30 Jul 2022 08:20:22 +0200
Subject: [PATCH 010/132] Add note for plot-dataframe and current-whitelist

closes #7142
---
 docs/strategy-customization.md | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/docs/strategy-customization.md b/docs/strategy-customization.md
index 6947380dd..78256e0ee 100644
--- a/docs/strategy-customization.md
+++ b/docs/strategy-customization.md
@@ -646,6 +646,9 @@ This is where calling `self.dp.current_whitelist()` comes in handy.
         return informative_pairs
 ```
 
+??? Note "Plotting with current_whitelist"
+    Current whitelist is not supported for `plot-dataframe`, as this command is usually used by providing an explicit pairlist - and would therefore make the return values of this method misleading.
+
 ### *get_pair_dataframe(pair, timeframe)*
 
 ``` python

From dd8288c090a7abb0c6e503e80bdfd7c2220decca Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Sat, 30 Jul 2022 13:40:05 +0200
Subject: [PATCH 011/132] expose full parameter set for SVM outlier detection.
 Set default shuffle to false to improve reproducibility

---
 docs/freqai.md                   | 2 +-
 freqtrade/freqai/data_kitchen.py | 5 +++--
 2 files changed, 4 insertions(+), 3 deletions(-)

diff --git a/docs/freqai.md b/docs/freqai.md
index 3c04d5b31..c4d0ad0f8 100644
--- a/docs/freqai.md
+++ b/docs/freqai.md
@@ -97,7 +97,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `weight_factor` | Used to set weights for training data points according to their recency, see details and a figure of how it works [here](##controlling-the-model-learning-process). <br> **Datatype:** positive float (typically below 1).
 | `principal_component_analysis` | Ask FreqAI to automatically reduce the dimensionality of the data set using PCA. <br> **Datatype:** boolean.
 | `use_SVM_to_remove_outliers` | Ask FreqAI to train a support vector machine to detect and remove outliers from the training data set as well as from incoming data points. <br> **Datatype:** boolean.
-| `svm_nu` | The `nu` parameter for the support vector machine. *Very* broadly, this is the percentage of data points that should be considered outliers. <br> **Datatype:** float between 0 and 1.
+| `svm_params` | All parameters available in Sklearn's `SGDOneClassSVM()`. E.g. `nu` *Very* broadly, is the percentage of data points that should be considered outliers. `shuffle` is by default false to maintain reprodicibility. But these and all others can be added/changed in this dictionary. <br> **Datatype:** dictionary.
 | `stratify_training_data` | This value is used to indicate the stratification of the data. e.g. 2 would set every 2nd data point into a separate dataset to be pulled from during training/testing. <br> **Datatype:** positive integer.
 | `indicator_max_period_candles` | The maximum *period* used in `populate_any_indicators()` for indicator creation. FreqAI uses this information in combination with the maximum timeframe to calculate how many data points it should download so that the first data point does not have a NaN <br> **Datatype:** positive integer.
 | `indicator_periods_candles` | A list of integers used to duplicate all indicators according to a set of periods and add them to the feature set. <br> **Datatype:** list of positive integers.
diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index 788572ba6..4a936475a 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -530,8 +530,9 @@ class FreqaiDataKitchen:
 
         else:
             # use SGDOneClassSVM to increase speed?
-            nu = self.freqai_config["feature_parameters"].get("svm_nu", 0.2)
-            self.svm_model = linear_model.SGDOneClassSVM(nu=nu).fit(
+            svm_params = self.freqai_config["feature_parameters"].get(
+                "svm_params", {"shuffle": False, "nu": 0.1})
+            self.svm_model = linear_model.SGDOneClassSVM(**svm_params).fit(
                 self.data_dictionary["train_features"]
             )
             y_pred = self.svm_model.predict(self.data_dictionary["train_features"])

From 995be90f91a21c351a5c22264135694f3e11d62b Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Thu, 28 Jul 2022 20:35:23 +0200
Subject: [PATCH 012/132] Liquidation should be a separate exit type

---
 freqtrade/enums/exittype.py                     |  1 +
 freqtrade/optimize/backtesting.py               | 14 ++++++++++----
 freqtrade/persistence/trade_model.py            | 12 ++----------
 freqtrade/plugins/protections/stoploss_guard.py |  2 +-
 freqtrade/strategy/interface.py                 | 13 ++++++++++++-
 5 files changed, 26 insertions(+), 16 deletions(-)

diff --git a/freqtrade/enums/exittype.py b/freqtrade/enums/exittype.py
index b2c5b62ea..1e15e70cd 100644
--- a/freqtrade/enums/exittype.py
+++ b/freqtrade/enums/exittype.py
@@ -9,6 +9,7 @@ class ExitType(Enum):
     STOP_LOSS = "stop_loss"
     STOPLOSS_ON_EXCHANGE = "stoploss_on_exchange"
     TRAILING_STOP_LOSS = "trailing_stop_loss"
+    LIQUIDATION = "liquidation"
     EXIT_SIGNAL = "exit_signal"
     FORCE_EXIT = "force_exit"
     EMERGENCY_EXIT = "emergency_exit"
diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py
index 4d16dc0f1..598ce6710 100755
--- a/freqtrade/optimize/backtesting.py
+++ b/freqtrade/optimize/backtesting.py
@@ -381,7 +381,8 @@ class Backtesting:
         Get close rate for backtesting result
         """
         # Special handling if high or low hit STOP_LOSS or ROI
-        if exit.exit_type in (ExitType.STOP_LOSS, ExitType.TRAILING_STOP_LOSS):
+        if exit.exit_type in (
+                ExitType.STOP_LOSS, ExitType.TRAILING_STOP_LOSS, ExitType.LIQUIDATION):
             return self._get_close_rate_for_stoploss(row, trade, exit, trade_dur)
         elif exit.exit_type == (ExitType.ROI):
             return self._get_close_rate_for_roi(row, trade, exit, trade_dur)
@@ -396,11 +397,16 @@ class Backtesting:
         is_short = trade.is_short or False
         leverage = trade.leverage or 1.0
         side_1 = -1 if is_short else 1
+        if exit.exit_type == ExitType.LIQUIDATION and trade.liquidation_price:
+            stoploss_value = trade.liquidation_price
+        else:
+            stoploss_value = trade.stop_loss
+
         if is_short:
-            if trade.stop_loss < row[LOW_IDX]:
+            if stoploss_value < row[LOW_IDX]:
                 return row[OPEN_IDX]
         else:
-            if trade.stop_loss > row[HIGH_IDX]:
+            if stoploss_value > row[HIGH_IDX]:
                 return row[OPEN_IDX]
 
         # Special case: trailing triggers within same candle as trade opened. Assume most
@@ -433,7 +439,7 @@ class Backtesting:
                 return max(row[LOW_IDX], stop_rate)
 
         # Set close_rate to stoploss
-        return trade.stop_loss
+        return stoploss_value
 
     def _get_close_rate_for_roi(self, row: Tuple, trade: LocalTrade, exit: ExitCheckTuple,
                                 trade_dur: int) -> float:
diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py
index 5f302de71..2ff65d9d0 100644
--- a/freqtrade/persistence/trade_model.py
+++ b/freqtrade/persistence/trade_model.py
@@ -511,17 +511,9 @@ class LocalTrade():
         Method you should use to set self.stop_loss.
         Assures stop_loss is not passed the liquidation price
         """
-        if self.liquidation_price is not None:
-            if self.is_short:
-                sl = min(stop_loss, self.liquidation_price)
-            else:
-                sl = max(stop_loss, self.liquidation_price)
-        else:
-            sl = stop_loss
-
         if not self.stop_loss:
-            self.initial_stop_loss = sl
-        self.stop_loss = sl
+            self.initial_stop_loss = stop_loss
+        self.stop_loss = stop_loss
 
         self.stop_loss_pct = -1 * abs(percent)
         self.stoploss_last_update = datetime.utcnow()
diff --git a/freqtrade/plugins/protections/stoploss_guard.py b/freqtrade/plugins/protections/stoploss_guard.py
index abc90a685..e80d13e9d 100644
--- a/freqtrade/plugins/protections/stoploss_guard.py
+++ b/freqtrade/plugins/protections/stoploss_guard.py
@@ -49,7 +49,7 @@ class StoplossGuard(IProtection):
         trades1 = Trade.get_trades_proxy(pair=pair, is_open=False, close_date=look_back_until)
         trades = [trade for trade in trades1 if (str(trade.exit_reason) in (
             ExitType.TRAILING_STOP_LOSS.value, ExitType.STOP_LOSS.value,
-            ExitType.STOPLOSS_ON_EXCHANGE.value)
+            ExitType.STOPLOSS_ON_EXCHANGE.value, ExitType.LIQUIDATION.value)
             and trade.close_profit and trade.close_profit < self._profit_limit)]
 
         if self._only_per_side:
diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py
index c60817c99..f50721583 100644
--- a/freqtrade/strategy/interface.py
+++ b/freqtrade/strategy/interface.py
@@ -963,7 +963,7 @@ class IStrategy(ABC, HyperStrategyMixin):
         # ROI
         # Trailing stoploss
 
-        if stoplossflag.exit_type == ExitType.STOP_LOSS:
+        if stoplossflag.exit_type in (ExitType.STOP_LOSS, ExitType.LIQUIDATION):
 
             logger.debug(f"{trade.pair} - Stoploss hit. exit_type={stoplossflag.exit_type}")
             exits.append(stoplossflag)
@@ -1035,6 +1035,17 @@ class IStrategy(ABC, HyperStrategyMixin):
 
         sl_higher_long = (trade.stop_loss >= (low or current_rate) and not trade.is_short)
         sl_lower_short = (trade.stop_loss <= (high or current_rate) and trade.is_short)
+        liq_higher_long = (trade.liquidation_price
+                           and trade.liquidation_price >= (low or current_rate)
+                           and not trade.is_short)
+        liq_lower_short = (trade.liquidation_price
+                           and trade.liquidation_price <= (high or current_rate)
+                           and trade.is_short)
+
+        if (liq_higher_long or liq_lower_short):
+            logger.debug(f"{trade.pair} - Liquidation price hit. exit_type=ExitType.LIQUIDATION")
+            return ExitCheckTuple(exit_type=ExitType.LIQUIDATION)
+
         # evaluate if the stoploss was hit if stoploss is not on exchange
         # in Dry-Run, this handles stoploss logic as well, as the logic will not be different to
         # regular stoploss handling.

From 8711b7d99f224b3d0ee26553e32774dd247d605a Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Thu, 28 Jul 2022 20:37:10 +0200
Subject: [PATCH 013/132] Liquidations cannot be rejected.

---
 freqtrade/freqtradebot.py         | 5 +++--
 freqtrade/optimize/backtesting.py | 5 +++--
 2 files changed, 6 insertions(+), 4 deletions(-)

diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py
index 43608cae7..d58c05d7f 100644
--- a/freqtrade/freqtradebot.py
+++ b/freqtrade/freqtradebot.py
@@ -1463,11 +1463,12 @@ class FreqtradeBot(LoggingMixin):
         amount = self._safe_exit_amount(trade.pair, trade.amount)
         time_in_force = self.strategy.order_time_in_force['exit']
 
-        if not strategy_safe_wrapper(self.strategy.confirm_trade_exit, default_retval=True)(
+        if (exit_check.exit_type != ExitType.LIQUIDATION and not strategy_safe_wrapper(
+            self.strategy.confirm_trade_exit, default_retval=True)(
                 pair=trade.pair, trade=trade, order_type=order_type, amount=amount, rate=limit,
                 time_in_force=time_in_force, exit_reason=exit_reason,
                 sell_reason=exit_reason,  # sellreason -> compatibility
-                current_time=datetime.now(timezone.utc)):
+                current_time=datetime.now(timezone.utc))):
             logger.info(f"User denied exit for {trade.pair}.")
             return False
 
diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py
index 598ce6710..6bbace185 100755
--- a/freqtrade/optimize/backtesting.py
+++ b/freqtrade/optimize/backtesting.py
@@ -598,7 +598,8 @@ class Backtesting:
             # Confirm trade exit:
             time_in_force = self.strategy.order_time_in_force['exit']
 
-            if not strategy_safe_wrapper(self.strategy.confirm_trade_exit, default_retval=True)(
+            if (exit_.exit_type != ExitType.LIQUIDATION and not strategy_safe_wrapper(
+                self.strategy.confirm_trade_exit, default_retval=True)(
                     pair=trade.pair,
                     trade=trade,  # type: ignore[arg-type]
                     order_type='limit',
@@ -607,7 +608,7 @@ class Backtesting:
                     time_in_force=time_in_force,
                     sell_reason=exit_reason,  # deprecated
                     exit_reason=exit_reason,
-                    current_time=exit_candle_time):
+                    current_time=exit_candle_time)):
                 return None
 
             trade.exit_reason = exit_reason

From f57ecb18615dc2e75fc73d0da78540ea0ebd6804 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Fri, 29 Jul 2022 06:55:42 +0200
Subject: [PATCH 014/132] Simplify adjust_stop test

---
 tests/test_persistence.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/tests/test_persistence.py b/tests/test_persistence.py
index 838c4c22a..4703075eb 100644
--- a/tests/test_persistence.py
+++ b/tests/test_persistence.py
@@ -1537,26 +1537,26 @@ def test_adjust_stop_loss(fee):
 
     # Get percent of profit with a custom rate (Higher than open rate)
     trade.adjust_stop_loss(1.3, -0.1)
-    assert round(trade.stop_loss, 8) == 1.17
+    assert pytest.approx(trade.stop_loss) == 1.17
     assert trade.stop_loss_pct == -0.1
     assert trade.initial_stop_loss == 0.95
     assert trade.initial_stop_loss_pct == -0.05
 
     # current rate lower again ... should not change
     trade.adjust_stop_loss(1.2, 0.1)
-    assert round(trade.stop_loss, 8) == 1.17
+    assert pytest.approx(trade.stop_loss) == 1.17
     assert trade.initial_stop_loss == 0.95
     assert trade.initial_stop_loss_pct == -0.05
 
     # current rate higher... should raise stoploss
     trade.adjust_stop_loss(1.4, 0.1)
-    assert round(trade.stop_loss, 8) == 1.26
+    assert pytest.approx(trade.stop_loss) == 1.26
     assert trade.initial_stop_loss == 0.95
     assert trade.initial_stop_loss_pct == -0.05
 
     #  Initial is true but stop_loss set - so doesn't do anything
     trade.adjust_stop_loss(1.7, 0.1, True)
-    assert round(trade.stop_loss, 8) == 1.26
+    assert pytest.approx(trade.stop_loss) == 1.26
     assert trade.initial_stop_loss == 0.95
     assert trade.initial_stop_loss_pct == -0.05
     assert trade.stop_loss_pct == -0.1

From 9852733ef7f7284765b8092eb6cd27edd2b7c0e8 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Fri, 29 Jul 2022 06:58:59 +0200
Subject: [PATCH 015/132] Improve tests to align with modified logic

---
 freqtrade/persistence/trade_model.py |  6 ------
 tests/test_persistence.py            | 17 ++++++++++-------
 2 files changed, 10 insertions(+), 13 deletions(-)

diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py
index 2ff65d9d0..919750886 100644
--- a/freqtrade/persistence/trade_model.py
+++ b/freqtrade/persistence/trade_model.py
@@ -535,14 +535,8 @@ class LocalTrade():
         leverage = self.leverage or 1.0
         if self.is_short:
             new_loss = float(current_price * (1 + abs(stoploss / leverage)))
-            # If trading with leverage, don't set the stoploss below the liquidation price
-            if self.liquidation_price:
-                new_loss = min(self.liquidation_price, new_loss)
         else:
             new_loss = float(current_price * (1 - abs(stoploss / leverage)))
-            # If trading with leverage, don't set the stoploss below the liquidation price
-            if self.liquidation_price:
-                new_loss = max(self.liquidation_price, new_loss)
 
         # no stop loss assigned yet
         if self.initial_stop_loss_pct is None or refresh:
diff --git a/tests/test_persistence.py b/tests/test_persistence.py
index 4703075eb..5476e1d50 100644
--- a/tests/test_persistence.py
+++ b/tests/test_persistence.py
@@ -133,13 +133,14 @@ def test_set_stop_loss_isolated_liq(fee):
     trade.set_isolated_liq(0.11)
     trade._set_stop_loss(0.1, 0)
     assert trade.liquidation_price == 0.11
-    assert trade.stop_loss == 0.11
+    # Stoploss does not change from liquidation price
+    assert trade.stop_loss == 0.1
     assert trade.initial_stop_loss == 0.1
 
     # lower stop doesn't move stoploss
     trade._set_stop_loss(0.1, 0)
     assert trade.liquidation_price == 0.11
-    assert trade.stop_loss == 0.11
+    assert trade.stop_loss == 0.1
     assert trade.initial_stop_loss == 0.1
 
     trade.stop_loss = None
@@ -174,13 +175,14 @@ def test_set_stop_loss_isolated_liq(fee):
     trade.set_isolated_liq(0.07)
     trade._set_stop_loss(0.1, (1.0 / 8.0))
     assert trade.liquidation_price == 0.07
-    assert trade.stop_loss == 0.07
+    # Stoploss does not change from liquidation price
+    assert trade.stop_loss == 0.1
     assert trade.initial_stop_loss == 0.08
 
     # Stop doesn't move stop higher
     trade._set_stop_loss(0.1, (1.0 / 9.0))
     assert trade.liquidation_price == 0.07
-    assert trade.stop_loss == 0.07
+    assert trade.stop_loss == 0.1
     assert trade.initial_stop_loss == 0.08
 
 
@@ -1609,9 +1611,10 @@ def test_adjust_stop_loss_short(fee):
     assert trade.initial_stop_loss == 1.05
     assert trade.initial_stop_loss_pct == -0.05
     assert trade.stop_loss_pct == -0.1
+    # Liquidation price is lower than stoploss - so liquidation would trigger first.
     trade.set_isolated_liq(0.63)
     trade.adjust_stop_loss(0.59, -0.1)
-    assert trade.stop_loss == 0.63
+    assert trade.stop_loss == 0.649
     assert trade.liquidation_price == 0.63
 
 
@@ -2011,8 +2014,8 @@ def test_stoploss_reinitialization_short(default_conf, fee):
     # Stoploss can't go above liquidation price
     trade_adj.set_isolated_liq(0.985)
     trade.adjust_stop_loss(0.9799, -0.05)
-    assert trade_adj.stop_loss == 0.985
-    assert trade_adj.stop_loss == 0.985
+    assert trade_adj.stop_loss == 0.989699
+    assert trade_adj.liquidation_price == 0.985
 
 
 def test_update_fee(fee):

From ff4cc5d3165b53058c1b80f8f94bb16df2345269 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Fri, 29 Jul 2022 07:14:25 +0200
Subject: [PATCH 016/132] Revamp liquidation test to actually make sense

---
 tests/test_persistence.py | 79 +++++++++++++++++++++++----------------
 1 file changed, 46 insertions(+), 33 deletions(-)

diff --git a/tests/test_persistence.py b/tests/test_persistence.py
index 5476e1d50..5dbd6b86b 100644
--- a/tests/test_persistence.py
+++ b/tests/test_persistence.py
@@ -120,70 +120,83 @@ def test_set_stop_loss_isolated_liq(fee):
     assert trade.stop_loss is None
     assert trade.initial_stop_loss is None
 
-    trade._set_stop_loss(0.1, (1.0 / 9.0))
+    trade.adjust_stop_loss(2.0, 0.2, True)
     assert trade.liquidation_price == 0.09
-    assert trade.stop_loss == 0.1
-    assert trade.initial_stop_loss == 0.1
+    assert trade.stop_loss == 1.8
+    assert trade.initial_stop_loss == 1.8
 
     trade.set_isolated_liq(0.08)
     assert trade.liquidation_price == 0.08
-    assert trade.stop_loss == 0.1
-    assert trade.initial_stop_loss == 0.1
+    assert trade.stop_loss == 1.8
+    assert trade.initial_stop_loss == 1.8
 
     trade.set_isolated_liq(0.11)
-    trade._set_stop_loss(0.1, 0)
+    trade.adjust_stop_loss(2.0, 0.2)
     assert trade.liquidation_price == 0.11
     # Stoploss does not change from liquidation price
-    assert trade.stop_loss == 0.1
-    assert trade.initial_stop_loss == 0.1
+    assert trade.stop_loss == 1.8
+    assert trade.initial_stop_loss == 1.8
 
     # lower stop doesn't move stoploss
-    trade._set_stop_loss(0.1, 0)
+    trade.adjust_stop_loss(1.8, 0.2)
     assert trade.liquidation_price == 0.11
-    assert trade.stop_loss == 0.1
-    assert trade.initial_stop_loss == 0.1
+    assert trade.stop_loss == 1.8
+    assert trade.initial_stop_loss == 1.8
+
+    # higher stop does move stoploss
+    trade.adjust_stop_loss(2.1, 0.1)
+    assert trade.liquidation_price == 0.11
+    assert pytest.approx(trade.stop_loss) == 1.994999
+    assert trade.initial_stop_loss == 1.8
 
     trade.stop_loss = None
     trade.liquidation_price = None
     trade.initial_stop_loss = None
+    trade.initial_stop_loss_pct = None
 
-    trade._set_stop_loss(0.07, 0)
+    trade.adjust_stop_loss(2.0, 0.1, True)
     assert trade.liquidation_price is None
-    assert trade.stop_loss == 0.07
-    assert trade.initial_stop_loss == 0.07
+    assert trade.stop_loss == 1.9
+    assert trade.initial_stop_loss == 1.9
 
     trade.is_short = True
     trade.recalc_open_trade_value()
     trade.stop_loss = None
     trade.initial_stop_loss = None
+    trade.initial_stop_loss_pct = None
 
-    trade.set_isolated_liq(0.09)
-    assert trade.liquidation_price == 0.09
+    trade.set_isolated_liq(3.09)
+    assert trade.liquidation_price == 3.09
     assert trade.stop_loss is None
     assert trade.initial_stop_loss is None
 
-    trade._set_stop_loss(0.08, (1.0 / 9.0))
-    assert trade.liquidation_price == 0.09
-    assert trade.stop_loss == 0.08
-    assert trade.initial_stop_loss == 0.08
+    trade.adjust_stop_loss(2.0, 0.2)
+    assert trade.liquidation_price == 3.09
+    assert trade.stop_loss == 2.2
+    assert trade.initial_stop_loss == 2.2
 
-    trade.set_isolated_liq(0.1)
-    assert trade.liquidation_price == 0.1
-    assert trade.stop_loss == 0.08
-    assert trade.initial_stop_loss == 0.08
+    trade.set_isolated_liq(3.1)
+    assert trade.liquidation_price == 3.1
+    assert trade.stop_loss == 2.2
+    assert trade.initial_stop_loss == 2.2
 
-    trade.set_isolated_liq(0.07)
-    trade._set_stop_loss(0.1, (1.0 / 8.0))
-    assert trade.liquidation_price == 0.07
+    trade.set_isolated_liq(3.8)
+    assert trade.liquidation_price == 3.8
     # Stoploss does not change from liquidation price
-    assert trade.stop_loss == 0.1
-    assert trade.initial_stop_loss == 0.08
+    assert trade.stop_loss == 2.2
+    assert trade.initial_stop_loss == 2.2
 
     # Stop doesn't move stop higher
-    trade._set_stop_loss(0.1, (1.0 / 9.0))
-    assert trade.liquidation_price == 0.07
-    assert trade.stop_loss == 0.1
-    assert trade.initial_stop_loss == 0.08
+    trade.adjust_stop_loss(2.0, 0.3)
+    assert trade.liquidation_price == 3.8
+    assert trade.stop_loss == 2.2
+    assert trade.initial_stop_loss == 2.2
+
+    # Stoploss does move lower
+    trade.adjust_stop_loss(1.8, 0.1)
+    assert trade.liquidation_price == 3.8
+    assert pytest.approx(trade.stop_loss) == 1.89
+    assert trade.initial_stop_loss == 2.2
 
 
 @pytest.mark.parametrize('exchange,is_short,lev,minutes,rate,interest,trading_mode', [

From 15752ce3c2d4b2131e9141c3aa496dda25c5d9d7 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Fri, 29 Jul 2022 07:15:01 +0200
Subject: [PATCH 017/132] Rename set_stoploss method to be fully private

---
 freqtrade/persistence/trade_model.py | 9 ++++-----
 1 file changed, 4 insertions(+), 5 deletions(-)

diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py
index 919750886..1b8bcc42f 100644
--- a/freqtrade/persistence/trade_model.py
+++ b/freqtrade/persistence/trade_model.py
@@ -506,10 +506,9 @@ class LocalTrade():
             return
         self.liquidation_price = liquidation_price
 
-    def _set_stop_loss(self, stop_loss: float, percent: float):
+    def __set_stop_loss(self, stop_loss: float, percent: float):
         """
-        Method you should use to set self.stop_loss.
-        Assures stop_loss is not passed the liquidation price
+        Method used internally to set self.stop_loss.
         """
         if not self.stop_loss:
             self.initial_stop_loss = stop_loss
@@ -540,7 +539,7 @@ class LocalTrade():
 
         # no stop loss assigned yet
         if self.initial_stop_loss_pct is None or refresh:
-            self._set_stop_loss(new_loss, stoploss)
+            self.__set_stop_loss(new_loss, stoploss)
             self.initial_stop_loss = new_loss
             self.initial_stop_loss_pct = -1 * abs(stoploss)
 
@@ -555,7 +554,7 @@ class LocalTrade():
             #   ? decreasing the minimum stoploss
             if (higher_stop and not self.is_short) or (lower_stop and self.is_short):
                 logger.debug(f"{self.pair} - Adjusting stoploss...")
-                self._set_stop_loss(new_loss, stoploss)
+                self.__set_stop_loss(new_loss, stoploss)
             else:
                 logger.debug(f"{self.pair} - Keeping current stoploss...")
 

From 4da96bc511c1a01ee717f304d60696141797d200 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 30 Jul 2022 07:27:24 +0200
Subject: [PATCH 018/132] Update docs

---
 docs/strategy-callbacks.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/docs/strategy-callbacks.md b/docs/strategy-callbacks.md
index f584bd1bb..59d221bfc 100644
--- a/docs/strategy-callbacks.md
+++ b/docs/strategy-callbacks.md
@@ -623,6 +623,7 @@ class AwesomeStrategy(IStrategy):
 
 !!! Warning
     `confirm_trade_exit()` can prevent stoploss exits, causing significant losses as this would ignore stoploss exits.
+    `confirm_trade_exit()` will not be called for Liquidations - as liquidations are forced by the exchange, and therefore cannot be rejected.
 
 ## Adjust trade position
 

From 845cecd38fe0acfed72d99eddccc5aea37234cfc Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 30 Jul 2022 08:12:48 +0200
Subject: [PATCH 019/132] Add stoploss or liquidation property

---
 freqtrade/persistence/trade_model.py | 10 ++++++++++
 freqtrade/strategy/interface.py      |  7 -------
 tests/test_persistence.py            | 10 +++++++++-
 3 files changed, 19 insertions(+), 8 deletions(-)

diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py
index 1b8bcc42f..244ca79cd 100644
--- a/freqtrade/persistence/trade_model.py
+++ b/freqtrade/persistence/trade_model.py
@@ -302,6 +302,16 @@ class LocalTrade():
     # Futures properties
     funding_fees: Optional[float] = None
 
+    @property
+    def stoploss_or_liquidation(self) -> float:
+        if self.liquidation_price:
+            if self.is_short:
+                return min(self.stop_loss, self.liquidation_price)
+            else:
+                return max(self.stop_loss, self.liquidation_price)
+
+        return self.stop_loss
+
     @property
     def buy_tag(self) -> Optional[str]:
         """
diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py
index f50721583..824f31258 100644
--- a/freqtrade/strategy/interface.py
+++ b/freqtrade/strategy/interface.py
@@ -1063,13 +1063,6 @@ class IStrategy(ABC, HyperStrategyMixin):
                     f"stoploss is {trade.stop_loss:.6f}, "
                     f"initial stoploss was at {trade.initial_stop_loss:.6f}, "
                     f"trade opened at {trade.open_rate:.6f}")
-                new_stoploss = (
-                    trade.stop_loss + trade.initial_stop_loss
-                    if trade.is_short else
-                    trade.stop_loss - trade.initial_stop_loss
-                )
-                logger.debug(f"{trade.pair} - Trailing stop saved "
-                             f"{new_stoploss:.6f}")
 
             return ExitCheckTuple(exit_type=exit_type)
 
diff --git a/tests/test_persistence.py b/tests/test_persistence.py
index 5dbd6b86b..3eca035c9 100644
--- a/tests/test_persistence.py
+++ b/tests/test_persistence.py
@@ -148,6 +148,7 @@ def test_set_stop_loss_isolated_liq(fee):
     assert trade.liquidation_price == 0.11
     assert pytest.approx(trade.stop_loss) == 1.994999
     assert trade.initial_stop_loss == 1.8
+    assert trade.stoploss_or_liquidation == trade.stop_loss
 
     trade.stop_loss = None
     trade.liquidation_price = None
@@ -158,6 +159,7 @@ def test_set_stop_loss_isolated_liq(fee):
     assert trade.liquidation_price is None
     assert trade.stop_loss == 1.9
     assert trade.initial_stop_loss == 1.9
+    assert trade.stoploss_or_liquidation == 1.9
 
     trade.is_short = True
     trade.recalc_open_trade_value()
@@ -174,11 +176,13 @@ def test_set_stop_loss_isolated_liq(fee):
     assert trade.liquidation_price == 3.09
     assert trade.stop_loss == 2.2
     assert trade.initial_stop_loss == 2.2
+    assert trade.stoploss_or_liquidation == 2.2
 
     trade.set_isolated_liq(3.1)
     assert trade.liquidation_price == 3.1
     assert trade.stop_loss == 2.2
     assert trade.initial_stop_loss == 2.2
+    assert trade.stoploss_or_liquidation == 2.2
 
     trade.set_isolated_liq(3.8)
     assert trade.liquidation_price == 3.8
@@ -193,10 +197,14 @@ def test_set_stop_loss_isolated_liq(fee):
     assert trade.initial_stop_loss == 2.2
 
     # Stoploss does move lower
+    trade.set_isolated_liq(1.5)
     trade.adjust_stop_loss(1.8, 0.1)
-    assert trade.liquidation_price == 3.8
+    assert trade.liquidation_price == 1.5
     assert pytest.approx(trade.stop_loss) == 1.89
     assert trade.initial_stop_loss == 2.2
+    assert trade.stoploss_or_liquidation == 1.5
+
+
 
 
 @pytest.mark.parametrize('exchange,is_short,lev,minutes,rate,interest,trading_mode', [

From dba7a7257dec1371c1bea14c099dbca06474e3ff Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 30 Jul 2022 09:18:15 +0200
Subject: [PATCH 020/132] Use stop_or_liquidation instead of stop_loss

---
 freqtrade/freqtradebot.py | 11 ++++++-----
 1 file changed, 6 insertions(+), 5 deletions(-)

diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py
index d58c05d7f..7440212c3 100644
--- a/freqtrade/freqtradebot.py
+++ b/freqtrade/freqtradebot.py
@@ -1015,7 +1015,7 @@ class FreqtradeBot(LoggingMixin):
             trade.stoploss_order_id = None
             logger.error(f'Unable to place a stoploss order on exchange. {e}')
             logger.warning('Exiting the trade forcefully')
-            self.execute_trade_exit(trade, trade.stop_loss, exit_check=ExitCheckTuple(
+            self.execute_trade_exit(trade, stop_price, exit_check=ExitCheckTuple(
                 exit_type=ExitType.EMERGENCY_EXIT))
 
         except ExchangeError:
@@ -1114,7 +1114,7 @@ class FreqtradeBot(LoggingMixin):
         :param order: Current on exchange stoploss order
         :return: None
         """
-        stoploss_norm = self.exchange.price_to_precision(trade.pair, trade.stop_loss)
+        stoploss_norm = self.exchange.price_to_precision(trade.pair, trade.stoploss_or_liquidation)
 
         if self.exchange.stoploss_adjust(stoploss_norm, order, side=trade.exit_side):
             # we check if the update is necessary
@@ -1132,7 +1132,7 @@ class FreqtradeBot(LoggingMixin):
                                      f"for pair {trade.pair}")
 
                 # Create new stoploss order
-                if not self.create_stoploss_order(trade=trade, stop_price=trade.stop_loss):
+                if not self.create_stoploss_order(trade=trade, stop_price=stoploss_norm):
                     logger.warning(f"Could not create trailing stoploss order "
                                    f"for pair {trade.pair}.")
 
@@ -1431,14 +1431,15 @@ class FreqtradeBot(LoggingMixin):
         )
         exit_type = 'exit'
         exit_reason = exit_tag or exit_check.exit_reason
-        if exit_check.exit_type in (ExitType.STOP_LOSS, ExitType.TRAILING_STOP_LOSS):
+        if exit_check.exit_type in (
+                ExitType.STOP_LOSS, ExitType.TRAILING_STOP_LOSS, ExitType.LIQUIDATION):
             exit_type = 'stoploss'
 
         # if stoploss is on exchange and we are on dry_run mode,
         # we consider the sell price stop price
         if (self.config['dry_run'] and exit_type == 'stoploss'
            and self.strategy.order_types['stoploss_on_exchange']):
-            limit = trade.stop_loss
+            limit = trade.stoploss_or_liquidation
 
         # set custom_exit_price if available
         proposed_limit_rate = limit

From d046f0cc5e766ec24f5c88fd967b44ea88698481 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 30 Jul 2022 09:19:48 +0200
Subject: [PATCH 021/132] Improve method wording for liquidation price setter

---
 freqtrade/freqtradebot.py            |  4 ++--
 freqtrade/optimize/backtesting.py    |  2 +-
 freqtrade/persistence/trade_model.py |  2 +-
 tests/test_persistence.py            | 22 ++++++++++------------
 4 files changed, 14 insertions(+), 16 deletions(-)

diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py
index 7440212c3..3490b58d6 100644
--- a/freqtrade/freqtradebot.py
+++ b/freqtrade/freqtradebot.py
@@ -1085,7 +1085,7 @@ class FreqtradeBot(LoggingMixin):
         if (trade.is_open
                 and stoploss_order
                 and stoploss_order['status'] in ('canceled', 'cancelled')):
-            if self.create_stoploss_order(trade=trade, stop_price=trade.stop_loss):
+            if self.create_stoploss_order(trade=trade, stop_price=trade.stoploss_or_liquidation):
                 return False
             else:
                 trade.stoploss_order_id = None
@@ -1662,7 +1662,7 @@ class FreqtradeBot(LoggingMixin):
                 trade = self.cancel_stoploss_on_exchange(trade)
                 # TODO: Margin will need to use interest_rate as well.
                 # interest_rate = self.exchange.get_interest_rate()
-                trade.set_isolated_liq(self.exchange.get_liquidation_price(
+                trade.set_liquidation_price(self.exchange.get_liquidation_price(
                     leverage=trade.leverage,
                     pair=trade.pair,
                     amount=trade.amount,
diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py
index 6bbace185..2c6cfb0e9 100755
--- a/freqtrade/optimize/backtesting.py
+++ b/freqtrade/optimize/backtesting.py
@@ -814,7 +814,7 @@ class Backtesting:
 
             trade.adjust_stop_loss(trade.open_rate, self.strategy.stoploss, initial=True)
 
-            trade.set_isolated_liq(self.exchange.get_liquidation_price(
+            trade.set_liquidation_price(self.exchange.get_liquidation_price(
                 pair=pair,
                 open_rate=propose_rate,
                 amount=amount,
diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py
index 244ca79cd..44e148a0c 100644
--- a/freqtrade/persistence/trade_model.py
+++ b/freqtrade/persistence/trade_model.py
@@ -507,7 +507,7 @@ class LocalTrade():
         self.max_rate = max(current_price, self.max_rate or self.open_rate)
         self.min_rate = min(current_price_low, self.min_rate or self.open_rate)
 
-    def set_isolated_liq(self, liquidation_price: Optional[float]):
+    def set_liquidation_price(self, liquidation_price: Optional[float]):
         """
         Method you should use to set self.liquidation price.
         Assures stop_loss is not passed the liquidation price
diff --git a/tests/test_persistence.py b/tests/test_persistence.py
index 3eca035c9..0c1fc01a5 100644
--- a/tests/test_persistence.py
+++ b/tests/test_persistence.py
@@ -99,7 +99,7 @@ def test_enter_exit_side(fee, is_short):
 
 
 @pytest.mark.usefixtures("init_persistence")
-def test_set_stop_loss_isolated_liq(fee):
+def test_set_stop_loss_liquidation(fee):
     trade = Trade(
         id=2,
         pair='ADA/USDT',
@@ -115,7 +115,7 @@ def test_set_stop_loss_isolated_liq(fee):
         leverage=2.0,
         trading_mode=margin
     )
-    trade.set_isolated_liq(0.09)
+    trade.set_liquidation_price(0.09)
     assert trade.liquidation_price == 0.09
     assert trade.stop_loss is None
     assert trade.initial_stop_loss is None
@@ -125,12 +125,12 @@ def test_set_stop_loss_isolated_liq(fee):
     assert trade.stop_loss == 1.8
     assert trade.initial_stop_loss == 1.8
 
-    trade.set_isolated_liq(0.08)
+    trade.set_liquidation_price(0.08)
     assert trade.liquidation_price == 0.08
     assert trade.stop_loss == 1.8
     assert trade.initial_stop_loss == 1.8
 
-    trade.set_isolated_liq(0.11)
+    trade.set_liquidation_price(0.11)
     trade.adjust_stop_loss(2.0, 0.2)
     assert trade.liquidation_price == 0.11
     # Stoploss does not change from liquidation price
@@ -167,7 +167,7 @@ def test_set_stop_loss_isolated_liq(fee):
     trade.initial_stop_loss = None
     trade.initial_stop_loss_pct = None
 
-    trade.set_isolated_liq(3.09)
+    trade.set_liquidation_price(3.09)
     assert trade.liquidation_price == 3.09
     assert trade.stop_loss is None
     assert trade.initial_stop_loss is None
@@ -178,13 +178,13 @@ def test_set_stop_loss_isolated_liq(fee):
     assert trade.initial_stop_loss == 2.2
     assert trade.stoploss_or_liquidation == 2.2
 
-    trade.set_isolated_liq(3.1)
+    trade.set_liquidation_price(3.1)
     assert trade.liquidation_price == 3.1
     assert trade.stop_loss == 2.2
     assert trade.initial_stop_loss == 2.2
     assert trade.stoploss_or_liquidation == 2.2
 
-    trade.set_isolated_liq(3.8)
+    trade.set_liquidation_price(3.8)
     assert trade.liquidation_price == 3.8
     # Stoploss does not change from liquidation price
     assert trade.stop_loss == 2.2
@@ -197,7 +197,7 @@ def test_set_stop_loss_isolated_liq(fee):
     assert trade.initial_stop_loss == 2.2
 
     # Stoploss does move lower
-    trade.set_isolated_liq(1.5)
+    trade.set_liquidation_price(1.5)
     trade.adjust_stop_loss(1.8, 0.1)
     assert trade.liquidation_price == 1.5
     assert pytest.approx(trade.stop_loss) == 1.89
@@ -205,8 +205,6 @@ def test_set_stop_loss_isolated_liq(fee):
     assert trade.stoploss_or_liquidation == 1.5
 
 
-
-
 @pytest.mark.parametrize('exchange,is_short,lev,minutes,rate,interest,trading_mode', [
     ("binance", False, 3, 10, 0.0005, round(0.0008333333333333334, 8), margin),
     ("binance", True, 3, 10, 0.0005, 0.000625, margin),
@@ -1633,7 +1631,7 @@ def test_adjust_stop_loss_short(fee):
     assert trade.initial_stop_loss_pct == -0.05
     assert trade.stop_loss_pct == -0.1
     # Liquidation price is lower than stoploss - so liquidation would trigger first.
-    trade.set_isolated_liq(0.63)
+    trade.set_liquidation_price(0.63)
     trade.adjust_stop_loss(0.59, -0.1)
     assert trade.stop_loss == 0.649
     assert trade.liquidation_price == 0.63
@@ -2033,7 +2031,7 @@ def test_stoploss_reinitialization_short(default_conf, fee):
     assert trade_adj.initial_stop_loss == 1.01
     assert trade_adj.initial_stop_loss_pct == -0.05
     # Stoploss can't go above liquidation price
-    trade_adj.set_isolated_liq(0.985)
+    trade_adj.set_liquidation_price(0.985)
     trade.adjust_stop_loss(0.9799, -0.05)
     assert trade_adj.stop_loss == 0.989699
     assert trade_adj.liquidation_price == 0.985

From dc82675f00e5ed1b006eeb1490a3f14147cde979 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 30 Jul 2022 17:28:16 +0200
Subject: [PATCH 022/132] Add Test for liquidation in stop-loss-reached

---
 tests/strategy/test_interface.py | 30 +++++++++++++++++-------------
 1 file changed, 17 insertions(+), 13 deletions(-)

diff --git a/tests/strategy/test_interface.py b/tests/strategy/test_interface.py
index f6996a7a2..4257b2cf9 100644
--- a/tests/strategy/test_interface.py
+++ b/tests/strategy/test_interface.py
@@ -408,28 +408,31 @@ def test_min_roi_reached3(default_conf, fee) -> None:
 
 
 @pytest.mark.parametrize(
-    'profit,adjusted,expected,trailing,custom,profit2,adjusted2,expected2,custom_stop', [
+    'profit,adjusted,expected,liq,trailing,custom,profit2,adjusted2,expected2,custom_stop', [
         # Profit, adjusted stoploss(absolute), profit for 2nd call, enable trailing,
         #   enable custom stoploss, expected after 1st call, expected after 2nd call
-        (0.2, 0.9, ExitType.NONE, False, False, 0.3, 0.9, ExitType.NONE, None),
-        (0.2, 0.9, ExitType.NONE, False, False, -0.2, 0.9, ExitType.STOP_LOSS, None),
-        (0.2, 1.14, ExitType.NONE, True, False, 0.05, 1.14, ExitType.TRAILING_STOP_LOSS, None),
-        (0.01, 0.96, ExitType.NONE, True, False, 0.05, 1, ExitType.NONE, None),
-        (0.05, 1, ExitType.NONE, True, False, -0.01, 1, ExitType.TRAILING_STOP_LOSS, None),
+        (0.2, 0.9, ExitType.NONE, None, False, False, 0.3, 0.9, ExitType.NONE, None),
+        (0.2, 0.9, ExitType.NONE, None, False, False, -0.2, 0.9, ExitType.STOP_LOSS, None),
+        (0.2, 0.9, ExitType.NONE, 0.8, False, False, -0.2, 0.9, ExitType.LIQUIDATION, None),
+        (0.2, 1.14, ExitType.NONE, None, True, False, 0.05, 1.14, ExitType.TRAILING_STOP_LOSS,
+         None),
+        (0.01, 0.96, ExitType.NONE, None, True, False, 0.05, 1, ExitType.NONE, None),
+        (0.05, 1, ExitType.NONE, None, True, False, -0.01, 1, ExitType.TRAILING_STOP_LOSS, None),
         # Default custom case - trails with 10%
-        (0.05, 0.95, ExitType.NONE, False, True, -0.02, 0.95, ExitType.NONE, None),
-        (0.05, 0.95, ExitType.NONE, False, True, -0.06, 0.95, ExitType.TRAILING_STOP_LOSS, None),
-        (0.05, 1, ExitType.NONE, False, True, -0.06, 1, ExitType.TRAILING_STOP_LOSS,
+        (0.05, 0.95, ExitType.NONE, None, False, True, -0.02, 0.95, ExitType.NONE, None),
+        (0.05, 0.95, ExitType.NONE, None, False, True, -0.06, 0.95, ExitType.TRAILING_STOP_LOSS,
+         None),
+        (0.05, 1, ExitType.NONE, None, False, True, -0.06, 1, ExitType.TRAILING_STOP_LOSS,
          lambda **kwargs: -0.05),
-        (0.05, 1, ExitType.NONE, False, True, 0.09, 1.04, ExitType.NONE,
+        (0.05, 1, ExitType.NONE, None, False, True, 0.09, 1.04, ExitType.NONE,
          lambda **kwargs: -0.05),
-        (0.05, 0.95, ExitType.NONE, False, True, 0.09, 0.98, ExitType.NONE,
+        (0.05, 0.95, ExitType.NONE, None, False, True, 0.09, 0.98, ExitType.NONE,
          lambda current_profit, **kwargs: -0.1 if current_profit < 0.6 else -(current_profit * 2)),
         # Error case - static stoploss in place
-        (0.05, 0.9, ExitType.NONE, False, True, 0.09, 0.9, ExitType.NONE,
+        (0.05, 0.9, ExitType.NONE, None, False, True, 0.09, 0.9, ExitType.NONE,
          lambda **kwargs: None),
     ])
-def test_stop_loss_reached(default_conf, fee, profit, adjusted, expected, trailing, custom,
+def test_stop_loss_reached(default_conf, fee, profit, adjusted, expected, liq, trailing, custom,
                            profit2, adjusted2, expected2, custom_stop) -> None:
 
     strategy = StrategyResolver.load_strategy(default_conf)
@@ -442,6 +445,7 @@ def test_stop_loss_reached(default_conf, fee, profit, adjusted, expected, traili
         fee_close=fee.return_value,
         exchange='binance',
         open_rate=1,
+        liquidation_price=liq,
     )
     trade.adjust_min_max_rates(trade.open_rate, trade.open_rate)
     strategy.trailing_stop = trailing

From bad15f077c66710314b7dea75d0e5f7abee767a3 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 30 Jul 2022 17:49:06 +0200
Subject: [PATCH 023/132] Simplify fetch_positions by using already existing
 method

---
 freqtrade/exchange/exchange.py  | 33 ++++++++++++++++-----------------
 tests/exchange/test_exchange.py | 14 --------------
 2 files changed, 16 insertions(+), 31 deletions(-)

diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py
index 79bc769e6..e180c90b2 100644
--- a/freqtrade/exchange/exchange.py
+++ b/freqtrade/exchange/exchange.py
@@ -1332,11 +1332,19 @@ class Exchange:
             raise OperationalException(e) from e
 
     @retrier
-    def fetch_positions(self) -> List[Dict]:
+    def fetch_positions(self, pair: str = None) -> List[Dict]:
+        """
+        Fetch positions from the exchange.
+        If no pair is given, all positions are returned.
+        :param pair: Pair for the query
+        """
         if self._config['dry_run'] or self.trading_mode != TradingMode.FUTURES:
             return []
         try:
-            positions: List[Dict] = self._api.fetch_positions()
+            symbols = []
+            if pair:
+                symbols.append(pair)
+            positions: List[Dict] = self._api.fetch_positions(symbols)
             self._log_exchange_response('fetch_positions', positions)
             return positions
         except ccxt.DDoSProtection as e:
@@ -2539,7 +2547,6 @@ class Exchange:
         else:
             return 0.0
 
-    @retrier
     def get_or_calculate_liquidation_price(
         self,
         pair: str,
@@ -2573,20 +2580,12 @@ class Exchange:
                 upnl_ex_1=upnl_ex_1
             )
         else:
-            try:
-                positions = self._api.fetch_positions([pair])
-                if len(positions) > 0:
-                    pos = positions[0]
-                    isolated_liq = pos['liquidationPrice']
-                else:
-                    return None
-            except ccxt.DDoSProtection as e:
-                raise DDosProtection(e) from e
-            except (ccxt.NetworkError, ccxt.ExchangeError) as e:
-                raise TemporaryError(
-                    f'Could not set margin mode due to {e.__class__.__name__}. Message: {e}') from e
-            except ccxt.BaseError as e:
-                raise OperationalException(e) from e
+            positions = self.fetch_positions(pair)
+            if len(positions) > 0:
+                pos = positions[0]
+                isolated_liq = pos['liquidationPrice']
+            else:
+                return None
 
         if isolated_liq:
             buffer_amount = abs(open_rate - isolated_liq) * self.liquidation_buffer
diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py
index 9252040ea..e968b12c2 100644
--- a/tests/exchange/test_exchange.py
+++ b/tests/exchange/test_exchange.py
@@ -4099,20 +4099,6 @@ def test_get_or_calculate_liquidation_price(mocker, default_conf):
     )
     assert liq_price == 17.540699999999998
 
-    ccxt_exceptionhandlers(
-        mocker,
-        default_conf,
-        api_mock,
-        "binance",
-        "get_or_calculate_liquidation_price",
-        "fetch_positions",
-        pair="XRP/USDT",
-        open_rate=0.0,
-        is_short=False,
-        position=0.0,
-        wallet_balance=0.0,
-    )
-
 
 @pytest.mark.parametrize('exchange,rate_start,rate_end,d1,d2,amount,expected_fees', [
     ('binance', 0, 2, "2021-09-01 01:00:00", "2021-09-01 04:00:00",  30.0, 0.0),

From c2eaa3d2cde4db76111d93f9a1281676838861e0 Mon Sep 17 00:00:00 2001
From: Robert Caulk <rob.caulk@gmail.com>
Date: Sat, 30 Jul 2022 18:51:00 +0200
Subject: [PATCH 024/132] add image of algorithmic overview to doc

---
 docs/assets/freqai_algo.png | Bin 0 -> 335507 bytes
 docs/freqai.md              |  18 ++++++++----------
 2 files changed, 8 insertions(+), 10 deletions(-)
 create mode 100644 docs/assets/freqai_algo.png

diff --git a/docs/assets/freqai_algo.png b/docs/assets/freqai_algo.png
new file mode 100644
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diff --git a/docs/freqai.md b/docs/freqai.md
index c4d0ad0f8..bffa12e5d 100644
--- a/docs/freqai.md
+++ b/docs/freqai.md
@@ -19,12 +19,13 @@ Among the the features included:
 
 ## General approach
 
-The user provides FreqAI with a set of custom indicators (created inside the strategy the same way
-a typical Freqtrade strategy is created) as well as a target value (typically some price change into the future).
-FreqAI trains a model to predict the target value based on the input of custom indicators.
-FreqAI will train and save a new model for each pair in the config whitelist.
-Users employ FreqAI to backtest a strategy (emulate reality with retraining a model as new data is introduced) and run the model live to generate entry and exit signals. 
-In dry/live, FreqAI works in a background thread to keep all models as updated as possible with consistent retraining.
+The user provides FreqAI with a set of custom *base* indicators (created inside the strategy the same way
+a typical Freqtrade strategy is created) as well as target values which look into the future.
+FreqAI trains a model to predict the target value based on the input of custom indicators for each pair in the whitelist. These models are consistently retrained to adapt to market conditions. FreqAI offers the ability to both backtest strategies (emulating reality with periodic retraining) and deploy dry/live. In dry/live conditions, FreqAI can be set to constant retraining in a background thread in an effort to keep models as young as possible. 
+
+An overview of the algorithm is shown here to help users understand the data processing pipeline and the model usage. 
+
+![freqai-algo](assets/freqai_algo.png)
 
 ## Background and vocabulary
 
@@ -97,7 +98,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `weight_factor` | Used to set weights for training data points according to their recency, see details and a figure of how it works [here](##controlling-the-model-learning-process). <br> **Datatype:** positive float (typically below 1).
 | `principal_component_analysis` | Ask FreqAI to automatically reduce the dimensionality of the data set using PCA. <br> **Datatype:** boolean.
 | `use_SVM_to_remove_outliers` | Ask FreqAI to train a support vector machine to detect and remove outliers from the training data set as well as from incoming data points. <br> **Datatype:** boolean.
-| `svm_params` | All parameters available in Sklearn's `SGDOneClassSVM()`. E.g. `nu` *Very* broadly, is the percentage of data points that should be considered outliers. `shuffle` is by default false to maintain reprodicibility. But these and all others can be added/changed in this dictionary. <br> **Datatype:** dictionary.
+| `svm_nu` | The `nu` parameter for the support vector machine. *Very* broadly, this is the percentage of data points that should be considered outliers. <br> **Datatype:** float between 0 and 1.
 | `stratify_training_data` | This value is used to indicate the stratification of the data. e.g. 2 would set every 2nd data point into a separate dataset to be pulled from during training/testing. <br> **Datatype:** positive integer.
 | `indicator_max_period_candles` | The maximum *period* used in `populate_any_indicators()` for indicator creation. FreqAI uses this information in combination with the maximum timeframe to calculate how many data points it should download so that the first data point does not have a NaN <br> **Datatype:** positive integer.
 | `indicator_periods_candles` | A list of integers used to duplicate all indicators according to a set of periods and add them to the feature set. <br> **Datatype:** list of positive integers.
@@ -110,9 +111,6 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `n_estimators` | A common parameter among regressors which sets the number of boosted trees to fit <br> **Datatype:** integer.
 | `learning_rate` | A common parameter among regressors which sets the boosting learning rate. <br> **Datatype:** float.
 | `n_jobs`, `thread_count`, `task_type` | Different libraries use different parameter names to control the number of threads used for parallel processing or whether or not it is a `task_type` of `gpu` or `cpu`. <br> **Datatype:** float.
-|  |  **Extraneous parameters**
-| `keras` | If your model makes use of keras (typical of Tensorflow based prediction models), activate this flag so that the model save/loading follows keras standards. Default value `false`  <br> **Datatype:** boolean.
-| `conv_width` | The width of a convolutional neural network input tensor. This replaces the need for `shift` by feeding in historical data points as the second dimension of the tensor. Technically, this parameter can also be used for regressors, but it only adds computational overhead and does not change the model training/prediction. Default value, 2 <br> **Datatype:** integer.
 
 
 ### Important FreqAI dataframe key patterns

From 09e5fb2f55cf368b8a3126fb1f00be2f8eb1f613 Mon Sep 17 00:00:00 2001
From: rzrymiak <106121613+rzrymiak@users.noreply.github.com>
Date: Sat, 30 Jul 2022 22:37:46 +0000
Subject: [PATCH 025/132] Removed description header

---
 README.md | 2 --
 1 file changed, 2 deletions(-)

diff --git a/README.md b/README.md
index 828a3d1f9..aa446ad54 100644
--- a/README.md
+++ b/README.md
@@ -5,8 +5,6 @@
 [![Documentation](https://readthedocs.org/projects/freqtrade/badge/)](https://www.freqtrade.io)
 [![Maintainability](https://api.codeclimate.com/v1/badges/5737e6d668200b7518ff/maintainability)](https://codeclimate.com/github/freqtrade/freqtrade/maintainability)
 
-## Description
-
 Freqtrade is a free and open source crypto trading bot written in Python. It is designed to support all major exchanges and be controlled via Telegram or webUI. It contains backtesting, plotting and money management tools as well as strategy optimization by machine learning.
 
 ![freqtrade](https://raw.githubusercontent.com/freqtrade/freqtrade/develop/docs/assets/freqtrade-screenshot.png)

From e6ebc0443ee3d738b29f78ec41f2c8d1c9e82127 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Sun, 31 Jul 2022 13:08:43 +0200
Subject: [PATCH 026/132] make single generalized config for freqai. update
 docs to reflect that.

---
 .gitignore                                    |  3 +-
 ...xample.json => config_freqai.example.json} |  6 +-
 .../config_freqai_spot.example.json           | 96 -------------------
 docs/freqai.md                                |  9 +-
 4 files changed, 9 insertions(+), 105 deletions(-)
 rename config_examples/{config_freqai_futures.example.json => config_freqai.example.json} (94%)
 delete mode 100644 config_examples/config_freqai_spot.example.json

diff --git a/.gitignore b/.gitignore
index 4498e42ac..73a11b47c 100644
--- a/.gitignore
+++ b/.gitignore
@@ -111,5 +111,4 @@ target/
 !config_examples/config_ftx.example.json
 !config_examples/config_full.example.json
 !config_examples/config_kraken.example.json
-!config_examples/config_freqai_futures.example.json
-!config_examples/config_freqai_spot.example.json
+!config_examples/config_freqai.example.json
diff --git a/config_examples/config_freqai_futures.example.json b/config_examples/config_freqai.example.json
similarity index 94%
rename from config_examples/config_freqai_futures.example.json
rename to config_examples/config_freqai.example.json
index 60e1cce82..e9fc50a4a 100644
--- a/config_examples/config_freqai_futures.example.json
+++ b/config_examples/config_freqai.example.json
@@ -57,8 +57,7 @@
         "train_period_days": 15,
         "backtest_period_days": 7,
         "live_retrain_hours": 0,
-        "identifier": "uniqe-id6",
-        "live_trained_timestamp": 0,
+        "identifier": "uniqe-id",
         "feature_parameters": {
             "include_timeframes": [
                 "3m",
@@ -84,8 +83,7 @@
             "random_state": 1
         },
         "model_training_parameters": {
-            "n_estimators": 1000,
-            "task_type": "CPU"
+            "n_estimators": 1000
         }
     },
     "bot_name": "",
diff --git a/config_examples/config_freqai_spot.example.json b/config_examples/config_freqai_spot.example.json
deleted file mode 100644
index 1ea6ddecb..000000000
--- a/config_examples/config_freqai_spot.example.json
+++ /dev/null
@@ -1,96 +0,0 @@
-{
-    "max_open_trades": 1,
-    "stake_currency": "USDT",
-    "stake_amount": 900,
-    "tradable_balance_ratio": 1,
-    "fiat_display_currency": "USD",
-    "dry_run": true,
-    "timeframe": "5m",
-    "dry_run_wallet": 4000,
-    "dataformat_ohlcv": "json",
-    "cancel_open_orders_on_exit": true,
-    "unfilledtimeout": {
-        "entry": 10,
-        "exit": 30
-    },
-    "exchange": {
-        "name": "binance",
-        "key": "",
-        "secret": "",
-        "ccxt_config": {
-            "enableRateLimit": true
-        },
-        "ccxt_async_config": {
-            "enableRateLimit": true,
-            "rateLimit": 200
-        },
-        "pair_whitelist": [
-            "BTC/USDT",
-            "ETH/USDT"
-        ],
-        "pair_blacklist": []
-    },
-    "entry_pricing": {
-        "price_side": "same",
-        "use_order_book": true,
-        "order_book_top": 1,
-        "price_last_balance": 0.0,
-        "check_depth_of_market": {
-            "enabled": false,
-            "bids_to_ask_delta": 1
-        }
-    },
-    "exit_pricing": {
-        "price_side": "other",
-        "use_order_book": true,
-        "order_book_top": 1
-    },
-    "pairlists": [
-        {
-            "method": "StaticPairList"
-        }
-    ],
-    "freqai": {
-        "startup_candles": 10000,
-
-        "train_period_days": 30,
-        "backtest_period_days": 7,
-        "live_retrain_hours": 1,
-        "identifier": "example",
-        "live_trained_timestamp": 0,
-        "feature_parameters": {
-            "include_timeframes": [
-                "5m",
-                "15m",
-                "4h"
-            ],
-            "include_corr_pairlist": [
-                "BTC/USDT",
-                "ETH/USDT"
-            ],
-            "label_period_candles": 500,
-            "include_shifted_candles": 1,
-            "DI_threshold": 0,
-            "weight_factor": 0.9,
-            "principal_component_analysis": false,
-            "use_SVM_to_remove_outliers": false,
-            "stratify_training_data": 0,
-            "indicator_max_period_candles": 50,
-            "indicator_periods_candles": [10, 20]
-        },
-        "data_split_parameters": {
-            "test_size": 0.33,
-            "random_state": 1
-        },
-        "model_training_parameters": {
-            "n_estimators": 1000,
-            "task_type": "CPU"
-        }
-    },
-    "bot_name": "",
-    "initial_state": "running",
-    "forcebuy_enable": false,
-    "internals": {
-        "process_throttle_secs": 5
-    }
-}
diff --git a/docs/freqai.md b/docs/freqai.md
index bffa12e5d..de321b787 100644
--- a/docs/freqai.md
+++ b/docs/freqai.md
@@ -60,7 +60,7 @@ pip install -r requirements-freqai.txt
 
 An example strategy, an example prediction model, and example config can all be found in
 `freqtrade/templates/FreqaiExampleStrategy.py`, `freqtrade/freqai/prediction_models/LightGBMPredictionModel.py`,
-`config_examples/config_freqai_futures.example.json`, respectively.
+`config_examples/config_freqai.example.json`, respectively.
 
 Assuming the user has downloaded the necessary data, Freqai can be executed from these templates with:
 
@@ -98,7 +98,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `weight_factor` | Used to set weights for training data points according to their recency, see details and a figure of how it works [here](##controlling-the-model-learning-process). <br> **Datatype:** positive float (typically below 1).
 | `principal_component_analysis` | Ask FreqAI to automatically reduce the dimensionality of the data set using PCA. <br> **Datatype:** boolean.
 | `use_SVM_to_remove_outliers` | Ask FreqAI to train a support vector machine to detect and remove outliers from the training data set as well as from incoming data points. <br> **Datatype:** boolean.
-| `svm_nu` | The `nu` parameter for the support vector machine. *Very* broadly, this is the percentage of data points that should be considered outliers. <br> **Datatype:** float between 0 and 1.
+| `svm_params` | All parameters available in Sklearn's `SGDOneClassSVM()`. E.g. `nu` *Very* broadly, is the percentage of data points that should be considered outliers. `shuffle` is by default false to maintain reprodicibility. But these and all others can be added/changed in this dictionary. <br> **Datatype:** dictionary.
 | `stratify_training_data` | This value is used to indicate the stratification of the data. e.g. 2 would set every 2nd data point into a separate dataset to be pulled from during training/testing. <br> **Datatype:** positive integer.
 | `indicator_max_period_candles` | The maximum *period* used in `populate_any_indicators()` for indicator creation. FreqAI uses this information in combination with the maximum timeframe to calculate how many data points it should download so that the first data point does not have a NaN <br> **Datatype:** positive integer.
 | `indicator_periods_candles` | A list of integers used to duplicate all indicators according to a set of periods and add them to the feature set. <br> **Datatype:** list of positive integers.
@@ -111,6 +111,9 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `n_estimators` | A common parameter among regressors which sets the number of boosted trees to fit <br> **Datatype:** integer.
 | `learning_rate` | A common parameter among regressors which sets the boosting learning rate. <br> **Datatype:** float.
 | `n_jobs`, `thread_count`, `task_type` | Different libraries use different parameter names to control the number of threads used for parallel processing or whether or not it is a `task_type` of `gpu` or `cpu`. <br> **Datatype:** float.
+|  |  **Extraneous parameters**
+| `keras` | If your model makes use of keras (typical of Tensorflow based prediction models), activate this flag so that the model save/loading follows keras standards. Default value `false`  <br> **Datatype:** boolean.
+| `conv_width` | The width of a convolutional neural network input tensor. This replaces the need for `shift` by feeding in historical data points as the second dimension of the tensor. Technically, this parameter can also be used for regressors, but it only adds computational overhead and does not change the model training/prediction. Default value, 2 <br> **Datatype:** integer.
 
 
 ### Important FreqAI dataframe key patterns
@@ -349,7 +352,7 @@ and adding this to the `train_period_days`. The units need to be in the base can
 The freqai training/backtesting module can be executed with the following command:
 
 ```bash
-freqtrade backtesting --strategy FreqaiExampleStrategy --config config_freqai_futures.example.json --freqaimodel LightGBMPredictionModel --timerange 20210501-20210701
+freqtrade backtesting --strategy FreqaiExampleStrategy --config config_freqai.example.json --freqaimodel LightGBMPredictionModel --timerange 20210501-20210701
 ```
 
 If this command has never been executed with the existing config file, then it will train a new model

From 61693f6c8bfc5c3e7eb4dc345fea4534ea5edb0a Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Sun, 31 Jul 2022 13:20:11 +0200
Subject: [PATCH 027/132] fix tests after changing config_example file

---
 tests/freqai/conftest.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/tests/freqai/conftest.py b/tests/freqai/conftest.py
index ff70a40a4..ecd8b2d57 100644
--- a/tests/freqai/conftest.py
+++ b/tests/freqai/conftest.py
@@ -49,7 +49,7 @@ def freqai_conf(default_conf, tmpdir):
                 "data_split_parameters": {"test_size": 0.33, "random_state": 1},
                 "model_training_parameters": {"n_estimators": 100, "verbosity": 0},
             },
-            "config_files": [Path('config_examples', 'config_freqai_futures.example.json')]
+            "config_files": [Path('config_examples', 'config_freqai.example.json')]
         }
     )
     freqaiconf['exchange'].update({'pair_whitelist': ['ADA/BTC', 'DASH/BTC', 'ETH/BTC', 'LTC/BTC']})
@@ -57,7 +57,6 @@ def freqai_conf(default_conf, tmpdir):
 
 
 def get_patched_data_kitchen(mocker, freqaiconf):
-    # dd = mocker.patch('freqtrade.freqai.data_drawer', MagicMock())
     dk = FreqaiDataKitchen(freqaiconf)
     return dk
 

From a4bada3ebe5ff927503b067545260ef5fe608c87 Mon Sep 17 00:00:00 2001
From: Kavinkumar <33546454+mkavinkumar1@users.noreply.github.com>
Date: Sun, 31 Jul 2022 17:49:04 +0530
Subject: [PATCH 028/132] Partial exit using average price (#6545)

Introduce Partial exits
---
 docs/strategy-callbacks.md                    |  67 ++-
 freqtrade/enums/exittype.py                   |   1 +
 freqtrade/exchange/exchange.py                |  44 +-
 freqtrade/freqtradebot.py                     | 194 +++++---
 freqtrade/optimize/backtesting.py             | 115 +++--
 freqtrade/persistence/migrations.py           |  10 +-
 freqtrade/persistence/trade_model.py          | 160 +++++--
 freqtrade/rpc/rpc.py                          |   2 +-
 freqtrade/rpc/telegram.py                     | 101 +++--
 freqtrade/strategy/interface.py               |  19 +-
 .../subtemplates/strategy_methods_advanced.j2 |  26 +-
 tests/conftest.py                             |   3 +-
 tests/exchange/test_exchange.py               | 199 ++++++---
 .../test_backtesting_adjust_position.py       |  86 ++++
 tests/rpc/test_rpc.py                         |   5 +-
 tests/rpc/test_rpc_telegram.py                | 102 ++++-
 tests/strategy/strats/strategy_test_v3.py     |   9 +-
 tests/test_freqtradebot.py                    | 414 ++++++++++++++++--
 tests/test_integration.py                     |  59 ++-
 tests/test_persistence.py                     | 193 +++++++-
 20 files changed, 1462 insertions(+), 347 deletions(-)
 mode change 100755 => 100644 freqtrade/optimize/backtesting.py

diff --git a/docs/strategy-callbacks.md b/docs/strategy-callbacks.md
index 59d221bfc..18de3513b 100644
--- a/docs/strategy-callbacks.md
+++ b/docs/strategy-callbacks.md
@@ -629,7 +629,7 @@ class AwesomeStrategy(IStrategy):
 
 The `position_adjustment_enable` strategy property enables the usage of `adjust_trade_position()` callback in the strategy.
 For performance reasons, it's disabled by default and freqtrade will show a warning message on startup if enabled.
-`adjust_trade_position()` can be used to perform additional orders, for example to manage risk with DCA (Dollar Cost Averaging).
+`adjust_trade_position()` can be used to perform additional orders, for example to manage risk with DCA (Dollar Cost Averaging) or to increase or decrease positions.
 
 `max_entry_position_adjustment` property is used to limit the number of additional buys per trade (on top of the first buy) that the bot can execute. By default, the value is -1 which means the bot have no limit on number of adjustment buys.
 
@@ -637,10 +637,13 @@ The strategy is expected to return a stake_amount (in stake currency) between `m
 If there are not enough funds in the wallet (the return value is above `max_stake`) then the signal will be ignored.
 Additional orders also result in additional fees and those orders don't count towards `max_open_trades`.
 
-This callback is **not** called when there is an open order (either buy or sell) waiting for execution, or when you have reached the maximum amount of extra buys that you have set on `max_entry_position_adjustment`.
+This callback is **not** called when there is an open order (either buy or sell) waiting for execution.
+
 `adjust_trade_position()` is called very frequently for the duration of a trade, so you must keep your implementation as performant as possible.
 
-Position adjustments will always be applied in the direction of the trade, so a positive value will always increase your position, no matter if it's a long or short trade. Modifications to leverage are not possible.
+Additional Buys are ignored once you have reached the maximum amount of extra buys that you have set on `max_entry_position_adjustment`, but the callback is called anyway looking for partial exits.
+
+Position adjustments will always be applied in the direction of the trade, so a positive value will always increase your position (negative values will decrease your position), no matter if it's a long or short trade. Modifications to leverage are not possible.
 
 !!! Note "About stake size"
     Using fixed stake size means it will be the amount used for the first order, just like without position adjustment.
@@ -649,12 +652,12 @@ Position adjustments will always be applied in the direction of the trade, so a
 
 !!! Warning
     Stoploss is still calculated from the initial opening price, not averaged price.
+    Regular stoploss rules still apply (cannot move down).
 
-!!! Warning "/stopbuy"
     While `/stopbuy` command stops the bot from entering new trades, the position adjustment feature will continue buying new orders on existing trades.
 
 !!! Warning "Backtesting"
-    During backtesting this callback is called for each candle in `timeframe` or `timeframe_detail`, so performance will be affected.
+    During backtesting this callback is called for each candle in `timeframe` or `timeframe_detail`, so run-time performance will be affected.
 
 ``` python
 from freqtrade.persistence import Trade
@@ -675,7 +678,7 @@ class DigDeeperStrategy(IStrategy):
     max_dca_multiplier = 5.5
 
     # This is called when placing the initial order (opening trade)
-def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
+    def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
                             proposed_stake: float, min_stake: Optional[float], max_stake: float,
                             leverage: float, entry_tag: Optional[str], side: str,
                             **kwargs) -> float:
@@ -685,22 +688,41 @@ def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: f
         return proposed_stake / self.max_dca_multiplier
 
     def adjust_trade_position(self, trade: Trade, current_time: datetime,
-                              current_rate: float, current_profit: float, min_stake: Optional[float],
-                              max_stake: float, **kwargs):
+                              current_rate: float, current_profit: float,
+                              min_stake: Optional[float], max_stake: float,
+                              current_entry_rate: float, current_exit_rate: float,
+                              current_entry_profit: float, current_exit_profit: float,
+                              **kwargs) -> Optional[float]:
         """
-        Custom trade adjustment logic, returning the stake amount that a trade should be increased.
-        This means extra buy orders with additional fees.
+        Custom trade adjustment logic, returning the stake amount that a trade should be
+        increased or decreased.
+        This means extra buy or sell orders with additional fees.
+        Only called when `position_adjustment_enable` is set to True.
+
+        For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+        When not implemented by a strategy, returns None
 
         :param trade: trade object.
         :param current_time: datetime object, containing the current datetime
         :param current_rate: Current buy rate.
         :param current_profit: Current profit (as ratio), calculated based on current_rate.
-        :param min_stake: Minimal stake size allowed by exchange.
-        :param max_stake: Balance available for trading.
+        :param min_stake: Minimal stake size allowed by exchange (for both entries and exits)
+        :param max_stake: Maximum stake allowed (either through balance, or by exchange limits).
+        :param current_entry_rate: Current rate using entry pricing.
+        :param current_exit_rate: Current rate using exit pricing.
+        :param current_entry_profit: Current profit using entry pricing.
+        :param current_exit_profit: Current profit using exit pricing.
         :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
-        :return float: Stake amount to adjust your trade
+        :return float: Stake amount to adjust your trade,
+                       Positive values to increase position, Negative values to decrease position.
+                       Return None for no action.
         """
 
+        if current_profit > 0.05 and trade.nr_of_successful_exits == 0:
+            # Take half of the profit at +5%
+            return -(trade.amount / 2)
+
         if current_profit > -0.05:
             return None
 
@@ -735,6 +757,25 @@ def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: f
 
 ```
 
+### Position adjust calculations
+
+* Entry rates are calculated using weighted averages.
+* Exits will not influence the average entry rate.
+* Partial exit relative profit is relative to the average entry price at this point.
+* Final exit relative profit is calculated based on the total invested capital. (See example below)
+
+??? example "Calculation example"
+    *This example assumes 0 fees for simplicity, and a long position on an imaginary coin.*  
+    
+    * Buy 100@8\$ 
+    * Buy 100@9\$ -> Avg price: 8.5\$
+    * Sell 100@10\$ -> Avg price: 8.5\$, realized profit 150\$, 17.65%
+    * Buy 150@11\$ -> Avg price: 10\$, realized profit 150\$, 17.65%
+    * Sell 100@12\$ -> Avg price: 10\$, total realized profit 350\$, 20%
+    * Sell 150@14\$ -> Avg price: 10\$, total realized profit 950\$, 40%
+
+    The total profit for this trade was 950$ on a 3350$ investment (`100@8$ + 100@9$ + 150@11$`). As such - the final relative profit is 28.35% (`950 / 3350`).
+
 ## Adjust Entry Price
 
 The `adjust_entry_price()` callback may be used by strategy developer to refresh/replace limit orders upon arrival of new candles.
diff --git a/freqtrade/enums/exittype.py b/freqtrade/enums/exittype.py
index 1e15e70cd..b025230ba 100644
--- a/freqtrade/enums/exittype.py
+++ b/freqtrade/enums/exittype.py
@@ -14,6 +14,7 @@ class ExitType(Enum):
     FORCE_EXIT = "force_exit"
     EMERGENCY_EXIT = "emergency_exit"
     CUSTOM_EXIT = "custom_exit"
+    PARTIAL_EXIT = "partial_exit"
     NONE = ""
 
     def __str__(self):
diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py
index e180c90b2..b6996211f 100644
--- a/freqtrade/exchange/exchange.py
+++ b/freqtrade/exchange/exchange.py
@@ -1507,7 +1507,8 @@ class Exchange:
         return price_side
 
     def get_rate(self, pair: str, refresh: bool,
-                 side: EntryExit, is_short: bool) -> float:
+                 side: EntryExit, is_short: bool,
+                 order_book: Optional[dict] = None, ticker: Optional[dict] = None) -> float:
         """
         Calculates bid/ask target
         bid rate - between current ask price and last price
@@ -1539,22 +1540,24 @@ class Exchange:
         if conf_strategy.get('use_order_book', False):
 
             order_book_top = conf_strategy.get('order_book_top', 1)
-            order_book = self.fetch_l2_order_book(pair, order_book_top)
+            if order_book is None:
+                order_book = self.fetch_l2_order_book(pair, order_book_top)
             logger.debug('order_book %s', order_book)
             # top 1 = index 0
             try:
                 rate = order_book[f"{price_side}s"][order_book_top - 1][0]
             except (IndexError, KeyError) as e:
                 logger.warning(
-                    f"{name} Price at location {order_book_top} from orderbook could not be "
-                    f"determined. Orderbook: {order_book}"
+                    f"{pair} - {name} Price at location {order_book_top} from orderbook "
+                    f"could not be determined. Orderbook: {order_book}"
                 )
                 raise PricingError from e
-            logger.debug(f"{name} price from orderbook {price_side_word}"
+            logger.debug(f"{pair} - {name} price from orderbook {price_side_word}"
                          f"side - top {order_book_top} order book {side} rate {rate:.8f}")
         else:
             logger.debug(f"Using Last {price_side_word} / Last Price")
-            ticker = self.fetch_ticker(pair)
+            if ticker is None:
+                ticker = self.fetch_ticker(pair)
             ticker_rate = ticker[price_side]
             if ticker['last'] and ticker_rate:
                 if side == 'entry' and ticker_rate > ticker['last']:
@@ -1571,6 +1574,33 @@ class Exchange:
 
         return rate
 
+    def get_rates(self, pair: str, refresh: bool, is_short: bool) -> Tuple[float, float]:
+        entry_rate = None
+        exit_rate = None
+        if not refresh:
+            entry_rate = self._entry_rate_cache.get(pair)
+            exit_rate = self._exit_rate_cache.get(pair)
+            if entry_rate:
+                logger.debug(f"Using cached buy rate for {pair}.")
+            if exit_rate:
+                logger.debug(f"Using cached sell rate for {pair}.")
+
+        entry_pricing = self._config.get('entry_pricing', {})
+        exit_pricing = self._config.get('exit_pricing', {})
+        order_book = ticker = None
+        if not entry_rate and entry_pricing.get('use_order_book', False):
+            order_book_top = max(entry_pricing.get('order_book_top', 1),
+                                 exit_pricing.get('order_book_top', 1))
+            order_book = self.fetch_l2_order_book(pair, order_book_top)
+            entry_rate = self.get_rate(pair, refresh, 'entry', is_short, order_book=order_book)
+        elif not entry_rate:
+            ticker = self.fetch_ticker(pair)
+            entry_rate = self.get_rate(pair, refresh, 'entry', is_short, ticker=ticker)
+        if not exit_rate:
+            exit_rate = self.get_rate(pair, refresh, 'exit',
+                                      is_short, order_book=order_book, ticker=ticker)
+        return entry_rate, exit_rate
+
     # Fee handling
 
     @retrier
@@ -1989,7 +2019,7 @@ class Exchange:
             else:
                 logger.debug(
                     "Fetching trades for pair %s, since %s %s...",
-                    pair,  since,
+                    pair, since,
                     '(' + arrow.get(since // 1000).isoformat() + ') ' if since is not None else ''
                 )
                 trades = await self._api_async.fetch_trades(pair, since=since, limit=1000)
diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py
index 50cfb9d7b..757449c8c 100644
--- a/freqtrade/freqtradebot.py
+++ b/freqtrade/freqtradebot.py
@@ -5,6 +5,7 @@ import copy
 import logging
 import traceback
 from datetime import datetime, time, timedelta, timezone
+from decimal import Decimal
 from math import isclose
 from threading import Lock
 from typing import Any, Dict, List, Optional, Tuple
@@ -525,39 +526,61 @@ class FreqtradeBot(LoggingMixin):
         If the strategy triggers the adjustment, a new order gets issued.
         Once that completes, the existing trade is modified to match new data.
         """
-        if self.strategy.max_entry_position_adjustment > -1:
-            count_of_buys = trade.nr_of_successful_entries
-            if count_of_buys > self.strategy.max_entry_position_adjustment:
-                logger.debug(f"Max adjustment entries for {trade.pair} has been reached.")
-                return
-        else:
-            logger.debug("Max adjustment entries is set to unlimited.")
-        current_rate = self.exchange.get_rate(
-            trade.pair, side='entry', is_short=trade.is_short, refresh=True)
-        current_profit = trade.calc_profit_ratio(current_rate)
+        current_entry_rate, current_exit_rate = self.exchange.get_rates(
+            trade.pair, True, trade.is_short)
 
-        min_stake_amount = self.exchange.get_min_pair_stake_amount(trade.pair,
-                                                                   current_rate,
-                                                                   self.strategy.stoploss)
-        max_stake_amount = self.exchange.get_max_pair_stake_amount(trade.pair, current_rate)
+        current_entry_profit = trade.calc_profit_ratio(current_entry_rate)
+        current_exit_profit = trade.calc_profit_ratio(current_exit_rate)
+
+        min_entry_stake = self.exchange.get_min_pair_stake_amount(trade.pair,
+                                                                  current_entry_rate,
+                                                                  self.strategy.stoploss)
+        min_exit_stake = self.exchange.get_min_pair_stake_amount(trade.pair,
+                                                                 current_exit_rate,
+                                                                 self.strategy.stoploss)
+        max_entry_stake = self.exchange.get_max_pair_stake_amount(trade.pair, current_entry_rate)
         stake_available = self.wallets.get_available_stake_amount()
         logger.debug(f"Calling adjust_trade_position for pair {trade.pair}")
         stake_amount = strategy_safe_wrapper(self.strategy.adjust_trade_position,
                                              default_retval=None)(
-            trade=trade, current_time=datetime.now(timezone.utc), current_rate=current_rate,
-            current_profit=current_profit, min_stake=min_stake_amount,
-            max_stake=min(max_stake_amount, stake_available))
+            trade=trade,
+            current_time=datetime.now(timezone.utc), current_rate=current_entry_rate,
+            current_profit=current_entry_profit, min_stake=min_entry_stake,
+            max_stake=min(max_entry_stake, stake_available),
+            current_entry_rate=current_entry_rate, current_exit_rate=current_exit_rate,
+            current_entry_profit=current_entry_profit, current_exit_profit=current_exit_profit
+        )
 
         if stake_amount is not None and stake_amount > 0.0:
             # We should increase our position
-            self.execute_entry(trade.pair, stake_amount, price=current_rate,
+            if self.strategy.max_entry_position_adjustment > -1:
+                count_of_entries = trade.nr_of_successful_entries
+                if count_of_entries > self.strategy.max_entry_position_adjustment:
+                    logger.debug(f"Max adjustment entries for {trade.pair} has been reached.")
+                    return
+                else:
+                    logger.debug("Max adjustment entries is set to unlimited.")
+            self.execute_entry(trade.pair, stake_amount, price=current_entry_rate,
                                trade=trade, is_short=trade.is_short)
 
         if stake_amount is not None and stake_amount < 0.0:
             # We should decrease our position
-            # TODO: Selling part of the trade not implemented yet.
-            logger.error(f"Unable to decrease trade position / sell partially"
-                         f" for pair {trade.pair}, feature not implemented.")
+            amount = abs(float(Decimal(stake_amount) / Decimal(current_exit_rate)))
+            if amount > trade.amount:
+                # This is currently ineffective as remaining would become < min tradable
+                # Fixing this would require checking for 0.0 there -
+                # if we decide that this callback is allowed to "fully exit"
+                logger.info(
+                    f"Adjusting amount to trade.amount as it is higher. {amount} > {trade.amount}")
+                amount = trade.amount
+
+            remaining = (trade.amount - amount) * current_exit_rate
+            if remaining < min_exit_stake:
+                logger.info(f'Remaining amount of {remaining} would be too small.')
+                return
+
+            self.execute_trade_exit(trade, current_exit_rate, exit_check=ExitCheckTuple(
+                exit_type=ExitType.PARTIAL_EXIT), sub_trade_amt=amount)
 
     def _check_depth_of_market(self, pair: str, conf: Dict, side: SignalDirection) -> bool:
         """
@@ -731,7 +754,7 @@ class FreqtradeBot(LoggingMixin):
         # Updating wallets
         self.wallets.update()
 
-        self._notify_enter(trade, order, order_type)
+        self._notify_enter(trade, order_obj, order_type, sub_trade=pos_adjust)
 
         if pos_adjust:
             if order_status == 'closed':
@@ -740,8 +763,8 @@ class FreqtradeBot(LoggingMixin):
             else:
                 logger.info(f"DCA order {order_status}, will wait for resolution: {trade}")
 
-        # Update fees if order is closed
-        if order_status == 'closed':
+        # Update fees if order is non-opened
+        if order_status in constants.NON_OPEN_EXCHANGE_STATES:
             self.update_trade_state(trade, order_id, order)
 
         return True
@@ -830,13 +853,14 @@ class FreqtradeBot(LoggingMixin):
 
         return enter_limit_requested, stake_amount, leverage
 
-    def _notify_enter(self, trade: Trade, order: Dict, order_type: Optional[str] = None,
-                      fill: bool = False) -> None:
+    def _notify_enter(self, trade: Trade, order: Order, order_type: Optional[str] = None,
+                      fill: bool = False, sub_trade: bool = False) -> None:
         """
         Sends rpc notification when a entry order occurred.
         """
         msg_type = RPCMessageType.ENTRY_FILL if fill else RPCMessageType.ENTRY
-        open_rate = safe_value_fallback(order, 'average', 'price')
+        open_rate = order.safe_price
+
         if open_rate is None:
             open_rate = trade.open_rate
 
@@ -860,15 +884,17 @@ class FreqtradeBot(LoggingMixin):
             'stake_amount': trade.stake_amount,
             'stake_currency': self.config['stake_currency'],
             'fiat_currency': self.config.get('fiat_display_currency', None),
-            'amount': safe_value_fallback(order, 'filled', 'amount') or trade.amount,
+            'amount': order.safe_amount_after_fee,
             'open_date': trade.open_date or datetime.utcnow(),
             'current_rate': current_rate,
+            'sub_trade': sub_trade,
         }
 
         # Send the message
         self.rpc.send_msg(msg)
 
-    def _notify_enter_cancel(self, trade: Trade, order_type: str, reason: str) -> None:
+    def _notify_enter_cancel(self, trade: Trade, order_type: str, reason: str,
+                             sub_trade: bool = False) -> None:
         """
         Sends rpc notification when a entry order cancel occurred.
         """
@@ -893,6 +919,7 @@ class FreqtradeBot(LoggingMixin):
             'open_date': trade.open_date,
             'current_rate': current_rate,
             'reason': reason,
+            'sub_trade': sub_trade,
         }
 
         # Send the message
@@ -1366,16 +1393,22 @@ class FreqtradeBot(LoggingMixin):
             trade.open_order_id = None
             trade.exit_reason = None
             cancelled = True
+            self.wallets.update()
         else:
             # TODO: figure out how to handle partially complete sell orders
             reason = constants.CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN']
             cancelled = False
 
-        self.wallets.update()
+        order_obj = trade.select_order_by_order_id(order['id'])
+        if not order_obj:
+            raise DependencyException(
+                f"Order_obj not found for {order['id']}. This should not have happened.")
+
+        sub_trade = order_obj.amount != trade.amount
         self._notify_exit_cancel(
             trade,
             order_type=self.strategy.order_types['exit'],
-            reason=reason
+            reason=reason, order=order_obj, sub_trade=sub_trade
         )
         return cancelled
 
@@ -1416,6 +1449,7 @@ class FreqtradeBot(LoggingMixin):
             *,
             exit_tag: Optional[str] = None,
             ordertype: Optional[str] = None,
+            sub_trade_amt: float = None,
     ) -> bool:
         """
         Executes a trade exit for the given trade and limit
@@ -1439,7 +1473,7 @@ class FreqtradeBot(LoggingMixin):
         # if stoploss is on exchange and we are on dry_run mode,
         # we consider the sell price stop price
         if (self.config['dry_run'] and exit_type == 'stoploss'
-           and self.strategy.order_types['stoploss_on_exchange']):
+                and self.strategy.order_types['stoploss_on_exchange']):
             limit = trade.stoploss_or_liquidation
 
         # set custom_exit_price if available
@@ -1462,15 +1496,17 @@ class FreqtradeBot(LoggingMixin):
             # Emergency sells (default to market!)
             order_type = self.strategy.order_types.get("emergency_exit", "market")
 
-        amount = self._safe_exit_amount(trade.pair, trade.amount)
+        amount = self._safe_exit_amount(trade.pair, sub_trade_amt or trade.amount)
         time_in_force = self.strategy.order_time_in_force['exit']
 
-        if (exit_check.exit_type != ExitType.LIQUIDATION and not strategy_safe_wrapper(
-            self.strategy.confirm_trade_exit, default_retval=True)(
-                pair=trade.pair, trade=trade, order_type=order_type, amount=amount, rate=limit,
-                time_in_force=time_in_force, exit_reason=exit_reason,
-                sell_reason=exit_reason,  # sellreason -> compatibility
-                current_time=datetime.now(timezone.utc))):
+        if (exit_check.exit_type != ExitType.LIQUIDATION
+                and not sub_trade_amt
+                and not strategy_safe_wrapper(
+                    self.strategy.confirm_trade_exit, default_retval=True)(
+                    pair=trade.pair, trade=trade, order_type=order_type, amount=amount, rate=limit,
+                    time_in_force=time_in_force, exit_reason=exit_reason,
+                    sell_reason=exit_reason,  # sellreason -> compatibility
+                    current_time=datetime.now(timezone.utc))):
             logger.info(f"User denied exit for {trade.pair}.")
             return False
 
@@ -1504,7 +1540,7 @@ class FreqtradeBot(LoggingMixin):
         self.strategy.lock_pair(trade.pair, datetime.now(timezone.utc),
                                 reason='Auto lock')
 
-        self._notify_exit(trade, order_type)
+        self._notify_exit(trade, order_type, sub_trade=bool(sub_trade_amt), order=order_obj)
         # In case of market sell orders the order can be closed immediately
         if order.get('status', 'unknown') in ('closed', 'expired'):
             self.update_trade_state(trade, trade.open_order_id, order)
@@ -1512,16 +1548,27 @@ class FreqtradeBot(LoggingMixin):
 
         return True
 
-    def _notify_exit(self, trade: Trade, order_type: str, fill: bool = False) -> None:
+    def _notify_exit(self, trade: Trade, order_type: str, fill: bool = False,
+                     sub_trade: bool = False, order: Order = None) -> None:
         """
         Sends rpc notification when a sell occurred.
         """
-        profit_rate = trade.close_rate if trade.close_rate else trade.close_rate_requested
-        profit_trade = trade.calc_profit(rate=profit_rate)
         # Use cached rates here - it was updated seconds ago.
         current_rate = self.exchange.get_rate(
             trade.pair, side='exit', is_short=trade.is_short, refresh=False) if not fill else None
-        profit_ratio = trade.calc_profit_ratio(profit_rate)
+
+        # second condition is for mypy only; order will always be passed during sub trade
+        if sub_trade and order is not None:
+            amount = order.safe_filled if fill else order.amount
+            profit_rate = order.safe_price
+
+            profit = trade.calc_profit(rate=profit_rate, amount=amount, open_rate=trade.open_rate)
+            profit_ratio = trade.calc_profit_ratio(profit_rate, amount, trade.open_rate)
+        else:
+            profit_rate = trade.close_rate if trade.close_rate else trade.close_rate_requested
+            profit = trade.calc_profit(rate=profit_rate) + trade.realized_profit
+            profit_ratio = trade.calc_profit_ratio(profit_rate)
+            amount = trade.amount
         gain = "profit" if profit_ratio > 0 else "loss"
 
         msg = {
@@ -1535,11 +1582,11 @@ class FreqtradeBot(LoggingMixin):
             'gain': gain,
             'limit': profit_rate,
             'order_type': order_type,
-            'amount': trade.amount,
+            'amount': amount,
             'open_rate': trade.open_rate,
-            'close_rate': trade.close_rate,
+            'close_rate': profit_rate,
             'current_rate': current_rate,
-            'profit_amount': profit_trade,
+            'profit_amount': profit,
             'profit_ratio': profit_ratio,
             'buy_tag': trade.enter_tag,
             'enter_tag': trade.enter_tag,
@@ -1547,19 +1594,18 @@ class FreqtradeBot(LoggingMixin):
             'exit_reason': trade.exit_reason,
             'open_date': trade.open_date,
             'close_date': trade.close_date or datetime.utcnow(),
+            'stake_amount': trade.stake_amount,
             'stake_currency': self.config['stake_currency'],
             'fiat_currency': self.config.get('fiat_display_currency'),
+            'sub_trade': sub_trade,
+            'cumulative_profit': trade.realized_profit,
         }
 
-        if 'fiat_display_currency' in self.config:
-            msg.update({
-                'fiat_currency': self.config['fiat_display_currency'],
-            })
-
         # Send the message
         self.rpc.send_msg(msg)
 
-    def _notify_exit_cancel(self, trade: Trade, order_type: str, reason: str) -> None:
+    def _notify_exit_cancel(self, trade: Trade, order_type: str, reason: str,
+                            order: Order, sub_trade: bool = False) -> None:
         """
         Sends rpc notification when a sell cancel occurred.
         """
@@ -1585,7 +1631,7 @@ class FreqtradeBot(LoggingMixin):
             'gain': gain,
             'limit': profit_rate or 0,
             'order_type': order_type,
-            'amount': trade.amount,
+            'amount': order.safe_amount_after_fee,
             'open_rate': trade.open_rate,
             'current_rate': current_rate,
             'profit_amount': profit_trade,
@@ -1599,6 +1645,8 @@ class FreqtradeBot(LoggingMixin):
             'stake_currency': self.config['stake_currency'],
             'fiat_currency': self.config.get('fiat_display_currency', None),
             'reason': reason,
+            'sub_trade': sub_trade,
+            'stake_amount': trade.stake_amount,
         }
 
         if 'fiat_display_currency' in self.config:
@@ -1653,14 +1701,18 @@ class FreqtradeBot(LoggingMixin):
         self.handle_order_fee(trade, order_obj, order)
 
         trade.update_trade(order_obj)
-        # TODO: is the below necessary? it's already done in update_trade for filled buys
-        trade.recalc_trade_from_orders()
         Trade.commit()
 
-        if order['status'] in constants.NON_OPEN_EXCHANGE_STATES:
+        if order.get('status') in constants.NON_OPEN_EXCHANGE_STATES:
             # If a entry order was closed, force update on stoploss on exchange
             if order.get('side') == trade.entry_side:
                 trade = self.cancel_stoploss_on_exchange(trade)
+                if not self.edge:
+                    # TODO: should shorting/leverage be supported by Edge,
+                    # then this will need to be fixed.
+                    trade.adjust_stop_loss(trade.open_rate, self.strategy.stoploss, initial=True)
+            if order.get('side') == trade.entry_side or trade.amount > 0:
+                # Must also run for partial exits
                 # TODO: Margin will need to use interest_rate as well.
                 # interest_rate = self.exchange.get_interest_rate()
                 trade.set_liquidation_price(self.exchange.get_liquidation_price(
@@ -1670,24 +1722,30 @@ class FreqtradeBot(LoggingMixin):
                     open_rate=trade.open_rate,
                     is_short=trade.is_short
                 ))
-                if not self.edge:
-                    # TODO: should shorting/leverage be supported by Edge,
-                    # then this will need to be fixed.
-                    trade.adjust_stop_loss(trade.open_rate, self.strategy.stoploss, initial=True)
 
             # Updating wallets when order is closed
             self.wallets.update()
 
-        if not trade.is_open:
-            if send_msg and not stoploss_order and not trade.open_order_id:
-                self._notify_exit(trade, '', True)
-            self.handle_protections(trade.pair, trade.trade_direction)
-        elif send_msg and not trade.open_order_id and not stoploss_order:
-            # Enter fill
-            self._notify_enter(trade, order, fill=True)
+        self.order_close_notify(trade, order_obj, stoploss_order, send_msg)
 
         return False
 
+    def order_close_notify(
+            self, trade: Trade, order: Order, stoploss_order: bool, send_msg: bool):
+        """send "fill" notifications"""
+
+        sub_trade = not isclose(order.safe_amount_after_fee,
+                                trade.amount, abs_tol=constants.MATH_CLOSE_PREC)
+        if order.ft_order_side == trade.exit_side:
+            # Exit notification
+            if send_msg and not stoploss_order and not trade.open_order_id:
+                self._notify_exit(trade, '', fill=True, sub_trade=sub_trade, order=order)
+            if not trade.is_open:
+                self.handle_protections(trade.pair, trade.trade_direction)
+        elif send_msg and not trade.open_order_id and not stoploss_order:
+            # Enter fill
+            self._notify_enter(trade, order, fill=True, sub_trade=sub_trade)
+
     def handle_protections(self, pair: str, side: LongShort) -> None:
         prot_trig = self.protections.stop_per_pair(pair, side=side)
         if prot_trig:
diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py
old mode 100755
new mode 100644
index 2c6cfb0e9..46774e8a5
--- a/freqtrade/optimize/backtesting.py
+++ b/freqtrade/optimize/backtesting.py
@@ -287,8 +287,8 @@ class Backtesting:
 
             if unavailable_pairs:
                 raise OperationalException(
-                        f"Pairs {', '.join(unavailable_pairs)} got no leverage tiers available. "
-                        "It is therefore impossible to backtest with this pair at the moment.")
+                    f"Pairs {', '.join(unavailable_pairs)} got no leverage tiers available. "
+                    "It is therefore impossible to backtest with this pair at the moment.")
         else:
             self.futures_data = {}
 
@@ -503,16 +503,20 @@ class Backtesting:
 
     def _get_adjust_trade_entry_for_candle(self, trade: LocalTrade, row: Tuple
                                            ) -> LocalTrade:
-        current_profit = trade.calc_profit_ratio(row[OPEN_IDX])
-        min_stake = self.exchange.get_min_pair_stake_amount(trade.pair, row[OPEN_IDX], -0.1)
-        max_stake = self.exchange.get_max_pair_stake_amount(trade.pair, row[OPEN_IDX])
+        current_rate = row[OPEN_IDX]
+        current_date = row[DATE_IDX].to_pydatetime()
+        current_profit = trade.calc_profit_ratio(current_rate)
+        min_stake = self.exchange.get_min_pair_stake_amount(trade.pair, current_rate, -0.1)
+        max_stake = self.exchange.get_max_pair_stake_amount(trade.pair, current_rate)
         stake_available = self.wallets.get_available_stake_amount()
         stake_amount = strategy_safe_wrapper(self.strategy.adjust_trade_position,
                                              default_retval=None)(
             trade=trade,  # type: ignore[arg-type]
-            current_time=row[DATE_IDX].to_pydatetime(), current_rate=row[OPEN_IDX],
+            current_time=current_date, current_rate=current_rate,
             current_profit=current_profit, min_stake=min_stake,
-            max_stake=min(max_stake, stake_available))
+            max_stake=min(max_stake, stake_available),
+            current_entry_rate=current_rate, current_exit_rate=current_rate,
+            current_entry_profit=current_profit, current_exit_profit=current_profit)
 
         # Check if we should increase our position
         if stake_amount is not None and stake_amount > 0.0:
@@ -523,6 +527,24 @@ class Backtesting:
                 self.wallets.update()
                 return pos_trade
 
+        if stake_amount is not None and stake_amount < 0.0:
+            amount = abs(stake_amount) / current_rate
+            if amount > trade.amount:
+                # This is currently ineffective as remaining would become < min tradable
+                amount = trade.amount
+            remaining = (trade.amount - amount) * current_rate
+            if remaining < min_stake:
+                # Remaining stake is too low to be sold.
+                return trade
+            pos_trade = self._exit_trade(trade, row, current_rate, amount)
+            if pos_trade is not None:
+                order = pos_trade.orders[-1]
+                if self._get_order_filled(order.price, row):
+                    order.close_bt_order(current_date, trade)
+                    trade.recalc_trade_from_orders()
+                self.wallets.update()
+                return pos_trade
+
         return trade
 
     def _get_order_filled(self, rate: float, row: Tuple) -> bool:
@@ -602,7 +624,7 @@ class Backtesting:
                 self.strategy.confirm_trade_exit, default_retval=True)(
                     pair=trade.pair,
                     trade=trade,  # type: ignore[arg-type]
-                    order_type='limit',
+                    order_type=order_type,
                     amount=trade.amount,
                     rate=close_rate,
                     time_in_force=time_in_force,
@@ -613,32 +635,38 @@ class Backtesting:
 
             trade.exit_reason = exit_reason
 
-            self.order_id_counter += 1
-            order = Order(
-                id=self.order_id_counter,
-                ft_trade_id=trade.id,
-                order_date=exit_candle_time,
-                order_update_date=exit_candle_time,
-                ft_is_open=True,
-                ft_pair=trade.pair,
-                order_id=str(self.order_id_counter),
-                symbol=trade.pair,
-                ft_order_side=trade.exit_side,
-                side=trade.exit_side,
-                order_type=order_type,
-                status="open",
-                price=close_rate,
-                average=close_rate,
-                amount=trade.amount,
-                filled=0,
-                remaining=trade.amount,
-                cost=trade.amount * close_rate,
-            )
-            trade.orders.append(order)
-            return trade
-
+            return self._exit_trade(trade, row, close_rate, trade.amount)
         return None
 
+    def _exit_trade(self, trade: LocalTrade, sell_row: Tuple,
+                    close_rate: float, amount: float = None) -> Optional[LocalTrade]:
+        self.order_id_counter += 1
+        exit_candle_time = sell_row[DATE_IDX].to_pydatetime()
+        order_type = self.strategy.order_types['exit']
+        amount = amount or trade.amount
+        order = Order(
+            id=self.order_id_counter,
+            ft_trade_id=trade.id,
+            order_date=exit_candle_time,
+            order_update_date=exit_candle_time,
+            ft_is_open=True,
+            ft_pair=trade.pair,
+            order_id=str(self.order_id_counter),
+            symbol=trade.pair,
+            ft_order_side=trade.exit_side,
+            side=trade.exit_side,
+            order_type=order_type,
+            status="open",
+            price=close_rate,
+            average=close_rate,
+            amount=amount,
+            filled=0,
+            remaining=amount,
+            cost=amount * close_rate,
+        )
+        trade.orders.append(order)
+        return trade
+
     def _get_exit_trade_entry(self, trade: LocalTrade, row: Tuple) -> Optional[LocalTrade]:
         exit_candle_time: datetime = row[DATE_IDX].to_pydatetime()
 
@@ -865,6 +893,8 @@ class Backtesting:
                         # Ignore trade if entry-order did not fill yet
                         continue
                     exit_row = data[pair][-1]
+                    self._exit_trade(trade, exit_row, exit_row[OPEN_IDX], trade.amount)
+                    trade.orders[-1].close_bt_order(exit_row[DATE_IDX].to_pydatetime(), trade)
 
                     trade.close_date = exit_row[DATE_IDX].to_pydatetime()
                     trade.exit_reason = ExitType.FORCE_EXIT.value
@@ -1006,7 +1036,7 @@ class Backtesting:
             return None
         return row
 
-    def backtest(self, processed: Dict,
+    def backtest(self, processed: Dict,  # noqa: max-complexity: 13
                  start_date: datetime, end_date: datetime,
                  max_open_trades: int = 0, position_stacking: bool = False,
                  enable_protections: bool = False) -> Dict[str, Any]:
@@ -1108,14 +1138,19 @@ class Backtesting:
                     if order and self._get_order_filled(order.price, row):
                         order.close_bt_order(current_time, trade)
                         trade.open_order_id = None
-                        trade.close_date = current_time
-                        trade.close(order.price, show_msg=False)
+                        sub_trade = order.safe_amount_after_fee != trade.amount
+                        if sub_trade:
+                            order.close_bt_order(current_time, trade)
+                            trade.recalc_trade_from_orders()
+                        else:
+                            trade.close_date = current_time
+                            trade.close(order.price, show_msg=False)
 
-                        # logger.debug(f"{pair} - Backtesting exit {trade}")
-                        open_trade_count -= 1
-                        open_trades[pair].remove(trade)
-                        LocalTrade.close_bt_trade(trade)
-                        trades.append(trade)
+                            # logger.debug(f"{pair} - Backtesting exit {trade}")
+                            open_trade_count -= 1
+                            open_trades[pair].remove(trade)
+                            LocalTrade.close_bt_trade(trade)
+                            trades.append(trade)
                         self.wallets.update()
                         self.run_protections(
                             enable_protections, pair, current_time, trade.trade_direction)
diff --git a/freqtrade/persistence/migrations.py b/freqtrade/persistence/migrations.py
index 2a8e34cdf..81757a7de 100644
--- a/freqtrade/persistence/migrations.py
+++ b/freqtrade/persistence/migrations.py
@@ -95,6 +95,7 @@ def migrate_trades_and_orders_table(
     exit_reason = get_column_def(cols, 'sell_reason', get_column_def(cols, 'exit_reason', 'null'))
     strategy = get_column_def(cols, 'strategy', 'null')
     enter_tag = get_column_def(cols, 'buy_tag', get_column_def(cols, 'enter_tag', 'null'))
+    realized_profit = get_column_def(cols, 'realized_profit', '0.0')
 
     trading_mode = get_column_def(cols, 'trading_mode', 'null')
 
@@ -155,7 +156,7 @@ def migrate_trades_and_orders_table(
             max_rate, min_rate, exit_reason, exit_order_status, strategy, enter_tag,
             timeframe, open_trade_value, close_profit_abs,
             trading_mode, leverage, liquidation_price, is_short,
-            interest_rate, funding_fees
+            interest_rate, funding_fees, realized_profit
             )
         select id, lower(exchange), pair, {base_currency} base_currency,
             {stake_currency} stake_currency,
@@ -181,7 +182,7 @@ def migrate_trades_and_orders_table(
             {open_trade_value} open_trade_value, {close_profit_abs} close_profit_abs,
             {trading_mode} trading_mode, {leverage} leverage, {liquidation_price} liquidation_price,
             {is_short} is_short, {interest_rate} interest_rate,
-            {funding_fees} funding_fees
+            {funding_fees} funding_fees, {realized_profit} realized_profit
             from {trade_back_name}
             """))
 
@@ -297,8 +298,9 @@ def check_migrate(engine, decl_base, previous_tables) -> None:
 
     # Check if migration necessary
     # Migrates both trades and orders table!
-    if not has_column(cols_orders, 'stop_price'):
-        # if not has_column(cols_trades, 'base_currency'):
+    # if ('orders' not in previous_tables
+    # or not has_column(cols_orders, 'stop_price')):
+    if not has_column(cols_trades, 'realized_profit'):
         logger.info(f"Running database migration for trades - "
                     f"backup: {table_back_name}, {order_table_bak_name}")
         migrate_trades_and_orders_table(
diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py
index 44e148a0c..fcb84a59a 100644
--- a/freqtrade/persistence/trade_model.py
+++ b/freqtrade/persistence/trade_model.py
@@ -4,13 +4,15 @@ This module contains the class to persist trades into SQLite
 import logging
 from datetime import datetime, timedelta, timezone
 from decimal import Decimal
+from math import isclose
 from typing import Any, Dict, List, Optional
 
 from sqlalchemy import (Boolean, Column, DateTime, Enum, Float, ForeignKey, Integer, String,
                         UniqueConstraint, desc, func)
 from sqlalchemy.orm import Query, lazyload, relationship
 
-from freqtrade.constants import DATETIME_PRINT_FORMAT, NON_OPEN_EXCHANGE_STATES, BuySell, LongShort
+from freqtrade.constants import (DATETIME_PRINT_FORMAT, MATH_CLOSE_PREC, NON_OPEN_EXCHANGE_STATES,
+                                 BuySell, LongShort)
 from freqtrade.enums import ExitType, TradingMode
 from freqtrade.exceptions import DependencyException, OperationalException
 from freqtrade.leverage import interest
@@ -176,10 +178,9 @@ class Order(_DECL_BASE):
         self.remaining = 0
         self.status = 'closed'
         self.ft_is_open = False
-        if (self.ft_order_side == trade.entry_side
-                and len(trade.select_filled_orders(trade.entry_side)) == 1):
+        if (self.ft_order_side == trade.entry_side):
             trade.open_rate = self.price
-            trade.recalc_open_trade_value()
+            trade.recalc_trade_from_orders()
             trade.adjust_stop_loss(trade.open_rate, trade.stop_loss_pct, refresh=True)
 
     @staticmethod
@@ -237,6 +238,7 @@ class LocalTrade():
     trades: List['LocalTrade'] = []
     trades_open: List['LocalTrade'] = []
     total_profit: float = 0
+    realized_profit: float = 0
 
     id: int = 0
 
@@ -447,6 +449,7 @@ class LocalTrade():
                            if self.close_date else None),
             'close_timestamp': int(self.close_date.replace(
                 tzinfo=timezone.utc).timestamp() * 1000) if self.close_date else None,
+            'realized_profit': self.realized_profit or 0.0,
             'close_rate': self.close_rate,
             'close_rate_requested': self.close_rate_requested,
             'close_profit': self.close_profit,  # Deprecated
@@ -596,14 +599,28 @@ class LocalTrade():
             if self.is_open:
                 payment = "SELL" if self.is_short else "BUY"
                 logger.info(f'{order.order_type.upper()}_{payment} has been fulfilled for {self}.')
-            self.open_order_id = None
+            # condition to avoid reset value when updating fees
+            if self.open_order_id == order.order_id:
+                self.open_order_id = None
+            else:
+                logger.warning(
+                    f'Got different open_order_id {self.open_order_id} != {order.order_id}')
             self.recalc_trade_from_orders()
         elif order.ft_order_side == self.exit_side:
             if self.is_open:
                 payment = "BUY" if self.is_short else "SELL"
                 # * On margin shorts, you buy a little bit more than the amount (amount + interest)
                 logger.info(f'{order.order_type.upper()}_{payment} has been fulfilled for {self}.')
-            self.close(order.safe_price)
+            # condition to avoid reset value when updating fees
+            if self.open_order_id == order.order_id:
+                self.open_order_id = None
+            else:
+                logger.warning(
+                    f'Got different open_order_id {self.open_order_id} != {order.order_id}')
+            if isclose(order.safe_amount_after_fee, self.amount, abs_tol=MATH_CLOSE_PREC):
+                self.close(order.safe_price)
+            else:
+                self.recalc_trade_from_orders()
         elif order.ft_order_side == 'stoploss':
             self.stoploss_order_id = None
             self.close_rate_requested = self.stop_loss
@@ -622,11 +639,11 @@ class LocalTrade():
         """
         self.close_rate = rate
         self.close_date = self.close_date or datetime.utcnow()
-        self.close_profit = self.calc_profit_ratio(rate)
-        self.close_profit_abs = self.calc_profit(rate)
+        self.close_profit_abs = self.calc_profit(rate) + self.realized_profit
         self.is_open = False
         self.exit_order_status = 'closed'
         self.open_order_id = None
+        self.recalc_trade_from_orders(is_closing=True)
         if show_msg:
             logger.info(
                 'Marking %s as closed as the trade is fulfilled and found no open orders for it.',
@@ -672,12 +689,12 @@ class LocalTrade():
         """
         return len([o for o in self.orders if o.ft_order_side == self.exit_side])
 
-    def _calc_open_trade_value(self) -> float:
+    def _calc_open_trade_value(self, amount: float, open_rate: float) -> float:
         """
         Calculate the open_rate including open_fee.
         :return: Price in of the open trade incl. Fees
         """
-        open_trade = Decimal(self.amount) * Decimal(self.open_rate)
+        open_trade = Decimal(amount) * Decimal(open_rate)
         fees = open_trade * Decimal(self.fee_open)
         if self.is_short:
             return float(open_trade - fees)
@@ -689,7 +706,7 @@ class LocalTrade():
         Recalculate open_trade_value.
         Must be called whenever open_rate, fee_open is changed.
         """
-        self.open_trade_value = self._calc_open_trade_value()
+        self.open_trade_value = self._calc_open_trade_value(self.amount, self.open_rate)
 
     def calculate_interest(self) -> Decimal:
         """
@@ -721,7 +738,7 @@ class LocalTrade():
         else:
             return close_trade - fees
 
-    def calc_close_trade_value(self, rate: float) -> float:
+    def calc_close_trade_value(self, rate: float, amount: float = None) -> float:
         """
         Calculate the Trade's close value including fees
         :param rate: rate to compare with.
@@ -730,96 +747,143 @@ class LocalTrade():
         if rate is None and not self.close_rate:
             return 0.0
 
-        amount = Decimal(self.amount)
+        amount1 = Decimal(amount or self.amount)
         trading_mode = self.trading_mode or TradingMode.SPOT
 
         if trading_mode == TradingMode.SPOT:
-            return float(self._calc_base_close(amount, rate, self.fee_close))
+            return float(self._calc_base_close(amount1, rate, self.fee_close))
 
         elif (trading_mode == TradingMode.MARGIN):
 
             total_interest = self.calculate_interest()
 
             if self.is_short:
-                amount = amount + total_interest
-                return float(self._calc_base_close(amount, rate, self.fee_close))
+                amount1 = amount1 + total_interest
+                return float(self._calc_base_close(amount1, rate, self.fee_close))
             else:
                 # Currency already owned for longs, no need to purchase
-                return float(self._calc_base_close(amount, rate, self.fee_close) - total_interest)
+                return float(self._calc_base_close(amount1, rate, self.fee_close) - total_interest)
 
         elif (trading_mode == TradingMode.FUTURES):
             funding_fees = self.funding_fees or 0.0
             # Positive funding_fees -> Trade has gained from fees.
             # Negative funding_fees -> Trade had to pay the fees.
             if self.is_short:
-                return float(self._calc_base_close(amount, rate, self.fee_close)) - funding_fees
+                return float(self._calc_base_close(amount1, rate, self.fee_close)) - funding_fees
             else:
-                return float(self._calc_base_close(amount, rate, self.fee_close)) + funding_fees
+                return float(self._calc_base_close(amount1, rate, self.fee_close)) + funding_fees
         else:
             raise OperationalException(
                 f"{self.trading_mode.value} trading is not yet available using freqtrade")
 
-    def calc_profit(self, rate: float) -> float:
+    def calc_profit(self, rate: float, amount: float = None, open_rate: float = None) -> float:
         """
         Calculate the absolute profit in stake currency between Close and Open trade
         :param rate: close rate to compare with.
+        :param amount: Amount to use for the calculation. Falls back to trade.amount if not set.
+        :param open_rate: open_rate to use. Defaults to self.open_rate if not provided.
         :return: profit in stake currency as float
         """
-        close_trade_value = self.calc_close_trade_value(rate)
+        close_trade_value = self.calc_close_trade_value(rate, amount)
+        if amount is None or open_rate is None:
+            open_trade_value = self.open_trade_value
+        else:
+            open_trade_value = self._calc_open_trade_value(amount, open_rate)
 
         if self.is_short:
-            profit = self.open_trade_value - close_trade_value
+            profit = open_trade_value - close_trade_value
         else:
-            profit = close_trade_value - self.open_trade_value
+            profit = close_trade_value - open_trade_value
         return float(f"{profit:.8f}")
 
-    def calc_profit_ratio(self, rate: float) -> float:
+    def calc_profit_ratio(
+            self, rate: float, amount: float = None, open_rate: float = None) -> float:
         """
         Calculates the profit as ratio (including fee).
         :param rate: rate to compare with.
+        :param amount: Amount to use for the calculation. Falls back to trade.amount if not set.
+        :param open_rate: open_rate to use. Defaults to self.open_rate if not provided.
         :return: profit ratio as float
         """
-        close_trade_value = self.calc_close_trade_value(rate)
+        close_trade_value = self.calc_close_trade_value(rate, amount)
+
+        if amount is None or open_rate is None:
+            open_trade_value = self.open_trade_value
+        else:
+            open_trade_value = self._calc_open_trade_value(amount, open_rate)
 
         short_close_zero = (self.is_short and close_trade_value == 0.0)
-        long_close_zero = (not self.is_short and self.open_trade_value == 0.0)
+        long_close_zero = (not self.is_short and open_trade_value == 0.0)
         leverage = self.leverage or 1.0
 
         if (short_close_zero or long_close_zero):
             return 0.0
         else:
             if self.is_short:
-                profit_ratio = (1 - (close_trade_value / self.open_trade_value)) * leverage
+                profit_ratio = (1 - (close_trade_value / open_trade_value)) * leverage
             else:
-                profit_ratio = ((close_trade_value / self.open_trade_value) - 1) * leverage
+                profit_ratio = ((close_trade_value / open_trade_value) - 1) * leverage
 
         return float(f"{profit_ratio:.8f}")
 
-    def recalc_trade_from_orders(self):
+    def recalc_trade_from_orders(self, is_closing: bool = False):
+
+        current_amount = 0.0
+        current_stake = 0.0
+        total_stake = 0.0  # Total stake after all buy orders (does not subtract!)
+        avg_price = 0.0
+        close_profit = 0.0
+        close_profit_abs = 0.0
 
-        total_amount = 0.0
-        total_stake = 0.0
         for o in self.orders:
-            if (o.ft_is_open or
-                    (o.ft_order_side != self.entry_side) or
-                    (o.status not in NON_OPEN_EXCHANGE_STATES)):
+            if o.ft_is_open or not o.filled:
                 continue
 
             tmp_amount = o.safe_amount_after_fee
-            tmp_price = o.average or o.price
-            if tmp_amount > 0.0 and tmp_price is not None:
-                total_amount += tmp_amount
-                total_stake += tmp_price * tmp_amount
+            tmp_price = o.safe_price
 
-        if total_amount > 0:
+            is_exit = o.ft_order_side != self.entry_side
+            side = -1 if is_exit else 1
+            if tmp_amount > 0.0 and tmp_price is not None:
+                current_amount += tmp_amount * side
+                price = avg_price if is_exit else tmp_price
+                current_stake += price * tmp_amount * side
+
+                if current_amount > 0:
+                    avg_price = current_stake / current_amount
+
+            if is_exit:
+                # Process partial exits
+                exit_rate = o.safe_price
+                exit_amount = o.safe_amount_after_fee
+                profit = self.calc_profit(rate=exit_rate, amount=exit_amount, open_rate=avg_price)
+                close_profit_abs += profit
+                close_profit = self.calc_profit_ratio(
+                    exit_rate, amount=exit_amount, open_rate=avg_price)
+                if current_amount <= 0:
+                    profit = close_profit_abs
+            else:
+                total_stake = total_stake + self._calc_open_trade_value(tmp_amount, price)
+
+        if close_profit:
+            self.close_profit = close_profit
+            self.realized_profit = close_profit_abs
+            self.close_profit_abs = profit
+
+        if current_amount > 0:
+            # Trade is still open
             # Leverage not updated, as we don't allow changing leverage through DCA at the moment.
-            self.open_rate = total_stake / total_amount
-            self.stake_amount = total_stake / (self.leverage or 1.0)
-            self.amount = total_amount
-            self.fee_open_cost = self.fee_open * total_stake
+            self.open_rate = current_stake / current_amount
+            self.stake_amount = current_stake / (self.leverage or 1.0)
+            self.amount = current_amount
+            self.fee_open_cost = self.fee_open * current_stake
             self.recalc_open_trade_value()
             if self.stop_loss_pct is not None and self.open_rate is not None:
                 self.adjust_stop_loss(self.open_rate, self.stop_loss_pct)
+        elif is_closing and total_stake > 0:
+            # Close profit abs / maximum owned
+            # Fees are considered as they are part of close_profit_abs
+            self.close_profit = (close_profit_abs / total_stake) * self.leverage
 
     def select_order_by_order_id(self, order_id: str) -> Optional[Order]:
         """
@@ -841,7 +905,7 @@ class LocalTrade():
         """
         orders = self.orders
         if order_side:
-            orders = [o for o in self.orders if o.ft_order_side == order_side]
+            orders = [o for o in orders if o.ft_order_side == order_side]
         if is_open is not None:
             orders = [o for o in orders if o.ft_is_open == is_open]
         if len(orders) > 0:
@@ -856,9 +920,9 @@ class LocalTrade():
         :return: array of Order objects
         """
         return [o for o in self.orders if ((o.ft_order_side == order_side) or (order_side is None))
-                and o.ft_is_open is False and
-                (o.filled or 0) > 0 and
-                o.status in NON_OPEN_EXCHANGE_STATES]
+                and o.ft_is_open is False
+                and o.filled
+                and o.status in NON_OPEN_EXCHANGE_STATES]
 
     def select_filled_or_open_orders(self) -> List['Order']:
         """
@@ -1023,6 +1087,7 @@ class Trade(_DECL_BASE, LocalTrade):
     open_trade_value = Column(Float)
     close_rate: Optional[float] = Column(Float)
     close_rate_requested = Column(Float)
+    realized_profit = Column(Float, default=0.0)
     close_profit = Column(Float)
     close_profit_abs = Column(Float)
     stake_amount = Column(Float, nullable=False)
@@ -1068,6 +1133,7 @@ class Trade(_DECL_BASE, LocalTrade):
 
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
+        self.realized_profit = 0
         self.recalc_open_trade_value()
 
     def delete(self) -> None:
diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py
index e6948c9e2..9d6696803 100644
--- a/freqtrade/rpc/rpc.py
+++ b/freqtrade/rpc/rpc.py
@@ -201,7 +201,7 @@ class RPC:
 
                 trade_dict = trade.to_json()
                 trade_dict.update(dict(
-                    close_profit=trade.close_profit if trade.close_profit is not None else None,
+                    close_profit=trade.close_profit if not trade.is_open else None,
                     current_rate=current_rate,
                     current_profit=current_profit,  # Deprecated
                     current_profit_pct=round(current_profit * 100, 2),  # Deprecated
diff --git a/freqtrade/rpc/telegram.py b/freqtrade/rpc/telegram.py
index 121324d90..66192fb16 100644
--- a/freqtrade/rpc/telegram.py
+++ b/freqtrade/rpc/telegram.py
@@ -274,7 +274,7 @@ class Telegram(RPCHandler):
             f"{emoji} *{self._exchange_from_msg(msg)}:*"
             f" {entry_side['entered'] if is_fill else entry_side['enter']} {msg['pair']}"
             f" (#{msg['trade_id']})\n"
-            )
+        )
         message += self._add_analyzed_candle(msg['pair'])
         message += f"*Enter Tag:* `{msg['enter_tag']}`\n" if msg.get('enter_tag') else ""
         message += f"*Amount:* `{msg['amount']:.8f}`\n"
@@ -315,20 +315,36 @@ class Telegram(RPCHandler):
             msg['profit_fiat'] = self._rpc._fiat_converter.convert_amount(
                 msg['profit_amount'], msg['stake_currency'], msg['fiat_currency'])
             msg['profit_extra'] = (
-                f" ({msg['gain']}: {msg['profit_amount']:.8f} {msg['stake_currency']}"
-                f" / {msg['profit_fiat']:.3f} {msg['fiat_currency']})")
+                f" / {msg['profit_fiat']:.3f} {msg['fiat_currency']}")
         else:
             msg['profit_extra'] = ''
+        msg['profit_extra'] = (
+            f" ({msg['gain']}: {msg['profit_amount']:.8f} {msg['stake_currency']}"
+            f"{msg['profit_extra']})")
         is_fill = msg['type'] == RPCMessageType.EXIT_FILL
+        is_sub_trade = msg.get('sub_trade')
+        is_sub_profit = msg['profit_amount'] != msg.get('cumulative_profit')
+        profit_prefix = ('Sub ' if is_sub_profit
+                         else 'Cumulative ') if is_sub_trade else ''
+        cp_extra = ''
+        if is_sub_profit and is_sub_trade:
+            if self._rpc._fiat_converter:
+                cp_fiat = self._rpc._fiat_converter.convert_amount(
+                    msg['cumulative_profit'], msg['stake_currency'], msg['fiat_currency'])
+                cp_extra = f" / {cp_fiat:.3f} {msg['fiat_currency']}"
+            else:
+                cp_extra = ''
+            cp_extra = f"*Cumulative Profit:* (`{msg['cumulative_profit']:.8f} " \
+                       f"{msg['stake_currency']}{cp_extra}`)\n"
         message = (
             f"{msg['emoji']} *{self._exchange_from_msg(msg)}:* "
             f"{'Exited' if is_fill else 'Exiting'} {msg['pair']} (#{msg['trade_id']})\n"
             f"{self._add_analyzed_candle(msg['pair'])}"
-            f"*{'Profit' if is_fill else 'Unrealized Profit'}:* "
+            f"*{f'{profit_prefix}Profit' if is_fill else f'Unrealized {profit_prefix}Profit'}:* "
             f"`{msg['profit_ratio']:.2%}{msg['profit_extra']}`\n"
+            f"{cp_extra}"
             f"*Enter Tag:* `{msg['enter_tag']}`\n"
             f"*Exit Reason:* `{msg['exit_reason']}`\n"
-            f"*Duration:* `{msg['duration']} ({msg['duration_min']:.1f} min)`\n"
             f"*Direction:* `{msg['direction']}`\n"
             f"{msg['leverage_text']}"
             f"*Amount:* `{msg['amount']:.8f}`\n"
@@ -336,11 +352,25 @@ class Telegram(RPCHandler):
         )
         if msg['type'] == RPCMessageType.EXIT:
             message += (f"*Current Rate:* `{msg['current_rate']:.8f}`\n"
-                        f"*Close Rate:* `{msg['limit']:.8f}`")
+                        f"*Exit Rate:* `{msg['limit']:.8f}`")
 
         elif msg['type'] == RPCMessageType.EXIT_FILL:
-            message += f"*Close Rate:* `{msg['close_rate']:.8f}`"
+            message += f"*Exit Rate:* `{msg['close_rate']:.8f}`"
+        if msg.get('sub_trade'):
+            if self._rpc._fiat_converter:
+                msg['stake_amount_fiat'] = self._rpc._fiat_converter.convert_amount(
+                    msg['stake_amount'], msg['stake_currency'], msg['fiat_currency'])
+            else:
+                msg['stake_amount_fiat'] = 0
+            rem = round_coin_value(msg['stake_amount'], msg['stake_currency'])
+            message += f"\n*Remaining:* `({rem}"
 
+            if msg.get('fiat_currency', None):
+                message += f", {round_coin_value(msg['stake_amount_fiat'], msg['fiat_currency'])}"
+
+            message += ")`"
+        else:
+            message += f"\n*Duration:* `{msg['duration']} ({msg['duration_min']:.1f} min)`"
         return message
 
     def compose_message(self, msg: Dict[str, Any], msg_type: RPCMessageType) -> str:
@@ -353,7 +383,8 @@ class Telegram(RPCHandler):
         elif msg_type in (RPCMessageType.ENTRY_CANCEL, RPCMessageType.EXIT_CANCEL):
             msg['message_side'] = 'enter' if msg_type in [RPCMessageType.ENTRY_CANCEL] else 'exit'
             message = (f"\N{WARNING SIGN} *{self._exchange_from_msg(msg)}:* "
-                       f"Cancelling {msg['message_side']} Order for {msg['pair']} "
+                       f"Cancelling {'partial ' if msg.get('sub_trade') else ''}"
+                       f"{msg['message_side']} Order for {msg['pair']} "
                        f"(#{msg['trade_id']}). Reason: {msg['reason']}.")
 
         elif msg_type == RPCMessageType.PROTECTION_TRIGGER:
@@ -424,7 +455,7 @@ class Telegram(RPCHandler):
         else:
             return "\N{CROSS MARK}"
 
-    def _prepare_entry_details(self, filled_orders: List, quote_currency: str, is_open: bool):
+    def _prepare_order_details(self, filled_orders: List, quote_currency: str, is_open: bool):
         """
         Prepare details of trade with entry adjustment enabled
         """
@@ -433,44 +464,51 @@ class Telegram(RPCHandler):
             first_avg = filled_orders[0]["safe_price"]
 
         for x, order in enumerate(filled_orders):
-            if not order['ft_is_entry'] or order['is_open'] is True:
+            if order['is_open'] is True:
                 continue
+            wording = 'Entry' if order['ft_is_entry'] else 'Exit'
+
             cur_entry_datetime = arrow.get(order["order_filled_date"])
-            cur_entry_amount = order["amount"]
+            cur_entry_amount = order["filled"] or order["amount"]
             cur_entry_average = order["safe_price"]
             lines.append("  ")
             if x == 0:
-                lines.append(f"*Entry #{x+1}:*")
+                lines.append(f"*{wording} #{x+1}:*")
                 lines.append(
-                    f"*Entry Amount:* {cur_entry_amount} ({order['cost']:.8f} {quote_currency})")
-                lines.append(f"*Average Entry Price:* {cur_entry_average}")
+                    f"*Amount:* {cur_entry_amount} ({order['cost']:.8f} {quote_currency})")
+                lines.append(f"*Average Price:* {cur_entry_average}")
             else:
                 sumA = 0
                 sumB = 0
                 for y in range(x):
-                    sumA += (filled_orders[y]["amount"] * filled_orders[y]["safe_price"])
-                    sumB += filled_orders[y]["amount"]
+                    amount = filled_orders[y]["filled"] or filled_orders[y]["amount"]
+                    sumA += amount * filled_orders[y]["safe_price"]
+                    sumB += amount
                 prev_avg_price = sumA / sumB
+                # TODO: This calculation ignores fees.
                 price_to_1st_entry = ((cur_entry_average - first_avg) / first_avg)
                 minus_on_entry = 0
                 if prev_avg_price:
                     minus_on_entry = (cur_entry_average - prev_avg_price) / prev_avg_price
 
-                dur_entry = cur_entry_datetime - arrow.get(
-                    filled_orders[x - 1]["order_filled_date"])
-                days = dur_entry.days
-                hours, remainder = divmod(dur_entry.seconds, 3600)
-                minutes, seconds = divmod(remainder, 60)
-                lines.append(f"*Entry #{x+1}:* at {minus_on_entry:.2%} avg profit")
+                lines.append(f"*{wording} #{x+1}:* at {minus_on_entry:.2%} avg profit")
                 if is_open:
                     lines.append("({})".format(cur_entry_datetime
                                                .humanize(granularity=["day", "hour", "minute"])))
                 lines.append(
-                    f"*Entry Amount:* {cur_entry_amount} ({order['cost']:.8f} {quote_currency})")
-                lines.append(f"*Average Entry Price:* {cur_entry_average} "
+                    f"*Amount:* {cur_entry_amount} ({order['cost']:.8f} {quote_currency})")
+                lines.append(f"*Average {wording} Price:* {cur_entry_average} "
                              f"({price_to_1st_entry:.2%} from 1st entry rate)")
-                lines.append(f"*Order filled at:* {order['order_filled_date']}")
-                lines.append(f"({days}d {hours}h {minutes}m {seconds}s from previous entry)")
+                lines.append(f"*Order filled:* {order['order_filled_date']}")
+
+                # TODO: is this really useful?
+                # dur_entry = cur_entry_datetime - arrow.get(
+                #     filled_orders[x - 1]["order_filled_date"])
+                # days = dur_entry.days
+                # hours, remainder = divmod(dur_entry.seconds, 3600)
+                # minutes, seconds = divmod(remainder, 60)
+                # lines.append(
+                # f"({days}d {hours}h {minutes}m {seconds}s from previous {wording.lower()})")
         return lines
 
     @authorized_only
@@ -486,7 +524,14 @@ class Telegram(RPCHandler):
         if context.args and 'table' in context.args:
             self._status_table(update, context)
             return
+        else:
+            self._status_msg(update, context)
 
+    def _status_msg(self, update: Update, context: CallbackContext) -> None:
+        """
+        handler for `/status` and `/status <id>`.
+
+        """
         try:
 
             # Check if there's at least one numerical ID provided.
@@ -529,6 +574,8 @@ class Telegram(RPCHandler):
                 ])
 
                 if r['is_open']:
+                    if r.get('realized_profit'):
+                        lines.append("*Realized Profit:* `{realized_profit:.8f}`")
                     if (r['stop_loss_abs'] != r['initial_stop_loss_abs']
                             and r['initial_stop_loss_ratio'] is not None):
                         # Adding initial stoploss only if it is different from stoploss
@@ -546,7 +593,7 @@ class Telegram(RPCHandler):
                         else:
                             lines.append("*Open Order:* `{open_order}`")
 
-                lines_detail = self._prepare_entry_details(
+                lines_detail = self._prepare_order_details(
                     r['orders'], r['quote_currency'], r['is_open'])
                 lines.extend(lines_detail if lines_detail else "")
 
diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py
index 824f31258..5e0aba2fe 100644
--- a/freqtrade/strategy/interface.py
+++ b/freqtrade/strategy/interface.py
@@ -463,10 +463,13 @@ class IStrategy(ABC, HyperStrategyMixin):
     def adjust_trade_position(self, trade: Trade, current_time: datetime,
                               current_rate: float, current_profit: float,
                               min_stake: Optional[float], max_stake: float,
+                              current_entry_rate: float, current_exit_rate: float,
+                              current_entry_profit: float, current_exit_profit: float,
                               **kwargs) -> Optional[float]:
         """
-        Custom trade adjustment logic, returning the stake amount that a trade should be increased.
-        This means extra buy orders with additional fees.
+        Custom trade adjustment logic, returning the stake amount that a trade should be
+        increased or decreased.
+        This means extra buy or sell orders with additional fees.
         Only called when `position_adjustment_enable` is set to True.
 
         For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
@@ -477,10 +480,16 @@ class IStrategy(ABC, HyperStrategyMixin):
         :param current_time: datetime object, containing the current datetime
         :param current_rate: Current buy rate.
         :param current_profit: Current profit (as ratio), calculated based on current_rate.
-        :param min_stake: Minimal stake size allowed by exchange.
-        :param max_stake: Balance available for trading.
+        :param min_stake: Minimal stake size allowed by exchange (for both entries and exits)
+        :param max_stake: Maximum stake allowed (either through balance, or by exchange limits).
+        :param current_entry_rate: Current rate using entry pricing.
+        :param current_exit_rate: Current rate using exit pricing.
+        :param current_entry_profit: Current profit using entry pricing.
+        :param current_exit_profit: Current profit using exit pricing.
         :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
-        :return float: Stake amount to adjust your trade
+        :return float: Stake amount to adjust your trade,
+                       Positive values to increase position, Negative values to decrease position.
+                       Return None for no action.
         """
         return None
 
diff --git a/freqtrade/templates/subtemplates/strategy_methods_advanced.j2 b/freqtrade/templates/subtemplates/strategy_methods_advanced.j2
index 989f1d37a..488ca2fd7 100644
--- a/freqtrade/templates/subtemplates/strategy_methods_advanced.j2
+++ b/freqtrade/templates/subtemplates/strategy_methods_advanced.j2
@@ -247,12 +247,16 @@ def check_exit_timeout(self, pair: str, trade: 'Trade', order: 'Order',
     """
     return False
 
-def adjust_trade_position(self, trade: 'Trade', current_time: 'datetime',
-                          current_rate: float, current_profit: float, min_stake: Optional[float],
-                          max_stake: float, **kwargs) -> 'Optional[float]':
+def adjust_trade_position(self, trade: 'Trade', current_time: datetime,
+                          current_rate: float, current_profit: float,
+                          min_stake: Optional[float], max_stake: float,
+                          current_entry_rate: float, current_exit_rate: float,
+                          current_entry_profit: float, current_exit_profit: float,
+                          **kwargs) -> Optional[float]:
     """
-    Custom trade adjustment logic, returning the stake amount that a trade should be increased.
-    This means extra buy orders with additional fees.
+    Custom trade adjustment logic, returning the stake amount that a trade should be
+    increased or decreased.
+    This means extra buy or sell orders with additional fees.
     Only called when `position_adjustment_enable` is set to True.
 
     For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
@@ -263,10 +267,16 @@ def adjust_trade_position(self, trade: 'Trade', current_time: 'datetime',
     :param current_time: datetime object, containing the current datetime
     :param current_rate: Current buy rate.
     :param current_profit: Current profit (as ratio), calculated based on current_rate.
-    :param min_stake: Minimal stake size allowed by exchange.
-    :param max_stake: Balance available for trading.
+    :param min_stake: Minimal stake size allowed by exchange (for both entries and exits)
+    :param max_stake: Maximum stake allowed (either through balance, or by exchange limits).
+    :param current_entry_rate: Current rate using entry pricing.
+    :param current_exit_rate: Current rate using exit pricing.
+    :param current_entry_profit: Current profit using entry pricing.
+    :param current_exit_profit: Current profit using exit pricing.
     :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
-    :return float: Stake amount to adjust your trade
+    :return float: Stake amount to adjust your trade,
+                    Positive values to increase position, Negative values to decrease position.
+                    Return None for no action.
     """
     return None
 
diff --git a/tests/conftest.py b/tests/conftest.py
index ff3e1007f..a02fc4566 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -1627,8 +1627,8 @@ def limit_buy_order_open():
         'timestamp': arrow.utcnow().int_timestamp * 1000,
         'datetime': arrow.utcnow().isoformat(),
         'price': 0.00001099,
+        'average': 0.00001099,
         'amount': 90.99181073,
-        'average': None,
         'filled': 0.0,
         'cost': 0.0009999,
         'remaining': 90.99181073,
@@ -2817,6 +2817,7 @@ def limit_buy_order_usdt_open():
         'datetime': arrow.utcnow().isoformat(),
         'timestamp': arrow.utcnow().int_timestamp * 1000,
         'price': 2.00,
+        'average': 2.00,
         'amount': 30.0,
         'filled': 0.0,
         'cost': 60.0,
diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py
index e968b12c2..d73e26683 100644
--- a/tests/exchange/test_exchange.py
+++ b/tests/exchange/test_exchange.py
@@ -27,6 +27,57 @@ from tests.conftest import get_mock_coro, get_patched_exchange, log_has, log_has
 # Make sure to always keep one exchange here which is NOT subclassed!!
 EXCHANGES = ['bittrex', 'binance', 'kraken', 'ftx', 'gateio']
 
+get_entry_rate_data = [
+    ('other', 20, 19, 10, 0.0, 20),  # Full ask side
+    ('ask', 20, 19, 10, 0.0, 20),  # Full ask side
+    ('ask', 20, 19, 10, 1.0, 10),  # Full last side
+    ('ask', 20, 19, 10, 0.5, 15),  # Between ask and last
+    ('ask', 20, 19, 10, 0.7, 13),  # Between ask and last
+    ('ask', 20, 19, 10, 0.3, 17),  # Between ask and last
+    ('ask', 5, 6, 10, 1.0, 5),  # last bigger than ask
+    ('ask', 5, 6, 10, 0.5, 5),  # last bigger than ask
+    ('ask', 20, 19, 10, None, 20),  # price_last_balance missing
+    ('ask', 10, 20, None, 0.5, 10),  # last not available - uses ask
+    ('ask', 4, 5, None, 0.5, 4),  # last not available - uses ask
+    ('ask', 4, 5, None, 1, 4),  # last not available - uses ask
+    ('ask', 4, 5, None, 0, 4),  # last not available - uses ask
+    ('same', 21, 20, 10, 0.0, 20),  # Full bid side
+    ('bid', 21, 20, 10, 0.0, 20),  # Full bid side
+    ('bid', 21, 20, 10, 1.0, 10),  # Full last side
+    ('bid', 21, 20, 10, 0.5, 15),  # Between bid and last
+    ('bid', 21, 20, 10, 0.7, 13),  # Between bid and last
+    ('bid', 21, 20, 10, 0.3, 17),  # Between bid and last
+    ('bid', 6, 5, 10, 1.0, 5),  # last bigger than bid
+    ('bid', 21, 20, 10, None, 20),  # price_last_balance missing
+    ('bid', 6, 5, 10, 0.5, 5),  # last bigger than bid
+    ('bid', 21, 20, None, 0.5, 20),  # last not available - uses bid
+    ('bid', 6, 5, None, 0.5, 5),  # last not available - uses bid
+    ('bid', 6, 5, None, 1, 5),  # last not available - uses bid
+    ('bid', 6, 5, None, 0, 5),  # last not available - uses bid
+]
+
+get_sell_rate_data = [
+    ('bid', 12.0, 11.0, 11.5, 0.0, 11.0),  # full bid side
+    ('bid', 12.0, 11.0, 11.5, 1.0, 11.5),  # full last side
+    ('bid', 12.0, 11.0, 11.5, 0.5, 11.25),  # between bid and lat
+    ('bid', 12.0, 11.2, 10.5, 0.0, 11.2),  # Last smaller than bid
+    ('bid', 12.0, 11.2, 10.5, 1.0, 11.2),  # Last smaller than bid - uses bid
+    ('bid', 12.0, 11.2, 10.5, 0.5, 11.2),  # Last smaller than bid - uses bid
+    ('bid', 0.003, 0.002, 0.005, 0.0, 0.002),
+    ('bid', 0.003, 0.002, 0.005, None, 0.002),
+    ('ask', 12.0, 11.0, 12.5, 0.0, 12.0),  # full ask side
+    ('ask', 12.0, 11.0, 12.5, 1.0, 12.5),  # full last side
+    ('ask', 12.0, 11.0, 12.5, 0.5, 12.25),  # between bid and lat
+    ('ask', 12.2, 11.2, 10.5, 0.0, 12.2),  # Last smaller than ask
+    ('ask', 12.0, 11.0, 10.5, 1.0, 12.0),  # Last smaller than ask - uses ask
+    ('ask', 12.0, 11.2, 10.5, 0.5, 12.0),  # Last smaller than ask - uses ask
+    ('ask', 10.0, 11.0, 11.0, 0.0, 10.0),
+    ('ask', 10.11, 11.2, 11.0, 0.0, 10.11),
+    ('ask', 0.001, 0.002, 11.0, 0.0, 0.001),
+    ('ask', 0.006, 1.0, 11.0, 0.0, 0.006),
+    ('ask', 0.006, 1.0, 11.0, None, 0.006),
+]
+
 
 def ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
                            fun, mock_ccxt_fun, retries=API_RETRY_COUNT + 1, **kwargs):
@@ -2360,34 +2411,7 @@ def test_fetch_l2_order_book_exception(default_conf, mocker, exchange_name):
         exchange.fetch_l2_order_book(pair='ETH/BTC', limit=50)
 
 
-@pytest.mark.parametrize("side,ask,bid,last,last_ab,expected", [
-    ('other', 20, 19, 10, 0.0, 20),  # Full ask side
-    ('ask', 20, 19, 10, 0.0, 20),  # Full ask side
-    ('ask', 20, 19, 10, 1.0, 10),  # Full last side
-    ('ask', 20, 19, 10, 0.5, 15),  # Between ask and last
-    ('ask', 20, 19, 10, 0.7, 13),  # Between ask and last
-    ('ask', 20, 19, 10, 0.3, 17),  # Between ask and last
-    ('ask', 5, 6, 10, 1.0, 5),  # last bigger than ask
-    ('ask', 5, 6, 10, 0.5, 5),  # last bigger than ask
-    ('ask', 20, 19, 10, None, 20),  # price_last_balance missing
-    ('ask', 10, 20, None, 0.5, 10),  # last not available - uses ask
-    ('ask', 4, 5, None, 0.5, 4),  # last not available - uses ask
-    ('ask', 4, 5, None, 1, 4),  # last not available - uses ask
-    ('ask', 4, 5, None, 0, 4),  # last not available - uses ask
-    ('same', 21, 20, 10, 0.0, 20),  # Full bid side
-    ('bid', 21, 20, 10, 0.0, 20),  # Full bid side
-    ('bid', 21, 20, 10, 1.0, 10),  # Full last side
-    ('bid', 21, 20, 10, 0.5, 15),  # Between bid and last
-    ('bid', 21, 20, 10, 0.7, 13),  # Between bid and last
-    ('bid', 21, 20, 10, 0.3, 17),  # Between bid and last
-    ('bid', 6, 5, 10, 1.0, 5),  # last bigger than bid
-    ('bid', 21, 20, 10, None, 20),  # price_last_balance missing
-    ('bid', 6, 5, 10, 0.5, 5),  # last bigger than bid
-    ('bid', 21, 20, None, 0.5, 20),  # last not available - uses bid
-    ('bid', 6, 5, None, 0.5, 5),  # last not available - uses bid
-    ('bid', 6, 5, None, 1, 5),  # last not available - uses bid
-    ('bid', 6, 5, None, 0, 5),  # last not available - uses bid
-])
+@pytest.mark.parametrize("side,ask,bid,last,last_ab,expected", get_entry_rate_data)
 def test_get_entry_rate(mocker, default_conf, caplog, side, ask, bid,
                         last, last_ab, expected) -> None:
     caplog.set_level(logging.DEBUG)
@@ -2411,27 +2435,7 @@ def test_get_entry_rate(mocker, default_conf, caplog, side, ask, bid,
     assert not log_has("Using cached entry rate for ETH/BTC.", caplog)
 
 
-@pytest.mark.parametrize('side,ask,bid,last,last_ab,expected', [
-    ('bid', 12.0, 11.0, 11.5, 0.0, 11.0),  # full bid side
-    ('bid', 12.0, 11.0, 11.5, 1.0, 11.5),  # full last side
-    ('bid', 12.0, 11.0, 11.5, 0.5, 11.25),  # between bid and lat
-    ('bid', 12.0, 11.2, 10.5, 0.0, 11.2),  # Last smaller than bid
-    ('bid', 12.0, 11.2, 10.5, 1.0, 11.2),  # Last smaller than bid - uses bid
-    ('bid', 12.0, 11.2, 10.5, 0.5, 11.2),  # Last smaller than bid - uses bid
-    ('bid', 0.003, 0.002, 0.005, 0.0, 0.002),
-    ('bid', 0.003, 0.002, 0.005, None, 0.002),
-    ('ask', 12.0, 11.0, 12.5, 0.0, 12.0),  # full ask side
-    ('ask', 12.0, 11.0, 12.5, 1.0, 12.5),  # full last side
-    ('ask', 12.0, 11.0, 12.5, 0.5, 12.25),  # between bid and lat
-    ('ask', 12.2, 11.2, 10.5, 0.0, 12.2),  # Last smaller than ask
-    ('ask', 12.0, 11.0, 10.5, 1.0, 12.0),  # Last smaller than ask - uses ask
-    ('ask', 12.0, 11.2, 10.5, 0.5, 12.0),  # Last smaller than ask - uses ask
-    ('ask', 10.0, 11.0, 11.0, 0.0, 10.0),
-    ('ask', 10.11, 11.2, 11.0, 0.0, 10.11),
-    ('ask', 0.001, 0.002, 11.0, 0.0, 0.001),
-    ('ask', 0.006, 1.0, 11.0, 0.0, 0.006),
-    ('ask', 0.006, 1.0, 11.0, None, 0.006),
-])
+@pytest.mark.parametrize('side,ask,bid,last,last_ab,expected', get_sell_rate_data)
 def test_get_exit_rate(default_conf, mocker, caplog, side, bid, ask,
                        last, last_ab, expected) -> None:
     caplog.set_level(logging.DEBUG)
@@ -2481,14 +2485,14 @@ def test_get_ticker_rate_error(mocker, entry, default_conf, caplog, side, is_sho
 
 
 @pytest.mark.parametrize('is_short,side,expected', [
-    (False, 'bid', 0.043936),  # Value from order_book_l2 fitxure - bids side
-    (False, 'ask', 0.043949),  # Value from order_book_l2 fitxure - asks side
-    (False, 'other', 0.043936),  # Value from order_book_l2 fitxure - bids side
-    (False, 'same', 0.043949),  # Value from order_book_l2 fitxure - asks side
-    (True, 'bid', 0.043936),  # Value from order_book_l2 fitxure - bids side
-    (True, 'ask', 0.043949),  # Value from order_book_l2 fitxure - asks side
-    (True, 'other', 0.043949),  # Value from order_book_l2 fitxure - asks side
-    (True, 'same', 0.043936),  # Value from order_book_l2 fitxure - bids side
+    (False, 'bid', 0.043936),  # Value from order_book_l2 fixture - bids side
+    (False, 'ask', 0.043949),  # Value from order_book_l2 fixture - asks side
+    (False, 'other', 0.043936),  # Value from order_book_l2 fixture - bids side
+    (False, 'same', 0.043949),  # Value from order_book_l2 fixture - asks side
+    (True, 'bid', 0.043936),  # Value from order_book_l2 fixture - bids side
+    (True, 'ask', 0.043949),  # Value from order_book_l2 fixture - asks side
+    (True, 'other', 0.043949),  # Value from order_book_l2 fixture - asks side
+    (True, 'same', 0.043936),  # Value from order_book_l2 fixture - bids side
 ])
 def test_get_exit_rate_orderbook(
         default_conf, mocker, caplog, is_short, side, expected, order_book_l2):
@@ -2521,7 +2525,8 @@ def test_get_exit_rate_orderbook_exception(default_conf, mocker, caplog):
     exchange = get_patched_exchange(mocker, default_conf)
     with pytest.raises(PricingError):
         exchange.get_rate(pair, refresh=True, side="exit", is_short=False)
-    assert log_has_re(r"Exit Price at location 1 from orderbook could not be determined\..*",
+    assert log_has_re(rf"{pair} - Exit Price at location 1 from orderbook "
+                      rf"could not be determined\..*",
                       caplog)
 
 
@@ -2548,6 +2553,84 @@ def test_get_exit_rate_exception(default_conf, mocker, is_short):
     assert exchange.get_rate(pair, refresh=True, side="exit", is_short=is_short) == 0.13
 
 
+@pytest.mark.parametrize("side,ask,bid,last,last_ab,expected", get_entry_rate_data)
+@pytest.mark.parametrize("side2", ['bid', 'ask'])
+@pytest.mark.parametrize("use_order_book", [True, False])
+def test_get_rates_testing_buy(mocker, default_conf, caplog, side, ask, bid,
+                               last, last_ab, expected,
+                               side2, use_order_book, order_book_l2) -> None:
+    caplog.set_level(logging.DEBUG)
+    if last_ab is None:
+        del default_conf['entry_pricing']['price_last_balance']
+    else:
+        default_conf['entry_pricing']['price_last_balance'] = last_ab
+    default_conf['entry_pricing']['price_side'] = side
+    default_conf['exit_pricing']['price_side'] = side2
+    default_conf['exit_pricing']['use_order_book'] = use_order_book
+    api_mock = MagicMock()
+    api_mock.fetch_l2_order_book = order_book_l2
+    api_mock.fetch_ticker = MagicMock(
+        return_value={'ask': ask, 'last': last, 'bid': bid})
+    exchange = get_patched_exchange(mocker, default_conf, api_mock)
+
+    assert exchange.get_rates('ETH/BTC', refresh=True, is_short=False)[0] == expected
+    assert not log_has("Using cached buy rate for ETH/BTC.", caplog)
+
+    api_mock.fetch_l2_order_book.reset_mock()
+    api_mock.fetch_ticker.reset_mock()
+    assert exchange.get_rates('ETH/BTC', refresh=False, is_short=False)[0] == expected
+    assert log_has("Using cached buy rate for ETH/BTC.", caplog)
+    assert api_mock.fetch_l2_order_book.call_count == 0
+    assert api_mock.fetch_ticker.call_count == 0
+    # Running a 2nd time with Refresh on!
+    caplog.clear()
+
+    assert exchange.get_rates('ETH/BTC', refresh=True, is_short=False)[0] == expected
+    assert not log_has("Using cached buy rate for ETH/BTC.", caplog)
+
+    assert api_mock.fetch_l2_order_book.call_count == int(use_order_book)
+    assert api_mock.fetch_ticker.call_count == 1
+
+
+@pytest.mark.parametrize('side,ask,bid,last,last_ab,expected', get_sell_rate_data)
+@pytest.mark.parametrize("side2", ['bid', 'ask'])
+@pytest.mark.parametrize("use_order_book", [True, False])
+def test_get_rates_testing_sell(default_conf, mocker, caplog, side, bid, ask,
+                                last, last_ab, expected,
+                                side2, use_order_book, order_book_l2) -> None:
+    caplog.set_level(logging.DEBUG)
+
+    default_conf['exit_pricing']['price_side'] = side
+    if last_ab is not None:
+        default_conf['exit_pricing']['price_last_balance'] = last_ab
+
+    default_conf['entry_pricing']['price_side'] = side2
+    default_conf['entry_pricing']['use_order_book'] = use_order_book
+    api_mock = MagicMock()
+    api_mock.fetch_l2_order_book = order_book_l2
+    api_mock.fetch_ticker = MagicMock(
+                return_value={'ask': ask, 'last': last, 'bid': bid})
+    exchange = get_patched_exchange(mocker, default_conf, api_mock)
+
+    pair = "ETH/BTC"
+
+    # Test regular mode
+    rate = exchange.get_rates(pair, refresh=True, is_short=False)[1]
+    assert not log_has("Using cached sell rate for ETH/BTC.", caplog)
+    assert isinstance(rate, float)
+    assert rate == expected
+    # Use caching
+    api_mock.fetch_l2_order_book.reset_mock()
+    api_mock.fetch_ticker.reset_mock()
+
+    rate = exchange.get_rates(pair, refresh=False, is_short=False)[1]
+    assert rate == expected
+    assert log_has("Using cached sell rate for ETH/BTC.", caplog)
+
+    assert api_mock.fetch_l2_order_book.call_count == 0
+    assert api_mock.fetch_ticker.call_count == 0
+
+
 @pytest.mark.parametrize("exchange_name", EXCHANGES)
 @pytest.mark.asyncio
 async def test___async_get_candle_history_sort(default_conf, mocker, exchange_name):
diff --git a/tests/optimize/test_backtesting_adjust_position.py b/tests/optimize/test_backtesting_adjust_position.py
index fca9c01b2..2bb7de574 100644
--- a/tests/optimize/test_backtesting_adjust_position.py
+++ b/tests/optimize/test_backtesting_adjust_position.py
@@ -1,8 +1,10 @@
 # pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, unused-argument
 
 from copy import deepcopy
+from unittest.mock import MagicMock
 
 import pandas as pd
+import pytest
 from arrow import Arrow
 
 from freqtrade.configuration import TimeRange
@@ -87,3 +89,87 @@ def test_backtest_position_adjustment(default_conf, fee, mocker, testdatadir) ->
         assert (round(ln.iloc[0]["open"], 6) == round(t["close_rate"], 6) or
                 round(ln.iloc[0]["low"], 6) < round(
                 t["close_rate"], 6) < round(ln.iloc[0]["high"], 6))
+
+
+def test_backtest_position_adjustment_detailed(default_conf, fee, mocker) -> None:
+    default_conf['use_exit_signal'] = False
+    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
+    mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=10)
+    mocker.patch("freqtrade.exchange.Exchange.get_max_pair_stake_amount", return_value=float('inf'))
+    patch_exchange(mocker)
+    default_conf.update({
+        "stake_amount": 100.0,
+        "dry_run_wallet": 1000.0,
+        "strategy": "StrategyTestV3"
+    })
+    backtesting = Backtesting(default_conf)
+    backtesting._set_strategy(backtesting.strategylist[0])
+    pair = 'XRP/USDT'
+    row = [
+            pd.Timestamp(year=2020, month=1, day=1, hour=5, minute=0),
+            2.1,  # Open
+            2.2,  # High
+            1.9,  # Low
+            2.1,  # Close
+            1,  # enter_long
+            0,  # exit_long
+            0,  # enter_short
+            0,  # exit_short
+            '',  # enter_tag
+            '',  # exit_tag
+            ]
+    trade = backtesting._enter_trade(pair, row=row, direction='long')
+    trade.orders[0].close_bt_order(row[0], trade)
+    assert trade
+    assert pytest.approx(trade.stake_amount) == 100.0
+    assert pytest.approx(trade.amount) == 47.61904762
+    assert len(trade.orders) == 1
+    backtesting.strategy.adjust_trade_position = MagicMock(return_value=None)
+
+    trade = backtesting._get_adjust_trade_entry_for_candle(trade, row)
+    assert trade
+    assert pytest.approx(trade.stake_amount) == 100.0
+    assert pytest.approx(trade.amount) == 47.61904762
+    assert len(trade.orders) == 1
+    # Increase position by 100
+    backtesting.strategy.adjust_trade_position = MagicMock(return_value=100)
+
+    trade = backtesting._get_adjust_trade_entry_for_candle(trade, row)
+
+    assert trade
+    assert pytest.approx(trade.stake_amount) == 200.0
+    assert pytest.approx(trade.amount) == 95.23809524
+    assert len(trade.orders) == 2
+
+    # Reduce by more than amount - no change to trade.
+    backtesting.strategy.adjust_trade_position = MagicMock(return_value=-500)
+
+    trade = backtesting._get_adjust_trade_entry_for_candle(trade, row)
+
+    assert trade
+    assert pytest.approx(trade.stake_amount) == 200.0
+    assert pytest.approx(trade.amount) == 95.23809524
+    assert len(trade.orders) == 2
+    assert trade.nr_of_successful_entries == 2
+
+    # Reduce position by 50
+    backtesting.strategy.adjust_trade_position = MagicMock(return_value=-100)
+    trade = backtesting._get_adjust_trade_entry_for_candle(trade, row)
+
+    assert trade
+    assert pytest.approx(trade.stake_amount) == 100.0
+    assert pytest.approx(trade.amount) == 47.61904762
+    assert len(trade.orders) == 3
+    assert trade.nr_of_successful_entries == 2
+    assert trade.nr_of_successful_exits == 1
+
+    # Adjust below minimum
+    backtesting.strategy.adjust_trade_position = MagicMock(return_value=-99)
+    trade = backtesting._get_adjust_trade_entry_for_candle(trade, row)
+
+    assert trade
+    assert pytest.approx(trade.stake_amount) == 100.0
+    assert pytest.approx(trade.amount) == 47.61904762
+    assert len(trade.orders) == 3
+    assert trade.nr_of_successful_entries == 2
+    assert trade.nr_of_successful_exits == 1
diff --git a/tests/rpc/test_rpc.py b/tests/rpc/test_rpc.py
index 6e19fcaf3..02c62e337 100644
--- a/tests/rpc/test_rpc.py
+++ b/tests/rpc/test_rpc.py
@@ -111,6 +111,7 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
         'stoploss_entry_dist': -0.00010475,
         'stoploss_entry_dist_ratio': -0.10448878,
         'open_order': None,
+        'realized_profit': 0.0,
         'exchange': 'binance',
         'leverage': 1.0,
         'interest_rate': 0.0,
@@ -196,6 +197,7 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
         'stoploss_entry_dist_ratio': -0.10448878,
         'open_order': None,
         'exchange': 'binance',
+        'realized_profit': 0.0,
         'leverage': 1.0,
         'interest_rate': 0.0,
         'liquidation_price': None,
@@ -841,7 +843,8 @@ def test_rpc_force_exit(default_conf, ticker, fee, mocker) -> None:
             'side': 'sell',
             'amount': amount,
             'remaining': amount,
-            'filled': 0.0
+            'filled': 0.0,
+            'id': trade.orders[0].order_id,
         }
     )
     msg = rpc._rpc_force_exit('3')
diff --git a/tests/rpc/test_rpc_telegram.py b/tests/rpc/test_rpc_telegram.py
index 8d244f3fd..98c06c8e9 100644
--- a/tests/rpc/test_rpc_telegram.py
+++ b/tests/rpc/test_rpc_telegram.py
@@ -272,7 +272,7 @@ def test_telegram_status_multi_entry(default_conf, update, mocker, fee) -> None:
     msg = msg_mock.call_args_list[0][0][0]
     assert re.search(r'Number of Entries.*2', msg)
     assert re.search(r'Average Entry Price', msg)
-    assert re.search(r'Order filled at', msg)
+    assert re.search(r'Order filled', msg)
     assert re.search(r'Close Date:', msg) is None
     assert re.search(r'Close Profit:', msg) is None
 
@@ -959,6 +959,9 @@ def test_telegram_forceexit_handle(default_conf, update, ticker, fee,
         'open_date': ANY,
         'close_date': ANY,
         'close_rate': ANY,
+        'stake_amount': 0.0009999999999054,
+        'sub_trade': False,
+        'cumulative_profit': 0.0,
     } == last_msg
 
 
@@ -1028,6 +1031,9 @@ def test_telegram_force_exit_down_handle(default_conf, update, ticker, fee,
         'open_date': ANY,
         'close_date': ANY,
         'close_rate': ANY,
+        'stake_amount': 0.0009999999999054,
+        'sub_trade': False,
+        'cumulative_profit': 0.0,
     } == last_msg
 
 
@@ -1087,6 +1093,9 @@ def test_forceexit_all_handle(default_conf, update, ticker, fee, mocker) -> None
         'open_date': ANY,
         'close_date': ANY,
         'close_rate': ANY,
+        'stake_amount': 0.0009999999999054,
+        'sub_trade': False,
+        'cumulative_profit': 0.0,
     } == msg
 
 
@@ -1437,7 +1446,7 @@ def test_whitelist_static(default_conf, update, mocker) -> None:
 def test_whitelist_dynamic(default_conf, update, mocker) -> None:
     mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
     default_conf['pairlists'] = [{'method': 'VolumePairList',
-                                 'number_assets': 4
+                                  'number_assets': 4
                                   }]
     telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
 
@@ -1789,7 +1798,6 @@ def test_send_msg_entry_fill_notification(default_conf, mocker, message_type, en
         'leverage': leverage,
         'stake_amount': 0.01465333,
         'direction': entered,
-        # 'stake_amount_fiat': 0.0,
         'stake_currency': 'BTC',
         'fiat_currency': 'USD',
         'open_rate': 1.099e-05,
@@ -1806,6 +1814,33 @@ def test_send_msg_entry_fill_notification(default_conf, mocker, message_type, en
         '*Total:* `(0.01465333 BTC, 180.895 USD)`'
     )
 
+    msg_mock.reset_mock()
+    telegram.send_msg({
+        'type': message_type,
+        'trade_id': 1,
+        'enter_tag': enter_signal,
+        'exchange': 'Binance',
+        'pair': 'ETH/BTC',
+        'leverage': leverage,
+        'stake_amount': 0.01465333,
+        'sub_trade': True,
+        'direction': entered,
+        'stake_currency': 'BTC',
+        'fiat_currency': 'USD',
+        'open_rate': 1.099e-05,
+        'amount': 1333.3333333333335,
+        'open_date': arrow.utcnow().shift(hours=-1)
+    })
+
+    assert msg_mock.call_args[0][0] == (
+        f'\N{CHECK MARK} *Binance (dry):* {entered}ed ETH/BTC (#1)\n'
+        f'*Enter Tag:* `{enter_signal}`\n'
+        '*Amount:* `1333.33333333`\n'
+        f"{leverage_text}"
+        '*Open Rate:* `0.00001099`\n'
+        '*Total:* `(0.01465333 BTC, 180.895 USD)`'
+    )
+
 
 def test_send_msg_sell_notification(default_conf, mocker) -> None:
 
@@ -1840,14 +1875,53 @@ def test_send_msg_sell_notification(default_conf, mocker) -> None:
         '*Unrealized Profit:* `-57.41% (loss: -0.05746268 ETH / -24.812 USD)`\n'
         '*Enter Tag:* `buy_signal1`\n'
         '*Exit Reason:* `stop_loss`\n'
-        '*Duration:* `1:00:00 (60.0 min)`\n'
         '*Direction:* `Long`\n'
         '*Amount:* `1333.33333333`\n'
         '*Open Rate:* `0.00007500`\n'
         '*Current Rate:* `0.00003201`\n'
-        '*Close Rate:* `0.00003201`'
+        '*Exit Rate:* `0.00003201`\n'
+        '*Duration:* `1:00:00 (60.0 min)`'
     )
 
+    msg_mock.reset_mock()
+    telegram.send_msg({
+        'type': RPCMessageType.EXIT,
+        'trade_id': 1,
+        'exchange': 'Binance',
+        'pair': 'KEY/ETH',
+        'direction': 'Long',
+        'gain': 'loss',
+        'limit': 3.201e-05,
+        'amount': 1333.3333333333335,
+        'order_type': 'market',
+        'open_rate': 7.5e-05,
+        'current_rate': 3.201e-05,
+        'cumulative_profit': -0.15746268,
+        'profit_amount': -0.05746268,
+        'profit_ratio': -0.57405275,
+        'stake_currency': 'ETH',
+        'fiat_currency': 'USD',
+        'enter_tag': 'buy_signal1',
+        'exit_reason': ExitType.STOP_LOSS.value,
+        'open_date': arrow.utcnow().shift(days=-1, hours=-2, minutes=-30),
+        'close_date': arrow.utcnow(),
+        'stake_amount': 0.01,
+        'sub_trade': True,
+    })
+    assert msg_mock.call_args[0][0] == (
+        '\N{WARNING SIGN} *Binance (dry):* Exiting KEY/ETH (#1)\n'
+        '*Unrealized Sub Profit:* `-57.41% (loss: -0.05746268 ETH / -24.812 USD)`\n'
+        '*Cumulative Profit:* (`-0.15746268 ETH / -24.812 USD`)\n'
+        '*Enter Tag:* `buy_signal1`\n'
+        '*Exit Reason:* `stop_loss`\n'
+        '*Direction:* `Long`\n'
+        '*Amount:* `1333.33333333`\n'
+        '*Open Rate:* `0.00007500`\n'
+        '*Current Rate:* `0.00003201`\n'
+        '*Exit Rate:* `0.00003201`\n'
+        '*Remaining:* `(0.01 ETH, -24.812 USD)`'
+        )
+
     msg_mock.reset_mock()
     telegram.send_msg({
         'type': RPCMessageType.EXIT,
@@ -1871,15 +1945,15 @@ def test_send_msg_sell_notification(default_conf, mocker) -> None:
     })
     assert msg_mock.call_args[0][0] == (
         '\N{WARNING SIGN} *Binance (dry):* Exiting KEY/ETH (#1)\n'
-        '*Unrealized Profit:* `-57.41%`\n'
+        '*Unrealized Profit:* `-57.41% (loss: -0.05746268 ETH)`\n'
         '*Enter Tag:* `buy_signal1`\n'
         '*Exit Reason:* `stop_loss`\n'
-        '*Duration:* `1 day, 2:30:00 (1590.0 min)`\n'
         '*Direction:* `Long`\n'
         '*Amount:* `1333.33333333`\n'
         '*Open Rate:* `0.00007500`\n'
         '*Current Rate:* `0.00003201`\n'
-        '*Close Rate:* `0.00003201`'
+        '*Exit Rate:* `0.00003201`\n'
+        '*Duration:* `1 day, 2:30:00 (1590.0 min)`'
     )
     # Reset singleton function to avoid random breaks
     telegram._rpc._fiat_converter.convert_amount = old_convamount
@@ -1954,15 +2028,15 @@ def test_send_msg_sell_fill_notification(default_conf, mocker, direction,
     leverage_text = f'*Leverage:* `{leverage}`\n' if leverage and leverage != 1.0 else ''
     assert msg_mock.call_args[0][0] == (
         '\N{WARNING SIGN} *Binance (dry):* Exited KEY/ETH (#1)\n'
-        '*Profit:* `-57.41%`\n'
+        '*Profit:* `-57.41% (loss: -0.05746268 ETH)`\n'
         f'*Enter Tag:* `{enter_signal}`\n'
         '*Exit Reason:* `stop_loss`\n'
-        '*Duration:* `1 day, 2:30:00 (1590.0 min)`\n'
         f"*Direction:* `{direction}`\n"
         f"{leverage_text}"
         '*Amount:* `1333.33333333`\n'
         '*Open Rate:* `0.00007500`\n'
-        '*Close Rate:* `0.00003201`'
+        '*Exit Rate:* `0.00003201`\n'
+        '*Duration:* `1 day, 2:30:00 (1590.0 min)`'
     )
 
 
@@ -2090,16 +2164,16 @@ def test_send_msg_sell_notification_no_fiat(
     leverage_text = f'*Leverage:* `{leverage}`\n' if leverage and leverage != 1.0 else ''
     assert msg_mock.call_args[0][0] == (
         '\N{WARNING SIGN} *Binance (dry):* Exiting KEY/ETH (#1)\n'
-        '*Unrealized Profit:* `-57.41%`\n'
+        '*Unrealized Profit:* `-57.41% (loss: -0.05746268 ETH)`\n'
         f'*Enter Tag:* `{enter_signal}`\n'
         '*Exit Reason:* `stop_loss`\n'
-        '*Duration:* `2:35:03 (155.1 min)`\n'
         f'*Direction:* `{direction}`\n'
         f'{leverage_text}'
         '*Amount:* `1333.33333333`\n'
         '*Open Rate:* `0.00007500`\n'
         '*Current Rate:* `0.00003201`\n'
-        '*Close Rate:* `0.00003201`'
+        '*Exit Rate:* `0.00003201`\n'
+        '*Duration:* `2:35:03 (155.1 min)`'
     )
 
 
diff --git a/tests/strategy/strats/strategy_test_v3.py b/tests/strategy/strats/strategy_test_v3.py
index 2c7ccbdf2..088ab21d4 100644
--- a/tests/strategy/strats/strategy_test_v3.py
+++ b/tests/strategy/strats/strategy_test_v3.py
@@ -185,9 +185,12 @@ class StrategyTestV3(IStrategy):
 
         return 3.0
 
-    def adjust_trade_position(self, trade: Trade, current_time: datetime, current_rate: float,
-                              current_profit: float,
-                              min_stake: Optional[float], max_stake: float, **kwargs):
+    def adjust_trade_position(self, trade: Trade, current_time: datetime,
+                              current_rate: float, current_profit: float,
+                              min_stake: Optional[float], max_stake: float,
+                              current_entry_rate: float, current_exit_rate: float,
+                              current_entry_profit: float, current_exit_profit: float,
+                              **kwargs) -> Optional[float]:
 
         if current_profit < -0.0075:
             orders = trade.select_filled_orders(trade.entry_side)
diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py
index 438a2704c..0b073a062 100644
--- a/tests/test_freqtradebot.py
+++ b/tests/test_freqtradebot.py
@@ -843,8 +843,8 @@ def test_execute_entry(mocker, default_conf_usdt, fee, limit_order,
 
     # In case of closed order
     order['status'] = 'closed'
-    order['price'] = 10
-    order['cost'] = 100
+    order['average'] = 10
+    order['cost'] = 300
     order['id'] = '444'
 
     mocker.patch('freqtrade.exchange.Exchange.create_order',
@@ -855,7 +855,7 @@ def test_execute_entry(mocker, default_conf_usdt, fee, limit_order,
     assert trade
     assert trade.open_order_id is None
     assert trade.open_rate == 10
-    assert trade.stake_amount == round(order['price'] * order['filled'] / leverage, 8)
+    assert trade.stake_amount == round(order['average'] * order['filled'] / leverage, 8)
     assert pytest.approx(trade.liquidation_price) == liq_price
 
     # In case of rejected or expired order and partially filled
@@ -863,8 +863,8 @@ def test_execute_entry(mocker, default_conf_usdt, fee, limit_order,
     order['amount'] = 30.0
     order['filled'] = 20.0
     order['remaining'] = 10.00
-    order['price'] = 0.5
-    order['cost'] = 15.0
+    order['average'] = 0.5
+    order['cost'] = 10.0
     order['id'] = '555'
     mocker.patch('freqtrade.exchange.Exchange.create_order',
                  MagicMock(return_value=order))
@@ -872,9 +872,9 @@ def test_execute_entry(mocker, default_conf_usdt, fee, limit_order,
     trade = Trade.query.all()[3]
     trade.is_short = is_short
     assert trade
-    assert trade.open_order_id == '555'
+    assert trade.open_order_id is None
     assert trade.open_rate == 0.5
-    assert trade.stake_amount == round(order['price'] * order['filled'] / leverage, 8)
+    assert trade.stake_amount == round(order['average'] * order['filled'] / leverage, 8)
 
     # Test with custom stake
     order['status'] = 'open'
@@ -901,7 +901,7 @@ def test_execute_entry(mocker, default_conf_usdt, fee, limit_order,
     order['amount'] = 30.0 * leverage
     order['filled'] = 0.0
     order['remaining'] = 30.0
-    order['price'] = 0.5
+    order['average'] = 0.5
     order['cost'] = 0.0
     order['id'] = '66'
     mocker.patch('freqtrade.exchange.Exchange.create_order',
@@ -1083,7 +1083,7 @@ def test_handle_stoploss_on_exchange(mocker, default_conf_usdt, fee, caplog, is_
             'last': 1.9
         }),
         create_order=MagicMock(side_effect=[
-            {'id': enter_order['id']},
+            enter_order,
             exit_order,
         ]),
         get_fee=fee,
@@ -1109,20 +1109,20 @@ def test_handle_stoploss_on_exchange(mocker, default_conf_usdt, fee, caplog, is_
     # should do nothing and return false
     trade.is_open = True
     trade.open_order_id = None
-    trade.stoploss_order_id = 100
+    trade.stoploss_order_id = "100"
 
     hanging_stoploss_order = MagicMock(return_value={'status': 'open'})
     mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', hanging_stoploss_order)
 
     assert freqtrade.handle_stoploss_on_exchange(trade) is False
-    assert trade.stoploss_order_id == 100
+    assert trade.stoploss_order_id == "100"
 
     # Third case: when stoploss was set but it was canceled for some reason
     # should set a stoploss immediately and return False
     caplog.clear()
     trade.is_open = True
     trade.open_order_id = None
-    trade.stoploss_order_id = 100
+    trade.stoploss_order_id = "100"
 
     canceled_stoploss_order = MagicMock(return_value={'status': 'canceled'})
     mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', canceled_stoploss_order)
@@ -2039,6 +2039,7 @@ def test_update_trade_state_exception(mocker, default_conf_usdt, is_short, limit
 
     trade = MagicMock()
     trade.open_order_id = '123'
+    trade.amount = 123
 
     # Test raise of OperationalException exception
     mocker.patch(
@@ -2352,9 +2353,9 @@ def test_close_trade(
     trade.is_short = is_short
     assert trade
 
-    oobj = Order.parse_from_ccxt_object(enter_order, enter_order['symbol'], 'buy')
+    oobj = Order.parse_from_ccxt_object(enter_order, enter_order['symbol'], trade.enter_side)
     trade.update_trade(oobj)
-    oobj = Order.parse_from_ccxt_object(exit_order, exit_order['symbol'], 'sell')
+    oobj = Order.parse_from_ccxt_object(exit_order, exit_order['symbol'], trade.exit_side)
     trade.update_trade(oobj)
     assert trade.is_open is False
 
@@ -2397,8 +2398,8 @@ def test_manage_open_orders_entry_usercustom(
         'freqtrade.exchange.Exchange',
         fetch_ticker=ticker_usdt,
         fetch_order=MagicMock(return_value=old_order),
-        cancel_order_with_result=cancel_order_wr_mock,
         cancel_order=cancel_order_mock,
+        cancel_order_with_result=cancel_order_wr_mock,
         get_fee=fee
     )
     freqtrade = FreqtradeBot(default_conf_usdt)
@@ -2446,7 +2447,9 @@ def test_manage_open_orders_entry(
 ) -> None:
     old_order = limit_sell_order_old if is_short else limit_buy_order_old
     rpc_mock = patch_RPCManager(mocker)
-    old_order['id'] = open_trade.open_order_id
+    open_trade.open_order_id = old_order['id']
+    order = Order.parse_from_ccxt_object(old_order, 'mocked', 'buy')
+    open_trade.orders[0] = order
     limit_buy_cancel = deepcopy(old_order)
     limit_buy_cancel['status'] = 'canceled'
     cancel_order_mock = MagicMock(return_value=limit_buy_cancel)
@@ -2637,7 +2640,9 @@ def test_manage_open_orders_exit_usercustom(
     is_short, open_trade_usdt, caplog
 ) -> None:
     default_conf_usdt["unfilledtimeout"] = {"entry": 1440, "exit": 1440, "exit_timeout_count": 1}
-    limit_sell_order_old['id'] = open_trade_usdt.open_order_id
+    open_trade_usdt.open_order_id = limit_sell_order_old['id']
+    order = Order.parse_from_ccxt_object(limit_sell_order_old, 'mocked', 'sell')
+    open_trade_usdt.orders[0] = order
     if is_short:
         limit_sell_order_old['side'] = 'buy'
         open_trade_usdt.is_short = is_short
@@ -3250,6 +3255,9 @@ def test_execute_trade_exit_up(default_conf_usdt, ticker_usdt, fee, ticker_usdt_
         'open_date': ANY,
         'close_date': ANY,
         'close_rate': ANY,
+        'sub_trade': False,
+        'cumulative_profit': 0.0,
+        'stake_amount': pytest.approx(60),
     } == last_msg
 
 
@@ -3310,6 +3318,9 @@ def test_execute_trade_exit_down(default_conf_usdt, ticker_usdt, fee, ticker_usd
         'open_date': ANY,
         'close_date': ANY,
         'close_rate': ANY,
+        'sub_trade': False,
+        'cumulative_profit': 0.0,
+        'stake_amount': pytest.approx(60),
     } == last_msg
 
 
@@ -3391,6 +3402,9 @@ def test_execute_trade_exit_custom_exit_price(
         'open_date': ANY,
         'close_date': ANY,
         'close_rate': ANY,
+        'sub_trade': False,
+        'cumulative_profit': 0.0,
+        'stake_amount': pytest.approx(60),
     } == last_msg
 
 
@@ -3459,6 +3473,9 @@ def test_execute_trade_exit_down_stoploss_on_exchange_dry_run(
         'open_date': ANY,
         'close_date': ANY,
         'close_rate': ANY,
+        'sub_trade': False,
+        'cumulative_profit': 0.0,
+        'stake_amount': pytest.approx(60),
     } == last_msg
 
 
@@ -3690,7 +3707,7 @@ def test_execute_trade_exit_market_order(
     )
 
     assert not trade.is_open
-    assert trade.close_profit == profit_ratio
+    assert pytest.approx(trade.close_profit) == profit_ratio
 
     assert rpc_mock.call_count == 4
     last_msg = rpc_mock.call_args_list[-2][0][0]
@@ -3718,6 +3735,9 @@ def test_execute_trade_exit_market_order(
         'open_date': ANY,
         'close_date': ANY,
         'close_rate': ANY,
+        'sub_trade': False,
+        'cumulative_profit': 0.0,
+        'stake_amount': pytest.approx(60),
 
     } == last_msg
 
@@ -3789,7 +3809,7 @@ def test_exit_profit_only(
             'last': bid
         }),
         create_order=MagicMock(side_effect=[
-            limit_order_open[eside],
+            limit_order[eside],
             {'id': 1234553382},
         ]),
         get_fee=fee,
@@ -4081,7 +4101,7 @@ def test_trailing_stop_loss_positive(
             'last': enter_price - (-0.01 if is_short else 0.01),
         }),
         create_order=MagicMock(side_effect=[
-            limit_order_open[eside],
+            limit_order[eside],
             {'id': 1234553382},
         ]),
         get_fee=fee,
@@ -4632,7 +4652,7 @@ def test_order_book_entry_pricing1(mocker, default_conf_usdt, order_book_l2, exc
         with pytest.raises(PricingError):
             freqtrade.exchange.get_rate('ETH/USDT', side="entry", is_short=False, refresh=True)
         assert log_has_re(
-            r'Entry Price at location 1 from orderbook could not be determined.', caplog)
+            r'ETH/USDT - Entry Price at location 1 from orderbook could not be determined.', caplog)
     else:
         assert freqtrade.exchange.get_rate(
             'ETH/USDT', side="entry", is_short=False, refresh=True) == 0.043935
@@ -4711,8 +4731,9 @@ def test_order_book_exit_pricing(
                  return_value={'bids': [[]], 'asks': [[]]})
     with pytest.raises(PricingError):
         freqtrade.handle_trade(trade)
-    assert log_has_re(r'Exit Price at location 1 from orderbook could not be determined\..*',
-                      caplog)
+    assert log_has_re(
+        r"ETH/USDT - Exit Price at location 1 from orderbook could not be determined\..*",
+        caplog)
 
 
 def test_startup_state(default_conf_usdt, mocker):
@@ -5385,7 +5406,7 @@ def test_position_adjust(mocker, default_conf_usdt, fee) -> None:
         'status': None,
         'price': 9,
         'amount': 12,
-        'cost': 100,
+        'cost': 108,
         'ft_is_open': True,
         'id': '651',
         'order_id': '651'
@@ -5480,7 +5501,7 @@ def test_position_adjust(mocker, default_conf_usdt, fee) -> None:
     assert trade.open_order_id is None
     assert pytest.approx(trade.open_rate) == 9.90909090909
     assert trade.amount == 22
-    assert trade.stake_amount == 218
+    assert pytest.approx(trade.stake_amount) == 218
 
     orders = Order.query.all()
     assert orders
@@ -5533,6 +5554,329 @@ def test_position_adjust(mocker, default_conf_usdt, fee) -> None:
     # Make sure the closed order is found as the second order.
     order = trade.select_order('buy', False)
     assert order.order_id == '652'
+    closed_sell_dca_order_1 = {
+        'ft_pair': pair,
+        'status': 'closed',
+        'ft_order_side': 'sell',
+        'side': 'sell',
+        'type': 'limit',
+        'price': 8,
+        'average': 8,
+        'amount': 15,
+        'filled': 15,
+        'cost': 120,
+        'ft_is_open': False,
+        'id': '653',
+        'order_id': '653'
+    }
+    mocker.patch('freqtrade.exchange.Exchange.create_order',
+                 MagicMock(return_value=closed_sell_dca_order_1))
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order',
+                 MagicMock(return_value=closed_sell_dca_order_1))
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order_or_stoploss_order',
+                 MagicMock(return_value=closed_sell_dca_order_1))
+    assert freqtrade.execute_trade_exit(trade=trade, limit=8,
+                                        exit_check=ExitCheckTuple(exit_type=ExitType.PARTIAL_EXIT),
+                                        sub_trade_amt=15)
+
+    # Assert trade is as expected (averaged dca)
+    trade = Trade.query.first()
+    assert trade
+    assert trade.open_order_id is None
+    assert trade.is_open
+    assert trade.amount == 22
+    assert trade.stake_amount == 192.05405405405406
+    assert pytest.approx(trade.open_rate) == 8.729729729729
+
+    orders = Order.query.all()
+    assert orders
+    assert len(orders) == 4
+
+    # Make sure the closed order is found as the second order.
+    order = trade.select_order('sell', False)
+    assert order.order_id == '653'
+
+
+def test_position_adjust2(mocker, default_conf_usdt, fee) -> None:
+    """
+    TODO: Should be adjusted to test both long and short
+    buy 100 @ 11
+    sell 50 @ 8
+    sell 50 @ 16
+    """
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    patch_wallet(mocker, free=10000)
+    default_conf_usdt.update({
+        "position_adjustment_enable": True,
+        "dry_run": False,
+        "stake_amount": 200.0,
+        "dry_run_wallet": 1000.0,
+    })
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    freqtrade.strategy.confirm_trade_entry = MagicMock(return_value=True)
+    bid = 11
+    amount = 100
+    buy_rate_mock = MagicMock(return_value=bid)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_rate=buy_rate_mock,
+        fetch_ticker=MagicMock(return_value={
+            'bid': 10,
+            'ask': 12,
+            'last': 11
+        }),
+        get_min_pair_stake_amount=MagicMock(return_value=1),
+        get_fee=fee,
+    )
+    pair = 'ETH/USDT'
+    # Initial buy
+    closed_successful_buy_order = {
+        'pair': pair,
+        'ft_pair': pair,
+        'ft_order_side': 'buy',
+        'side': 'buy',
+        'type': 'limit',
+        'status': 'closed',
+        'price': bid,
+        'average': bid,
+        'cost': bid * amount,
+        'amount': amount,
+        'filled': amount,
+        'ft_is_open': False,
+        'id': '600',
+        'order_id': '600'
+    }
+    mocker.patch('freqtrade.exchange.Exchange.create_order',
+                 MagicMock(return_value=closed_successful_buy_order))
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order_or_stoploss_order',
+                 MagicMock(return_value=closed_successful_buy_order))
+    assert freqtrade.execute_entry(pair, amount)
+    # Should create an closed trade with an no open order id
+    # Order is filled and trade is open
+    orders = Order.query.all()
+    assert orders
+    assert len(orders) == 1
+    trade = Trade.query.first()
+    assert trade
+    assert trade.is_open is True
+    assert trade.open_order_id is None
+    assert trade.open_rate == bid
+    assert trade.stake_amount == bid * amount
+
+    # Assume it does nothing since order is closed and trade is open
+    freqtrade.update_closed_trades_without_assigned_fees()
+
+    trade = Trade.query.first()
+    assert trade
+    assert trade.is_open is True
+    assert trade.open_order_id is None
+    assert trade.open_rate == bid
+    assert trade.stake_amount == bid * amount
+    assert not trade.fee_updated(trade.entry_side)
+
+    freqtrade.manage_open_orders()
+
+    trade = Trade.query.first()
+    assert trade
+    assert trade.is_open is True
+    assert trade.open_order_id is None
+    assert trade.open_rate == bid
+    assert trade.stake_amount == bid * amount
+    assert not trade.fee_updated(trade.entry_side)
+
+    amount = 50
+    ask = 8
+    closed_sell_dca_order_1 = {
+        'ft_pair': pair,
+        'status': 'closed',
+        'ft_order_side': 'sell',
+        'side': 'sell',
+        'type': 'limit',
+        'price': ask,
+        'average': ask,
+        'amount': amount,
+        'filled': amount,
+        'cost': amount * ask,
+        'ft_is_open': False,
+        'id': '601',
+        'order_id': '601'
+    }
+    mocker.patch('freqtrade.exchange.Exchange.create_order',
+                 MagicMock(return_value=closed_sell_dca_order_1))
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order',
+                 MagicMock(return_value=closed_sell_dca_order_1))
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order_or_stoploss_order',
+                 MagicMock(return_value=closed_sell_dca_order_1))
+    assert freqtrade.execute_trade_exit(trade=trade, limit=ask,
+                                        exit_check=ExitCheckTuple(exit_type=ExitType.PARTIAL_EXIT),
+                                        sub_trade_amt=amount)
+    trades: List[Trade] = trade.get_open_trades_without_assigned_fees()
+    assert len(trades) == 1
+    # Assert trade is as expected (averaged dca)
+
+    trade = Trade.query.first()
+    assert trade
+    assert trade.open_order_id is None
+    assert trade.amount == 50
+    assert trade.open_rate == 11
+    assert trade.stake_amount == 550
+    assert pytest.approx(trade.realized_profit) == -152.375
+    assert pytest.approx(trade.close_profit_abs) == -152.375
+
+    orders = Order.query.all()
+    assert orders
+    assert len(orders) == 2
+    # Make sure the closed order is found as the second order.
+    order = trade.select_order('sell', False)
+    assert order.order_id == '601'
+
+    amount = 50
+    ask = 16
+    closed_sell_dca_order_2 = {
+        'ft_pair': pair,
+        'status': 'closed',
+        'ft_order_side': 'sell',
+        'side': 'sell',
+        'type': 'limit',
+        'price': ask,
+        'average': ask,
+        'amount': amount,
+        'filled': amount,
+        'cost': amount * ask,
+        'ft_is_open': False,
+        'id': '602',
+        'order_id': '602'
+    }
+    mocker.patch('freqtrade.exchange.Exchange.create_order',
+                 MagicMock(return_value=closed_sell_dca_order_2))
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order',
+                 MagicMock(return_value=closed_sell_dca_order_2))
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order_or_stoploss_order',
+                 MagicMock(return_value=closed_sell_dca_order_2))
+    assert freqtrade.execute_trade_exit(trade=trade, limit=ask,
+                                        exit_check=ExitCheckTuple(exit_type=ExitType.PARTIAL_EXIT),
+                                        sub_trade_amt=amount)
+    # Assert trade is as expected (averaged dca)
+
+    trade = Trade.query.first()
+    assert trade
+    assert trade.open_order_id is None
+    assert trade.amount == 50
+    assert trade.open_rate == 11
+    assert trade.stake_amount == 550
+    # Trade fully realized
+    assert pytest.approx(trade.realized_profit) == 94.25
+    assert pytest.approx(trade.close_profit_abs) == 94.25
+    orders = Order.query.all()
+    assert orders
+    assert len(orders) == 3
+
+    # Make sure the closed order is found as the second order.
+    order = trade.select_order('sell', False)
+    assert order.order_id == '602'
+    assert trade.is_open is False
+
+
+@pytest.mark.parametrize('data', [
+    (
+        # tuple 1 - side amount, price
+        # tuple 2 - amount, open_rate, stake_amount, cumulative_profit, realized_profit, rel_profit
+        (('buy', 100, 10), (100.0, 10.0, 1000.0, 0.0, None, None)),
+        (('buy', 100, 15), (200.0, 12.5, 2500.0, 0.0, None, None)),
+        (('sell', 50, 12), (150.0, 12.5, 1875.0, -28.0625, -28.0625, -0.044788)),
+        (('sell', 100, 20), (50.0, 12.5, 625.0, 713.8125, 741.875, 0.59201995)),
+        (('sell', 50, 5), (50.0, 12.5, 625.0, 336.625, 336.625, 0.1343142)),  # final profit (sum)
+    ),
+    (
+        (('buy', 100, 3), (100.0, 3.0, 300.0, 0.0, None, None)),
+        (('buy', 100, 7), (200.0, 5.0, 1000.0, 0.0, None, None)),
+        (('sell', 100, 11), (100.0, 5.0, 500.0, 596.0, 596.0, 1.189027)),
+        (('buy', 150, 15), (250.0, 11.0, 2750.0, 596.0, 596.0, 1.189027)),
+        (('sell', 100, 19), (150.0, 11.0, 1650.0, 1388.5, 792.5, 0.7186579)),
+        (('sell', 150, 23), (150.0, 11.0, 1650.0, 3175.75, 3175.75, 0.9747170)),  # final profit
+    )
+])
+def test_position_adjust3(mocker, default_conf_usdt, fee, data) -> None:
+    default_conf_usdt.update({
+        "position_adjustment_enable": True,
+        "dry_run": False,
+        "stake_amount": 200.0,
+        "dry_run_wallet": 1000.0,
+    })
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    patch_wallet(mocker, free=10000)
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    trade = None
+    freqtrade.strategy.confirm_trade_entry = MagicMock(return_value=True)
+    for idx, (order, result) in enumerate(data):
+        amount = order[1]
+        price = order[2]
+        price_mock = MagicMock(return_value=price)
+        mocker.patch.multiple(
+            'freqtrade.exchange.Exchange',
+            get_rate=price_mock,
+            fetch_ticker=MagicMock(return_value={
+                'bid': 10,
+                'ask': 12,
+                'last': 11
+            }),
+            get_min_pair_stake_amount=MagicMock(return_value=1),
+            get_fee=fee,
+        )
+        pair = 'ETH/USDT'
+        closed_successful_order = {
+            'pair': pair,
+            'ft_pair': pair,
+            'ft_order_side': order[0],
+            'side': order[0],
+            'type': 'limit',
+            'status': 'closed',
+            'price': price,
+            'average': price,
+            'cost': price * amount,
+            'amount': amount,
+            'filled': amount,
+            'ft_is_open': False,
+            'id': f'60{idx}',
+            'order_id': f'60{idx}'
+        }
+        mocker.patch('freqtrade.exchange.Exchange.create_order',
+                     MagicMock(return_value=closed_successful_order))
+        mocker.patch('freqtrade.exchange.Exchange.fetch_order_or_stoploss_order',
+                     MagicMock(return_value=closed_successful_order))
+        if order[0] == 'buy':
+            assert freqtrade.execute_entry(pair, amount, trade=trade)
+        else:
+            assert freqtrade.execute_trade_exit(
+                trade=trade, limit=price,
+                exit_check=ExitCheckTuple(exit_type=ExitType.PARTIAL_EXIT),
+                sub_trade_amt=amount)
+
+        orders1 = Order.query.all()
+        assert orders1
+        assert len(orders1) == idx + 1
+
+        trade = Trade.query.first()
+        assert trade
+        if idx < len(data) - 1:
+            assert trade.is_open is True
+        assert trade.open_order_id is None
+        assert trade.amount == result[0]
+        assert trade.open_rate == result[1]
+        assert trade.stake_amount == result[2]
+        assert pytest.approx(trade.realized_profit) == result[3]
+        assert pytest.approx(trade.close_profit_abs) == result[4]
+        assert pytest.approx(trade.close_profit) == result[5]
+
+        order_obj = trade.select_order(order[0], False)
+        assert order_obj.order_id == f'60{idx}'
+
+    trade = Trade.query.first()
+    assert trade
+    assert trade.open_order_id is None
+    assert trade.is_open is False
 
 
 def test_process_open_trade_positions_exception(mocker, default_conf_usdt, fee, caplog) -> None:
@@ -5556,9 +5900,25 @@ def test_check_and_call_adjust_trade_position(mocker, default_conf_usdt, fee, ca
         "max_entry_position_adjustment": 0,
     })
     freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
-
+    buy_rate_mock = MagicMock(return_value=10)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_rate=buy_rate_mock,
+        fetch_ticker=MagicMock(return_value={
+            'bid': 10,
+            'ask': 12,
+            'last': 11
+        }),
+        get_min_pair_stake_amount=MagicMock(return_value=1),
+        get_fee=fee,
+    )
     create_mock_trades(fee)
     caplog.set_level(logging.DEBUG)
-
+    freqtrade.strategy.adjust_trade_position = MagicMock(return_value=10)
     freqtrade.process_open_trade_positions()
     assert log_has_re(r"Max adjustment entries for .* has been reached\.", caplog)
+
+    caplog.clear()
+    freqtrade.strategy.adjust_trade_position = MagicMock(return_value=-10)
+    freqtrade.process_open_trade_positions()
+    assert log_has_re(r"LIMIT_SELL has been fulfilled.*", caplog)
diff --git a/tests/test_integration.py b/tests/test_integration.py
index 83f54becb..40fdb4277 100644
--- a/tests/test_integration.py
+++ b/tests/test_integration.py
@@ -6,7 +6,7 @@ from freqtrade.enums import ExitCheckTuple, ExitType
 from freqtrade.persistence import Trade
 from freqtrade.persistence.models import Order
 from freqtrade.rpc.rpc import RPC
-from tests.conftest import get_patched_freqtradebot, patch_get_signal
+from tests.conftest import get_patched_freqtradebot, log_has_re, patch_get_signal
 
 
 def test_may_execute_exit_stoploss_on_exchange_multi(default_conf, ticker, fee,
@@ -455,3 +455,60 @@ def test_dca_order_adjust(default_conf_usdt, ticker_usdt, fee, mocker) -> None:
     # Check the 2 filled orders equal the above amount
     assert pytest.approx(trade.orders[1].amount) == 30.150753768
     assert pytest.approx(trade.orders[-1].amount) == 61.538461232
+
+
+def test_dca_exiting(default_conf_usdt, ticker_usdt, fee, mocker, caplog) -> None:
+    default_conf_usdt['position_adjustment_enable'] = True
+
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker_usdt,
+        get_fee=fee,
+        amount_to_precision=lambda s, x, y: y,
+        price_to_precision=lambda s, x, y: y,
+        get_min_pair_stake_amount=MagicMock(return_value=10),
+    )
+
+    patch_get_signal(freqtrade)
+    freqtrade.enter_positions()
+
+    assert len(Trade.get_trades().all()) == 1
+    trade = Trade.get_trades().first()
+    assert len(trade.orders) == 1
+    assert pytest.approx(trade.stake_amount) == 60
+    assert pytest.approx(trade.amount) == 30.0
+    assert trade.open_rate == 2.0
+
+    # Too small size
+    freqtrade.strategy.adjust_trade_position = MagicMock(return_value=-59)
+    freqtrade.process()
+    trade = Trade.get_trades().first()
+    assert len(trade.orders) == 1
+    assert pytest.approx(trade.stake_amount) == 60
+    assert pytest.approx(trade.amount) == 30.0
+    assert log_has_re("Remaining amount of 1.6.* would be too small.", caplog)
+
+    freqtrade.strategy.adjust_trade_position = MagicMock(return_value=-20)
+
+    freqtrade.process()
+    trade = Trade.get_trades().first()
+    assert len(trade.orders) == 2
+    assert trade.orders[-1].ft_order_side == 'sell'
+    assert pytest.approx(trade.stake_amount) == 40.198
+    assert pytest.approx(trade.amount) == 20.099
+    assert trade.open_rate == 2.0
+    assert trade.is_open
+    caplog.clear()
+
+    # Sell more than what we got (we got ~20 coins left)
+    # First adjusts the amount to 20 - then rejects.
+    freqtrade.strategy.adjust_trade_position = MagicMock(return_value=-50)
+    freqtrade.process()
+    assert log_has_re("Adjusting amount to trade.amount as it is higher.*", caplog)
+    assert log_has_re("Remaining amount of 0.0 would be too small.", caplog)
+    trade = Trade.get_trades().first()
+    assert len(trade.orders) == 2
+    assert trade.orders[-1].ft_order_side == 'sell'
+    assert pytest.approx(trade.stake_amount) == 40.198
+    assert trade.is_open
diff --git a/tests/test_persistence.py b/tests/test_persistence.py
index 0c1fc01a5..42fcc7413 100644
--- a/tests/test_persistence.py
+++ b/tests/test_persistence.py
@@ -500,7 +500,7 @@ def test_update_limit_order(fee, caplog, limit_buy_order_usdt, limit_sell_order_
     assert trade.close_profit is None
     assert trade.close_date is None
 
-    trade.open_order_id = 'something'
+    trade.open_order_id = enter_order['id']
     oobj = Order.parse_from_ccxt_object(enter_order, 'ADA/USDT', entry_side)
     trade.orders.append(oobj)
     trade.update_trade(oobj)
@@ -515,7 +515,7 @@ def test_update_limit_order(fee, caplog, limit_buy_order_usdt, limit_sell_order_
                       caplog)
 
     caplog.clear()
-    trade.open_order_id = 'something'
+    trade.open_order_id = enter_order['id']
     time_machine.move_to("2022-03-31 21:45:05 +00:00")
     oobj = Order.parse_from_ccxt_object(exit_order, 'ADA/USDT', exit_side)
     trade.orders.append(oobj)
@@ -550,7 +550,7 @@ def test_update_market_order(market_buy_order_usdt, market_sell_order_usdt, fee,
         leverage=1.0,
     )
 
-    trade.open_order_id = 'something'
+    trade.open_order_id = 'mocked_market_buy'
     oobj = Order.parse_from_ccxt_object(market_buy_order_usdt, 'ADA/USDT', 'buy')
     trade.orders.append(oobj)
     trade.update_trade(oobj)
@@ -565,7 +565,7 @@ def test_update_market_order(market_buy_order_usdt, market_sell_order_usdt, fee,
 
     caplog.clear()
     trade.is_open = True
-    trade.open_order_id = 'something'
+    trade.open_order_id = 'mocked_market_sell'
     oobj = Order.parse_from_ccxt_object(market_sell_order_usdt, 'ADA/USDT', 'sell')
     trade.orders.append(oobj)
     trade.update_trade(oobj)
@@ -630,14 +630,14 @@ def test_calc_open_close_trade_price(
     trade.open_rate = 2.0
     trade.close_rate = 2.2
     trade.recalc_open_trade_value()
-    assert isclose(trade._calc_open_trade_value(), open_value)
+    assert isclose(trade._calc_open_trade_value(trade.amount, trade.open_rate), open_value)
     assert isclose(trade.calc_close_trade_value(trade.close_rate), close_value)
     assert isclose(trade.calc_profit(trade.close_rate), round(profit, 8))
     assert pytest.approx(trade.calc_profit_ratio(trade.close_rate)) == profit_ratio
 
 
 @pytest.mark.usefixtures("init_persistence")
-def test_trade_close(limit_buy_order_usdt, limit_sell_order_usdt, fee):
+def test_trade_close(fee):
     trade = Trade(
         pair='ADA/USDT',
         stake_amount=60.0,
@@ -815,7 +815,7 @@ def test_calc_open_trade_value(
     trade.update_trade(oobj)  # Buy @ 2.0
 
     # Get the open rate price with the standard fee rate
-    assert trade._calc_open_trade_value() == result
+    assert trade._calc_open_trade_value(trade.amount, trade.open_rate) == result
 
 
 @pytest.mark.parametrize(
@@ -905,7 +905,7 @@ def test_calc_close_trade_price(
         ('binance', False, 1, 1.9, 0.003, -3.3209999, -0.055211970, spot, 0),
         ('binance', False, 1, 2.2, 0.003, 5.6520000, 0.093965087, spot, 0),
 
-        # # FUTURES, funding_fee=1
+        # FUTURES, funding_fee=1
         ('binance', False, 1, 2.1, 0.0025, 3.6925, 0.06138819, futures, 1),
         ('binance', False, 3, 2.1, 0.0025, 3.6925, 0.18416458, futures, 1),
         ('binance', True, 1, 2.1, 0.0025, -2.3074999, -0.03855472, futures, 1),
@@ -1191,6 +1191,11 @@ def test_calc_profit(
     assert pytest.approx(trade.calc_profit(rate=close_rate)) == round(profit, 8)
     assert pytest.approx(trade.calc_profit_ratio(rate=close_rate)) == round(profit_ratio, 8)
 
+    assert pytest.approx(trade.calc_profit(close_rate, trade.amount,
+                         trade.open_rate)) == round(profit, 8)
+    assert pytest.approx(trade.calc_profit_ratio(close_rate, trade.amount,
+                         trade.open_rate)) == round(profit_ratio, 8)
+
 
 def test_migrate_new(mocker, default_conf, fee, caplog):
     """
@@ -1382,7 +1387,7 @@ def test_migrate_new(mocker, default_conf, fee, caplog):
     assert log_has("trying trades_bak2", caplog)
     assert log_has("Running database migration for trades - backup: trades_bak2, orders_bak0",
                    caplog)
-    assert trade.open_trade_value == trade._calc_open_trade_value()
+    assert trade.open_trade_value == trade._calc_open_trade_value(trade.amount, trade.open_rate)
     assert trade.close_profit_abs is None
 
     orders = trade.orders
@@ -1744,6 +1749,7 @@ def test_to_json(fee):
                       'stake_amount': 0.001,
                       'trade_duration': None,
                       'trade_duration_s': None,
+                      'realized_profit': 0.0,
                       'close_profit': None,
                       'close_profit_pct': None,
                       'close_profit_abs': None,
@@ -1820,6 +1826,7 @@ def test_to_json(fee):
                       'initial_stop_loss_abs': None,
                       'initial_stop_loss_pct': None,
                       'initial_stop_loss_ratio': None,
+                      'realized_profit': 0.0,
                       'close_profit': None,
                       'close_profit_pct': None,
                       'close_profit_abs': None,
@@ -2262,7 +2269,7 @@ def test_update_order_from_ccxt(caplog):
         'symbol': 'ADA/USDT',
         'type': 'limit',
         'price': 1234.5,
-        'amount':  20.0,
+        'amount': 20.0,
         'filled': 9,
         'remaining': 11,
         'status': 'open',
@@ -2421,7 +2428,7 @@ def test_recalc_trade_from_orders(fee):
     )
 
     assert fee.return_value == 0.0025
-    assert trade._calc_open_trade_value() == o1_trade_val
+    assert trade._calc_open_trade_value(trade.amount, trade.open_rate) == o1_trade_val
     assert trade.amount == o1_amount
     assert trade.stake_amount == o1_cost
     assert trade.open_rate == o1_rate
@@ -2533,7 +2540,8 @@ def test_recalc_trade_from_orders(fee):
     assert pytest.approx(trade.fee_open_cost) == o1_fee_cost + o2_fee_cost + o3_fee_cost
     assert pytest.approx(trade.open_trade_value) == o1_trade_val + o2_trade_val + o3_trade_val
 
-    # Just to make sure sell orders are ignored, let's calculate one more time.
+    # Just to make sure full sell orders are ignored, let's calculate one more time.
+
     sell1 = Order(
         ft_order_side='sell',
         ft_pair=trade.pair,
@@ -2695,7 +2703,7 @@ def test_recalc_trade_from_orders_ignores_bad_orders(fee, is_short):
     assert trade.open_trade_value == 2 * o1_trade_val
     assert trade.nr_of_successful_entries == 2
 
-    # Just to make sure exit orders are ignored, let's calculate one more time.
+    # Reduce position - this will reduce amount again.
     sell1 = Order(
         ft_order_side=exit_side,
         ft_pair=trade.pair,
@@ -2706,7 +2714,7 @@ def test_recalc_trade_from_orders_ignores_bad_orders(fee, is_short):
         side=exit_side,
         price=4,
         average=3,
-        filled=2,
+        filled=o1_amount,
         remaining=1,
         cost=5,
         order_date=trade.open_date,
@@ -2715,11 +2723,11 @@ def test_recalc_trade_from_orders_ignores_bad_orders(fee, is_short):
     trade.orders.append(sell1)
     trade.recalc_trade_from_orders()
 
-    assert trade.amount == 2 * o1_amount
-    assert trade.stake_amount == 2 * o1_amount
+    assert trade.amount == o1_amount
+    assert trade.stake_amount == o1_amount
     assert trade.open_rate == o1_rate
-    assert trade.fee_open_cost == 2 * o1_fee_cost
-    assert trade.open_trade_value == 2 * o1_trade_val
+    assert trade.fee_open_cost == o1_fee_cost
+    assert trade.open_trade_value == o1_trade_val
     assert trade.nr_of_successful_entries == 2
 
     # Check with 1 order
@@ -2743,11 +2751,11 @@ def test_recalc_trade_from_orders_ignores_bad_orders(fee, is_short):
     trade.recalc_trade_from_orders()
 
     # Calling recalc with single initial order should not change anything
-    assert trade.amount == 3 * o1_amount
-    assert trade.stake_amount == 3 * o1_amount
+    assert trade.amount == 2 * o1_amount
+    assert trade.stake_amount == 2 * o1_amount
     assert trade.open_rate == o1_rate
-    assert trade.fee_open_cost == 3 * o1_fee_cost
-    assert trade.open_trade_value == 3 * o1_trade_val
+    assert trade.fee_open_cost == 2 * o1_fee_cost
+    assert trade.open_trade_value == 2 * o1_trade_val
     assert trade.nr_of_successful_entries == 3
 
 
@@ -2815,3 +2823,144 @@ def test_order_to_ccxt(limit_buy_order_open):
     del raw_order['stopPrice']
     del limit_buy_order_open['datetime']
     assert raw_order == limit_buy_order_open
+
+
+@pytest.mark.usefixtures("init_persistence")
+@pytest.mark.parametrize('data', [
+    {
+        # tuple 1 - side, amount, price
+        # tuple 2 - amount, open_rate, stake_amount, cumulative_profit, realized_profit, rel_profit
+        'orders': [
+            (('buy', 100, 10), (100.0, 10.0, 1000.0, 0.0, None, None)),
+            (('buy', 100, 15), (200.0, 12.5, 2500.0, 0.0, None, None)),
+            (('sell', 50, 12), (150.0, 12.5, 1875.0, -25.0, -25.0, -0.04)),
+            (('sell', 100, 20), (50.0, 12.5, 625.0, 725.0, 750.0, 0.60)),
+            (('sell', 50, 5), (50.0, 12.5, 625.0, 350.0, -375.0, -0.60)),
+        ],
+        'end_profit': 350.0,
+        'end_profit_ratio': 0.14,
+        'fee': 0.0,
+    },
+    {
+        'orders': [
+            (('buy', 100, 10), (100.0, 10.0, 1000.0, 0.0, None, None)),
+            (('buy', 100, 15), (200.0, 12.5, 2500.0, 0.0, None, None)),
+            (('sell', 50, 12), (150.0, 12.5, 1875.0, -28.0625, -28.0625, -0.044788)),
+            (('sell', 100, 20), (50.0, 12.5, 625.0, 713.8125, 741.875, 0.59201995)),
+            (('sell', 50, 5), (50.0, 12.5, 625.0, 336.625, -377.1875, -0.60199501)),
+        ],
+        'end_profit': 336.625,
+        'end_profit_ratio': 0.1343142,
+        'fee': 0.0025,
+    },
+    {
+        'orders': [
+            (('buy', 100, 3), (100.0, 3.0, 300.0, 0.0, None, None)),
+            (('buy', 100, 7), (200.0, 5.0, 1000.0, 0.0, None, None)),
+            (('sell', 100, 11), (100.0, 5.0, 500.0, 596.0, 596.0, 1.189027)),
+            (('buy', 150, 15), (250.0, 11.0, 2750.0, 596.0, 596.0, 1.189027)),
+            (('sell', 100, 19), (150.0, 11.0, 1650.0, 1388.5, 792.5, 0.7186579)),
+            (('sell', 150, 23), (150.0, 11.0, 1650.0, 3175.75, 1787.25, 1.08048062)),
+        ],
+        'end_profit': 3175.75,
+        'end_profit_ratio': 0.9747170,
+        'fee': 0.0025,
+    },
+    {
+        # Test above without fees
+        'orders': [
+            (('buy', 100, 3), (100.0, 3.0, 300.0, 0.0, None, None)),
+            (('buy', 100, 7), (200.0, 5.0, 1000.0, 0.0, None, None)),
+            (('sell', 100, 11), (100.0, 5.0, 500.0, 600.0, 600.0, 1.2)),
+            (('buy', 150, 15), (250.0, 11.0, 2750.0, 600.0, 600.0, 1.2)),
+            (('sell', 100, 19), (150.0, 11.0, 1650.0, 1400.0, 800.0, 0.72727273)),
+            (('sell', 150, 23), (150.0, 11.0, 1650.0, 3200.0, 1800.0, 1.09090909)),
+        ],
+        'end_profit': 3200.0,
+        'end_profit_ratio': 0.98461538,
+        'fee': 0.0,
+    },
+    {
+        'orders': [
+            (('buy', 100, 8), (100.0, 8.0, 800.0, 0.0, None, None)),
+            (('buy', 100, 9), (200.0, 8.5, 1700.0, 0.0, None, None)),
+            (('sell', 100, 10), (100.0, 8.5, 850.0, 150.0, 150.0, 0.17647059)),
+            (('buy', 150, 11), (250.0, 10, 2500.0, 150.0, 150.0, 0.17647059)),
+            (('sell', 100, 12), (150.0, 10.0, 1500.0, 350.0, 350.0, 0.2)),
+            (('sell', 150, 14), (150.0, 10.0, 1500.0, 950.0, 950.0, 0.40)),
+        ],
+        'end_profit': 950.0,
+        'end_profit_ratio': 0.283582,
+        'fee': 0.0,
+    },
+])
+def test_recalc_trade_from_orders_dca(data) -> None:
+
+    pair = 'ETH/USDT'
+    trade = Trade(
+        id=2,
+        pair=pair,
+        stake_amount=1000,
+        open_rate=data['orders'][0][0][2],
+        amount=data['orders'][0][0][1],
+        is_open=True,
+        open_date=arrow.utcnow().datetime,
+        fee_open=data['fee'],
+        fee_close=data['fee'],
+        exchange='binance',
+        is_short=False,
+        leverage=1.0,
+        trading_mode=TradingMode.SPOT
+    )
+    Trade.query.session.add(trade)
+
+    for idx, (order, result) in enumerate(data['orders']):
+        amount = order[1]
+        price = order[2]
+
+        order_obj = Order(
+            ft_order_side=order[0],
+            ft_pair=trade.pair,
+            order_id=f"order_{order[0]}_{idx}",
+            ft_is_open=False,
+            status="closed",
+            symbol=trade.pair,
+            order_type="market",
+            side=order[0],
+            price=price,
+            average=price,
+            filled=amount,
+            remaining=0,
+            cost=amount * price,
+            order_date=arrow.utcnow().shift(hours=-10 + idx).datetime,
+            order_filled_date=arrow.utcnow().shift(hours=-10 + idx).datetime,
+        )
+        trade.orders.append(order_obj)
+        trade.recalc_trade_from_orders()
+        Trade.commit()
+
+        orders1 = Order.query.all()
+        assert orders1
+        assert len(orders1) == idx + 1
+
+        trade = Trade.query.first()
+        assert trade
+        assert len(trade.orders) == idx + 1
+        if idx < len(data) - 1:
+            assert trade.is_open is True
+        assert trade.open_order_id is None
+        assert trade.amount == result[0]
+        assert trade.open_rate == result[1]
+        assert trade.stake_amount == result[2]
+        # TODO: enable the below.
+        assert pytest.approx(trade.realized_profit) == result[3]
+        # assert pytest.approx(trade.close_profit_abs) == result[4]
+        assert pytest.approx(trade.close_profit) == result[5]
+
+    trade.close(price)
+    assert pytest.approx(trade.close_profit_abs) == data['end_profit']
+    assert pytest.approx(trade.close_profit) == data['end_profit_ratio']
+    assert not trade.is_open
+    trade = Trade.query.first()
+    assert trade
+    assert trade.open_order_id is None

From cbb05354a8968c10bfcb5944db2c5fa13eb6fd5b Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sun, 31 Jul 2022 15:10:01 +0200
Subject: [PATCH 029/132] Add install variant for freqai

---
 requirements-freqai.txt |  1 -
 setup.py                | 10 +++++++++-
 2 files changed, 9 insertions(+), 2 deletions(-)

diff --git a/requirements-freqai.txt b/requirements-freqai.txt
index c3aa2e4db..060a5219d 100644
--- a/requirements-freqai.txt
+++ b/requirements-freqai.txt
@@ -3,7 +3,6 @@
 
 # Required for freqai
 scikit-learn==1.1.1
-scikit-optimize==0.9.0
 joblib==1.1.0
 catboost==1.0.4
 lightgbm==3.3.2
diff --git a/setup.py b/setup.py
index 7aa56bf81..33e35c5ab 100644
--- a/setup.py
+++ b/setup.py
@@ -12,6 +12,13 @@ hyperopt = [
     'progressbar2',
 ]
 
+freqai = [
+    'scikit-learn',
+    'joblib',
+    'catboost',
+    'lightgbm',
+]
+
 develop = [
     'coveralls',
     'flake8',
@@ -31,7 +38,7 @@ jupyter = [
     'nbconvert',
 ]
 
-all_extra = plot + develop + jupyter + hyperopt
+all_extra = plot + develop + jupyter + hyperopt + freqai
 
 setup(
     tests_require=[
@@ -79,6 +86,7 @@ setup(
         'plot': plot,
         'jupyter': jupyter,
         'hyperopt': hyperopt,
+        'freqai': freqai,
         'all': all_extra,
     },
 )

From 659870312df456036372a3afa7825220292a3229 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sun, 31 Jul 2022 15:23:27 +0200
Subject: [PATCH 030/132] Use JSON Schema validation for freaAI schema
 validation

---
 freqtrade/configuration/config_validation.py | 17 ------------
 freqtrade/constants.py                       | 29 +++++++++-----------
 2 files changed, 13 insertions(+), 33 deletions(-)

diff --git a/freqtrade/configuration/config_validation.py b/freqtrade/configuration/config_validation.py
index 5d9667196..ee846e7e6 100644
--- a/freqtrade/configuration/config_validation.py
+++ b/freqtrade/configuration/config_validation.py
@@ -85,7 +85,6 @@ def validate_config_consistency(conf: Dict[str, Any], preliminary: bool = False)
     _validate_unlimited_amount(conf)
     _validate_ask_orderbook(conf)
     validate_migrated_strategy_settings(conf)
-    _validate_freqai(conf)
 
     # validate configuration before returning
     logger.info('Validating configuration ...')
@@ -164,22 +163,6 @@ def _validate_edge(conf: Dict[str, Any]) -> None:
         )
 
 
-def _validate_freqai(conf: Dict[str, Any]) -> None:
-    """
-    Freqai param validator
-    """
-
-    if not conf.get('freqai', {}):
-        return
-
-    for param in constants.SCHEMA_FREQAI_REQUIRED:
-        if param not in conf.get('freqai', {}):
-            if param not in conf.get('freqai', {}).get('feature_parameters', {}):
-                raise OperationalException(
-                    f'{param} not found in Freqai config'
-                )
-
-
 def _validate_whitelist(conf: Dict[str, Any]) -> None:
     """
     Dynamic whitelist does not require pair_whitelist to be set - however StaticWhitelist does.
diff --git a/freqtrade/constants.py b/freqtrade/constants.py
index 0134dafc0..af2e4748a 100644
--- a/freqtrade/constants.py
+++ b/freqtrade/constants.py
@@ -241,6 +241,7 @@ CONF_SCHEMA = {
         },
         'exchange': {'$ref': '#/definitions/exchange'},
         'edge': {'$ref': '#/definitions/edge'},
+        'freqai': {'$ref': '#/definitions/freqai'},
         'experimental': {
             'type': 'object',
             'properties': {
@@ -484,20 +485,21 @@ CONF_SCHEMA = {
                 "keras": {"type": "boolean", "default": False},
                 "conv_width": {"type": "integer", "default": 2},
                 "train_period_days": {"type": "integer", "default": 0},
-                "backtest_period_days": {"type": "float", "default": 7},
-                "identifier": {"type": "str", "default": "example"},
+                "backtest_period_days": {"type": "number", "default": 7},
+                "identifier": {"type": "string", "default": "example"},
                 "feature_parameters": {
                     "type": "object",
                     "properties": {
-                        "include_corr_pairlist": {"type": "list"},
-                        "include_timeframes": {"type": "list"},
+                        "include_corr_pairlist": {"type": "array"},
+                        "include_timeframes": {"type": "array"},
                         "label_period_candles": {"type": "integer"},
                         "include_shifted_candles": {"type": "integer", "default": 0},
-                        "DI_threshold": {"type": "float", "default": 0},
+                        "DI_threshold": {"type": "number", "default": 0},
                         "weight_factor": {"type": "number", "default": 0},
                         "principal_component_analysis": {"type": "boolean", "default": False},
                         "use_SVM_to_remove_outliers": {"type": "boolean", "default": False},
                     },
+                    "required": ["include_timeframes", "include_corr_pairlist", ]
                 },
                 "data_split_parameters": {
                     "type": "object",
@@ -516,6 +518,12 @@ CONF_SCHEMA = {
                     },
                 },
             },
+            "required": ["train_period_days",
+                         "backtest_period_days",
+                         "identifier",
+                         "feature_parameters",
+                         "data_split_parameters",
+                         "model_training_parameters"]
         },
     },
 }
@@ -560,17 +568,6 @@ SCHEMA_MINIMAL_REQUIRED = [
     'dataformat_trades',
 ]
 
-SCHEMA_FREQAI_REQUIRED = [
-    'include_timeframes',
-    'train_period_days',
-    'backtest_period_days',
-    'identifier',
-    'include_corr_pairlist',
-    'feature_parameters',
-    'data_split_parameters',
-    'model_training_parameters'
-]
-
 CANCEL_REASON = {
     "TIMEOUT": "cancelled due to timeout",
     "PARTIALLY_FILLED_KEEP_OPEN": "partially filled - keeping order open",

From 153336d4241b79c8c9195ca19124fe6be56cfb29 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Sun, 31 Jul 2022 15:45:15 +0200
Subject: [PATCH 031/132] move corr_pairlist expansion to after
 expand_pairlist()

---
 freqtrade/plugins/pairlist/pairlist_helpers.py | 8 +++-----
 1 file changed, 3 insertions(+), 5 deletions(-)

diff --git a/freqtrade/plugins/pairlist/pairlist_helpers.py b/freqtrade/plugins/pairlist/pairlist_helpers.py
index ee17c1be9..a07a0f783 100644
--- a/freqtrade/plugins/pairlist/pairlist_helpers.py
+++ b/freqtrade/plugins/pairlist/pairlist_helpers.py
@@ -43,12 +43,10 @@ def expand_pairlist(wildcardpl: List[str], available_pairs: List[str],
 
 
 def dynamic_expand_pairlist(config: dict, markets: list) -> List[str]:
+    expanded_pairs = expand_pairlist(config['pairs'], markets)
     if config.get('freqai', {}):
         corr_pairlist = config['freqai']['feature_parameters']['include_corr_pairlist']
-        full_pairs = config['pairs'] + [pair for pair in corr_pairlist
-                                        if pair not in config['pairs']]
-        expanded_pairs = expand_pairlist(full_pairs, markets)
-    else:
-        expanded_pairs = expand_pairlist(config['pairs'], markets)
+        expanded_pairs += [pair for pair in corr_pairlist
+                           if pair not in config['pairs']]
 
     return expanded_pairs

From d830105605863c2c88839d7df864c35b6db7de4f Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Sun, 31 Jul 2022 17:05:29 +0200
Subject: [PATCH 032/132] *BREAKING CHANGE* remove unnecessary arguments from
 populate_any_indicators(), accommodate tests

---
 freqtrade/freqai/data_kitchen.py              | 13 +++-----
 freqtrade/strategy/interface.py               |  5 ++-
 freqtrade/templates/FreqaiExampleStrategy.py  | 31 +++++++++++++------
 .../strats/freqai_test_multimodel_strat.py    |  4 ++-
 tests/strategy/strats/freqai_test_strat.py    |  4 ++-
 5 files changed, 35 insertions(+), 22 deletions(-)

diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index 4a936475a..aedf01d11 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -892,29 +892,26 @@ class FreqaiDataKitchen:
         else:
             dataframe = base_dataframes[self.config["timeframe"]].copy()
 
-        sgi = True
+        sgi = False
         for tf in tfs:
+            if tf == tfs[-1]:
+                sgi = True  # doing this last allows user to use all tf raw prices in labels
             dataframe = strategy.populate_any_indicators(
-                pair,
                 pair,
                 dataframe.copy(),
                 tf,
                 informative=base_dataframes[tf],
-                coin=pair.split("/")[0] + "-",
-                set_generalized_indicators=sgi,
+                set_generalized_indicators=sgi
             )
-            sgi = False
             if pairs:
                 for i in pairs:
                     if pair in i:
                         continue  # dont repeat anything from whitelist
                     dataframe = strategy.populate_any_indicators(
-                        pair,
                         i,
                         dataframe.copy(),
                         tf,
-                        informative=corr_dataframes[i][tf],
-                        coin=i.split("/")[0] + "-",
+                        informative=corr_dataframes[i][tf]
                     )
 
         return dataframe
diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py
index 431e67a98..be6447811 100644
--- a/freqtrade/strategy/interface.py
+++ b/freqtrade/strategy/interface.py
@@ -557,8 +557,8 @@ class IStrategy(ABC, HyperStrategyMixin):
         """
         return None
 
-    def populate_any_indicators(self, basepair: str, pair: str, df: DataFrame, tf: str,
-                                informative: DataFrame = None, coin: str = "",
+    def populate_any_indicators(self, pair: str, df: DataFrame, tf: str,
+                                informative: DataFrame = None,
                                 set_generalized_indicators: bool = False) -> DataFrame:
         """
         Function designed to automatically generate, name and merge features
@@ -570,7 +570,6 @@ class IStrategy(ABC, HyperStrategyMixin):
         :param df: strategy dataframe which will receive merges from informatives
         :param tf: timeframe of the dataframe which will modify the feature names
         :param informative: the dataframe associated with the informative pair
-        :param coin: the name of the coin which will modify the feature names.
         """
         return df
 
diff --git a/freqtrade/templates/FreqaiExampleStrategy.py b/freqtrade/templates/FreqaiExampleStrategy.py
index 1196405ab..90343cc80 100644
--- a/freqtrade/templates/FreqaiExampleStrategy.py
+++ b/freqtrade/templates/FreqaiExampleStrategy.py
@@ -65,7 +65,7 @@ class FreqaiExampleStrategy(IStrategy):
         return informative_pairs
 
     def populate_any_indicators(
-        self, metadata, pair, df, tf, informative=None, coin="", set_generalized_indicators=False
+        self, pair, df, tf, informative=None, set_generalized_indicators=False
     ):
         """
         Function designed to automatically generate, name and merge features
@@ -78,9 +78,10 @@ class FreqaiExampleStrategy(IStrategy):
         :param df: strategy dataframe which will receive merges from informatives
         :param tf: timeframe of the dataframe which will modify the feature names
         :param informative: the dataframe associated with the informative pair
-        :param coin: the name of the coin which will modify the feature names.
         """
 
+        coin = pair.split('/')[0]
+
         with self.freqai.lock:
             if informative is None:
                 informative = self.dp.get_pair_dataframe(pair, tf)
@@ -92,11 +93,8 @@ class FreqaiExampleStrategy(IStrategy):
                 informative[f"%-{coin}rsi-period_{t}"] = ta.RSI(informative, timeperiod=t)
                 informative[f"%-{coin}mfi-period_{t}"] = ta.MFI(informative, timeperiod=t)
                 informative[f"%-{coin}adx-period_{t}"] = ta.ADX(informative, window=t)
-                informative[f"{coin}20sma-period_{t}"] = ta.SMA(informative, timeperiod=t)
-                informative[f"{coin}21ema-period_{t}"] = ta.EMA(informative, timeperiod=t)
-                informative[f"%-{coin}close_over_20sma-period_{t}"] = (
-                    informative["close"] / informative[f"{coin}20sma-period_{t}"]
-                )
+                informative[f"{coin}sma-period_{t}"] = ta.SMA(informative, timeperiod=t)
+                informative[f"{coin}ema-period_{t}"] = ta.EMA(informative, timeperiod=t)
 
                 informative[f"%-{coin}mfi-period_{t}"] = ta.MFI(informative, timeperiod=t)
 
@@ -148,8 +146,6 @@ class FreqaiExampleStrategy(IStrategy):
                 df["%-hour_of_day"] = (df["date"].dt.hour + 1) / 25
 
                 # user adds targets here by prepending them with &- (see convention below)
-                # If user wishes to use multiple targets, a multioutput prediction model
-                # needs to be used such as templates/CatboostPredictionMultiModel.py
                 df["&-s_close"] = (
                     df["close"]
                     .shift(-self.freqai_info["feature_parameters"]["label_period_candles"])
@@ -159,6 +155,23 @@ class FreqaiExampleStrategy(IStrategy):
                     - 1
                 )
 
+                # If user wishes to use multiple targets, they can add more by
+                # appending more columns with '&'. User should keep in mind that multi targets
+                # requires a multioutput prediction model such as
+                # templates/CatboostPredictionMultiModel.py,
+
+                # df["&-s_range"] = (
+                #     df["close"]
+                #     .shift(-self.freqai_info["feature_parameters"]["label_period_candles"])
+                #     .rolling(self.freqai_info["feature_parameters"]["label_period_candles"])
+                #     .max()
+                #     -
+                #     df["close"]
+                #     .shift(-self.freqai_info["feature_parameters"]["label_period_candles"])
+                #     .rolling(self.freqai_info["feature_parameters"]["label_period_candles"])
+                #     .min()
+                # )
+
         return df
 
     def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
diff --git a/tests/strategy/strats/freqai_test_multimodel_strat.py b/tests/strategy/strats/freqai_test_multimodel_strat.py
index 9652e816b..e58086757 100644
--- a/tests/strategy/strats/freqai_test_multimodel_strat.py
+++ b/tests/strategy/strats/freqai_test_multimodel_strat.py
@@ -62,7 +62,7 @@ class freqai_test_multimodel_strat(IStrategy):
         return informative_pairs
 
     def populate_any_indicators(
-        self, metadata, pair, df, tf, informative=None, coin="", set_generalized_indicators=False
+        self, pair, df, tf, informative=None, set_generalized_indicators=False
     ):
         """
         Function designed to automatically generate, name and merge features
@@ -79,6 +79,8 @@ class freqai_test_multimodel_strat(IStrategy):
         :coin: the name of the coin which will modify the feature names.
         """
 
+        coin = pair.split('/')[0]
+
         with self.freqai.lock:
             if informative is None:
                 informative = self.dp.get_pair_dataframe(pair, tf)
diff --git a/tests/strategy/strats/freqai_test_strat.py b/tests/strategy/strats/freqai_test_strat.py
index 8679d4d74..8288228d1 100644
--- a/tests/strategy/strats/freqai_test_strat.py
+++ b/tests/strategy/strats/freqai_test_strat.py
@@ -62,7 +62,7 @@ class freqai_test_strat(IStrategy):
         return informative_pairs
 
     def populate_any_indicators(
-        self, metadata, pair, df, tf, informative=None, coin="", set_generalized_indicators=False
+        self, pair, df, tf, informative=None, set_generalized_indicators=False
     ):
         """
         Function designed to automatically generate, name and merge features
@@ -79,6 +79,8 @@ class freqai_test_strat(IStrategy):
         :coin: the name of the coin which will modify the feature names.
         """
 
+        coin = pair.split('/')[0]
+
         with self.freqai.lock:
             if informative is None:
                 informative = self.dp.get_pair_dataframe(pair, tf)

From 4e68626bcbced4ac2d7e6a41b6e330802b6bf097 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Sun, 31 Jul 2022 17:51:19 +0200
Subject: [PATCH 033/132] ensure convolutional window is prepended for frequi
 consistency

---
 freqtrade/freqai/data_drawer.py | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py
index 97cf7607a..6844af0ec 100644
--- a/freqtrade/freqai/data_drawer.py
+++ b/freqtrade/freqai/data_drawer.py
@@ -238,6 +238,15 @@ class FreqaiDataDrawer:
 
         mrv_df["do_predict"] = do_preds
 
+        # for keras type models, the conv_window needs to be prepended so 
+        # viewing is correct in frequi
+        if self.freqai_info.get('keras', False):
+            n_lost_points = self.freqai_info.get('conv_width', 2)
+            zeros_df = DataFrame(np.zeros((n_lost_points, len(mrv_df.columns))),
+                                 columns=mrv_df.columns)
+            self.model_return_values[pair] = pd.concat(
+                [zeros_df, mrv_df], axis=0, ignore_index=True)
+
     def append_model_predictions(self, pair: str, predictions: DataFrame,
                                  do_preds: NDArray[np.int_],
                                  dk: FreqaiDataKitchen, len_df: int) -> None:

From 946d4c7cfcc645f3061b714d6b3579bdb68c820d Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Sun, 31 Jul 2022 18:39:46 +0200
Subject: [PATCH 034/132] fix trailing whitespace for flake8

---
 freqtrade/freqai/data_drawer.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py
index 6844af0ec..f14277bed 100644
--- a/freqtrade/freqai/data_drawer.py
+++ b/freqtrade/freqai/data_drawer.py
@@ -238,7 +238,7 @@ class FreqaiDataDrawer:
 
         mrv_df["do_predict"] = do_preds
 
-        # for keras type models, the conv_window needs to be prepended so 
+        # for keras type models, the conv_window needs to be prepended so
         # viewing is correct in frequi
         if self.freqai_info.get('keras', False):
             n_lost_points = self.freqai_info.get('conv_width', 2)

From 7a696f58f95839c917d3a95225e86c166fb21afd Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 1 Aug 2022 03:01:30 +0000
Subject: [PATCH 035/132] Bump ccxt from 1.91.29 to 1.91.52

Bumps [ccxt](https://github.com/ccxt/ccxt) from 1.91.29 to 1.91.52.
- [Release notes](https://github.com/ccxt/ccxt/releases)
- [Changelog](https://github.com/ccxt/ccxt/blob/master/exchanges.cfg)
- [Commits](https://github.com/ccxt/ccxt/compare/1.91.29...1.91.52)

---
updated-dependencies:
- dependency-name: ccxt
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 requirements.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements.txt b/requirements.txt
index b9e87749d..9aec6af63 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -2,7 +2,7 @@ numpy==1.23.1
 pandas==1.4.3
 pandas-ta==0.3.14b
 
-ccxt==1.91.29
+ccxt==1.91.52
 # Pin cryptography for now due to rust build errors with piwheels
 cryptography==37.0.4
 aiohttp==3.8.1

From a75fa26caf915d3235b9e0e7bda794a43441a8b6 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 1 Aug 2022 03:01:38 +0000
Subject: [PATCH 036/132] Bump scipy from 1.8.1 to 1.9.0

Bumps [scipy](https://github.com/scipy/scipy) from 1.8.1 to 1.9.0.
- [Release notes](https://github.com/scipy/scipy/releases)
- [Commits](https://github.com/scipy/scipy/compare/v1.8.1...v1.9.0)

---
updated-dependencies:
- dependency-name: scipy
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 requirements-hyperopt.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements-hyperopt.txt b/requirements-hyperopt.txt
index 94e59ec15..cc659fc50 100644
--- a/requirements-hyperopt.txt
+++ b/requirements-hyperopt.txt
@@ -2,7 +2,7 @@
 -r requirements.txt
 
 # Required for hyperopt
-scipy==1.8.1
+scipy==1.9.0
 scikit-learn==1.1.1
 scikit-optimize==0.9.0
 filelock==3.7.1

From b4ded59c63f6c2fa92e6e1722f0bb6cf758589e2 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 1 Aug 2022 03:01:43 +0000
Subject: [PATCH 037/132] Bump flake8 from 4.0.1 to 5.0.1

Bumps [flake8](https://github.com/pycqa/flake8) from 4.0.1 to 5.0.1.
- [Release notes](https://github.com/pycqa/flake8/releases)
- [Commits](https://github.com/pycqa/flake8/compare/4.0.1...5.0.1)

---
updated-dependencies:
- dependency-name: flake8
  dependency-type: direct:development
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 requirements-dev.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements-dev.txt b/requirements-dev.txt
index 3b98e20db..ee7899eeb 100644
--- a/requirements-dev.txt
+++ b/requirements-dev.txt
@@ -5,7 +5,7 @@
 -r docs/requirements-docs.txt
 
 coveralls==3.3.1
-flake8==4.0.1
+flake8==5.0.1
 flake8-tidy-imports==4.8.0
 mypy==0.971
 pre-commit==2.20.0

From 372be542528457a22ce16f5d408551abe170377e Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 1 Aug 2022 03:01:46 +0000
Subject: [PATCH 038/132] Bump types-requests from 2.28.3 to 2.28.6

Bumps [types-requests](https://github.com/python/typeshed) from 2.28.3 to 2.28.6.
- [Release notes](https://github.com/python/typeshed/releases)
- [Commits](https://github.com/python/typeshed/commits)

---
updated-dependencies:
- dependency-name: types-requests
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 requirements-dev.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements-dev.txt b/requirements-dev.txt
index 3b98e20db..d34e551d2 100644
--- a/requirements-dev.txt
+++ b/requirements-dev.txt
@@ -24,6 +24,6 @@ nbconvert==6.5.0
 # mypy types
 types-cachetools==5.2.1
 types-filelock==3.2.7
-types-requests==2.28.3
+types-requests==2.28.6
 types-tabulate==0.8.11
 types-python-dateutil==2.8.19

From ed230dd750e48ecc2148f91ea72bb39cf95dac09 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 1 Aug 2022 03:01:52 +0000
Subject: [PATCH 039/132] Bump orjson from 3.7.8 to 3.7.11

Bumps [orjson](https://github.com/ijl/orjson) from 3.7.8 to 3.7.11.
- [Release notes](https://github.com/ijl/orjson/releases)
- [Changelog](https://github.com/ijl/orjson/blob/master/CHANGELOG.md)
- [Commits](https://github.com/ijl/orjson/compare/3.7.8...3.7.11)

---
updated-dependencies:
- dependency-name: orjson
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 requirements.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements.txt b/requirements.txt
index b9e87749d..7aee44d85 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -28,7 +28,7 @@ py_find_1st==1.1.5
 # Load ticker files 30% faster
 python-rapidjson==1.8
 # Properly format api responses
-orjson==3.7.8
+orjson==3.7.11
 
 # Notify systemd
 sdnotify==0.3.2

From 79b650258ee719b5438b37036ef255379aa0fafe Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 1 Aug 2022 03:02:02 +0000
Subject: [PATCH 040/132] Bump urllib3 from 1.26.10 to 1.26.11

Bumps [urllib3](https://github.com/urllib3/urllib3) from 1.26.10 to 1.26.11.
- [Release notes](https://github.com/urllib3/urllib3/releases)
- [Changelog](https://github.com/urllib3/urllib3/blob/1.26.11/CHANGES.rst)
- [Commits](https://github.com/urllib3/urllib3/compare/1.26.10...1.26.11)

---
updated-dependencies:
- dependency-name: urllib3
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 requirements.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements.txt b/requirements.txt
index b9e87749d..36989119c 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -11,7 +11,7 @@ python-telegram-bot==13.13
 arrow==1.2.2
 cachetools==4.2.2
 requests==2.28.1
-urllib3==1.26.10
+urllib3==1.26.11
 jsonschema==4.7.2
 TA-Lib==0.4.24
 technical==1.3.0

From 97064a9ce3bbc25350966a47d1e549f985b076ab Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 1 Aug 2022 03:13:38 +0000
Subject: [PATCH 041/132] Bump pypa/gh-action-pypi-publish from 1.5.0 to 1.5.1

Bumps [pypa/gh-action-pypi-publish](https://github.com/pypa/gh-action-pypi-publish) from 1.5.0 to 1.5.1.
- [Release notes](https://github.com/pypa/gh-action-pypi-publish/releases)
- [Commits](https://github.com/pypa/gh-action-pypi-publish/compare/v1.5.0...v1.5.1)

---
updated-dependencies:
- dependency-name: pypa/gh-action-pypi-publish
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 .github/workflows/ci.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 7b077be04..bb5bc209e 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -351,7 +351,7 @@ jobs:
         python setup.py sdist bdist_wheel
 
     - name: Publish to PyPI (Test)
-      uses: pypa/gh-action-pypi-publish@v1.5.0
+      uses: pypa/gh-action-pypi-publish@v1.5.1
       if: (github.event_name == 'release')
       with:
         user: __token__
@@ -359,7 +359,7 @@ jobs:
         repository_url: https://test.pypi.org/legacy/
 
     - name: Publish to PyPI
-      uses: pypa/gh-action-pypi-publish@v1.5.0
+      uses: pypa/gh-action-pypi-publish@v1.5.1
       if: (github.event_name == 'release')
       with:
         user: __token__

From 3013282dbf83ee06985478cfcf8866b633c5af53 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Mon, 1 Aug 2022 05:39:38 +0200
Subject: [PATCH 042/132] remove non-catboost stuff from schema

---
 freqtrade/constants.py                       | 11 +++++++----
 freqtrade/templates/FreqaiExampleStrategy.py |  4 ++--
 2 files changed, 9 insertions(+), 6 deletions(-)

diff --git a/freqtrade/constants.py b/freqtrade/constants.py
index af2e4748a..d1a009ece 100644
--- a/freqtrade/constants.py
+++ b/freqtrade/constants.py
@@ -498,6 +498,12 @@ CONF_SCHEMA = {
                         "weight_factor": {"type": "number", "default": 0},
                         "principal_component_analysis": {"type": "boolean", "default": False},
                         "use_SVM_to_remove_outliers": {"type": "boolean", "default": False},
+                        "svm_params": {"type": "object",
+                                       "properties": {
+                                           "shuffle": {"type": "boolean", "default": False},
+                                           "nu": {"type": "number", "default": 0.1}
+                                           },
+                                       }
                     },
                     "required": ["include_timeframes", "include_corr_pairlist", ]
                 },
@@ -511,10 +517,7 @@ CONF_SCHEMA = {
                 "model_training_parameters": {
                     "type": "object",
                     "properties": {
-                        "n_estimators": {"type": "integer", "default": 2000},
-                        "random_state": {"type": "integer", "default": 1},
-                        "learning_rate": {"type": "number", "default": 0.02},
-                        "task_type": {"type": "string", "default": "CPU"},
+                        "n_estimators": {"type": "integer", "default": 1000}
                     },
                 },
             },
diff --git a/freqtrade/templates/FreqaiExampleStrategy.py b/freqtrade/templates/FreqaiExampleStrategy.py
index 90343cc80..4f632f907 100644
--- a/freqtrade/templates/FreqaiExampleStrategy.py
+++ b/freqtrade/templates/FreqaiExampleStrategy.py
@@ -93,8 +93,8 @@ class FreqaiExampleStrategy(IStrategy):
                 informative[f"%-{coin}rsi-period_{t}"] = ta.RSI(informative, timeperiod=t)
                 informative[f"%-{coin}mfi-period_{t}"] = ta.MFI(informative, timeperiod=t)
                 informative[f"%-{coin}adx-period_{t}"] = ta.ADX(informative, window=t)
-                informative[f"{coin}sma-period_{t}"] = ta.SMA(informative, timeperiod=t)
-                informative[f"{coin}ema-period_{t}"] = ta.EMA(informative, timeperiod=t)
+                informative[f"%-{coin}sma-period_{t}"] = ta.SMA(informative, timeperiod=t)
+                informative[f"%-{coin}ema-period_{t}"] = ta.EMA(informative, timeperiod=t)
 
                 informative[f"%-{coin}mfi-period_{t}"] = ta.MFI(informative, timeperiod=t)
 

From f3154a4313cb03ea09f3517272b554ccb9b6664a Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 1 Aug 2022 04:35:30 +0000
Subject: [PATCH 043/132] Bump jsonschema from 4.7.2 to 4.9.0

Bumps [jsonschema](https://github.com/python-jsonschema/jsonschema) from 4.7.2 to 4.9.0.
- [Release notes](https://github.com/python-jsonschema/jsonschema/releases)
- [Changelog](https://github.com/python-jsonschema/jsonschema/blob/main/CHANGELOG.rst)
- [Commits](https://github.com/python-jsonschema/jsonschema/compare/v4.7.2...v4.9.0)

---
updated-dependencies:
- dependency-name: jsonschema
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 requirements.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements.txt b/requirements.txt
index 69f6d1d24..f6ba2a444 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -12,7 +12,7 @@ arrow==1.2.2
 cachetools==4.2.2
 requests==2.28.1
 urllib3==1.26.11
-jsonschema==4.7.2
+jsonschema==4.9.0
 TA-Lib==0.4.24
 technical==1.3.0
 tabulate==0.8.10

From 707a4e7c9eee26ec29749465dda9aa12de69c9bd Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Mon, 1 Aug 2022 06:41:08 +0200
Subject: [PATCH 044/132] types-requests bump pre-commit

---
 .pre-commit-config.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 759ac0a6a..398d09875 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -15,7 +15,7 @@ repos:
         additional_dependencies:
           - types-cachetools==5.2.1
           - types-filelock==3.2.7
-          - types-requests==2.28.3
+          - types-requests==2.28.6
           - types-tabulate==0.8.11
           - types-python-dateutil==2.8.19
         # stages: [push]

From d75e0a982091bbe99e5f7795ca83fb56c210617d Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Mon, 1 Aug 2022 06:43:59 +0200
Subject: [PATCH 045/132] Fix Flake8 errors after flake update

---
 freqtrade/optimize/backtesting.py      | 2 +-
 freqtrade/optimize/optimize_reports.py | 2 +-
 freqtrade/persistence/trade_model.py   | 8 ++++----
 tests/edge/test_edge.py                | 2 +-
 tests/exchange/test_exchange.py        | 4 ++--
 5 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py
index 46774e8a5..029946cfb 100644
--- a/freqtrade/optimize/backtesting.py
+++ b/freqtrade/optimize/backtesting.py
@@ -595,7 +595,7 @@ class Backtesting:
             if exit_.exit_type in (ExitType.EXIT_SIGNAL, ExitType.CUSTOM_EXIT):
                 # Checks and adds an exit tag, after checking that the length of the
                 # row has the length for an exit tag column
-                if(
+                if (
                     len(row) > EXIT_TAG_IDX
                     and row[EXIT_TAG_IDX] is not None
                     and len(row[EXIT_TAG_IDX]) > 0
diff --git a/freqtrade/optimize/optimize_reports.py b/freqtrade/optimize/optimize_reports.py
index 44ac4a5b3..519022db2 100644
--- a/freqtrade/optimize/optimize_reports.py
+++ b/freqtrade/optimize/optimize_reports.py
@@ -639,7 +639,7 @@ def text_table_tags(tag_type: str, tag_results: List[Dict[str, Any]], stake_curr
     :param stake_currency: stake-currency - used to correctly name headers
     :return: pretty printed table with tabulate as string
     """
-    if(tag_type == "enter_tag"):
+    if (tag_type == "enter_tag"):
         headers = _get_line_header("TAG", stake_currency)
     else:
         headers = _get_line_header("TAG", stake_currency, 'Sells')
diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py
index fcb84a59a..19d9361b6 100644
--- a/freqtrade/persistence/trade_model.py
+++ b/freqtrade/persistence/trade_model.py
@@ -1300,7 +1300,7 @@ class Trade(_DECL_BASE, LocalTrade):
         """
 
         filters = [Trade.is_open.is_(False)]
-        if(pair is not None):
+        if (pair is not None):
             filters.append(Trade.pair == pair)
 
         enter_tag_perf = Trade.query.with_entities(
@@ -1333,7 +1333,7 @@ class Trade(_DECL_BASE, LocalTrade):
         """
 
         filters = [Trade.is_open.is_(False)]
-        if(pair is not None):
+        if (pair is not None):
             filters.append(Trade.pair == pair)
 
         sell_tag_perf = Trade.query.with_entities(
@@ -1366,7 +1366,7 @@ class Trade(_DECL_BASE, LocalTrade):
         """
 
         filters = [Trade.is_open.is_(False)]
-        if(pair is not None):
+        if (pair is not None):
             filters.append(Trade.pair == pair)
 
         mix_tag_perf = Trade.query.with_entities(
@@ -1386,7 +1386,7 @@ class Trade(_DECL_BASE, LocalTrade):
             enter_tag = enter_tag if enter_tag is not None else "Other"
             exit_reason = exit_reason if exit_reason is not None else "Other"
 
-            if(exit_reason is not None and enter_tag is not None):
+            if (exit_reason is not None and enter_tag is not None):
                 mix_tag = enter_tag + " " + exit_reason
                 i = 0
                 if not any(item["mix_tag"] == mix_tag for item in return_list):
diff --git a/tests/edge/test_edge.py b/tests/edge/test_edge.py
index b30d6f998..1b0191fda 100644
--- a/tests/edge/test_edge.py
+++ b/tests/edge/test_edge.py
@@ -136,7 +136,7 @@ def test_adjust(mocker, edge_conf):
     ))
 
     pairs = ['A/B', 'C/D', 'E/F', 'G/H']
-    assert(edge.adjust(pairs) == ['E/F', 'C/D'])
+    assert (edge.adjust(pairs) == ['E/F', 'C/D'])
 
 
 def test_stoploss(mocker, edge_conf):
diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py
index d73e26683..bbe424430 100644
--- a/tests/exchange/test_exchange.py
+++ b/tests/exchange/test_exchange.py
@@ -3810,8 +3810,8 @@ def test__get_funding_fees_from_exchange(default_conf, mocker, exchange_name):
         since=unix_time
     )
 
-    assert(isclose(expected_fees, fees_from_datetime))
-    assert(isclose(expected_fees, fees_from_unix_time))
+    assert (isclose(expected_fees, fees_from_datetime))
+    assert (isclose(expected_fees, fees_from_unix_time))
 
     ccxt_exceptionhandlers(
         mocker,

From 895ebbfd1836b3d9964b70422ba221aa084df2f3 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Mon, 1 Aug 2022 07:32:25 +0000
Subject: [PATCH 046/132] Exclude aarch64 from catboost requirements

---
 docs/freqai.md          | 3 +++
 requirements-freqai.txt | 2 +-
 setup.py                | 2 +-
 3 files changed, 5 insertions(+), 2 deletions(-)

diff --git a/docs/freqai.md b/docs/freqai.md
index de321b787..adf64dd07 100644
--- a/docs/freqai.md
+++ b/docs/freqai.md
@@ -56,6 +56,9 @@ Use `pip` to install the prerequisites with:
 pip install -r requirements-freqai.txt
 ```
 
+!!! Note
+    Catboost will not be installed on arm devices (raspberry, Mac M1, ARM based VPS, ...), since Catboost does not provide wheels for this platform.
+
 ## Running from the example files
 
 An example strategy, an example prediction model, and example config can all be found in
diff --git a/requirements-freqai.txt b/requirements-freqai.txt
index 060a5219d..e4f4a7c17 100644
--- a/requirements-freqai.txt
+++ b/requirements-freqai.txt
@@ -4,5 +4,5 @@
 # Required for freqai
 scikit-learn==1.1.1
 joblib==1.1.0
-catboost==1.0.4
+catboost==1.0.4; platform_machine != 'aarch64'
 lightgbm==3.3.2
diff --git a/setup.py b/setup.py
index 33e35c5ab..dfadbdefa 100644
--- a/setup.py
+++ b/setup.py
@@ -15,7 +15,7 @@ hyperopt = [
 freqai = [
     'scikit-learn',
     'joblib',
-    'catboost',
+    'catboost; platform_machine != "aarch64"',
     'lightgbm',
 ]
 

From ae0d6f63fa458cc2435dcfd8704a2258b7a82358 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Mon, 1 Aug 2022 19:43:13 +0200
Subject: [PATCH 047/132] Version bump ccxt to 1.91.55

closes #7151
---
 requirements.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements.txt b/requirements.txt
index f6ba2a444..4cb6519b3 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -2,7 +2,7 @@ numpy==1.23.1
 pandas==1.4.3
 pandas-ta==0.3.14b
 
-ccxt==1.91.52
+ccxt==1.91.55
 # Pin cryptography for now due to rust build errors with piwheels
 cryptography==37.0.4
 aiohttp==3.8.1

From 95d3009a9531c99802cfa5ce3c9c46ff8010d633 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Tue, 2 Aug 2022 20:14:02 +0200
Subject: [PATCH 048/132] give user ability to analyze live trade dataframe
 inside custom prediction model. Add documentation to explain new
 functionality

---
 docs/freqai.md                       | 40 ++++++++++++++++
 freqtrade/freqai/data_drawer.py      | 22 +++++++--
 freqtrade/freqai/data_kitchen.py     | 30 ++++++++++--
 freqtrade/freqai/freqai_interface.py | 68 ++++++++++++++++++++++++++--
 4 files changed, 147 insertions(+), 13 deletions(-)

diff --git a/docs/freqai.md b/docs/freqai.md
index adf64dd07..0a07f45ef 100644
--- a/docs/freqai.md
+++ b/docs/freqai.md
@@ -619,6 +619,46 @@ If the user sets this value, FreqAI will initially use the predictions from the
 and then subsequently begin introducing real prediction data as it is generated. FreqAI will save 
 this historical data to be reloaded if the user stops and restarts with the same `identifier`.
 
+## Extra returns per train
+
+Users may find that there are some important metrics that they'd like to return to the strategy at the end of each retrain.
+Users can include these metrics by assigining them to `dk.data['extra_returns_per_train']['my_new_value'] = XYZ` inside their custom prediction
+model class. FreqAI takes the `my_new_value` assigned in this dictionary and expands it to fit the return dataframe to the strategy.
+The user can then use the value in the strategy with `dataframe['my_new_value']`. An example of how this is already used in FreqAI is 
+the `&*_mean` and `&*_std` values, which indicate the mean and standard deviation of that particular label during the most recent training. 
+Another example is shown below if the user wants to use live metrics from the trade databse.
+
+The user needs to set the standard dictionary in the config so FreqAI can return proper dataframe shapes:
+
+```json
+    "freqai": {
+        "extra_returns_per_train": {"total_profit": 4}
+    }
+```
+
+These values will likely be overridden by the user prediction model, but in the case where the user model has yet to set them, or needs
+a default initial value - this is the value that will be returned.
+
+## Analyzing the trade live database
+
+Users can analyze the live trade database by calling `analyze_trade_database()` in their custom prediction model. FreqAI already has the
+database setup in a pandas dataframe and ready to be analyzed. Here is an example usecase:
+
+```python
+    def analyze_trade_database(self, dk: FreqaiDataKitchen, pair: str) -> None:
+        """
+        User analyzes the trade database here and returns summary stats which will be passed back
+        to the strategy for reinforcement learning or for additional adaptive metrics for use
+        in entry/exit signals. Store these metrics in dk.data['extra_returns_per_train'] and
+        they will format themselves into the dataframe as an additional column in the user
+        strategy. User has access to the current trade database in dk.trade_database_df.
+        """
+        total_profit = dk.trade_database_df['close_profit_abs'].sum()
+        dk.data['extra_returns_per_train']['total_profit'] = total_profit
+
+        return
+```
+
 <!-- ## Dynamic target expectation
 
 The labels used for model training have a unique statistical distribution for each separate model training. 
diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py
index f14277bed..42338966d 100644
--- a/freqtrade/freqai/data_drawer.py
+++ b/freqtrade/freqai/data_drawer.py
@@ -39,7 +39,7 @@ class FreqaiDataDrawer:
     Robert Caulk @robcaulk
 
     Theoretical brainstorming:
-    Elin Törnquist @thorntwig
+    Elin Törnquist @th0rntwig
 
     Code review, software architecture brainstorming:
     @xmatthias
@@ -238,6 +238,11 @@ class FreqaiDataDrawer:
 
         mrv_df["do_predict"] = do_preds
 
+        if dk.data['extra_returns_per_train']:
+            rets = dk.data['extra_returns_per_train']
+            for return_str in rets:
+                mrv_df[return_str] = rets[return_str]
+
         # for keras type models, the conv_window needs to be prepended so
         # viewing is correct in frequi
         if self.freqai_info.get('keras', False):
@@ -282,9 +287,15 @@ class FreqaiDataDrawer:
         if self.freqai_info["feature_parameters"].get("DI_threshold", 0) > 0:
             df["DI_values"].iloc[-1] = dk.DI_values[-1]
 
+        if dk.data['extra_returns_per_train']:
+            rets = dk.data['extra_returns_per_train']
+            for return_str in rets:
+                df[return_str].iloc[-1] = rets[return_str]
+
         # append the new predictions to persistent storage
         if pair in self.historic_predictions:
-            self.historic_predictions[pair].iloc[-1] = df[label].iloc[-1]
+            for key in df.keys():
+                self.historic_predictions[pair][key].iloc[-1] = df[key].iloc[-1]
 
         if length_difference < 0:
             prepend_df = pd.DataFrame(
@@ -320,7 +331,12 @@ class FreqaiDataDrawer:
         dataframe["do_predict"] = 0
 
         if self.freqai_info["feature_parameters"].get("DI_threshold", 0) > 0:
-            dataframe["DI_value"] = 0
+            dataframe["DI_values"] = 0
+
+        if dk.data['extra_returns_per_train']:
+            rets = dk.data['extra_returns_per_train']
+            for return_str in rets:
+                dataframe[return_str] = 0
 
         dk.return_dataframe = dataframe
 
diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index aedf01d11..8f4a24401 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -2,6 +2,7 @@ import copy
 import datetime
 import logging
 import shutil
+import sqlite3
 from pathlib import Path
 from typing import Any, Dict, List, Tuple
 
@@ -39,7 +40,7 @@ class FreqaiDataKitchen:
     Robert Caulk @robcaulk
 
     Theoretical brainstorming:
-    Elin Törnquist @thorntwig
+    Elin Törnquist @th0rntwig
 
     Code review, software architecture brainstorming:
     @xmatthias
@@ -84,6 +85,12 @@ class FreqaiDataKitchen:
                 config["freqai"]["backtest_period_days"],
             )
 
+        db_url = self.config.get('db_url', None)
+        self.database_path = '' if db_url == 'sqlite://' else str(db_url).split('///')[1]
+        self.trade_database_df: DataFrame = pd.DataFrame()
+
+        self.data['extra_returns_per_train'] = self.freqai_config.get('extra_returns_per_train', {})
+
     def set_paths(
         self,
         pair: str,
@@ -101,7 +108,7 @@ class FreqaiDataKitchen:
 
         self.data_path = Path(
             self.full_path
-            / str("sub-train" + "-" + pair.split("/")[0] + "_" + str(trained_timestamp))
+            / f"sub-train-{pair.split('/')[0]}_{trained_timestamp}"
         )
 
         return
@@ -328,7 +335,7 @@ class FreqaiDataKitchen:
         """
 
         for label in self.label_list:
-            if df[label].dtype == str:
+            if df[label].dtype == object:
                 continue
             df[label] = (
                 (df[label] + 1)
@@ -493,7 +500,6 @@ class FreqaiDataKitchen:
         tc = self.freqai_config.get("model_training_parameters", {}).get("thread_count", -1)
         pairwise = pairwise_distances(self.data_dictionary["train_features"], n_jobs=tc)
         avg_mean_dist = pairwise.mean(axis=1).mean()
-        logger.info(f"avg_mean_dist {avg_mean_dist:.2f}")
 
         return avg_mean_dist
 
@@ -599,10 +605,11 @@ class FreqaiDataKitchen:
         from the training data set.
         """
 
+        tc = self.freqai_config.get("model_training_parameters", {}).get("thread_count", -1)
         distance = pairwise_distances(
             self.data_dictionary["train_features"],
             self.data_dictionary["prediction_features"],
-            n_jobs=-1,
+            n_jobs=tc,
         )
 
         self.DI_values = distance.min(axis=0) / self.data["avg_mean_dist"]
@@ -946,6 +953,19 @@ class FreqaiDataKitchen:
         ]
         return dataframe[to_keep]
 
+    def get_current_trade_database(self) -> None:
+
+        if self.database_path == '':
+            logger.warning('No trade databse found. Skipping analysis.')
+            return
+
+        data = sqlite3.connect(self.database_path)
+        query = data.execute("SELECT * From trades")
+        cols = [column[0] for column in query.description]
+        df = pd.DataFrame.from_records(data=query.fetchall(), columns=cols)
+        self.trade_database_df = df.dropna(subset='close_date')
+        data.close()
+
     def np_encoder(self, object):
         if isinstance(object, np.generic):
             return object.item()
diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py
index 3b97637a8..6af1021c5 100644
--- a/freqtrade/freqai/freqai_interface.py
+++ b/freqtrade/freqai/freqai_interface.py
@@ -1,5 +1,4 @@
 # import contextlib
-import copy
 import datetime
 import logging
 import shutil
@@ -46,7 +45,7 @@ class IFreqaiModel(ABC):
     Robert Caulk @robcaulk
 
     Theoretical brainstorming:
-    Elin Törnquist @thorntwig
+    Elin Törnquist @th0rntwig
 
     Code review, software architecture brainstorming:
     @xmatthias
@@ -81,6 +80,8 @@ class IFreqaiModel(ABC):
         self.CONV_WIDTH = self.freqai_info.get("conv_width", 2)
         self.pair_it = 0
         self.total_pairs = len(self.config.get("exchange", {}).get("pair_whitelist"))
+        self.last_trade_database_summary: DataFrame = {}
+        self.current_trade_database_summary: DataFrame = {}
 
     def assert_config(self, config: Dict[str, Any]) -> None:
 
@@ -479,6 +480,9 @@ class IFreqaiModel(ABC):
 
         model = self.train(unfiltered_dataframe, pair, dk)
 
+        dk.get_current_trade_database()
+        self.analyze_trade_database(dk, pair)
+
         self.dd.pair_dict[pair]["trained_timestamp"] = new_trained_timerange.stopts
         dk.set_new_model_names(pair, new_trained_timerange)
         self.dd.pair_dict[pair]["first"] = False
@@ -493,13 +497,50 @@ class IFreqaiModel(ABC):
     def set_initial_historic_predictions(
         self, df: DataFrame, model: Any, dk: FreqaiDataKitchen, pair: str
     ) -> None:
-        trained_predictions = model.predict(df)
+        """
+        This function is called only if the datadrawer failed to load an
+        existing set of historic predictions. In this case, it builds
+        the structure and sets fake predictions off the first training
+        data. After that, FreqAI will append new real predictions to the
+        set of historic predictions.
+
+        These values are used to generate live statistics which can be used
+        in the strategy for adaptive values. E.g. &*_mean/std are quantities
+        that can computed based on live predictions from the set of historical
+        predictions. Those values can be used in the user strategy to better
+        assess prediction rarity, and thus wait for probabilistically favorable
+        entries relative to the live historical predictions.
+
+        If the user reuses an identifier on a subsequent instance,
+        this function will not be called. In that case, "real" predictions
+        will be appended to the loaded set of historic predictions.
+        :param: df: DataFrame = the dataframe containing the training feature data
+        :param: model: Any = A model which was `fit` using a common librariy such as
+        catboost or lightgbm
+        :param: dk: FreqaiDataKitchen = object containing methods for data analysis
+        :param: pair: str = current pair
+        """
+        num_candles = self.freqai_info.get('fit_live_predictions_candles', 600)
+        df_tail = df.tail(num_candles)
+        trained_predictions = model.predict(df_tail)
         pred_df = DataFrame(trained_predictions, columns=dk.label_list)
 
         pred_df = dk.denormalize_labels_from_metadata(pred_df)
 
-        self.dd.historic_predictions[pair] = pd.DataFrame()
-        self.dd.historic_predictions[pair] = copy.deepcopy(pred_df)
+        self.dd.historic_predictions[pair] = pred_df
+        hist_preds_df = self.dd.historic_predictions[pair]
+
+        hist_preds_df['do_predict'] = 0
+
+        if self.freqai_info['feature_parameters'].get('DI_threshold', 0) > 0:
+            hist_preds_df['DI_values'] = 0
+
+        for label in dk.data['labels_mean']:
+            hist_preds_df[f'{label}_mean'] = 0
+            hist_preds_df[f'{label}_std'] = 0
+
+        for return_str in dk.data['extra_returns_per_train']:
+            hist_preds_df[return_str] = 0
 
     def fit_live_predictions(self, dk: FreqaiDataKitchen) -> None:
         """
@@ -565,3 +606,20 @@ class IFreqaiModel(ABC):
         """
 
         return
+
+    def analyze_trade_database(self, dk: FreqaiDataKitchen, pair: str) -> None:
+        """
+        User analyzes the trade database here and returns summary stats which will be passed back
+        to the strategy for reinforcement learning or for additional adaptive metrics for use
+        in entry/exit signals. Store these metrics in dk.data['extra_returns_per_train'] and
+        they will format themselves into the dataframe as an additional column in the user
+        strategy. User has access to the current trade database in dk.trade_database_df.
+        """
+        if dk.trade_database_df.empty:
+            logger.warning(f'No trades found for {pair} to analyze DB')
+            return
+
+        total_profit = dk.trade_database_df['close_profit_abs'].sum()
+        dk.data['extra_returns_per_train']['total_profit'] = total_profit
+
+        return

From eae82d0222a9a8cce4bb6ef4ea5dabe2f3490618 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Wed, 3 Aug 2022 16:17:57 +0200
Subject: [PATCH 049/132] fix bug with database url during backtesting. comment
 out example trade db analysis.

---
 freqtrade/freqai/data_kitchen.py     |  7 ++++---
 freqtrade/freqai/freqai_interface.py | 10 +++++-----
 2 files changed, 9 insertions(+), 8 deletions(-)

diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index 8f4a24401..f3beeb1ba 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -85,9 +85,10 @@ class FreqaiDataKitchen:
                 config["freqai"]["backtest_period_days"],
             )
 
-        db_url = self.config.get('db_url', None)
-        self.database_path = '' if db_url == 'sqlite://' else str(db_url).split('///')[1]
-        self.trade_database_df: DataFrame = pd.DataFrame()
+        if self.live:
+            db_url = self.config.get('db_url', 'sqlite://')
+            self.database_path = '' if db_url == 'sqlite://' else str(db_url).split('///')[1]
+            self.trade_database_df: DataFrame = pd.DataFrame()
 
         self.data['extra_returns_per_train'] = self.freqai_config.get('extra_returns_per_train', {})
 
diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py
index 6af1021c5..7c9f87664 100644
--- a/freqtrade/freqai/freqai_interface.py
+++ b/freqtrade/freqai/freqai_interface.py
@@ -615,11 +615,11 @@ class IFreqaiModel(ABC):
         they will format themselves into the dataframe as an additional column in the user
         strategy. User has access to the current trade database in dk.trade_database_df.
         """
-        if dk.trade_database_df.empty:
-            logger.warning(f'No trades found for {pair} to analyze DB')
-            return
+        # if dk.trade_database_df.empty:
+        #     logger.warning(f'No trades found for {pair} to analyze DB')
+        #     return
 
-        total_profit = dk.trade_database_df['close_profit_abs'].sum()
-        dk.data['extra_returns_per_train']['total_profit'] = total_profit
+        # total_profit = dk.trade_database_df['close_profit_abs'].sum()
+        # dk.data['extra_returns_per_train']['total_profit'] = total_profit
 
         return

From 95327750dca68592d552e9cbe59347435d2f7fac Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Thu, 4 Aug 2022 07:07:54 +0200
Subject: [PATCH 050/132] Final abs. profit should not be doubled in rpc
 messages

---
 freqtrade/freqtradebot.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py
index 757449c8c..657e0bd82 100644
--- a/freqtrade/freqtradebot.py
+++ b/freqtrade/freqtradebot.py
@@ -1566,7 +1566,7 @@ class FreqtradeBot(LoggingMixin):
             profit_ratio = trade.calc_profit_ratio(profit_rate, amount, trade.open_rate)
         else:
             profit_rate = trade.close_rate if trade.close_rate else trade.close_rate_requested
-            profit = trade.calc_profit(rate=profit_rate) + trade.realized_profit
+            profit = trade.calc_profit(rate=profit_rate) + (0.0 if fill else trade.realized_profit)
             profit_ratio = trade.calc_profit_ratio(profit_rate)
             amount = trade.amount
         gain = "profit" if profit_ratio > 0 else "loss"

From 778833f90e0bc8ec04a030b6c93982d15e49c8f2 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Thu, 4 Aug 2022 07:17:26 +0200
Subject: [PATCH 051/132] Modify comment in new test-strategies to point out
 their purpose

---
 .../strats/freqai_test_multimodel_strat.py    | 28 ++-----------------
 tests/strategy/strats/freqai_test_strat.py    | 28 ++-----------------
 2 files changed, 4 insertions(+), 52 deletions(-)

diff --git a/tests/strategy/strats/freqai_test_multimodel_strat.py b/tests/strategy/strats/freqai_test_multimodel_strat.py
index e58086757..4f8877f14 100644
--- a/tests/strategy/strats/freqai_test_multimodel_strat.py
+++ b/tests/strategy/strats/freqai_test_multimodel_strat.py
@@ -13,13 +13,8 @@ logger = logging.getLogger(__name__)
 
 class freqai_test_multimodel_strat(IStrategy):
     """
-    Example strategy showing how the user connects their own
-    IFreqaiModel to the strategy. Namely, the user uses:
-    self.freqai.start(dataframe, metadata)
-
-    to make predictions on their data. populate_any_indicators() automatically
-    generates the variety of features indicated by the user in the
-    canonical freqtrade configuration file under config['freqai'].
+    Test strategy - used for testing freqAI multimodel functionalities.
+    DO not use in production.
     """
 
     minimal_roi = {"0": 0.1, "240": -1}
@@ -64,20 +59,6 @@ class freqai_test_multimodel_strat(IStrategy):
     def populate_any_indicators(
         self, pair, df, tf, informative=None, set_generalized_indicators=False
     ):
-        """
-        Function designed to automatically generate, name and merge features
-        from user indicated timeframes in the configuration file. User controls the indicators
-        passed to the training/prediction by prepending indicators with `'%-' + coin `
-        (see convention below). I.e. user should not prepend any supporting metrics
-        (e.g. bb_lowerband below) with % unless they explicitly want to pass that metric to the
-        model.
-        :params:
-        :pair: pair to be used as informative
-        :df: strategy dataframe which will receive merges from informatives
-        :tf: timeframe of the dataframe which will modify the feature names
-        :informative: the dataframe associated with the informative pair
-        :coin: the name of the coin which will modify the feature names.
-        """
 
         coin = pair.split('/')[0]
 
@@ -149,11 +130,6 @@ class freqai_test_multimodel_strat(IStrategy):
 
         self.freqai_info = self.config["freqai"]
 
-        # All indicators must be populated by populate_any_indicators() for live functionality
-        # to work correctly.
-        # the model will return 4 values, its prediction, an indication of whether or not the
-        # prediction should be accepted, the target mean/std values from the labels used during
-        # each training period.
         dataframe = self.freqai.start(dataframe, metadata, self)
 
         dataframe["target_roi"] = dataframe["&-s_close_mean"] + dataframe["&-s_close_std"] * 1.25
diff --git a/tests/strategy/strats/freqai_test_strat.py b/tests/strategy/strats/freqai_test_strat.py
index 8288228d1..e239a30b0 100644
--- a/tests/strategy/strats/freqai_test_strat.py
+++ b/tests/strategy/strats/freqai_test_strat.py
@@ -13,13 +13,8 @@ logger = logging.getLogger(__name__)
 
 class freqai_test_strat(IStrategy):
     """
-    Example strategy showing how the user connects their own
-    IFreqaiModel to the strategy. Namely, the user uses:
-    self.freqai.start(dataframe, metadata)
-
-    to make predictions on their data. populate_any_indicators() automatically
-    generates the variety of features indicated by the user in the
-    canonical freqtrade configuration file under config['freqai'].
+    Test strategy - used for testing freqAI functionalities.
+    DO not use in production.
     """
 
     minimal_roi = {"0": 0.1, "240": -1}
@@ -64,20 +59,6 @@ class freqai_test_strat(IStrategy):
     def populate_any_indicators(
         self, pair, df, tf, informative=None, set_generalized_indicators=False
     ):
-        """
-        Function designed to automatically generate, name and merge features
-        from user indicated timeframes in the configuration file. User controls the indicators
-        passed to the training/prediction by prepending indicators with `'%-' + coin `
-        (see convention below). I.e. user should not prepend any supporting metrics
-        (e.g. bb_lowerband below) with % unless they explicitly want to pass that metric to the
-        model.
-        :params:
-        :pair: pair to be used as informative
-        :df: strategy dataframe which will receive merges from informatives
-        :tf: timeframe of the dataframe which will modify the feature names
-        :informative: the dataframe associated with the informative pair
-        :coin: the name of the coin which will modify the feature names.
-        """
 
         coin = pair.split('/')[0]
 
@@ -137,11 +118,6 @@ class freqai_test_strat(IStrategy):
 
         self.freqai_info = self.config["freqai"]
 
-        # All indicators must be populated by populate_any_indicators() for live functionality
-        # to work correctly.
-        # the model will return 4 values, its prediction, an indication of whether or not the
-        # prediction should be accepted, the target mean/std values from the labels used during
-        # each training period.
         dataframe = self.freqai.start(dataframe, metadata, self)
 
         dataframe["target_roi"] = dataframe["&-s_close_mean"] + dataframe["&-s_close_std"] * 1.25

From 29225e4bafed091403f88e4728ceed1ec473b974 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Thu, 4 Aug 2022 12:14:56 +0200
Subject: [PATCH 052/132] add DBSCAN outlier detection feature, add supporting
 documentation

---
 docs/freqai.md                       | 16 +++++-
 freqtrade/freqai/data_kitchen.py     | 81 +++++++++++++++++++++++++---
 freqtrade/freqai/freqai_interface.py |  6 +++
 3 files changed, 94 insertions(+), 9 deletions(-)

diff --git a/docs/freqai.md b/docs/freqai.md
index 0a07f45ef..8537beac2 100644
--- a/docs/freqai.md
+++ b/docs/freqai.md
@@ -105,6 +105,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `stratify_training_data` | This value is used to indicate the stratification of the data. e.g. 2 would set every 2nd data point into a separate dataset to be pulled from during training/testing. <br> **Datatype:** positive integer.
 | `indicator_max_period_candles` | The maximum *period* used in `populate_any_indicators()` for indicator creation. FreqAI uses this information in combination with the maximum timeframe to calculate how many data points it should download so that the first data point does not have a NaN <br> **Datatype:** positive integer.
 | `indicator_periods_candles` | A list of integers used to duplicate all indicators according to a set of periods and add them to the feature set. <br> **Datatype:** list of positive integers.
+| `DBSCAN_outlier_pct` | Inactive by default. If user sets this to a fractional value, DBSCAN is used to cluster the training data and remove user set percentage of training data as outliers. <br> **Datatype:** float (fraction of 1).
 |  |  **Data split parameters**
 | `data_split_parameters` | Include any additional parameters available from Scikit-learn `test_train_split()`, which are shown [here](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html) <br> **Datatype:** dictionary.
 | `test_size` | Fraction of data that should be used for testing instead of training. <br> **Datatype:** positive float below 1.
@@ -519,7 +520,7 @@ variance of the data set is >= 0.999.
 
 ### Removing outliers using a Support Vector Machine (SVM)
 
-The user can tell Freqai to remove outlier data points from the training/test data sets by setting:
+The user can tell FreqAI to remove outlier data points from the training/test data sets by setting:
 
 ```json
     "freqai": {
@@ -529,9 +530,20 @@ The user can tell Freqai to remove outlier data points from the training/test da
     }
 ```
 
-Freqai will train an SVM on the training data (or components if the user activated
+FreqAI will train an SVM on the training data (or components if the user activated
 `principal_component_analysis`) and remove any data point that it deems to be sitting beyond the feature space.
 
+### Clustering the training data and removing outliers with DBSCAN
+
+The user can tell FreqAI to use DBSCAN to cluster training data and remove outliers from the training data set. The user set
+parameter `DBSCAN_outlier_pct` allows the user to indicate the percent of expected outliers to be removed during each training
+(typically set below 0.05). Higher value increases confidence in the model predictions but reduces the entry frequency.
+
+The FreqAI DBSCAN wrapper performs an interative solution to solving the `eps` hyper parameter. `eps` controls the fraction of 
+training data considered to be an outlier - thus the iterative solution finds the exact value associated with the user designated
+`DBSCAN_outlier_pct`. This iterative solution is performed once per training. FreqAI stores the `eps` to be used when DBSCAN
+is again called to determine if incoming prediction candles are outliers. 
+
 ### Stratifying the data
 
 The user can stratify the training/testing data using:
diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index f3beeb1ba..0cec0b9e1 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -19,7 +19,7 @@ from freqtrade.data.history.history_utils import refresh_backtest_ohlcv_data
 from freqtrade.exceptions import OperationalException
 from freqtrade.resolvers import ExchangeResolver
 from freqtrade.strategy.interface import IStrategy
-
+from sklearn.cluster import DBSCAN
 
 SECONDS_IN_DAY = 86400
 SECONDS_IN_HOUR = 3600
@@ -91,6 +91,7 @@ class FreqaiDataKitchen:
             self.trade_database_df: DataFrame = pd.DataFrame()
 
         self.data['extra_returns_per_train'] = self.freqai_config.get('extra_returns_per_train', {})
+        self.thread_count = self.freqai_config.get("data_kitchen_thread_count", -1)
 
     def set_paths(
         self,
@@ -498,8 +499,7 @@ class FreqaiDataKitchen:
         for prediction confidence in the Dissimilarity Index
         """
         logger.info("computing average mean distance for all training points")
-        tc = self.freqai_config.get("model_training_parameters", {}).get("thread_count", -1)
-        pairwise = pairwise_distances(self.data_dictionary["train_features"], n_jobs=tc)
+        pairwise = pairwise_distances(self.data_dictionary["train_features"], n_jobs=self.thread_count)
         avg_mean_dist = pairwise.mean(axis=1).mean()
 
         return avg_mean_dist
@@ -580,6 +580,76 @@ class FreqaiDataKitchen:
 
         return
 
+    def use_DBSCAN_to_remove_outliers(self, predict: bool) -> None:
+        """
+        Use DBSCAN to cluster training data and remove "noisy" data (read outliers).
+        User controls this via the config param `DBSCAN_outlier_pct` which indicates the
+        pct of training data that they want to be considered outliers.
+        :params:
+        predict: bool = If False (training), iterate to find the best hyper parameters to match
+        user requested outlier percent target. If True (prediction), use the parameters
+        determined from the previous training to estimate if the current prediction point
+        is an outlier.
+        """
+
+        if predict:
+            train_ft_df = self.data_dictionary['train_features']
+            pred_ft_df = self.data_dictionary['prediction_features']
+            num_preds = len(pred_ft_df)
+            df = pd.concat([train_ft_df, pred_ft_df], axis=0, ignore_index=True)
+            clustering = DBSCAN(
+                                    eps=self.data['DBSCAN_eps'],
+                                    min_samples=self.data['DBSCAN_min_samples'],
+                                    n_jobs=-1
+                                ).fit(df)
+            do_predict = np.where(clustering.labels_[-num_preds:] == -1, 0, 1)
+
+            if (len(do_predict) - do_predict.sum()) > 0:
+                logger.info(
+                    f"DBSCAN tossed {len(do_predict) - do_predict.sum()} predictions"
+                )
+            self.do_predict += do_predict
+            self.do_predict -= 1
+
+        else:
+            outlier_target = self.freqai_config['feature_parameters'].get('DBSCAN_outlier_pct')
+            eps = 1.8
+            error = 1.
+            MinPts = len(train_ft_df.columns) * 2
+            logger.info(
+                    f'DBSCAN finding best clustering for {outlier_target}% outliers.')
+
+            # find optimal value for epsilon using an iterative approach:
+            while abs(error) > 0.01:
+                clustering = DBSCAN(eps=eps, min_samples=MinPts, n_jobs=-1).fit(
+                    train_ft_df
+                )
+                outlier_pct = np.count_nonzero(clustering.labels_ == -1) / len(clustering.labels_)
+                error = (outlier_pct - outlier_target) / outlier_target
+                multiplier = 1 + error * (1.01 - 1.)
+                eps = multiplier * eps
+
+            self.data['DBSCAN_eps'] = eps
+            self.data['DBSCAN_min_samples'] = MinPts
+            dropped_points = np.where(clustering.labels_ == -1, 1, 0)
+
+            self.data_dictionary['train_features'] = self.data_dictionary['train_features'][
+                (clustering.labels_ != -1)
+            ]
+            self.data_dictionary["train_labels"] = self.data_dictionary["train_labels"][
+                (clustering.labels_ != -1)
+            ]
+            self.data_dictionary["train_weights"] = self.data_dictionary["train_weights"][
+                (clustering.labels_ != -1)
+            ]
+
+            logger.info(
+                f"DBSCAN tossed {dropped_points.sum()}"
+                f" train points from {len(clustering.labels_)}"
+            )
+
+        return
+
     def find_features(self, dataframe: DataFrame) -> None:
         """
         Find features in the strategy provided dataframe
@@ -596,7 +666,6 @@ class FreqaiDataKitchen:
 
         self.training_features_list = features
         self.label_list = labels
-        # return features, labels
 
     def check_if_pred_in_training_spaces(self) -> None:
         """
@@ -606,11 +675,10 @@ class FreqaiDataKitchen:
         from the training data set.
         """
 
-        tc = self.freqai_config.get("model_training_parameters", {}).get("thread_count", -1)
         distance = pairwise_distances(
             self.data_dictionary["train_features"],
             self.data_dictionary["prediction_features"],
-            n_jobs=tc,
+            n_jobs=self.thread_count,
         )
 
         self.DI_values = distance.min(axis=0) / self.data["avg_mean_dist"]
@@ -677,7 +745,6 @@ class FreqaiDataKitchen:
         to_keep = [col for col in dataframe.columns if not col.startswith("&")]
         self.return_dataframe = pd.concat([dataframe[to_keep], self.full_df], axis=1)
 
-        # self.append_df = DataFrame()
         self.full_df = DataFrame()
 
         return
diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py
index 7c9f87664..078a574b7 100644
--- a/freqtrade/freqai/freqai_interface.py
+++ b/freqtrade/freqai/freqai_interface.py
@@ -384,6 +384,9 @@ class IFreqaiModel(ABC):
         if self.freqai_info["feature_parameters"].get("DI_threshold", 0):
             dk.data["avg_mean_dist"] = dk.compute_distances()
 
+        if self.freqai_info["feature_parameters"].get("DBSCAN_outlier_pct", 0):
+            dk.use_DBSCAN_to_remove_outliers(predict=False)
+
     def data_cleaning_predict(self, dk: FreqaiDataKitchen, dataframe: DataFrame) -> None:
         """
         Base data cleaning method for predict.
@@ -406,6 +409,9 @@ class IFreqaiModel(ABC):
         if self.freqai_info["feature_parameters"].get("DI_threshold", 0):
             dk.check_if_pred_in_training_spaces()
 
+        if self.freqai_info["feature_parameters"].get("DBSCAN_outlier_pct", 0):
+            dk.use_DBSCAN_to_remove_outliers(predict=True)
+
     def model_exists(
         self,
         pair: str,

From febd809119f1d3cfe30444fbe7978c0ea51e990e Mon Sep 17 00:00:00 2001
From: Stefano Ariestasia <stefano.ariestasia@gmail.com>
Date: Thu, 4 Aug 2022 20:55:52 +0900
Subject: [PATCH 053/132] Fix typo

adjust_trade_position should return stake_amount, not amount
---
 docs/strategy-callbacks.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/strategy-callbacks.md b/docs/strategy-callbacks.md
index 18de3513b..a9b032818 100644
--- a/docs/strategy-callbacks.md
+++ b/docs/strategy-callbacks.md
@@ -721,7 +721,7 @@ class DigDeeperStrategy(IStrategy):
 
         if current_profit > 0.05 and trade.nr_of_successful_exits == 0:
             # Take half of the profit at +5%
-            return -(trade.amount / 2)
+            return -(trade.stake_amount / 2)
 
         if current_profit > -0.05:
             return None

From fe1b8515a85d2559a343f10a179e2ca2242e23e7 Mon Sep 17 00:00:00 2001
From: Robert Caulk <rob.caulk@gmail.com>
Date: Thu, 4 Aug 2022 17:00:59 +0200
Subject: [PATCH 054/132] fix bug in DBSCAN, update doc

---
 docs/freqai.md                   | 10 +++++++++-
 freqtrade/freqai/data_kitchen.py | 34 ++++++++++++++++++++++----------
 2 files changed, 33 insertions(+), 11 deletions(-)

diff --git a/docs/freqai.md b/docs/freqai.md
index 8537beac2..e38132cb1 100644
--- a/docs/freqai.md
+++ b/docs/freqai.md
@@ -539,11 +539,19 @@ The user can tell FreqAI to use DBSCAN to cluster training data and remove outli
 parameter `DBSCAN_outlier_pct` allows the user to indicate the percent of expected outliers to be removed during each training
 (typically set below 0.05). Higher value increases confidence in the model predictions but reduces the entry frequency.
 
-The FreqAI DBSCAN wrapper performs an interative solution to solving the `eps` hyper parameter. `eps` controls the fraction of 
+The FreqAI DBSCAN wrapper performs an iterative solution to solving the `eps` hyper parameter. `eps` controls the fraction of 
 training data considered to be an outlier - thus the iterative solution finds the exact value associated with the user designated
 `DBSCAN_outlier_pct`. This iterative solution is performed once per training. FreqAI stores the `eps` to be used when DBSCAN
 is again called to determine if incoming prediction candles are outliers. 
 
+```json
+    "freqai": {
+        "feature_parameters" : {
+            "DBSCAN_outlier_pct": 0.05
+        }
+    }
+```
+
 ### Stratifying the data
 
 The user can stratify the training/testing data using:
diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index 0cec0b9e1..823cf2a55 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -11,6 +11,7 @@ import numpy.typing as npt
 import pandas as pd
 from pandas import DataFrame
 from sklearn import linear_model
+from sklearn.cluster import DBSCAN
 from sklearn.metrics.pairwise import pairwise_distances
 from sklearn.model_selection import train_test_split
 
@@ -19,7 +20,7 @@ from freqtrade.data.history.history_utils import refresh_backtest_ohlcv_data
 from freqtrade.exceptions import OperationalException
 from freqtrade.resolvers import ExchangeResolver
 from freqtrade.strategy.interface import IStrategy
-from sklearn.cluster import DBSCAN
+
 
 SECONDS_IN_DAY = 86400
 SECONDS_IN_HOUR = 3600
@@ -499,7 +500,8 @@ class FreqaiDataKitchen:
         for prediction confidence in the Dissimilarity Index
         """
         logger.info("computing average mean distance for all training points")
-        pairwise = pairwise_distances(self.data_dictionary["train_features"], n_jobs=self.thread_count)
+        pairwise = pairwise_distances(
+            self.data_dictionary["train_features"], n_jobs=self.thread_count)
         avg_mean_dist = pairwise.mean(axis=1).mean()
 
         return avg_mean_dist
@@ -613,21 +615,33 @@ class FreqaiDataKitchen:
 
         else:
             outlier_target = self.freqai_config['feature_parameters'].get('DBSCAN_outlier_pct')
-            eps = 1.8
+            if 'DBSCAN_eps' in self.data:
+                eps = self.data['DBSCAN_eps']
+            else:
+                eps = 10
+                logger.info('DBSCAN starting from high value. This should be faster next train.')
+
             error = 1.
-            MinPts = len(train_ft_df.columns) * 2
+            MinPts = len(self.data_dictionary['train_features'].columns)
             logger.info(
                     f'DBSCAN finding best clustering for {outlier_target}% outliers.')
 
             # find optimal value for epsilon using an iterative approach:
-            while abs(error) > 0.01:
-                clustering = DBSCAN(eps=eps, min_samples=MinPts, n_jobs=-1).fit(
-                    train_ft_df
-                )
+            while abs(np.sqrt(error)) > 0.1:
+                clustering = DBSCAN(eps=eps, min_samples=MinPts,
+                                    n_jobs=int(self.thread_count / 2)).fit(
+                                        self.data_dictionary['train_features']
+                                    )
                 outlier_pct = np.count_nonzero(clustering.labels_ == -1) / len(clustering.labels_)
-                error = (outlier_pct - outlier_target) / outlier_target
-                multiplier = 1 + error * (1.01 - 1.)
+                error = (outlier_pct - outlier_target) ** 2 / outlier_target
+                multiplier = (outlier_pct - outlier_target) if outlier_pct > 0 else 1 * \
+                    np.sign(outlier_pct - outlier_target)
+                multiplier = 1 + error * multiplier
                 eps = multiplier * eps
+                logger.info(
+                    f'DBSCAN error {error:.2f} for eps {eps:.2f} and outliet pct {outlier_pct:.2f}')
+
+            logger.info(f'DBSCAN found eps of {eps}.')
 
             self.data['DBSCAN_eps'] = eps
             self.data['DBSCAN_min_samples'] = MinPts

From 51a6b4289ff303ab6a6963baf4d8ca4660299031 Mon Sep 17 00:00:00 2001
From: Robert Caulk <rob.caulk@gmail.com>
Date: Thu, 4 Aug 2022 17:41:58 +0200
Subject: [PATCH 055/132] improve DBSCAN performance for subsequent trainings

---
 freqtrade/freqai/data_drawer.py      |  1 +
 freqtrade/freqai/data_kitchen.py     | 19 ++++++++++---------
 freqtrade/freqai/freqai_interface.py |  7 ++++++-
 3 files changed, 17 insertions(+), 10 deletions(-)

diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py
index 42338966d..9a17797ff 100644
--- a/freqtrade/freqai/data_drawer.py
+++ b/freqtrade/freqai/data_drawer.py
@@ -76,6 +76,7 @@ class FreqaiDataDrawer:
         self.load_historic_predictions_from_disk()
         self.training_queue: Dict[str, int] = {}
         self.history_lock = threading.Lock()
+        self.old_DBSCAN_eps: Dict[str, float] = {}
 
     def load_drawer_from_disk(self):
         """
diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index 823cf2a55..1dfae3ef1 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -582,7 +582,7 @@ class FreqaiDataKitchen:
 
         return
 
-    def use_DBSCAN_to_remove_outliers(self, predict: bool) -> None:
+    def use_DBSCAN_to_remove_outliers(self, predict: bool, eps=None) -> None:
         """
         Use DBSCAN to cluster training data and remove "noisy" data (read outliers).
         User controls this via the config param `DBSCAN_outlier_pct` which indicates the
@@ -615,10 +615,10 @@ class FreqaiDataKitchen:
 
         else:
             outlier_target = self.freqai_config['feature_parameters'].get('DBSCAN_outlier_pct')
-            if 'DBSCAN_eps' in self.data:
-                eps = self.data['DBSCAN_eps']
+            if eps:
+                epsilon = eps
             else:
-                eps = 10
+                epsilon = 10
                 logger.info('DBSCAN starting from high value. This should be faster next train.')
 
             error = 1.
@@ -628,7 +628,7 @@ class FreqaiDataKitchen:
 
             # find optimal value for epsilon using an iterative approach:
             while abs(np.sqrt(error)) > 0.1:
-                clustering = DBSCAN(eps=eps, min_samples=MinPts,
+                clustering = DBSCAN(eps=epsilon, min_samples=MinPts,
                                     n_jobs=int(self.thread_count / 2)).fit(
                                         self.data_dictionary['train_features']
                                     )
@@ -637,13 +637,14 @@ class FreqaiDataKitchen:
                 multiplier = (outlier_pct - outlier_target) if outlier_pct > 0 else 1 * \
                     np.sign(outlier_pct - outlier_target)
                 multiplier = 1 + error * multiplier
-                eps = multiplier * eps
+                epsilon = multiplier * epsilon
                 logger.info(
-                    f'DBSCAN error {error:.2f} for eps {eps:.2f} and outliet pct {outlier_pct:.2f}')
+                    f'DBSCAN error {error:.2f} for eps {epsilon:.2f}'
+                    f' and outlier pct {outlier_pct:.2f}')
 
-            logger.info(f'DBSCAN found eps of {eps}.')
+            logger.info(f'DBSCAN found eps of {epsilon}.')
 
-            self.data['DBSCAN_eps'] = eps
+            self.data['DBSCAN_eps'] = epsilon
             self.data['DBSCAN_min_samples'] = MinPts
             dropped_points = np.where(clustering.labels_ == -1, 1, 0)
 
diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py
index 078a574b7..3978fc7b2 100644
--- a/freqtrade/freqai/freqai_interface.py
+++ b/freqtrade/freqai/freqai_interface.py
@@ -385,7 +385,12 @@ class IFreqaiModel(ABC):
             dk.data["avg_mean_dist"] = dk.compute_distances()
 
         if self.freqai_info["feature_parameters"].get("DBSCAN_outlier_pct", 0):
-            dk.use_DBSCAN_to_remove_outliers(predict=False)
+            if dk.pair in self.dd.old_DBSCAN_eps:
+                eps = self.dd.old_DBSCAN_eps[dk.pair]
+            else:
+                eps = None
+            dk.use_DBSCAN_to_remove_outliers(predict=False, eps=eps)
+            self.dd.old_DBSCAN_eps[dk.pair] = dk.data['DBSCAN_eps']
 
     def data_cleaning_predict(self, dk: FreqaiDataKitchen, dataframe: DataFrame) -> None:
         """

From df4a5a75731742dddaa76a76db167f8ccb14eda0 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Fri, 5 Aug 2022 03:02:12 +0000
Subject: [PATCH 056/132] Bump python from 3.10.5-slim-bullseye to
 3.10.6-slim-bullseye

Bumps python from 3.10.5-slim-bullseye to 3.10.6-slim-bullseye.

---
updated-dependencies:
- dependency-name: python
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 Dockerfile | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Dockerfile b/Dockerfile
index 5138ecec9..14a67edc8 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -1,4 +1,4 @@
-FROM python:3.10.5-slim-bullseye as base
+FROM python:3.10.6-slim-bullseye as base
 
 # Setup env
 ENV LANG C.UTF-8

From debc73b65465a5b9ee9407d854dc30cf9a666fa7 Mon Sep 17 00:00:00 2001
From: OGSK <53548542+Jetsukda@users.noreply.github.com>
Date: Fri, 5 Aug 2022 00:28:28 +0700
Subject: [PATCH 057/132] Edit Typo Custom-stake-amount

Edit Custom-stake-amount to `custom_stake_amount`
---
 docs/strategy_migration.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/strategy_migration.md b/docs/strategy_migration.md
index 471ffa601..042c2494f 100644
--- a/docs/strategy_migration.md
+++ b/docs/strategy_migration.md
@@ -192,7 +192,7 @@ class AwesomeStrategy(IStrategy):
         return False 
 ```
 
-### Custom-stake-amount
+### `custom_stake_amount`
 
 New string argument `side` - which can be either `"long"` or `"short"`.
 

From a8541d86fbf0406208e1122f0d346474b6327fb0 Mon Sep 17 00:00:00 2001
From: OGSK <53548542+Jetsukda@users.noreply.github.com>
Date: Fri, 5 Aug 2022 09:36:26 +0700
Subject: [PATCH 058/132] Edit index of `custom_stake_amount`

---
 docs/strategy_migration.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/strategy_migration.md b/docs/strategy_migration.md
index 042c2494f..064e7a59d 100644
--- a/docs/strategy_migration.md
+++ b/docs/strategy_migration.md
@@ -18,7 +18,7 @@ Note : `forcesell`, `forcebuy`, `emergencysell` are changed to `force_exit`, `fo
   * [`check_buy_timeout()` -> `check_entry_timeout()`](#custom_entry_timeout)
   * [`check_sell_timeout()` -> `check_exit_timeout()`](#custom_entry_timeout)
   * New `side` argument to callbacks without trade object
-    * [`custom_stake_amount`](#custom-stake-amount)
+    * [`custom_stake_amount`](#custom_stake_amount)
     * [`confirm_trade_entry`](#confirm_trade_entry)
     * [`custom_entry_price`](#custom_entry_price)
   * [Changed argument name in `confirm_trade_exit`](#confirm_trade_exit)

From c6e121ffb4cde7fa15326d006fc2d0a062146f4d Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Fri, 5 Aug 2022 07:17:58 +0200
Subject: [PATCH 059/132] Update tests with correct usdt mock trades

---
 tests/conftest_trades_usdt.py   |  4 ++--
 tests/rpc/test_rpc.py           | 32 +++++++++++++-------------
 tests/rpc/test_rpc_apiserver.py | 32 +++++++++++++-------------
 tests/rpc/test_rpc_telegram.py  | 40 ++++++++++++++++-----------------
 4 files changed, 54 insertions(+), 54 deletions(-)

diff --git a/tests/conftest_trades_usdt.py b/tests/conftest_trades_usdt.py
index 41d705c01..9a89eaca6 100644
--- a/tests/conftest_trades_usdt.py
+++ b/tests/conftest_trades_usdt.py
@@ -63,7 +63,7 @@ def mock_trade_usdt_1(fee, is_short: bool):
         open_rate=10.0,
         close_rate=8.0,
         close_profit=-0.2,
-        close_profit_abs=-4.0,
+        close_profit_abs=-4.09,
         exchange='binance',
         strategy='SampleStrategy',
         open_order_id=f'prod_exit_1_{direc(is_short)}',
@@ -183,7 +183,7 @@ def mock_trade_usdt_3(fee, is_short: bool):
         open_rate=1.0,
         close_rate=1.1,
         close_profit=0.1,
-        close_profit_abs=9.8425,
+        close_profit_abs=2.8425,
         exchange='binance',
         is_open=False,
         strategy='StrategyTestV2',
diff --git a/tests/rpc/test_rpc.py b/tests/rpc/test_rpc.py
index 02c62e337..4c580c3c2 100644
--- a/tests/rpc/test_rpc.py
+++ b/tests/rpc/test_rpc.py
@@ -314,10 +314,10 @@ def test__rpc_timeunit_profit(default_conf_usdt, ticker, fee,
         # {'date': datetime.date(2022, 6, 11), 'abs_profit': 13.8299999,
         #  'starting_balance': 1055.37, 'rel_profit': 0.0131044,
         #  'fiat_value': 0.0, 'trade_count': 2}
-        assert day['abs_profit'] in (0.0, pytest.approx(13.8299999), pytest.approx(-4.0))
-        assert day['rel_profit'] in (0.0, pytest.approx(0.01310441), pytest.approx(-0.00377583))
+        assert day['abs_profit'] in (0.0, pytest.approx(6.83), pytest.approx(-4.09))
+        assert day['rel_profit'] in (0.0, pytest.approx(0.00642902), pytest.approx(-0.00383512))
         assert day['trade_count'] in (0, 1, 2)
-        assert day['starting_balance'] in (pytest.approx(1059.37), pytest.approx(1055.37))
+        assert day['starting_balance'] in (pytest.approx(1062.37), pytest.approx(1066.46))
         assert day['fiat_value'] in (0.0, )
     # ensure first day is current date
     assert str(days['data'][0]['date']) == str(datetime.utcnow().date())
@@ -435,9 +435,9 @@ def test_rpc_trade_statistics(default_conf_usdt, ticker, fee, mocker) -> None:
     create_mock_trades_usdt(fee)
 
     stats = rpc._rpc_trade_statistics(stake_currency, fiat_display_currency)
-    assert pytest.approx(stats['profit_closed_coin']) == 9.83
+    assert pytest.approx(stats['profit_closed_coin']) == 2.74
     assert pytest.approx(stats['profit_closed_percent_mean']) == -1.67
-    assert pytest.approx(stats['profit_closed_fiat']) == 10.813
+    assert pytest.approx(stats['profit_closed_fiat']) == 3.014
     assert pytest.approx(stats['profit_all_coin']) == -77.45964918
     assert pytest.approx(stats['profit_all_percent_mean']) == -57.86
     assert pytest.approx(stats['profit_all_fiat']) == -85.205614098
@@ -870,9 +870,9 @@ def test_performance_handle(default_conf_usdt, ticker, fee, mocker) -> None:
 
     res = rpc._rpc_performance()
     assert len(res) == 3
-    assert res[0]['pair'] == 'XRP/USDT'
+    assert res[0]['pair'] == 'ETC/USDT'
     assert res[0]['count'] == 1
-    assert res[0]['profit_pct'] == 10.0
+    assert res[0]['profit_pct'] == 5.0
 
 
 def test_enter_tag_performance_handle(default_conf, ticker, fee, mocker) -> None:
@@ -896,16 +896,16 @@ def test_enter_tag_performance_handle(default_conf, ticker, fee, mocker) -> None
     res = rpc._rpc_enter_tag_performance(None)
 
     assert len(res) == 3
-    assert res[0]['enter_tag'] == 'TEST3'
+    assert res[0]['enter_tag'] == 'TEST1'
     assert res[0]['count'] == 1
-    assert res[0]['profit_pct'] == 10.0
+    assert res[0]['profit_pct'] == 5.0
 
     res = rpc._rpc_enter_tag_performance(None)
 
     assert len(res) == 3
-    assert res[0]['enter_tag'] == 'TEST3'
+    assert res[0]['enter_tag'] == 'TEST1'
     assert res[0]['count'] == 1
-    assert res[0]['profit_pct'] == 10.0
+    assert res[0]['profit_pct'] == 5.0
 
 
 def test_enter_tag_performance_handle_2(mocker, default_conf, markets, fee):
@@ -956,11 +956,11 @@ def test_exit_reason_performance_handle(default_conf_usdt, ticker, fee, mocker)
     res = rpc._rpc_exit_reason_performance(None)
 
     assert len(res) == 3
-    assert res[0]['exit_reason'] == 'roi'
+    assert res[0]['exit_reason'] == 'exit_signal'
     assert res[0]['count'] == 1
-    assert res[0]['profit_pct'] == 10.0
+    assert res[0]['profit_pct'] == 5.0
 
-    assert res[1]['exit_reason'] == 'exit_signal'
+    assert res[1]['exit_reason'] == 'roi'
     assert res[2]['exit_reason'] == 'Other'
 
 
@@ -1012,9 +1012,9 @@ def test_mix_tag_performance_handle(default_conf, ticker, fee, mocker) -> None:
     res = rpc._rpc_mix_tag_performance(None)
 
     assert len(res) == 3
-    assert res[0]['mix_tag'] == 'TEST3 roi'
+    assert res[0]['mix_tag'] == 'TEST1 exit_signal'
     assert res[0]['count'] == 1
-    assert res[0]['profit_pct'] == 10.0
+    assert res[0]['profit_pct'] == 5.0
 
 
 def test_mix_tag_performance_handle_2(mocker, default_conf, markets, fee):
diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py
index 57ba8e9f1..c6507d0ae 100644
--- a/tests/rpc/test_rpc_apiserver.py
+++ b/tests/rpc/test_rpc_apiserver.py
@@ -790,22 +790,22 @@ def test_api_profit(botclient, mocker, ticker, fee, markets, is_short, expected)
         'first_trade_timestamp': ANY,
         'latest_trade_date': '5 minutes ago',
         'latest_trade_timestamp': ANY,
-        'profit_all_coin': expected['profit_all_coin'],
-        'profit_all_fiat': expected['profit_all_fiat'],
-        'profit_all_percent_mean': expected['profit_all_percent_mean'],
-        'profit_all_ratio_mean': expected['profit_all_ratio_mean'],
-        'profit_all_percent_sum': expected['profit_all_percent_sum'],
-        'profit_all_ratio_sum': expected['profit_all_ratio_sum'],
-        'profit_all_percent': expected['profit_all_percent'],
-        'profit_all_ratio': expected['profit_all_ratio'],
-        'profit_closed_coin': expected['profit_closed_coin'],
-        'profit_closed_fiat': expected['profit_closed_fiat'],
-        'profit_closed_ratio_mean': expected['profit_closed_ratio_mean'],
-        'profit_closed_percent_mean': expected['profit_closed_percent_mean'],
-        'profit_closed_ratio_sum': expected['profit_closed_ratio_sum'],
-        'profit_closed_percent_sum': expected['profit_closed_percent_sum'],
-        'profit_closed_ratio': expected['profit_closed_ratio'],
-        'profit_closed_percent': expected['profit_closed_percent'],
+        'profit_all_coin': pytest.approx(expected['profit_all_coin']),
+        'profit_all_fiat': pytest.approx(expected['profit_all_fiat']),
+        'profit_all_percent_mean': pytest.approx(expected['profit_all_percent_mean']),
+        'profit_all_ratio_mean': pytest.approx(expected['profit_all_ratio_mean']),
+        'profit_all_percent_sum': pytest.approx(expected['profit_all_percent_sum']),
+        'profit_all_ratio_sum': pytest.approx(expected['profit_all_ratio_sum']),
+        'profit_all_percent': pytest.approx(expected['profit_all_percent']),
+        'profit_all_ratio': pytest.approx(expected['profit_all_ratio']),
+        'profit_closed_coin': pytest.approx(expected['profit_closed_coin']),
+        'profit_closed_fiat': pytest.approx(expected['profit_closed_fiat']),
+        'profit_closed_ratio_mean': pytest.approx(expected['profit_closed_ratio_mean']),
+        'profit_closed_percent_mean': pytest.approx(expected['profit_closed_percent_mean']),
+        'profit_closed_ratio_sum': pytest.approx(expected['profit_closed_ratio_sum']),
+        'profit_closed_percent_sum': pytest.approx(expected['profit_closed_percent_sum']),
+        'profit_closed_ratio': pytest.approx(expected['profit_closed_ratio']),
+        'profit_closed_percent': pytest.approx(expected['profit_closed_percent']),
         'trade_count': 6,
         'closed_trade_count': 2,
         'winning_trades': expected['winning_trades'],
diff --git a/tests/rpc/test_rpc_telegram.py b/tests/rpc/test_rpc_telegram.py
index 98c06c8e9..9508a6b42 100644
--- a/tests/rpc/test_rpc_telegram.py
+++ b/tests/rpc/test_rpc_telegram.py
@@ -433,10 +433,10 @@ def test_daily_handle(default_conf_usdt, update, ticker, fee, mocker, time_machi
     assert "Daily Profit over the last 2 days</b>:" in msg_mock.call_args_list[0][0][0]
     assert 'Day ' in msg_mock.call_args_list[0][0][0]
     assert str(datetime.utcnow().date()) in msg_mock.call_args_list[0][0][0]
-    assert '  13.83 USDT' in msg_mock.call_args_list[0][0][0]
-    assert '  15.21 USD' in msg_mock.call_args_list[0][0][0]
+    assert '  6.83 USDT' in msg_mock.call_args_list[0][0][0]
+    assert '  7.51 USD' in msg_mock.call_args_list[0][0][0]
     assert '(2)' in msg_mock.call_args_list[0][0][0]
-    assert '(2)  13.83 USDT  15.21 USD  1.31%' in msg_mock.call_args_list[0][0][0]
+    assert '(2)  6.83 USDT  7.51 USD  0.64%' in msg_mock.call_args_list[0][0][0]
     assert '(0)' in msg_mock.call_args_list[0][0][0]
 
     # Reset msg_mock
@@ -447,8 +447,8 @@ def test_daily_handle(default_conf_usdt, update, ticker, fee, mocker, time_machi
     assert "Daily Profit over the last 7 days</b>:" in msg_mock.call_args_list[0][0][0]
     assert str(datetime.utcnow().date()) in msg_mock.call_args_list[0][0][0]
     assert str((datetime.utcnow() - timedelta(days=5)).date()) in msg_mock.call_args_list[0][0][0]
-    assert '  13.83 USDT' in msg_mock.call_args_list[0][0][0]
-    assert '  15.21 USD' in msg_mock.call_args_list[0][0][0]
+    assert '  6.83 USDT' in msg_mock.call_args_list[0][0][0]
+    assert '  7.51 USD' in msg_mock.call_args_list[0][0][0]
     assert '(2)' in msg_mock.call_args_list[0][0][0]
     assert '(1)' in msg_mock.call_args_list[0][0][0]
     assert '(0)' in msg_mock.call_args_list[0][0][0]
@@ -460,8 +460,8 @@ def test_daily_handle(default_conf_usdt, update, ticker, fee, mocker, time_machi
     context = MagicMock()
     context.args = ["1"]
     telegram._daily(update=update, context=context)
-    assert '  13.83 USDT' in msg_mock.call_args_list[0][0][0]
-    assert '  15.21 USD' in msg_mock.call_args_list[0][0][0]
+    assert '  6.83 USDT' in msg_mock.call_args_list[0][0][0]
+    assert '  7.51 USD' in msg_mock.call_args_list[0][0][0]
     assert '(2)' in msg_mock.call_args_list[0][0][0]
 
 
@@ -523,8 +523,8 @@ def test_weekly_handle(default_conf_usdt, update, ticker, fee, mocker, time_mach
     today = datetime.utcnow().date()
     first_iso_day_of_current_week = today - timedelta(days=today.weekday())
     assert str(first_iso_day_of_current_week) in msg_mock.call_args_list[0][0][0]
-    assert '  9.83 USDT' in msg_mock.call_args_list[0][0][0]
-    assert '  10.81 USD' in msg_mock.call_args_list[0][0][0]
+    assert '  2.74 USDT' in msg_mock.call_args_list[0][0][0]
+    assert '  3.01 USD' in msg_mock.call_args_list[0][0][0]
     assert '(3)' in msg_mock.call_args_list[0][0][0]
     assert '(0)' in msg_mock.call_args_list[0][0][0]
 
@@ -536,8 +536,8 @@ def test_weekly_handle(default_conf_usdt, update, ticker, fee, mocker, time_mach
     assert "Weekly Profit over the last 8 weeks (starting from Monday)</b>:" \
            in msg_mock.call_args_list[0][0][0]
     assert 'Weekly' in msg_mock.call_args_list[0][0][0]
-    assert '  9.83 USDT' in msg_mock.call_args_list[0][0][0]
-    assert '  10.81 USD' in msg_mock.call_args_list[0][0][0]
+    assert '  2.74 USDT' in msg_mock.call_args_list[0][0][0]
+    assert '  3.01 USD' in msg_mock.call_args_list[0][0][0]
     assert '(3)' in msg_mock.call_args_list[0][0][0]
     assert '(0)' in msg_mock.call_args_list[0][0][0]
 
@@ -592,8 +592,8 @@ def test_monthly_handle(default_conf_usdt, update, ticker, fee, mocker, time_mac
     today = datetime.utcnow().date()
     current_month = f"{today.year}-{today.month:02} "
     assert current_month in msg_mock.call_args_list[0][0][0]
-    assert '  9.83 USDT' in msg_mock.call_args_list[0][0][0]
-    assert '  10.81 USD' in msg_mock.call_args_list[0][0][0]
+    assert '  2.74 USDT' in msg_mock.call_args_list[0][0][0]
+    assert '  3.01 USD' in msg_mock.call_args_list[0][0][0]
     assert '(3)' in msg_mock.call_args_list[0][0][0]
     assert '(0)' in msg_mock.call_args_list[0][0][0]
 
@@ -606,8 +606,8 @@ def test_monthly_handle(default_conf_usdt, update, ticker, fee, mocker, time_mac
     assert 'Monthly Profit over the last 6 months</b>:' in msg_mock.call_args_list[0][0][0]
     assert 'Month ' in msg_mock.call_args_list[0][0][0]
     assert current_month in msg_mock.call_args_list[0][0][0]
-    assert '  9.83 USDT' in msg_mock.call_args_list[0][0][0]
-    assert '  10.81 USD' in msg_mock.call_args_list[0][0][0]
+    assert '  2.74 USDT' in msg_mock.call_args_list[0][0][0]
+    assert '  3.01 USD' in msg_mock.call_args_list[0][0][0]
     assert '(3)' in msg_mock.call_args_list[0][0][0]
     assert '(0)' in msg_mock.call_args_list[0][0][0]
 
@@ -620,8 +620,8 @@ def test_monthly_handle(default_conf_usdt, update, ticker, fee, mocker, time_mac
     telegram._monthly(update=update, context=context)
     assert msg_mock.call_count == 1
     assert 'Monthly Profit over the last 12 months</b>:' in msg_mock.call_args_list[0][0][0]
-    assert '  9.83 USDT' in msg_mock.call_args_list[0][0][0]
-    assert '  10.81 USD' in msg_mock.call_args_list[0][0][0]
+    assert '  2.74 USDT' in msg_mock.call_args_list[0][0][0]
+    assert '  3.01 USD' in msg_mock.call_args_list[0][0][0]
     assert '(3)' in msg_mock.call_args_list[0][0][0]
 
     # The one-digit months should contain a zero, Eg: September 2021 = "2021-09"
@@ -1268,7 +1268,7 @@ def test_telegram_performance_handle(default_conf_usdt, update, ticker, fee, moc
     telegram._performance(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
     assert 'Performance' in msg_mock.call_args_list[0][0][0]
-    assert '<code>XRP/USDT\t9.842 USDT (10.00%) (1)</code>' in msg_mock.call_args_list[0][0][0]
+    assert '<code>XRP/USDT\t2.842 USDT (10.00%) (1)</code>' in msg_mock.call_args_list[0][0][0]
 
 
 def test_telegram_entry_tag_performance_handle(
@@ -1318,7 +1318,7 @@ def test_telegram_exit_reason_performance_handle(default_conf_usdt, update, tick
     telegram._exit_reason_performance(update=update, context=context)
     assert msg_mock.call_count == 1
     assert 'Exit Reason Performance' in msg_mock.call_args_list[0][0][0]
-    assert '<code>roi\t9.842 USDT (10.00%) (1)</code>' in msg_mock.call_args_list[0][0][0]
+    assert '<code>roi\t2.842 USDT (10.00%) (1)</code>' in msg_mock.call_args_list[0][0][0]
     context.args = ['XRP/USDT']
 
     telegram._exit_reason_performance(update=update, context=context)
@@ -1350,7 +1350,7 @@ def test_telegram_mix_tag_performance_handle(default_conf_usdt, update, ticker,
     telegram._mix_tag_performance(update=update, context=context)
     assert msg_mock.call_count == 1
     assert 'Mix Tag Performance' in msg_mock.call_args_list[0][0][0]
-    assert ('<code>TEST3 roi\t9.842 USDT (10.00%) (1)</code>'
+    assert ('<code>TEST3 roi\t2.842 USDT (10.00%) (1)</code>'
             in msg_mock.call_args_list[0][0][0])
 
     context.args = ['XRP/USDT']

From cffc7695491d39e653b229d7a1ec75f2cb0ca48b Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Fri, 5 Aug 2022 07:26:41 +0200
Subject: [PATCH 060/132] Fix /profit endpoint calculations for partial sells

* don't recalculate for closed trades
* include realized_profit in the calculation

part of #7178
---
 freqtrade/rpc/rpc.py            | 13 +++++++------
 tests/rpc/test_rpc_apiserver.py | 24 ++++++++++++------------
 2 files changed, 19 insertions(+), 18 deletions(-)

diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py
index 9d6696803..7e431ece9 100644
--- a/freqtrade/rpc/rpc.py
+++ b/freqtrade/rpc/rpc.py
@@ -431,14 +431,15 @@ class RPC:
 
             if not trade.is_open:
                 profit_ratio = trade.close_profit
-                profit_closed_coin.append(trade.close_profit_abs)
+                profit_abs = trade.close_profit_abs
+                profit_closed_coin.append(profit_abs)
                 profit_closed_ratio.append(profit_ratio)
                 if trade.close_profit >= 0:
                     winning_trades += 1
-                    winning_profit += trade.close_profit_abs
+                    winning_profit += profit_abs
                 else:
                     losing_trades += 1
-                    losing_profit += trade.close_profit_abs
+                    losing_profit += profit_abs
             else:
                 # Get current rate
                 try:
@@ -447,10 +448,10 @@ class RPC:
                 except (PricingError, ExchangeError):
                     current_rate = NAN
                 profit_ratio = trade.calc_profit_ratio(rate=current_rate)
+                profit_abs = trade.calc_profit(
+                    rate=trade.close_rate or current_rate) + trade.realized_profit
 
-            profit_all_coin.append(
-                trade.calc_profit(rate=trade.close_rate or current_rate)
-            )
+            profit_all_coin.append(profit_abs)
             profit_all_ratio.append(profit_ratio)
 
         best_pair = Trade.get_best_pair(start_date)
diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py
index c6507d0ae..b7161e680 100644
--- a/tests/rpc/test_rpc_apiserver.py
+++ b/tests/rpc/test_rpc_apiserver.py
@@ -717,11 +717,11 @@ def test_api_edge_disabled(botclient, mocker, ticker, fee, markets):
     (
         True,
         {'best_pair': 'ETC/BTC', 'best_rate': -0.5, 'best_pair_profit_ratio': -0.005,
-         'profit_all_coin': 43.61269123,
-         'profit_all_fiat': 538398.67323435, 'profit_all_percent_mean': 66.41,
+         'profit_all_coin': 45.561959,
+         'profit_all_fiat': 562462.39126200, 'profit_all_percent_mean': 66.41,
          'profit_all_ratio_mean': 0.664109545, 'profit_all_percent_sum': 398.47,
-         'profit_all_ratio_sum': 3.98465727, 'profit_all_percent': 4.36,
-         'profit_all_ratio': 0.043612222872799825, 'profit_closed_coin': -0.00673913,
+         'profit_all_ratio_sum': 3.98465727, 'profit_all_percent': 4.56,
+         'profit_all_ratio': 0.04556147, 'profit_closed_coin': -0.00673913,
          'profit_closed_fiat': -83.19455985, 'profit_closed_ratio_mean': -0.0075,
          'profit_closed_percent_mean': -0.75, 'profit_closed_ratio_sum': -0.015,
          'profit_closed_percent_sum': -1.5, 'profit_closed_ratio': -6.739057628404269e-06,
@@ -732,11 +732,11 @@ def test_api_edge_disabled(botclient, mocker, ticker, fee, markets):
     (
         False,
         {'best_pair': 'XRP/BTC', 'best_rate': 1.0, 'best_pair_profit_ratio': 0.01,
-         'profit_all_coin': -44.0631579,
-         'profit_all_fiat': -543959.6842755, 'profit_all_percent_mean': -66.41,
+         'profit_all_coin': -45.79641127,
+         'profit_all_fiat': -565356.69712815, 'profit_all_percent_mean': -66.41,
          'profit_all_ratio_mean': -0.6641100666666667, 'profit_all_percent_sum': -398.47,
-         'profit_all_ratio_sum': -3.9846604, 'profit_all_percent': -4.41,
-         'profit_all_ratio': -0.044063014216106644, 'profit_closed_coin': 0.00073913,
+         'profit_all_ratio_sum': -3.9846604, 'profit_all_percent': -4.58,
+         'profit_all_ratio': -0.045796261934205953, 'profit_closed_coin': 0.00073913,
          'profit_closed_fiat': 9.124559849999999, 'profit_closed_ratio_mean': 0.0075,
          'profit_closed_percent_mean': 0.75, 'profit_closed_ratio_sum': 0.015,
          'profit_closed_percent_sum': 1.5, 'profit_closed_ratio': 7.391275897987988e-07,
@@ -747,11 +747,11 @@ def test_api_edge_disabled(botclient, mocker, ticker, fee, markets):
     (
         None,
         {'best_pair': 'XRP/BTC', 'best_rate': 1.0, 'best_pair_profit_ratio': 0.01,
-         'profit_all_coin': -14.43790415,
-         'profit_all_fiat': -178235.92673175, 'profit_all_percent_mean': 0.08,
+         'profit_all_coin': -14.94732578,
+         'profit_all_fiat': -184524.7367541, 'profit_all_percent_mean': 0.08,
          'profit_all_ratio_mean': 0.000835751666666662, 'profit_all_percent_sum': 0.5,
-         'profit_all_ratio_sum': 0.005014509999999972, 'profit_all_percent': -1.44,
-         'profit_all_ratio': -0.014437768014451796, 'profit_closed_coin': -0.00542913,
+         'profit_all_ratio_sum': 0.005014509999999972, 'profit_all_percent': -1.49,
+         'profit_all_ratio': -0.014947184841095841, 'profit_closed_coin': -0.00542913,
          'profit_closed_fiat': -67.02260985, 'profit_closed_ratio_mean': 0.0025,
          'profit_closed_percent_mean': 0.25, 'profit_closed_ratio_sum': 0.005,
          'profit_closed_percent_sum': 0.5, 'profit_closed_ratio': -5.429078808526421e-06,

From 7675187c377865abe6d4fc3f58543e294ae7cb53 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Fri, 5 Aug 2022 07:29:49 +0200
Subject: [PATCH 061/132] Use telegram message length to avoid constants

---
 freqtrade/rpc/telegram.py      | 18 ++++++++----------
 tests/rpc/test_rpc_telegram.py |  2 +-
 2 files changed, 9 insertions(+), 11 deletions(-)

diff --git a/freqtrade/rpc/telegram.py b/freqtrade/rpc/telegram.py
index 66192fb16..84b051255 100644
--- a/freqtrade/rpc/telegram.py
+++ b/freqtrade/rpc/telegram.py
@@ -16,8 +16,8 @@ from typing import Any, Callable, Dict, List, Optional, Union
 
 import arrow
 from tabulate import tabulate
-from telegram import (CallbackQuery, InlineKeyboardButton, InlineKeyboardMarkup, KeyboardButton,
-                      ParseMode, ReplyKeyboardMarkup, Update)
+from telegram import (MAX_MESSAGE_LENGTH, CallbackQuery, InlineKeyboardButton, InlineKeyboardMarkup,
+                      KeyboardButton, ParseMode, ReplyKeyboardMarkup, Update)
 from telegram.error import BadRequest, NetworkError, TelegramError
 from telegram.ext import CallbackContext, CallbackQueryHandler, CommandHandler, Updater
 from telegram.utils.helpers import escape_markdown
@@ -35,8 +35,6 @@ logger = logging.getLogger(__name__)
 
 logger.debug('Included module rpc.telegram ...')
 
-MAX_TELEGRAM_MESSAGE_LENGTH = 4096
-
 
 @dataclass
 class TimeunitMappings:
@@ -908,7 +906,7 @@ class Telegram(RPCHandler):
                     total_dust_currencies += 1
 
                 # Handle overflowing message length
-                if len(output + curr_output) >= MAX_TELEGRAM_MESSAGE_LENGTH:
+                if len(output + curr_output) >= MAX_MESSAGE_LENGTH:
                     self._send_msg(output)
                     output = curr_output
                 else:
@@ -1171,7 +1169,7 @@ class Telegram(RPCHandler):
                     f"({trade['profit_ratio']:.2%}) "
                     f"({trade['count']})</code>\n")
 
-                if len(output + stat_line) >= MAX_TELEGRAM_MESSAGE_LENGTH:
+                if len(output + stat_line) >= MAX_MESSAGE_LENGTH:
                     self._send_msg(output, parse_mode=ParseMode.HTML)
                     output = stat_line
                 else:
@@ -1206,7 +1204,7 @@ class Telegram(RPCHandler):
                     f"({trade['profit_ratio']:.2%}) "
                     f"({trade['count']})</code>\n")
 
-                if len(output + stat_line) >= MAX_TELEGRAM_MESSAGE_LENGTH:
+                if len(output + stat_line) >= MAX_MESSAGE_LENGTH:
                     self._send_msg(output, parse_mode=ParseMode.HTML)
                     output = stat_line
                 else:
@@ -1241,7 +1239,7 @@ class Telegram(RPCHandler):
                     f"({trade['profit_ratio']:.2%}) "
                     f"({trade['count']})</code>\n")
 
-                if len(output + stat_line) >= MAX_TELEGRAM_MESSAGE_LENGTH:
+                if len(output + stat_line) >= MAX_MESSAGE_LENGTH:
                     self._send_msg(output, parse_mode=ParseMode.HTML)
                     output = stat_line
                 else:
@@ -1276,7 +1274,7 @@ class Telegram(RPCHandler):
                     f"({trade['profit']:.2%}) "
                     f"({trade['count']})</code>\n")
 
-                if len(output + stat_line) >= MAX_TELEGRAM_MESSAGE_LENGTH:
+                if len(output + stat_line) >= MAX_MESSAGE_LENGTH:
                     self._send_msg(output, parse_mode=ParseMode.HTML)
                     output = stat_line
                 else:
@@ -1415,7 +1413,7 @@ class Telegram(RPCHandler):
                                           escape_markdown(logrec[2], version=2),
                                           escape_markdown(logrec[3], version=2),
                                           escape_markdown(logrec[4], version=2))
-                if len(msgs + msg) + 10 >= MAX_TELEGRAM_MESSAGE_LENGTH:
+                if len(msgs + msg) + 10 >= MAX_MESSAGE_LENGTH:
                     # Send message immediately if it would become too long
                     self._send_msg(msgs, parse_mode=ParseMode.MARKDOWN_V2)
                     msgs = msg + '\n'
diff --git a/tests/rpc/test_rpc_telegram.py b/tests/rpc/test_rpc_telegram.py
index 9508a6b42..164ed0bc6 100644
--- a/tests/rpc/test_rpc_telegram.py
+++ b/tests/rpc/test_rpc_telegram.py
@@ -1516,7 +1516,7 @@ def test_telegram_logs(default_conf, update, mocker) -> None:
 
     msg_mock.reset_mock()
     # Test with changed MaxMessageLength
-    mocker.patch('freqtrade.rpc.telegram.MAX_TELEGRAM_MESSAGE_LENGTH', 200)
+    mocker.patch('freqtrade.rpc.telegram.MAX_MESSAGE_LENGTH', 200)
     context = MagicMock()
     context.args = []
     telegram._logs(update=update, context=context)

From 29e41cc8179f3c8514452e583c5037245131290b Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Fri, 5 Aug 2022 11:15:44 +0200
Subject: [PATCH 062/132] Update docs to reflect correct result

closes #7181
---
 docs/configuration.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/configuration.md b/docs/configuration.md
index 412571674..d5c0b3d8b 100644
--- a/docs/configuration.md
+++ b/docs/configuration.md
@@ -105,7 +105,7 @@ This is similar to using multiple `--config` parameters, but simpler in usage as
 
     ``` json title="Result"
     {
-        "max_open_trades": 10,
+        "max_open_trades": 3,
         "stake_currency": "USDT",
         "stake_amount": "unlimited"
     }

From 954540245209b1a79f707ba51e9e1b7c0f65c18e Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Fri, 5 Aug 2022 11:49:51 +0200
Subject: [PATCH 063/132] Improve defaults for config builder

---
 freqtrade/commands/build_config_commands.py | 6 +++---
 freqtrade/templates/base_config.json.j2     | 1 +
 2 files changed, 4 insertions(+), 3 deletions(-)

diff --git a/freqtrade/commands/build_config_commands.py b/freqtrade/commands/build_config_commands.py
index be881c8ed..01cfa800a 100644
--- a/freqtrade/commands/build_config_commands.py
+++ b/freqtrade/commands/build_config_commands.py
@@ -67,7 +67,7 @@ def ask_user_config() -> Dict[str, Any]:
             "type": "text",
             "name": "stake_amount",
             "message": f"Please insert your stake amount (Number or '{UNLIMITED_STAKE_AMOUNT}'):",
-            "default": "100",
+            "default": "unlimited",
             "validate": lambda val: val == UNLIMITED_STAKE_AMOUNT or validate_is_float(val),
             "filter": lambda val: '"' + UNLIMITED_STAKE_AMOUNT + '"'
             if val == UNLIMITED_STAKE_AMOUNT
@@ -164,7 +164,7 @@ def ask_user_config() -> Dict[str, Any]:
             "when": lambda x: x['telegram']
         },
         {
-            "type": "text",
+            "type": "password",
             "name": "telegram_chat_id",
             "message": "Insert Telegram chat id",
             "when": lambda x: x['telegram']
@@ -191,7 +191,7 @@ def ask_user_config() -> Dict[str, Any]:
             "when": lambda x: x['api_server']
         },
         {
-            "type": "text",
+            "type": "password",
             "name": "api_server_password",
             "message": "Insert api-server password",
             "when": lambda x: x['api_server']
diff --git a/freqtrade/templates/base_config.json.j2 b/freqtrade/templates/base_config.json.j2
index 914aa964b..681af84c6 100644
--- a/freqtrade/templates/base_config.json.j2
+++ b/freqtrade/templates/base_config.json.j2
@@ -12,6 +12,7 @@
     "tradable_balance_ratio": 0.99,
     "fiat_display_currency": "{{ fiat_display_currency }}",{{ ('\n    "timeframe": "' + timeframe + '",') if timeframe else '' }}
     "dry_run": {{ dry_run | lower }},
+    "dry_run_wallet": 1000,
     "cancel_open_orders_on_exit": false,
     "trading_mode": "{{ trading_mode }}",
     "margin_mode": "{{ margin_mode }}",

From 05ec5c5e54fddd0b8a071bb181d922a9499c7794 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Fri, 5 Aug 2022 12:19:29 +0200
Subject: [PATCH 064/132] generalize database url path for any db type

---
 freqtrade/freqai/data_kitchen.py | 16 ++++++++++------
 1 file changed, 10 insertions(+), 6 deletions(-)

diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index 1dfae3ef1..3b128b7c7 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -87,9 +87,13 @@ class FreqaiDataKitchen:
             )
 
         if self.live:
-            db_url = self.config.get('db_url', 'sqlite://')
-            self.database_path = '' if db_url == 'sqlite://' else str(db_url).split('///')[1]
-            self.trade_database_df: DataFrame = pd.DataFrame()
+            db_url = self.config.get('db_url', 'None')
+            self.database_path = Path(db_url)
+            self.database_name = self.database_path.parts[-1]
+        else:
+            self.database_path = Path('None')
+
+        self.trade_database_df: DataFrame = pd.DataFrame()
 
         self.data['extra_returns_per_train'] = self.freqai_config.get('extra_returns_per_train', {})
         self.thread_count = self.freqai_config.get("data_kitchen_thread_count", -1)
@@ -1038,11 +1042,11 @@ class FreqaiDataKitchen:
 
     def get_current_trade_database(self) -> None:
 
-        if self.database_path == '':
-            logger.warning('No trade databse found. Skipping analysis.')
+        if str(self.database_path) == 'None':
+            logger.warning('No trade database found. Skipping analysis.')
             return
 
-        data = sqlite3.connect(self.database_path)
+        data = sqlite3.connect(self.database_name)
         query = data.execute("SELECT * From trades")
         cols = [column[0] for column in query.description]
         df = pd.DataFrame.from_records(data=query.fetchall(), columns=cols)

From 26de992d20636d760adad203464daeeea2ce7db5 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Fri, 5 Aug 2022 12:23:14 +0200
Subject: [PATCH 065/132] ensure user sets startup candles in backtesting mode

---
 freqtrade/optimize/backtesting.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py
index 26519440f..b4675aace 100755
--- a/freqtrade/optimize/backtesting.py
+++ b/freqtrade/optimize/backtesting.py
@@ -208,7 +208,11 @@ class Backtesting:
         self.progress.init_step(BacktestState.DATALOAD, 1)
 
         if self.config.get('freqai') is not None:
-            self.required_startup += int(self.config.get('freqai', {}).get('startup_candles', 1000))
+            startup_candles = int(self.config.get('freqai', {}).get('startup_candles', 0))
+            if not startup_candles:
+                raise OperationalException('FreqAI backtesting module requires user set '
+                                           'startup_candles in config.')
+            self.required_startup += int(self.config.get('freqai', {}).get('startup_candles', 0))
             logger.info(f'Increasing startup_candle_count for freqai to {self.required_startup}')
             self.config['startup_candle_count'] = self.required_startup
 

From db1d3679415292fef702a64d66ec3f78bca8a255 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Fri, 5 Aug 2022 13:46:20 +0200
Subject: [PATCH 066/132] fix bug associated to fit_live_predictions_candles

---
 freqtrade/freqai/freqai_interface.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py
index 3978fc7b2..33828c743 100644
--- a/freqtrade/freqai/freqai_interface.py
+++ b/freqtrade/freqai/freqai_interface.py
@@ -532,6 +532,8 @@ class IFreqaiModel(ABC):
         :param: pair: str = current pair
         """
         num_candles = self.freqai_info.get('fit_live_predictions_candles', 600)
+        if not num_candles:
+            num_candles = 600
         df_tail = df.tail(num_candles)
         trained_predictions = model.predict(df_tail)
         pred_df = DataFrame(trained_predictions, columns=dk.label_list)

From 29b7b014e5ee460e9de2f74ea6c5c2343e1060df Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Fri, 5 Aug 2022 18:19:26 +0200
Subject: [PATCH 067/132] fix bug in DB path initialization

---
 freqtrade/freqai/data_kitchen.py | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index 3b128b7c7..0a8278e91 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -4,7 +4,7 @@ import logging
 import shutil
 import sqlite3
 from pathlib import Path
-from typing import Any, Dict, List, Tuple
+from typing import Any, Dict, List, Tuple, Optional
 
 import numpy as np
 import numpy.typing as npt
@@ -86,12 +86,12 @@ class FreqaiDataKitchen:
                 config["freqai"]["backtest_period_days"],
             )
 
+        self.database_path: Optional[Path] = None
+
         if self.live:
-            db_url = self.config.get('db_url', 'None')
+            db_url = self.config.get('db_url', None)
             self.database_path = Path(db_url)
             self.database_name = self.database_path.parts[-1]
-        else:
-            self.database_path = Path('None')
 
         self.trade_database_df: DataFrame = pd.DataFrame()
 
@@ -1042,7 +1042,7 @@ class FreqaiDataKitchen:
 
     def get_current_trade_database(self) -> None:
 
-        if str(self.database_path) == 'None':
+        if self.database_path is None:
             logger.warning('No trade database found. Skipping analysis.')
             return
 

From a3799c4d5dd710106eef344653b6198beaffe8ce Mon Sep 17 00:00:00 2001
From: Robert Caulk <rob.caulk@gmail.com>
Date: Fri, 5 Aug 2022 18:27:05 +0200
Subject: [PATCH 068/132] start frequi with historical data if available

---
 freqtrade/freqai/data_drawer.py | 36 +++++++++++++++++++++++----------
 1 file changed, 25 insertions(+), 11 deletions(-)

diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py
index 9a17797ff..f8022c8e0 100644
--- a/freqtrade/freqai/data_drawer.py
+++ b/freqtrade/freqai/data_drawer.py
@@ -229,20 +229,34 @@ class FreqaiDataDrawer:
         # dynamic df returned to strategy and plotted in frequi
         mrv_df = self.model_return_values[pair] = pd.DataFrame()
 
-        for label in dk.label_list:
-            mrv_df[label] = pred_df[label]
-            mrv_df[f"{label}_mean"] = dk.data["labels_mean"][label]
-            mrv_df[f"{label}_std"] = dk.data["labels_std"][label]
+        # if user reused `idenfitier` in config and has historical predictions collected, loadthem
+        # so that frequi remains uninterrupted after a crash
+        hist_df = self.historic_predictions
+        if pair in hist_df:
+            len_diff = len(hist_df[pair].index) - len(pred_df.index)
+            if len_diff < 0:
+                df_concat = pd.concat([pred_df.iloc[:abs(len_diff)], hist_df[pair]],
+                                      ignore_index=True, keys=hist_df[pair].keys())
+            else:
+                df_concat = hist_df[pair].tail(len(pred_df.index))
+            df_concat = df_concat.fillna(0)
+            self.model_return_values[pair] = df_concat
 
-        if self.freqai_info["feature_parameters"].get("DI_threshold", 0) > 0:
-            mrv_df["DI_values"] = dk.DI_values
+        else:
+            for label in dk.label_list:
+                mrv_df[label] = pred_df[label]
+                mrv_df[f"{label}_mean"] = dk.data["labels_mean"][label]
+                mrv_df[f"{label}_std"] = dk.data["labels_std"][label]
 
-        mrv_df["do_predict"] = do_preds
+            if self.freqai_info["feature_parameters"].get("DI_threshold", 0) > 0:
+                mrv_df["DI_values"] = dk.DI_values
 
-        if dk.data['extra_returns_per_train']:
-            rets = dk.data['extra_returns_per_train']
-            for return_str in rets:
-                mrv_df[return_str] = rets[return_str]
+            mrv_df["do_predict"] = do_preds
+
+            if dk.data['extra_returns_per_train']:
+                rets = dk.data['extra_returns_per_train']
+                for return_str in rets:
+                    mrv_df[return_str] = rets[return_str]
 
         # for keras type models, the conv_window needs to be prepended so
         # viewing is correct in frequi

From a42a060ab5f3fee7d84a36737d6d4dae56cbab19 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Fri, 5 Aug 2022 21:26:39 +0200
Subject: [PATCH 069/132] fix DB once and for all. Make DBSCAN more efficient
 and robust.

---
 docs/freqai.md                       | 13 ++----
 freqtrade/freqai/data_kitchen.py     | 67 +++++++++++++++++-----------
 freqtrade/freqai/freqai_interface.py |  4 +-
 3 files changed, 45 insertions(+), 39 deletions(-)

diff --git a/docs/freqai.md b/docs/freqai.md
index e38132cb1..b8a4718af 100644
--- a/docs/freqai.md
+++ b/docs/freqai.md
@@ -105,7 +105,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `stratify_training_data` | This value is used to indicate the stratification of the data. e.g. 2 would set every 2nd data point into a separate dataset to be pulled from during training/testing. <br> **Datatype:** positive integer.
 | `indicator_max_period_candles` | The maximum *period* used in `populate_any_indicators()` for indicator creation. FreqAI uses this information in combination with the maximum timeframe to calculate how many data points it should download so that the first data point does not have a NaN <br> **Datatype:** positive integer.
 | `indicator_periods_candles` | A list of integers used to duplicate all indicators according to a set of periods and add them to the feature set. <br> **Datatype:** list of positive integers.
-| `DBSCAN_outlier_pct` | Inactive by default. If user sets this to a fractional value, DBSCAN is used to cluster the training data and remove user set percentage of training data as outliers. <br> **Datatype:** float (fraction of 1).
+| `use_DBSCAN_to_remove_outliers` | Inactive by default. If true, FreqAI clusters data using DBSCAN to identify and remove outliers from training and prediction data. <br> **Datatype:** float (fraction of 1).
 |  |  **Data split parameters**
 | `data_split_parameters` | Include any additional parameters available from Scikit-learn `test_train_split()`, which are shown [here](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html) <br> **Datatype:** dictionary.
 | `test_size` | Fraction of data that should be used for testing instead of training. <br> **Datatype:** positive float below 1.
@@ -535,19 +535,12 @@ FreqAI will train an SVM on the training data (or components if the user activat
 
 ### Clustering the training data and removing outliers with DBSCAN
 
-The user can tell FreqAI to use DBSCAN to cluster training data and remove outliers from the training data set. The user set
-parameter `DBSCAN_outlier_pct` allows the user to indicate the percent of expected outliers to be removed during each training
-(typically set below 0.05). Higher value increases confidence in the model predictions but reduces the entry frequency.
-
-The FreqAI DBSCAN wrapper performs an iterative solution to solving the `eps` hyper parameter. `eps` controls the fraction of 
-training data considered to be an outlier - thus the iterative solution finds the exact value associated with the user designated
-`DBSCAN_outlier_pct`. This iterative solution is performed once per training. FreqAI stores the `eps` to be used when DBSCAN
-is again called to determine if incoming prediction candles are outliers. 
+The user can tell FreqAI to use DBSCAN to cluster training data and remove outliers from the training data set. The user activates `use_DBSCAN_to_remove_outliers` to cluster training data for identification of outliers. Also used to detect incoming outliers for prediction data points.
 
 ```json
     "freqai": {
         "feature_parameters" : {
-            "DBSCAN_outlier_pct": 0.05
+            "use_DBSCAN_to_remove_outliers": true
         }
     }
 ```
diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index 0a8278e91..709784e5f 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -21,6 +21,8 @@ from freqtrade.exceptions import OperationalException
 from freqtrade.resolvers import ExchangeResolver
 from freqtrade.strategy.interface import IStrategy
 
+from sklearn.neighbors import NearestNeighbors
+
 
 SECONDS_IN_DAY = 86400
 SECONDS_IN_HOUR = 3600
@@ -91,7 +93,7 @@ class FreqaiDataKitchen:
         if self.live:
             db_url = self.config.get('db_url', None)
             self.database_path = Path(db_url)
-            self.database_name = self.database_path.parts[-1]
+            self.database_name = Path(*self.database_path.parts[1:])
 
         self.trade_database_df: DataFrame = pd.DataFrame()
 
@@ -606,7 +608,7 @@ class FreqaiDataKitchen:
             clustering = DBSCAN(
                                     eps=self.data['DBSCAN_eps'],
                                     min_samples=self.data['DBSCAN_min_samples'],
-                                    n_jobs=-1
+                                    n_jobs=self.thread_count
                                 ).fit(df)
             do_predict = np.where(clustering.labels_[-num_preds:] == -1, 0, 1)
 
@@ -618,33 +620,22 @@ class FreqaiDataKitchen:
             self.do_predict -= 1
 
         else:
-            outlier_target = self.freqai_config['feature_parameters'].get('DBSCAN_outlier_pct')
-            if eps:
-                epsilon = eps
-            else:
-                epsilon = 10
-                logger.info('DBSCAN starting from high value. This should be faster next train.')
 
-            error = 1.
-            MinPts = len(self.data_dictionary['train_features'].columns)
-            logger.info(
-                    f'DBSCAN finding best clustering for {outlier_target}% outliers.')
+            MinPts = len(self.data_dictionary['train_features'].columns)*2
+            # measure pairwise distances to train_features.shape[1]*2 nearest neighbours
+            neighbors = NearestNeighbors(
+                n_neighbors=MinPts, n_jobs=self.thread_count)
+            neighbors_fit = neighbors.fit(self.data_dictionary['train_features'])
+            distances, _ = neighbors_fit.kneighbors(self.data_dictionary['train_features'])
+            distances = np.sort(distances, axis=0)
+            index_ten_pct = int(len(distances[:, 1]) * 0.1)
+            distances = distances[index_ten_pct:, 1]
+            epsilon = distances[-1]
 
-            # find optimal value for epsilon using an iterative approach:
-            while abs(np.sqrt(error)) > 0.1:
-                clustering = DBSCAN(eps=epsilon, min_samples=MinPts,
-                                    n_jobs=int(self.thread_count / 2)).fit(
-                                        self.data_dictionary['train_features']
-                                    )
-                outlier_pct = np.count_nonzero(clustering.labels_ == -1) / len(clustering.labels_)
-                error = (outlier_pct - outlier_target) ** 2 / outlier_target
-                multiplier = (outlier_pct - outlier_target) if outlier_pct > 0 else 1 * \
-                    np.sign(outlier_pct - outlier_target)
-                multiplier = 1 + error * multiplier
-                epsilon = multiplier * epsilon
-                logger.info(
-                    f'DBSCAN error {error:.2f} for eps {epsilon:.2f}'
-                    f' and outlier pct {outlier_pct:.2f}')
+            clustering = DBSCAN(eps=epsilon, min_samples=MinPts,
+                                n_jobs=int(self.thread_count)).fit(
+                                                    self.data_dictionary['train_features']
+                                                )
 
             logger.info(f'DBSCAN found eps of {epsilon}.')
 
@@ -939,6 +930,8 @@ class FreqaiDataKitchen:
             prepend=self.config.get("prepend_data", False),
         )
 
+        exchange.close()
+
     def set_all_pairs(self) -> None:
 
         self.all_pairs = copy.deepcopy(
@@ -1053,6 +1046,26 @@ class FreqaiDataKitchen:
         self.trade_database_df = df.dropna(subset='close_date')
         data.close()
 
+    def fit_circle_2d(self, x, y, w=[]) -> float:
+
+        A = np.array([x, y, np.ones(len(x))]).T
+        b = x**2 + y**2
+
+        # Modify A,b for weighted least squares
+        if len(w) == len(x):
+            W = np.diag(w)
+            A = np.dot(W, A)
+            b = np.dot(W, b)
+
+        # Solve by method of least squares
+        c = np.linalg.lstsq(A, b, rcond=None)[0]
+
+        # Get circle parameters from solution c
+        xc = c[0] / 2
+        yc = c[1] / 2
+        r = np.sqrt(c[2] + xc**2 + yc**2)
+        return r
+
     def np_encoder(self, object):
         if isinstance(object, np.generic):
             return object.item()
diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py
index 33828c743..8a2aaeddb 100644
--- a/freqtrade/freqai/freqai_interface.py
+++ b/freqtrade/freqai/freqai_interface.py
@@ -384,7 +384,7 @@ class IFreqaiModel(ABC):
         if self.freqai_info["feature_parameters"].get("DI_threshold", 0):
             dk.data["avg_mean_dist"] = dk.compute_distances()
 
-        if self.freqai_info["feature_parameters"].get("DBSCAN_outlier_pct", 0):
+        if self.freqai_info["feature_parameters"].get("use_DBSCAN_to_remove_outliers", False):
             if dk.pair in self.dd.old_DBSCAN_eps:
                 eps = self.dd.old_DBSCAN_eps[dk.pair]
             else:
@@ -414,7 +414,7 @@ class IFreqaiModel(ABC):
         if self.freqai_info["feature_parameters"].get("DI_threshold", 0):
             dk.check_if_pred_in_training_spaces()
 
-        if self.freqai_info["feature_parameters"].get("DBSCAN_outlier_pct", 0):
+        if self.freqai_info["feature_parameters"].get("use_DBSCAN_to_remove_outliers", False):
             dk.use_DBSCAN_to_remove_outliers(predict=True)
 
     def model_exists(

From 60d782e5c511d28f1ea92584a53c0b8a90fd5828 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Fri, 5 Aug 2022 21:31:32 +0200
Subject: [PATCH 070/132] remove unnecessary function

---
 freqtrade/freqai/data_kitchen.py | 20 --------------------
 1 file changed, 20 deletions(-)

diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index 709784e5f..52b251ddf 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -1046,26 +1046,6 @@ class FreqaiDataKitchen:
         self.trade_database_df = df.dropna(subset='close_date')
         data.close()
 
-    def fit_circle_2d(self, x, y, w=[]) -> float:
-
-        A = np.array([x, y, np.ones(len(x))]).T
-        b = x**2 + y**2
-
-        # Modify A,b for weighted least squares
-        if len(w) == len(x):
-            W = np.diag(w)
-            A = np.dot(W, A)
-            b = np.dot(W, b)
-
-        # Solve by method of least squares
-        c = np.linalg.lstsq(A, b, rcond=None)[0]
-
-        # Get circle parameters from solution c
-        xc = c[0] / 2
-        yc = c[1] / 2
-        r = np.sqrt(c[2] + xc**2 + yc**2)
-        return r
-
     def np_encoder(self, object):
         if isinstance(object, np.generic):
             return object.item()

From ce8fbbf7433ee1f1542495b55d6d821e23d20549 Mon Sep 17 00:00:00 2001
From: Robert Caulk <rob.caulk@gmail.com>
Date: Sat, 6 Aug 2022 07:25:59 +0200
Subject: [PATCH 071/132] ensure loading historical df matches frequi indices

---
 freqtrade/freqai/data_drawer.py  |  3 ++-
 freqtrade/freqai/data_kitchen.py | 19 +++++++++----------
 2 files changed, 11 insertions(+), 11 deletions(-)

diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py
index f8022c8e0..85a84160f 100644
--- a/freqtrade/freqai/data_drawer.py
+++ b/freqtrade/freqai/data_drawer.py
@@ -238,9 +238,10 @@ class FreqaiDataDrawer:
                 df_concat = pd.concat([pred_df.iloc[:abs(len_diff)], hist_df[pair]],
                                       ignore_index=True, keys=hist_df[pair].keys())
             else:
-                df_concat = hist_df[pair].tail(len(pred_df.index))
+                df_concat = hist_df[pair].tail(len(pred_df.index)).reset_index(drop=True)
             df_concat = df_concat.fillna(0)
             self.model_return_values[pair] = df_concat
+            logger.info(f'Setting initial FreqUI plots from historical data for {pair}.')
 
         else:
             for label in dk.label_list:
diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index 52b251ddf..6fb75374d 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -4,7 +4,7 @@ import logging
 import shutil
 import sqlite3
 from pathlib import Path
-from typing import Any, Dict, List, Tuple, Optional
+from typing import Any, Dict, List, Optional, Tuple
 
 import numpy as np
 import numpy.typing as npt
@@ -14,6 +14,7 @@ from sklearn import linear_model
 from sklearn.cluster import DBSCAN
 from sklearn.metrics.pairwise import pairwise_distances
 from sklearn.model_selection import train_test_split
+from sklearn.neighbors import NearestNeighbors
 
 from freqtrade.configuration import TimeRange
 from freqtrade.data.history.history_utils import refresh_backtest_ohlcv_data
@@ -21,8 +22,6 @@ from freqtrade.exceptions import OperationalException
 from freqtrade.resolvers import ExchangeResolver
 from freqtrade.strategy.interface import IStrategy
 
-from sklearn.neighbors import NearestNeighbors
-
 
 SECONDS_IN_DAY = 86400
 SECONDS_IN_HOUR = 3600
@@ -505,7 +504,7 @@ class FreqaiDataKitchen:
         point. This metric defines the neighborhood of trained data and is used
         for prediction confidence in the Dissimilarity Index
         """
-        logger.info("computing average mean distance for all training points")
+        # logger.info("computing average mean distance for all training points")
         pairwise = pairwise_distances(
             self.data_dictionary["train_features"], n_jobs=self.thread_count)
         avg_mean_dist = pairwise.mean(axis=1).mean()
@@ -538,7 +537,7 @@ class FreqaiDataKitchen:
 
             if (len(do_predict) - do_predict.sum()) > 0:
                 logger.info(
-                    f"svm_remove_outliers() tossed {len(do_predict) - do_predict.sum()} predictions"
+                    f"SVM tossed {len(do_predict) - do_predict.sum()} predictions."
                 )
             self.do_predict += do_predict
             self.do_predict -= 1
@@ -564,8 +563,8 @@ class FreqaiDataKitchen:
             ]
 
             logger.info(
-                f"svm_remove_outliers() tossed {len(y_pred) - dropped_points.sum()}"
-                f" train points from {len(y_pred)}"
+                f"SVM tossed {len(y_pred) - dropped_points.sum()}"
+                f" train points from {len(y_pred)} total points."
             )
 
             # same for test data
@@ -582,8 +581,8 @@ class FreqaiDataKitchen:
                 ]
 
             logger.info(
-                f"svm_remove_outliers() tossed {len(y_pred) - dropped_points.sum()}"
-                f" test points from {len(y_pred)}"
+                f"SVM tossed {len(y_pred) - dropped_points.sum()}"
+                f" test points from {len(y_pred)} total points."
             )
 
         return
@@ -621,7 +620,7 @@ class FreqaiDataKitchen:
 
         else:
 
-            MinPts = len(self.data_dictionary['train_features'].columns)*2
+            MinPts = len(self.data_dictionary['train_features'].columns) * 2
             # measure pairwise distances to train_features.shape[1]*2 nearest neighbours
             neighbors = NearestNeighbors(
                 n_neighbors=MinPts, n_jobs=self.thread_count)

From 07763d0d4f7749f2fdc697407b2328ed7a4d3247 Mon Sep 17 00:00:00 2001
From: Robert Caulk <rob.caulk@gmail.com>
Date: Sat, 9 Jul 2022 10:13:33 +0200
Subject: [PATCH 072/132] add classifier, improve model naming scheme

---
 freqtrade/freqai/data_drawer.py               |  5 +++
 freqtrade/freqai/data_kitchen.py              |  4 +-
 freqtrade/freqai/freqai_interface.py          | 13 +-----
 .../prediction_models/BaseRegressionModel.py  |  9 ----
 .../prediction_models/BaseTensorFlowModel.py  |  9 ----
 .../prediction_models/CatboostClassifier.py   | 44 +++++++++++++++++++
 ...redictionModel.py => CatboostRegressor.py} |  2 +-
 ...del.py => CatboostRegressorMultiTarget.py} |  2 +-
 ...redictionModel.py => LightGBMRegressor.py} |  2 +-
 ...del.py => LightGBMRegressorMultiTarget.py} |  2 +-
 tests/freqai/conftest.py                      |  2 +-
 tests/freqai/test_freqai_interface.py         |  7 +--
 12 files changed, 62 insertions(+), 39 deletions(-)
 create mode 100644 freqtrade/freqai/prediction_models/CatboostClassifier.py
 rename freqtrade/freqai/prediction_models/{CatboostPredictionModel.py => CatboostRegressor.py} (97%)
 rename freqtrade/freqai/prediction_models/{CatboostPredictionMultiModel.py => CatboostRegressorMultiTarget.py} (96%)
 rename freqtrade/freqai/prediction_models/{LightGBMPredictionModel.py => LightGBMRegressor.py} (96%)
 rename freqtrade/freqai/prediction_models/{LightGBMPredictionMultiModel.py => LightGBMRegressorMultiTarget.py} (96%)

diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py
index 85a84160f..5ef9f534d 100644
--- a/freqtrade/freqai/data_drawer.py
+++ b/freqtrade/freqai/data_drawer.py
@@ -226,6 +226,7 @@ class FreqaiDataDrawer:
         historical candles, and also stores historical predictions despite retrainings (so stored
         predictions are true predictions, not just inferencing on trained data)
         """
+
         # dynamic df returned to strategy and plotted in frequi
         mrv_df = self.model_return_values[pair] = pd.DataFrame()
 
@@ -246,6 +247,8 @@ class FreqaiDataDrawer:
         else:
             for label in dk.label_list:
                 mrv_df[label] = pred_df[label]
+                if mrv_df[label].dtype == object:
+                    continue
                 mrv_df[f"{label}_mean"] = dk.data["labels_mean"][label]
                 mrv_df[f"{label}_std"] = dk.data["labels_std"][label]
 
@@ -295,6 +298,8 @@ class FreqaiDataDrawer:
 
         for label in dk.label_list:
             df[label].iloc[-1] = predictions[label].iloc[-1]
+            if df[label].dtype == object:
+                continue
             df[f"{label}_mean"].iloc[-1] = dk.data["labels_mean"][label]
             df[f"{label}_std"].iloc[-1] = dk.data["labels_std"][label]
 
diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index 6fb75374d..eb3955f65 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -294,7 +294,7 @@ class FreqaiDataKitchen:
             self.data[item + "_min"] = train_min[item]
 
         for item in data_dictionary["train_labels"].keys():
-            if data_dictionary["train_labels"][item].dtype == str:
+            if data_dictionary["train_labels"][item].dtype == object:
                 continue
             train_labels_max = data_dictionary["train_labels"][item].max()
             train_labels_min = data_dictionary["train_labels"][item].min()
@@ -1010,6 +1010,8 @@ class FreqaiDataKitchen:
 
         self.data["labels_mean"], self.data["labels_std"] = {}, {}
         for label in self.label_list:
+            if self.data_dictionary["train_labels"][label].dtype == object:
+                continue
             f = spy.stats.norm.fit(self.data_dictionary["train_labels"][label])
             self.data["labels_mean"][label], self.data["labels_std"][label] = f[0], f[1]
 
diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py
index 8a2aaeddb..12e0abe97 100644
--- a/freqtrade/freqai/freqai_interface.py
+++ b/freqtrade/freqai/freqai_interface.py
@@ -123,7 +123,7 @@ class IFreqaiModel(ABC):
 
         dataframe = dk.remove_features_from_df(dk.return_dataframe)
         del dk
-        return self.return_values(dataframe)
+        return dataframe
 
     @threaded
     def start_scanning(self, strategy: IStrategy) -> None:
@@ -609,17 +609,6 @@ class IFreqaiModel(ABC):
         data (NaNs) or felt uncertain about data (i.e. SVM and/or DI index)
         """
 
-    @abstractmethod
-    def return_values(self, dataframe: DataFrame) -> DataFrame:
-        """
-        User defines the dataframe to be returned to strategy here.
-        :param dataframe: DataFrame = the full dataframe for the current prediction (live)
-                                      or --timerange (backtesting)
-        :return: dataframe: DataFrame = dataframe filled with user defined data
-        """
-
-        return
-
     def analyze_trade_database(self, dk: FreqaiDataKitchen, pair: str) -> None:
         """
         User analyzes the trade database here and returns summary stats which will be passed back
diff --git a/freqtrade/freqai/prediction_models/BaseRegressionModel.py b/freqtrade/freqai/prediction_models/BaseRegressionModel.py
index 112e48183..a3bd82a8f 100644
--- a/freqtrade/freqai/prediction_models/BaseRegressionModel.py
+++ b/freqtrade/freqai/prediction_models/BaseRegressionModel.py
@@ -19,15 +19,6 @@ class BaseRegressionModel(IFreqaiModel):
     such as prediction_models/CatboostPredictionModel.py for guidance.
     """
 
-    def return_values(self, dataframe: DataFrame) -> DataFrame:
-        """
-        User uses this function to add any additional return values to the dataframe.
-        e.g.
-        dataframe['volatility'] = dk.volatility_values
-        """
-
-        return dataframe
-
     def train(
         self, unfiltered_dataframe: DataFrame, pair: str, dk: FreqaiDataKitchen
     ) -> Any:
diff --git a/freqtrade/freqai/prediction_models/BaseTensorFlowModel.py b/freqtrade/freqai/prediction_models/BaseTensorFlowModel.py
index d94378494..afb439cbf 100644
--- a/freqtrade/freqai/prediction_models/BaseTensorFlowModel.py
+++ b/freqtrade/freqai/prediction_models/BaseTensorFlowModel.py
@@ -16,15 +16,6 @@ class BaseTensorFlowModel(IFreqaiModel):
     User *must* inherit from this class and set fit() and predict().
     """
 
-    def return_values(self, dataframe: DataFrame) -> DataFrame:
-        """
-        User uses this function to add any additional return values to the dataframe.
-        e.g.
-        dataframe['volatility'] = dk.volatility_values
-        """
-
-        return dataframe
-
     def train(
         self, unfiltered_dataframe: DataFrame, pair: str, dk: FreqaiDataKitchen
     ) -> Any:
diff --git a/freqtrade/freqai/prediction_models/CatboostClassifier.py b/freqtrade/freqai/prediction_models/CatboostClassifier.py
new file mode 100644
index 000000000..d003744fb
--- /dev/null
+++ b/freqtrade/freqai/prediction_models/CatboostClassifier.py
@@ -0,0 +1,44 @@
+import logging
+from typing import Any, Dict
+
+from catboost import CatBoostClassifier, Pool
+
+from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel
+
+
+logger = logging.getLogger(__name__)
+
+
+class CatboostClassifier(BaseRegressionModel):
+    """
+    User created prediction model. The class needs to override three necessary
+    functions, predict(), train(), fit(). The class inherits ModelHandler which
+    has its own DataHandler where data is held, saved, loaded, and managed.
+    """
+
+    def fit(self, data_dictionary: Dict) -> Any:
+        """
+        User sets up the training and test data to fit their desired model here
+        :params:
+        :data_dictionary: the dictionary constructed by DataHandler to hold
+        all the training and test data/labels.
+        """
+
+        train_data = Pool(
+            data=data_dictionary["train_features"],
+            label=data_dictionary["train_labels"],
+            weight=data_dictionary["train_weights"],
+        )
+
+        cbr = CatBoostClassifier(
+            allow_writing_files=False,
+            gpu_ram_part=0.5,
+            verbose=100,
+            early_stopping_rounds=400,
+            loss_function='MultiClass',
+            **self.model_training_parameters,
+        )
+
+        cbr.fit(train_data)
+
+        return cbr
diff --git a/freqtrade/freqai/prediction_models/CatboostPredictionModel.py b/freqtrade/freqai/prediction_models/CatboostRegressor.py
similarity index 97%
rename from freqtrade/freqai/prediction_models/CatboostPredictionModel.py
rename to freqtrade/freqai/prediction_models/CatboostRegressor.py
index 9731e0c01..d93569c91 100644
--- a/freqtrade/freqai/prediction_models/CatboostPredictionModel.py
+++ b/freqtrade/freqai/prediction_models/CatboostRegressor.py
@@ -10,7 +10,7 @@ from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressio
 logger = logging.getLogger(__name__)
 
 
-class CatboostPredictionModel(BaseRegressionModel):
+class CatboostRegressor(BaseRegressionModel):
     """
     User created prediction model. The class needs to override three necessary
     functions, predict(), train(), fit(). The class inherits ModelHandler which
diff --git a/freqtrade/freqai/prediction_models/CatboostPredictionMultiModel.py b/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py
similarity index 96%
rename from freqtrade/freqai/prediction_models/CatboostPredictionMultiModel.py
rename to freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py
index 35a93e808..9894decd1 100644
--- a/freqtrade/freqai/prediction_models/CatboostPredictionMultiModel.py
+++ b/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py
@@ -10,7 +10,7 @@ from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressio
 logger = logging.getLogger(__name__)
 
 
-class CatboostPredictionMultiModel(BaseRegressionModel):
+class CatboostRegressorMultiTarget(BaseRegressionModel):
     """
     User created prediction model. The class needs to override three necessary
     functions, predict(), train(), fit(). The class inherits ModelHandler which
diff --git a/freqtrade/freqai/prediction_models/LightGBMPredictionModel.py b/freqtrade/freqai/prediction_models/LightGBMRegressor.py
similarity index 96%
rename from freqtrade/freqai/prediction_models/LightGBMPredictionModel.py
rename to freqtrade/freqai/prediction_models/LightGBMRegressor.py
index c94bc5698..f72792611 100644
--- a/freqtrade/freqai/prediction_models/LightGBMPredictionModel.py
+++ b/freqtrade/freqai/prediction_models/LightGBMRegressor.py
@@ -9,7 +9,7 @@ from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressio
 logger = logging.getLogger(__name__)
 
 
-class LightGBMPredictionModel(BaseRegressionModel):
+class LightGBMRegressor(BaseRegressionModel):
     """
     User created prediction model. The class needs to override three necessary
     functions, predict(), train(), fit(). The class inherits ModelHandler which
diff --git a/freqtrade/freqai/prediction_models/LightGBMPredictionMultiModel.py b/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py
similarity index 96%
rename from freqtrade/freqai/prediction_models/LightGBMPredictionMultiModel.py
rename to freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py
index 4c51c9008..ecd405369 100644
--- a/freqtrade/freqai/prediction_models/LightGBMPredictionMultiModel.py
+++ b/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py
@@ -10,7 +10,7 @@ from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressio
 logger = logging.getLogger(__name__)
 
 
-class LightGBMPredictionMultiModel(BaseRegressionModel):
+class LightGBMRegressorMultiTarget(BaseRegressionModel):
     """
     User created prediction model. The class needs to override three necessary
     functions, predict(), train(), fit(). The class inherits ModelHandler which
diff --git a/tests/freqai/conftest.py b/tests/freqai/conftest.py
index ecd8b2d57..90e99951d 100644
--- a/tests/freqai/conftest.py
+++ b/tests/freqai/conftest.py
@@ -21,7 +21,7 @@ def freqai_conf(default_conf, tmpdir):
             "strategy": "freqai_test_strat",
             "user_data_dir": Path(tmpdir),
             "strategy-path": "freqtrade/tests/strategy/strats",
-            "freqaimodel": "LightGBMPredictionModel",
+            "freqaimodel": "LightGBMRegressor",
             "freqaimodel_path": "freqai/prediction_models",
             "timerange": "20180110-20180115",
             "freqai": {
diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py
index c4302e756..68fc14f71 100644
--- a/tests/freqai/test_freqai_interface.py
+++ b/tests/freqai/test_freqai_interface.py
@@ -43,7 +43,7 @@ def test_train_model_in_series_LightGBM(mocker, freqai_conf):
 def test_train_model_in_series_LightGBMMultiModel(mocker, freqai_conf):
     freqai_conf.update({"timerange": "20180110-20180130"})
     freqai_conf.update({"strategy": "freqai_test_multimodel_strat"})
-    freqai_conf.update({"freqaimodel": "LightGBMPredictionMultiModel"})
+    freqai_conf.update({"freqaimodel": "LightGBMRegressorMultiTarget"})
     strategy = get_patched_freqai_strategy(mocker, freqai_conf)
     exchange = get_patched_exchange(mocker, freqai_conf)
     strategy.dp = DataProvider(freqai_conf, exchange)
@@ -73,8 +73,9 @@ def test_train_model_in_series_LightGBMMultiModel(mocker, freqai_conf):
 @pytest.mark.skipif("arm" in platform.uname()[-1], reason="no ARM for Catboost ...")
 def test_train_model_in_series_Catboost(mocker, freqai_conf):
     freqai_conf.update({"timerange": "20180110-20180130"})
-    freqai_conf.update({"freqaimodel": "CatboostPredictionModel"})
-    del freqai_conf['freqai']['model_training_parameters']['verbosity']
+    freqai_conf.update({"freqaimodel": "CatboostRegressor"})
+    freqai_conf.get('freqai', {}).update(
+        {'model_training_parameters': {"n_estimators": 100, "verbose": 0}})
     strategy = get_patched_freqai_strategy(mocker, freqai_conf)
     exchange = get_patched_exchange(mocker, freqai_conf)
     strategy.dp = DataProvider(freqai_conf, exchange)

From b12dd15f4fcf41f912d0448a56725ab32b6fe98e Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 6 Aug 2022 09:10:12 +0200
Subject: [PATCH 073/132] Send multiple messages in /status  if required

---
 freqtrade/rpc/telegram.py      | 21 +++++++++++++--------
 tests/rpc/test_rpc_telegram.py |  4 ++--
 2 files changed, 15 insertions(+), 10 deletions(-)

diff --git a/freqtrade/rpc/telegram.py b/freqtrade/rpc/telegram.py
index 84b051255..c879676dc 100644
--- a/freqtrade/rpc/telegram.py
+++ b/freqtrade/rpc/telegram.py
@@ -457,11 +457,12 @@ class Telegram(RPCHandler):
         """
         Prepare details of trade with entry adjustment enabled
         """
-        lines: List[str] = []
+        lines_detail: List[str] = []
         if len(filled_orders) > 0:
             first_avg = filled_orders[0]["safe_price"]
 
         for x, order in enumerate(filled_orders):
+            lines: List[str] = []
             if order['is_open'] is True:
                 continue
             wording = 'Entry' if order['ft_is_entry'] else 'Exit'
@@ -507,7 +508,8 @@ class Telegram(RPCHandler):
                 # minutes, seconds = divmod(remainder, 60)
                 # lines.append(
                 # f"({days}d {hours}h {minutes}m {seconds}s from previous {wording.lower()})")
-        return lines
+            lines_detail.append("\n".join(lines))
+        return lines_detail
 
     @authorized_only
     def _status(self, update: Update, context: CallbackContext) -> None:
@@ -541,7 +543,6 @@ class Telegram(RPCHandler):
             results = self._rpc._rpc_trade_status(trade_ids=trade_ids)
             position_adjust = self._config.get('position_adjustment_enable', False)
             max_entries = self._config.get('max_entry_position_adjustment', -1)
-            messages = []
             for r in results:
                 r['open_date_hum'] = arrow.get(r['open_date']).humanize()
                 r['num_entries'] = len([o for o in r['orders'] if o['ft_is_entry']])
@@ -594,12 +595,16 @@ class Telegram(RPCHandler):
                 lines_detail = self._prepare_order_details(
                     r['orders'], r['quote_currency'], r['is_open'])
                 lines.extend(lines_detail if lines_detail else "")
+                msg = ''
+                for line in lines:
+                    if line:
+                        if (len(msg) + len(line) + 1) < MAX_MESSAGE_LENGTH:
+                            msg += line + '\n'
+                        else:
+                            self._send_msg(msg.format(**r))
+                            msg = "*Trade ID:* `{trade_id}` - continued\n" + line + '\n'
 
-                # Filter empty lines using list-comprehension
-                messages.append("\n".join([line for line in lines if line]).format(**r))
-
-            for msg in messages:
-                self._send_msg(msg)
+                self._send_msg(msg.format(**r))
 
         except RPCException as e:
             self._send_msg(str(e))
diff --git a/tests/rpc/test_rpc_telegram.py b/tests/rpc/test_rpc_telegram.py
index 164ed0bc6..5b96a8068 100644
--- a/tests/rpc/test_rpc_telegram.py
+++ b/tests/rpc/test_rpc_telegram.py
@@ -342,7 +342,7 @@ def test_status_handle(default_conf, update, ticker, fee, mocker) -> None:
     # close_rate should not be included in the message as the trade is not closed
     # and no line should be empty
     lines = msg_mock.call_args_list[0][0][0].split('\n')
-    assert '' not in lines
+    assert '' not in lines[:-1]
     assert 'Close Rate' not in ''.join(lines)
     assert 'Close Profit' not in ''.join(lines)
 
@@ -357,7 +357,7 @@ def test_status_handle(default_conf, update, ticker, fee, mocker) -> None:
     telegram._status(update=update, context=context)
 
     lines = msg_mock.call_args_list[0][0][0].split('\n')
-    assert '' not in lines
+    assert '' not in lines[:-1]
     assert 'Close Rate' not in ''.join(lines)
     assert 'Close Profit' not in ''.join(lines)
 

From 2687633941eb1c5cee8c0e2ea2a20da86bc20c84 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 6 Aug 2022 09:15:25 +0200
Subject: [PATCH 074/132] Test iterative sending of /status

---
 freqtrade/rpc/telegram.py      |  2 +-
 tests/rpc/test_rpc_telegram.py | 16 ++++++++++++++++
 2 files changed, 17 insertions(+), 1 deletion(-)

diff --git a/freqtrade/rpc/telegram.py b/freqtrade/rpc/telegram.py
index c879676dc..65e16cd35 100644
--- a/freqtrade/rpc/telegram.py
+++ b/freqtrade/rpc/telegram.py
@@ -549,7 +549,7 @@ class Telegram(RPCHandler):
                 r['exit_reason'] = r.get('exit_reason', "")
                 lines = [
                     "*Trade ID:* `{trade_id}`" +
-                    ("` (since {open_date_hum})`" if r['is_open'] else ""),
+                    (" `(since {open_date_hum})`" if r['is_open'] else ""),
                     "*Current Pair:* {pair}",
                     "*Direction:* " + ("`Short`" if r.get('is_short') else "`Long`"),
                     "*Leverage:* `{leverage}`" if r.get('leverage') else "",
diff --git a/tests/rpc/test_rpc_telegram.py b/tests/rpc/test_rpc_telegram.py
index 5b96a8068..2c9528b5e 100644
--- a/tests/rpc/test_rpc_telegram.py
+++ b/tests/rpc/test_rpc_telegram.py
@@ -364,6 +364,22 @@ def test_status_handle(default_conf, update, ticker, fee, mocker) -> None:
     assert msg_mock.call_count == 2
     assert 'LTC/BTC' in msg_mock.call_args_list[0][0][0]
 
+    mocker.patch('freqtrade.rpc.telegram.MAX_MESSAGE_LENGTH', 500)
+
+    msg_mock.reset_mock()
+    context = MagicMock()
+    context.args = ["2"]
+    telegram._status(update=update, context=context)
+
+    assert msg_mock.call_count == 2
+
+    msg1 = msg_mock.call_args_list[0][0][0]
+    msg2 = msg_mock.call_args_list[1][0][0]
+
+    assert 'Close Rate' not in msg1
+    assert 'Trade ID:* `2`' in msg1
+    assert 'Trade ID:* `2` - continued' in msg2
+
 
 def test_status_table_handle(default_conf, update, ticker, fee, mocker) -> None:
     mocker.patch.multiple(

From f8f1ade16387b327a7cfa6db33b3dec71557f558 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 6 Aug 2022 09:21:11 +0200
Subject: [PATCH 075/132] Reduce function complexity by extracting message
 sending

---
 freqtrade/rpc/telegram.py | 34 ++++++++++++++++++++--------------
 1 file changed, 20 insertions(+), 14 deletions(-)

diff --git a/freqtrade/rpc/telegram.py b/freqtrade/rpc/telegram.py
index 65e16cd35..02fb5b4ee 100644
--- a/freqtrade/rpc/telegram.py
+++ b/freqtrade/rpc/telegram.py
@@ -587,28 +587,34 @@ class Telegram(RPCHandler):
                     lines.append("*Stoploss distance:* `{stoploss_current_dist:.8f}` "
                                  "`({stoploss_current_dist_ratio:.2%})`")
                     if r['open_order']:
-                        if r['exit_order_status']:
-                            lines.append("*Open Order:* `{open_order}` - `{exit_order_status}`")
-                        else:
-                            lines.append("*Open Order:* `{open_order}`")
+                        lines.append(
+                            "*Open Order:* `{open_order}`"
+                            + "- `{exit_order_status}`" if r['exit_order_status'] else "")
 
                 lines_detail = self._prepare_order_details(
                     r['orders'], r['quote_currency'], r['is_open'])
                 lines.extend(lines_detail if lines_detail else "")
-                msg = ''
-                for line in lines:
-                    if line:
-                        if (len(msg) + len(line) + 1) < MAX_MESSAGE_LENGTH:
-                            msg += line + '\n'
-                        else:
-                            self._send_msg(msg.format(**r))
-                            msg = "*Trade ID:* `{trade_id}` - continued\n" + line + '\n'
-
-                self._send_msg(msg.format(**r))
+                self.__send_status_msg(lines, r)
 
         except RPCException as e:
             self._send_msg(str(e))
 
+    def __send_status_msg(self, lines: List[str], r: Dict[str, Any]) -> None:
+        """
+        Send status message.
+        """
+        msg = ''
+
+        for line in lines:
+            if line:
+                if (len(msg) + len(line) + 1) < MAX_MESSAGE_LENGTH:
+                    msg += line + '\n'
+                else:
+                    self._send_msg(msg.format(**r))
+                    msg = "*Trade ID:* `{trade_id}` - continued\n" + line + '\n'
+
+        self._send_msg(msg.format(**r))
+
     @authorized_only
     def _status_table(self, update: Update, context: CallbackContext) -> None:
         """

From fdc82f8302f6819e501b25c0c962934cb48a6684 Mon Sep 17 00:00:00 2001
From: Robert Caulk <rob.caulk@gmail.com>
Date: Sat, 6 Aug 2022 09:45:26 +0200
Subject: [PATCH 076/132] add doc section for classifier

---
 docs/freqai.md | 10 +++++++++-
 1 file changed, 9 insertions(+), 1 deletion(-)

diff --git a/docs/freqai.md b/docs/freqai.md
index b8a4718af..caef73d15 100644
--- a/docs/freqai.md
+++ b/docs/freqai.md
@@ -411,9 +411,17 @@ The Freqai strategy requires the user to include the following lines of code in
 The user should also include `populate_any_indicators()` from `templates/FreqaiExampleStrategy.py` which builds 
 the feature set with a proper naming convention for the IFreqaiModel to use later.
 
+### Setting classifier targets
+
+FreqAI includes a the `CatboostClassifier` via the flag `--freqaimodel CatboostClassifier`. Typically, the user would set the targets using strings:
+
+```python
+df['&s-up_or_down'] = np.where( df["close"].shift(-100) > df["close"], 'up', 'down')
+```
+
 ### Building an IFreqaiModel
 
-FreqAI has multiple example prediction model based libraries such as `Catboost` regression (`freqai/prediction_models/CatboostPredictionModel.py`) and `LightGBM` regression. 
+FreqAI has multiple example prediction model based libraries such as `Catboost` regression (`freqai/prediction_models/CatboostRegressor.py`) and `LightGBM` regression. 
 However, users can customize and create their own prediction models using the `IFreqaiModel` class.
 Users are encouraged to inherit `train()` and `predict()` to let them customize various aspects of their training procedures.
 

From 45d68222a177e62b81fd5d760e17cbf9614aa36a Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 6 Aug 2022 13:18:40 +0200
Subject: [PATCH 077/132] Reduce verbosity of Fiat Converter

---
 freqtrade/rpc/fiat_convert.py | 8 ++++++--
 1 file changed, 6 insertions(+), 2 deletions(-)

diff --git a/freqtrade/rpc/fiat_convert.py b/freqtrade/rpc/fiat_convert.py
index df33693ac..cbe4c0045 100644
--- a/freqtrade/rpc/fiat_convert.py
+++ b/freqtrade/rpc/fiat_convert.py
@@ -12,6 +12,7 @@ from pycoingecko import CoinGeckoAPI
 from requests.exceptions import RequestException
 
 from freqtrade.constants import SUPPORTED_FIAT
+from freqtrade.mixins.logging_mixin import LoggingMixin
 
 
 logger = logging.getLogger(__name__)
@@ -27,7 +28,7 @@ coingecko_mapping = {
 }
 
 
-class CryptoToFiatConverter:
+class CryptoToFiatConverter(LoggingMixin):
     """
     Main class to initiate Crypto to FIAT.
     This object contains a list of pair Crypto, FIAT
@@ -54,6 +55,7 @@ class CryptoToFiatConverter:
         # Timeout: 6h
         self._pair_price: TTLCache = TTLCache(maxsize=500, ttl=6 * 60 * 60)
 
+        LoggingMixin.__init__(self, logger, 3600)
         self._load_cryptomap()
 
     def _load_cryptomap(self) -> None:
@@ -177,7 +179,9 @@ class CryptoToFiatConverter:
 
         if not _gekko_id:
             # return 0 for unsupported stake currencies (fiat-convert should not break the bot)
-            logger.warning("unsupported crypto-symbol %s - returning 0.0", crypto_symbol)
+            self.log_once(
+                f"unsupported crypto-symbol {crypto_symbol.upper()} - returning 0.0",
+                logger.warning)
             return 0.0
 
         try:

From c172ce101132c4e422d7652e2708366fc1522aeb Mon Sep 17 00:00:00 2001
From: Robert Caulk <rob.caulk@gmail.com>
Date: Sat, 6 Aug 2022 13:51:19 +0200
Subject: [PATCH 078/132] improve flexibility of user defined prediction
 dataframe

---
 docs/freqai.md                        |  8 +++---
 freqtrade/freqai/data_drawer.py       | 37 ++++++++++++++++-----------
 freqtrade/freqai/data_kitchen.py      | 10 +++++---
 freqtrade/freqai/freqai_interface.py  | 12 +++++----
 tests/freqai/conftest.py              |  2 +-
 tests/freqai/test_freqai_interface.py |  4 +--
 6 files changed, 42 insertions(+), 31 deletions(-)

diff --git a/docs/freqai.md b/docs/freqai.md
index caef73d15..b3682127c 100644
--- a/docs/freqai.md
+++ b/docs/freqai.md
@@ -62,13 +62,13 @@ pip install -r requirements-freqai.txt
 ## Running from the example files
 
 An example strategy, an example prediction model, and example config can all be found in
-`freqtrade/templates/FreqaiExampleStrategy.py`, `freqtrade/freqai/prediction_models/LightGBMPredictionModel.py`,
+`freqtrade/templates/FreqaiExampleStrategy.py`, `freqtrade/freqai/prediction_models/LightGBMRegressor.py`,
 `config_examples/config_freqai.example.json`, respectively.
 
 Assuming the user has downloaded the necessary data, Freqai can be executed from these templates with:
 
 ```bash
-freqtrade backtesting --config config_examples/config_freqai.example.json --strategy FreqaiExampleStrategy --freqaimodel LightGBMPredictionModel --strategy-path freqtrade/templates --timerange 20220101-20220201
+freqtrade backtesting --config config_examples/config_freqai.example.json --strategy FreqaiExampleStrategy --freqaimodel LightGBMRegressor --strategy-path freqtrade/templates --timerange 20220101-20220201
 ```
 
 ## Configuring the bot
@@ -111,7 +111,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `test_size` | Fraction of data that should be used for testing instead of training. <br> **Datatype:** positive float below 1.
 | `shuffle` | Shuffle the training data points during training. Typically for time-series forecasting, this is set to False. **Datatype:** boolean.
 |  |  **Model training parameters**
-| `model_training_parameters` | A flexible dictionary that includes all parameters available by the user selected library. For example, if the user uses `LightGBMPredictionModel`, then this dictionary can contain any parameter available by the `LightGBMRegressor` [here](https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRegressor.html). If the user selects a different model, then this dictionary can contain any parameter from that different model.  <br> **Datatype:** dictionary.
+| `model_training_parameters` | A flexible dictionary that includes all parameters available by the user selected library. For example, if the user uses `LightGBMRegressor`, then this dictionary can contain any parameter available by the `LightGBMRegressor` [here](https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRegressor.html). If the user selects a different model, then this dictionary can contain any parameter from that different model.  <br> **Datatype:** dictionary.
 | `n_estimators` | A common parameter among regressors which sets the number of boosted trees to fit <br> **Datatype:** integer.
 | `learning_rate` | A common parameter among regressors which sets the boosting learning rate. <br> **Datatype:** float.
 | `n_jobs`, `thread_count`, `task_type` | Different libraries use different parameter names to control the number of threads used for parallel processing or whether or not it is a `task_type` of `gpu` or `cpu`. <br> **Datatype:** float.
@@ -356,7 +356,7 @@ and adding this to the `train_period_days`. The units need to be in the base can
 The freqai training/backtesting module can be executed with the following command:
 
 ```bash
-freqtrade backtesting --strategy FreqaiExampleStrategy --config config_freqai.example.json --freqaimodel LightGBMPredictionModel --timerange 20210501-20210701
+freqtrade backtesting --strategy FreqaiExampleStrategy --config config_freqai.example.json --freqaimodel LightGBMRegressor --timerange 20210501-20210701
 ```
 
 If this command has never been executed with the existing config file, then it will train a new model
diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py
index 5ef9f534d..0c1f18890 100644
--- a/freqtrade/freqai/data_drawer.py
+++ b/freqtrade/freqai/data_drawer.py
@@ -245,7 +245,7 @@ class FreqaiDataDrawer:
             logger.info(f'Setting initial FreqUI plots from historical data for {pair}.')
 
         else:
-            for label in dk.label_list:
+            for label in pred_df.columns:
                 mrv_df[label] = pred_df[label]
                 if mrv_df[label].dtype == object:
                     continue
@@ -278,15 +278,16 @@ class FreqaiDataDrawer:
         # strat seems to feed us variable sized dataframes - and since we are trying to build our
         # own return array in the same shape, we need to figure out how the size has changed
         # and adapt our stored/returned info accordingly.
-        length_difference = len(self.model_return_values[pair]) - len_df
-        i = 0
 
-        if length_difference == 0:
-            i = 1
-        elif length_difference > 0:
-            i = length_difference + 1
+        # length_difference = len(self.model_return_values[pair]) - len_df
+        # i = 0
 
-        df = self.model_return_values[pair] = self.model_return_values[pair].shift(-i)
+        # if length_difference == 0:
+        #     i = 1
+        # elif length_difference > 0:
+        #     i = length_difference + 1
+
+        df = self.model_return_values[pair] = self.model_return_values[pair].shift(-1)
 
         if pair in self.historic_predictions:
             hp_df = self.historic_predictions[pair]
@@ -296,7 +297,8 @@ class FreqaiDataDrawer:
             hp_df = pd.concat([hp_df, nan_df], ignore_index=True, axis=0)
             self.historic_predictions[pair] = hp_df[:-1]
 
-        for label in dk.label_list:
+        # incase user adds additional "predictions" e.g. predict_proba output:
+        for label in predictions.columns:
             df[label].iloc[-1] = predictions[label].iloc[-1]
             if df[label].dtype == object:
                 continue
@@ -318,11 +320,11 @@ class FreqaiDataDrawer:
             for key in df.keys():
                 self.historic_predictions[pair][key].iloc[-1] = df[key].iloc[-1]
 
-        if length_difference < 0:
-            prepend_df = pd.DataFrame(
-                np.zeros((abs(length_difference) - 1, len(df.columns))), columns=df.columns
-            )
-            df = pd.concat([prepend_df, df], axis=0)
+        # if length_difference < 0:
+        #     prepend_df = pd.DataFrame(
+        #         np.zeros((abs(length_difference) - 1, len(df.columns))), columns=df.columns
+        #     )
+        #     df = pd.concat([prepend_df, df], axis=0)
 
     def attach_return_values_to_return_dataframe(
             self, pair: str, dataframe: DataFrame) -> DataFrame:
@@ -343,7 +345,12 @@ class FreqaiDataDrawer:
 
         dk.find_features(dataframe)
 
-        for label in dk.label_list:
+        if self.freqai_info.get('predict_proba', []):
+            full_labels = dk.label_list + self.freqai_info['predict_proba']
+        else:
+            full_labels = dk.label_list
+
+        for label in full_labels:
             dataframe[label] = 0
             dataframe[f"{label}_mean"] = 0
             dataframe[f"{label}_std"] = 0
diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index eb3955f65..1b1f0c907 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -342,7 +342,7 @@ class FreqaiDataKitchen:
         :df: Dataframe of predictions to be denormalized
         """
 
-        for label in self.label_list:
+        for label in df.columns:
             if df[label].dtype == object:
                 continue
             df[label] = (
@@ -716,14 +716,16 @@ class FreqaiDataKitchen:
         weights = np.exp(-np.arange(num_weights) / (wfactor * num_weights))[::-1]
         return weights
 
-    def append_predictions(self, predictions, do_predict, len_dataframe):
+    def append_predictions(self, predictions: DataFrame, do_predict: npt.ArrayLike) -> None:
         """
         Append backtest prediction from current backtest period to all previous periods
         """
 
         append_df = DataFrame()
-        for label in self.label_list:
+        for label in predictions.columns:
             append_df[label] = predictions[label]
+            if append_df[label].dtype == object:
+                continue
             append_df[f"{label}_mean"] = self.data["labels_mean"][label]
             append_df[f"{label}_std"] = self.data["labels_std"][label]
 
@@ -1009,7 +1011,7 @@ class FreqaiDataKitchen:
         import scipy as spy
 
         self.data["labels_mean"], self.data["labels_std"] = {}, {}
-        for label in self.label_list:
+        for label in self.data_dictionary["train_labels"].columns:
             if self.data_dictionary["train_labels"][label].dtype == object:
                 continue
             f = spy.stats.norm.fit(self.data_dictionary["train_labels"][label])
diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py
index 12e0abe97..a1d0ec1a3 100644
--- a/freqtrade/freqai/freqai_interface.py
+++ b/freqtrade/freqai/freqai_interface.py
@@ -221,7 +221,7 @@ class IFreqaiModel(ABC):
 
             pred_df, do_preds = self.predict(dataframe_backtest, dk)
 
-            dk.append_predictions(pred_df, do_preds, len(dataframe_backtest))
+            dk.append_predictions(pred_df, do_preds)
 
         dk.fill_predictions(dataframe)
 
@@ -543,15 +543,17 @@ class IFreqaiModel(ABC):
         self.dd.historic_predictions[pair] = pred_df
         hist_preds_df = self.dd.historic_predictions[pair]
 
+        for label in hist_preds_df.columns:
+            if hist_preds_df[label].dtype == object:
+                continue
+            hist_preds_df[f'{label}_mean'] = 0
+            hist_preds_df[f'{label}_std'] = 0
+
         hist_preds_df['do_predict'] = 0
 
         if self.freqai_info['feature_parameters'].get('DI_threshold', 0) > 0:
             hist_preds_df['DI_values'] = 0
 
-        for label in dk.data['labels_mean']:
-            hist_preds_df[f'{label}_mean'] = 0
-            hist_preds_df[f'{label}_std'] = 0
-
         for return_str in dk.data['extra_returns_per_train']:
             hist_preds_df[return_str] = 0
 
diff --git a/tests/freqai/conftest.py b/tests/freqai/conftest.py
index 90e99951d..ee02cc097 100644
--- a/tests/freqai/conftest.py
+++ b/tests/freqai/conftest.py
@@ -47,7 +47,7 @@ def freqai_conf(default_conf, tmpdir):
                     "indicator_periods_candles": [10],
                 },
                 "data_split_parameters": {"test_size": 0.33, "random_state": 1},
-                "model_training_parameters": {"n_estimators": 100, "verbosity": 0},
+                "model_training_parameters": {"n_estimators": 100},
             },
             "config_files": [Path('config_examples', 'config_freqai.example.json')]
         }
diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py
index 68fc14f71..1f96cf6df 100644
--- a/tests/freqai/test_freqai_interface.py
+++ b/tests/freqai/test_freqai_interface.py
@@ -74,8 +74,8 @@ def test_train_model_in_series_LightGBMMultiModel(mocker, freqai_conf):
 def test_train_model_in_series_Catboost(mocker, freqai_conf):
     freqai_conf.update({"timerange": "20180110-20180130"})
     freqai_conf.update({"freqaimodel": "CatboostRegressor"})
-    freqai_conf.get('freqai', {}).update(
-        {'model_training_parameters': {"n_estimators": 100, "verbose": 0}})
+    # freqai_conf.get('freqai', {}).update(
+    #     {'model_training_parameters': {"n_estimators": 100, "verbose": 0}})
     strategy = get_patched_freqai_strategy(mocker, freqai_conf)
     exchange = get_patched_exchange(mocker, freqai_conf)
     strategy.dp = DataProvider(freqai_conf, exchange)

From b16f57cb0d86a76451ef89d488997c0b89144901 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 6 Aug 2022 14:55:46 +0200
Subject: [PATCH 079/132] Minor stylistic fixes

---
 freqtrade/freqai/data_kitchen.py     | 61 ++++++++++++----------------
 freqtrade/freqai/freqai_interface.py |  2 +-
 2 files changed, 27 insertions(+), 36 deletions(-)

diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index 1b1f0c907..be9284c92 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -61,7 +61,7 @@ class FreqaiDataKitchen:
         self.data: Dict[Any, Any] = {}
         self.data_dictionary: Dict[Any, Any] = {}
         self.config = config
-        self.freqai_config = config["freqai"]
+        self.freqai_config: Dict[str, Any] = config["freqai"]
         self.full_df: DataFrame = DataFrame()
         self.append_df: DataFrame = DataFrame()
         self.data_path = Path()
@@ -71,14 +71,14 @@ class FreqaiDataKitchen:
         self.live = live
         self.pair = pair
         self.svm_model: linear_model.SGDOneClassSVM = None
-        self.keras = self.freqai_config.get("keras", False)
+        self.keras: bool = self.freqai_config.get("keras", False)
         self.set_all_pairs()
         if not self.live:
             if not self.config["timerange"]:
                 raise OperationalException(
                     'Please pass --timerange if you intend to use FreqAI for backtesting.')
             self.full_timerange = self.create_fulltimerange(
-                self.config["timerange"], self.freqai_config.get("train_period_days")
+                self.config["timerange"], self.freqai_config.get("train_period_days", 0)
             )
 
             (self.training_timeranges, self.backtesting_timeranges) = self.split_timerange(
@@ -203,9 +203,8 @@ class FreqaiDataKitchen:
 
         drop_index = pd.isnull(filtered_dataframe).any(1)  # get the rows that have NaNs,
         drop_index = drop_index.replace(True, 1).replace(False, 0)  # pep8 requirement.
-        if (
-            training_filter
-        ):  # we don't care about total row number (total no. datapoints) in training, we only care
+        if (training_filter):
+            # we don't care about total row number (total no. datapoints) in training, we only care
             # about removing any row with NaNs
             # if labels has multiple columns (user wants to train multiple models), we detect here
             labels = unfiltered_dataframe.filter(label_list, axis=1)
@@ -320,8 +319,7 @@ class FreqaiDataKitchen:
         """
         Normalize a set of data using the mean and standard deviation from
         the associated training data.
-        :params:
-        :df: Dataframe to be standardized
+        :param df: Dataframe to be standardized
         """
 
         for item in df.keys():
@@ -338,8 +336,7 @@ class FreqaiDataKitchen:
         """
         Normalize a set of data using the mean and standard deviation from
         the associated training data.
-        :params:
-        :df: Dataframe of predictions to be denormalized
+        :param df: Dataframe of predictions to be denormalized
         """
 
         for label in df.columns:
@@ -367,7 +364,7 @@ class FreqaiDataKitchen:
 
         if not isinstance(train_split, int) or train_split < 1:
             raise OperationalException(
-                "train_period_days must be an integer greater than 0. " f"Got {train_split}."
+                f"train_period_days must be an integer greater than 0. Got {train_split}."
             )
         train_period_days = train_split * SECONDS_IN_DAY
         bt_period = bt_split * SECONDS_IN_DAY
@@ -423,10 +420,9 @@ class FreqaiDataKitchen:
     def slice_dataframe(self, timerange: TimeRange, df: DataFrame) -> DataFrame:
         """
         Given a full dataframe, extract the user desired window
-        :params:
-        :tr: timerange string that we wish to extract from df
-        :df: Dataframe containing all candles to run the entire backtest. Here
-        it is sliced down to just the present training period.
+        :param tr: timerange string that we wish to extract from df
+        :param df: Dataframe containing all candles to run the entire backtest. Here
+                   it is sliced down to just the present training period.
         """
 
         start = datetime.datetime.fromtimestamp(timerange.startts, tz=datetime.timezone.utc)
@@ -536,9 +532,7 @@ class FreqaiDataKitchen:
             do_predict = np.where(y_pred == -1, 0, y_pred)
 
             if (len(do_predict) - do_predict.sum()) > 0:
-                logger.info(
-                    f"SVM tossed {len(do_predict) - do_predict.sum()} predictions."
-                )
+                logger.info(f"SVM tossed {len(do_predict) - do_predict.sum()} predictions.")
             self.do_predict += do_predict
             self.do_predict -= 1
 
@@ -568,6 +562,8 @@ class FreqaiDataKitchen:
             )
 
             # same for test data
+            # TODO: This (and the part above) could be refactored into a separate function
+            # to reduce code duplication
             if self.freqai_config['data_split_parameters'].get('test_size', 0.1) != 0:
                 y_pred = self.svm_model.predict(self.data_dictionary["test_features"])
                 dropped_points = np.where(y_pred == -1, 0, y_pred)
@@ -604,17 +600,14 @@ class FreqaiDataKitchen:
             pred_ft_df = self.data_dictionary['prediction_features']
             num_preds = len(pred_ft_df)
             df = pd.concat([train_ft_df, pred_ft_df], axis=0, ignore_index=True)
-            clustering = DBSCAN(
-                                    eps=self.data['DBSCAN_eps'],
-                                    min_samples=self.data['DBSCAN_min_samples'],
-                                    n_jobs=self.thread_count
+            clustering = DBSCAN(eps=self.data['DBSCAN_eps'],
+                                min_samples=self.data['DBSCAN_min_samples'],
+                                n_jobs=self.thread_count
                                 ).fit(df)
             do_predict = np.where(clustering.labels_[-num_preds:] == -1, 0, 1)
 
             if (len(do_predict) - do_predict.sum()) > 0:
-                logger.info(
-                    f"DBSCAN tossed {len(do_predict) - do_predict.sum()} predictions"
-                )
+                logger.info(f"DBSCAN tossed {len(do_predict) - do_predict.sum()} predictions")
             self.do_predict += do_predict
             self.do_predict -= 1
 
@@ -662,9 +655,8 @@ class FreqaiDataKitchen:
     def find_features(self, dataframe: DataFrame) -> None:
         """
         Find features in the strategy provided dataframe
-        :params:
-        dataframe: DataFrame = strategy provided dataframe
-        :returns:
+        :param dataframe: DataFrame = strategy provided dataframe
+        :return:
         features: list = the features to be used for training/prediction
         """
         column_names = dataframe.columns
@@ -772,7 +764,7 @@ class FreqaiDataKitchen:
 
         if backtest_timerange.stopts == 0:
             # typically open ended time ranges do work, however, there are some edge cases where
-            # it does not. accomodating these kinds of edge cases just to allow open-ended
+            # it does not. accommodating these kinds of edge cases just to allow open-ended
             # timerange is not high enough priority to warrant the effort. It is safer for now
             # to simply ask user to add their end date
             raise OperationalException("FreqAI backtesting does not allow open ended timeranges. "
@@ -808,10 +800,9 @@ class FreqaiDataKitchen:
         """
         A model age checker to determine if the model is trustworthy based on user defined
         `expiration_hours` in the configuration file.
-        :params:
-        trained_timestamp: int = The time of training for the most recent model.
-        :returns:
-        bool = If the model is expired or not.
+        :param trained_timestamp: int = The time of training for the most recent model.
+        :return:
+            bool = If the model is expired or not.
         """
         time = datetime.datetime.now(tz=datetime.timezone.utc).timestamp()
         elapsed_time = (time - trained_timestamp) / 3600  # hours
@@ -873,7 +864,7 @@ class FreqaiDataKitchen:
                 data_load_timerange.stopts = int(time)
         else:  # user passed no live_trained_timerange in config
             trained_timerange.startts = int(
-                time - self.freqai_config.get("train_period_days") * SECONDS_IN_DAY
+                time - self.freqai_config.get("train_period_days", 0) * SECONDS_IN_DAY
             )
             trained_timerange.stopts = int(time)
 
@@ -1053,7 +1044,7 @@ class FreqaiDataKitchen:
         if isinstance(object, np.generic):
             return object.item()
 
-    # Functions containing useful data manpulation examples. but not actively in use.
+    # Functions containing useful data manipulation examples. but not actively in use.
 
     # Possibly phasing these outlier removal methods below out in favor of
     # use_SVM_to_remove_outliers (computationally more efficient and apparently higher performance).
diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py
index a1d0ec1a3..f5015c1b4 100644
--- a/freqtrade/freqai/freqai_interface.py
+++ b/freqtrade/freqai/freqai_interface.py
@@ -572,7 +572,7 @@ class IFreqaiModel(ABC):
         return
 
     # Following methods which are overridden by user made prediction models.
-    # See freqai/prediction_models/CatboostPredictionModlel.py for an example.
+    # See freqai/prediction_models/CatboostPredictionModel.py for an example.
 
     @abstractmethod
     def train(self, unfiltered_dataframe: DataFrame, pair: str, dk: FreqaiDataKitchen) -> Any:

From 47a30047eba29f5d65562143844d29a1d8a07b09 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 6 Aug 2022 15:02:35 +0200
Subject: [PATCH 080/132] Fix typo

---
 freqtrade/freqai/data_drawer.py      | 2 +-
 freqtrade/freqai/freqai_interface.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py
index 0c1f18890..6527eed98 100644
--- a/freqtrade/freqai/data_drawer.py
+++ b/freqtrade/freqai/data_drawer.py
@@ -230,7 +230,7 @@ class FreqaiDataDrawer:
         # dynamic df returned to strategy and plotted in frequi
         mrv_df = self.model_return_values[pair] = pd.DataFrame()
 
-        # if user reused `idenfitier` in config and has historical predictions collected, loadthem
+        # if user reused `identifier` in config and has historical predictions collected, load them
         # so that frequi remains uninterrupted after a crash
         hist_df = self.historic_predictions
         if pair in hist_df:
diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py
index f5015c1b4..248484b05 100644
--- a/freqtrade/freqai/freqai_interface.py
+++ b/freqtrade/freqai/freqai_interface.py
@@ -526,7 +526,7 @@ class IFreqaiModel(ABC):
         this function will not be called. In that case, "real" predictions
         will be appended to the loaded set of historic predictions.
         :param: df: DataFrame = the dataframe containing the training feature data
-        :param: model: Any = A model which was `fit` using a common librariy such as
+        :param: model: Any = A model which was `fit` using a common library such as
         catboost or lightgbm
         :param: dk: FreqaiDataKitchen = object containing methods for data analysis
         :param: pair: str = current pair

From 5250189f77bcc4c6c017fdcc3a60ae2a6104f714 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 6 Aug 2022 15:08:13 +0200
Subject: [PATCH 081/132] Add Rollback function to Trade

simplifies Session work
---
 freqtrade/persistence/trade_model.py | 6 +++++-
 freqtrade/rpc/api_server/deps.py     | 4 ++--
 freqtrade/rpc/rpc.py                 | 2 +-
 freqtrade/rpc/telegram.py            | 2 +-
 tests/test_persistence.py            | 1 +
 5 files changed, 10 insertions(+), 5 deletions(-)

diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py
index 19d9361b6..3ea6ddf2d 100644
--- a/freqtrade/persistence/trade_model.py
+++ b/freqtrade/persistence/trade_model.py
@@ -196,7 +196,7 @@ class Order(_DECL_BASE):
         if filtered_orders:
             oobj = filtered_orders[0]
             oobj.update_from_ccxt_object(order)
-            Order.query.session.commit()
+            Trade.commit()
         else:
             logger.warning(f"Did not find order for {order}.")
 
@@ -1148,6 +1148,10 @@ class Trade(_DECL_BASE, LocalTrade):
     def commit():
         Trade.query.session.commit()
 
+    @staticmethod
+    def rollback():
+        Trade.query.session.rollback()
+
     @staticmethod
     def get_trades_proxy(*, pair: str = None, is_open: bool = None,
                          open_date: datetime = None, close_date: datetime = None,
diff --git a/freqtrade/rpc/api_server/deps.py b/freqtrade/rpc/api_server/deps.py
index 81c013efa..66654c0b1 100644
--- a/freqtrade/rpc/api_server/deps.py
+++ b/freqtrade/rpc/api_server/deps.py
@@ -18,9 +18,9 @@ def get_rpc_optional() -> Optional[RPC]:
 def get_rpc() -> Optional[Iterator[RPC]]:
     _rpc = get_rpc_optional()
     if _rpc:
-        Trade.query.session.rollback()
+        Trade.rollback()
         yield _rpc
-        Trade.query.session.rollback()
+        Trade.rollback()
     else:
         raise RPCException('Bot is not in the correct state')
 
diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py
index 7e431ece9..d848da546 100644
--- a/freqtrade/rpc/rpc.py
+++ b/freqtrade/rpc/rpc.py
@@ -876,7 +876,7 @@ class RPC:
             lock.active = False
             lock.lock_end_time = datetime.now(timezone.utc)
 
-        PairLock.query.session.commit()
+        Trade.commit()
 
         return self._rpc_locks()
 
diff --git a/freqtrade/rpc/telegram.py b/freqtrade/rpc/telegram.py
index 02fb5b4ee..9e0cd7d86 100644
--- a/freqtrade/rpc/telegram.py
+++ b/freqtrade/rpc/telegram.py
@@ -70,7 +70,7 @@ def authorized_only(command_handler: Callable[..., None]) -> Callable[..., Any]:
             )
             return wrapper
         # Rollback session to avoid getting data stored in a transaction.
-        Trade.query.session.rollback()
+        Trade.rollback()
         logger.debug(
             'Executing handler: %s for chat_id: %s',
             command_handler.__name__,
diff --git a/tests/test_persistence.py b/tests/test_persistence.py
index 42fcc7413..eea6d6fa1 100644
--- a/tests/test_persistence.py
+++ b/tests/test_persistence.py
@@ -2375,6 +2375,7 @@ def test_Trade_object_idem():
         'delete',
         'session',
         'commit',
+        'rollback',
         'query',
         'open_date',
         'get_best_pair',

From bfa859e6188b60fb95cf14429b2bd5189f18902d Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 6 Aug 2022 17:45:18 +0200
Subject: [PATCH 082/132] Remove unnecessary method (simplify)

---
 freqtrade/freqtradebot.py         | 6 +++---
 freqtrade/persistence/__init__.py | 2 +-
 freqtrade/persistence/models.py   | 8 --------
 tests/test_freqtradebot.py        | 2 +-
 4 files changed, 5 insertions(+), 13 deletions(-)

diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py
index 657e0bd82..390c8e8f6 100644
--- a/freqtrade/freqtradebot.py
+++ b/freqtrade/freqtradebot.py
@@ -26,7 +26,7 @@ from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
 from freqtrade.exchange.exchange import timeframe_to_next_date
 from freqtrade.misc import safe_value_fallback, safe_value_fallback2
 from freqtrade.mixins import LoggingMixin
-from freqtrade.persistence import Order, PairLocks, Trade, cleanup_db, init_db
+from freqtrade.persistence import Order, PairLocks, Trade, init_db
 from freqtrade.plugins.pairlistmanager import PairListManager
 from freqtrade.plugins.protectionmanager import ProtectionManager
 from freqtrade.resolvers import ExchangeResolver, StrategyResolver
@@ -150,7 +150,7 @@ class FreqtradeBot(LoggingMixin):
         self.check_for_open_trades()
 
         self.rpc.cleanup()
-        cleanup_db()
+        Trade.commit()
         self.exchange.close()
 
     def startup(self) -> None:
@@ -1701,7 +1701,6 @@ class FreqtradeBot(LoggingMixin):
         self.handle_order_fee(trade, order_obj, order)
 
         trade.update_trade(order_obj)
-        Trade.commit()
 
         if order.get('status') in constants.NON_OPEN_EXCHANGE_STATES:
             # If a entry order was closed, force update on stoploss on exchange
@@ -1725,6 +1724,7 @@ class FreqtradeBot(LoggingMixin):
 
             # Updating wallets when order is closed
             self.wallets.update()
+        Trade.commit()
 
         self.order_close_notify(trade, order_obj, stoploss_order, send_msg)
 
diff --git a/freqtrade/persistence/__init__.py b/freqtrade/persistence/__init__.py
index f4e7470a7..9e1a7e922 100644
--- a/freqtrade/persistence/__init__.py
+++ b/freqtrade/persistence/__init__.py
@@ -1,5 +1,5 @@
 # flake8: noqa: F401
 
-from freqtrade.persistence.models import cleanup_db, init_db
+from freqtrade.persistence.models import init_db
 from freqtrade.persistence.pairlock_middleware import PairLocks
 from freqtrade.persistence.trade_model import LocalTrade, Order, Trade
diff --git a/freqtrade/persistence/models.py b/freqtrade/persistence/models.py
index 86d2f9f9c..f0fa05343 100644
--- a/freqtrade/persistence/models.py
+++ b/freqtrade/persistence/models.py
@@ -61,11 +61,3 @@ def init_db(db_url: str) -> None:
     previous_tables = inspect(engine).get_table_names()
     _DECL_BASE.metadata.create_all(engine)
     check_migrate(engine, decl_base=_DECL_BASE, previous_tables=previous_tables)
-
-
-def cleanup_db() -> None:
-    """
-    Flushes all pending operations to disk.
-    :return: None
-    """
-    Trade.commit()
diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py
index 0b073a062..f274e2119 100644
--- a/tests/test_freqtradebot.py
+++ b/tests/test_freqtradebot.py
@@ -75,7 +75,7 @@ def test_process_calls_sendmsg(mocker, default_conf_usdt) -> None:
 
 
 def test_bot_cleanup(mocker, default_conf_usdt, caplog) -> None:
-    mock_cleanup = mocker.patch('freqtrade.freqtradebot.cleanup_db')
+    mock_cleanup = mocker.patch('freqtrade.freqtradebot.Trade.commit')
     coo_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.cancel_all_open_orders')
     freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
     freqtrade.cleanup()

From eb8bde37c16d201cae16fa9f13883924cd8e697a Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Sat, 6 Aug 2022 17:51:21 +0200
Subject: [PATCH 083/132] Add lightgbm classifier, add classifier check test,
 fix classifier bug.

---
 freqtrade/freqai/freqai_interface.py          |   2 +
 .../prediction_models/CatboostClassifier.py   |   3 -
 .../prediction_models/LightGBMClassifier.py   |  38 +++++
 freqtrade/templates/FreqaiExampleStrategy.py  |   4 +
 tests/freqai/test_freqai_interface.py         |  63 ++++++++
 tests/rpc/test_rpc_apiserver.py               |   1 +
 .../strategy/strats/freqai_test_classifier.py | 138 ++++++++++++++++++
 tests/strategy/test_strategy_loading.py       |   6 +-
 8 files changed, 249 insertions(+), 6 deletions(-)
 create mode 100644 freqtrade/freqai/prediction_models/LightGBMClassifier.py
 create mode 100644 tests/strategy/strats/freqai_test_classifier.py

diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py
index 248484b05..097ecf553 100644
--- a/freqtrade/freqai/freqai_interface.py
+++ b/freqtrade/freqai/freqai_interface.py
@@ -566,6 +566,8 @@ class IFreqaiModel(ABC):
         num_candles = self.freqai_info.get("fit_live_predictions_candles", 100)
         dk.data["labels_mean"], dk.data["labels_std"] = {}, {}
         for label in dk.label_list:
+            if self.dd.historic_predictions[dk.pair][label].dtype == object:
+                continue
             f = spy.stats.norm.fit(self.dd.historic_predictions[dk.pair][label].tail(num_candles))
             dk.data["labels_mean"][label], dk.data["labels_std"][label] = f[0], f[1]
 
diff --git a/freqtrade/freqai/prediction_models/CatboostClassifier.py b/freqtrade/freqai/prediction_models/CatboostClassifier.py
index d003744fb..ac1386eee 100644
--- a/freqtrade/freqai/prediction_models/CatboostClassifier.py
+++ b/freqtrade/freqai/prediction_models/CatboostClassifier.py
@@ -32,9 +32,6 @@ class CatboostClassifier(BaseRegressionModel):
 
         cbr = CatBoostClassifier(
             allow_writing_files=False,
-            gpu_ram_part=0.5,
-            verbose=100,
-            early_stopping_rounds=400,
             loss_function='MultiClass',
             **self.model_training_parameters,
         )
diff --git a/freqtrade/freqai/prediction_models/LightGBMClassifier.py b/freqtrade/freqai/prediction_models/LightGBMClassifier.py
new file mode 100644
index 000000000..782dbce35
--- /dev/null
+++ b/freqtrade/freqai/prediction_models/LightGBMClassifier.py
@@ -0,0 +1,38 @@
+import logging
+from typing import Any, Dict
+
+from lightgbm import LGBMClassifier
+
+from freqtrade.freqai.prediction_models.BaseRegressionModel import BaseRegressionModel
+
+
+logger = logging.getLogger(__name__)
+
+
+class LightGBMClassifier(BaseRegressionModel):
+    """
+    User created prediction model. The class needs to override three necessary
+    functions, predict(), train(), fit(). The class inherits ModelHandler which
+    has its own DataHandler where data is held, saved, loaded, and managed.
+    """
+
+    def fit(self, data_dictionary: Dict) -> Any:
+        """
+        User sets up the training and test data to fit their desired model here
+        :params:
+        :data_dictionary: the dictionary constructed by DataHandler to hold
+        all the training and test data/labels.
+        """
+
+        if self.freqai_info.get('data_split_parameters', {}).get('test_size', 0.1) == 0:
+            eval_set = None
+        else:
+            eval_set = (data_dictionary["test_features"], data_dictionary["test_labels"])
+        X = data_dictionary["train_features"]
+        y = data_dictionary["train_labels"]
+
+        model = LGBMClassifier(**self.model_training_parameters)
+
+        model.fit(X=X, y=y, eval_set=eval_set)
+
+        return model
diff --git a/freqtrade/templates/FreqaiExampleStrategy.py b/freqtrade/templates/FreqaiExampleStrategy.py
index 4f632f907..ee1602725 100644
--- a/freqtrade/templates/FreqaiExampleStrategy.py
+++ b/freqtrade/templates/FreqaiExampleStrategy.py
@@ -155,6 +155,10 @@ class FreqaiExampleStrategy(IStrategy):
                     - 1
                 )
 
+                # Classifiers are typically set up with strings as targets:
+                # df['&s-up_or_down'] = np.where( df["close"].shift(-100) >
+                #                                 df["close"], 'up', 'down')
+
                 # If user wishes to use multiple targets, they can add more by
                 # appending more columns with '&'. User should keep in mind that multi targets
                 # requires a multioutput prediction model such as
diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py
index 1f96cf6df..676f451ab 100644
--- a/tests/freqai/test_freqai_interface.py
+++ b/tests/freqai/test_freqai_interface.py
@@ -103,6 +103,69 @@ def test_train_model_in_series_Catboost(mocker, freqai_conf):
     shutil.rmtree(Path(freqai.dk.full_path))
 
 
+@pytest.mark.skipif("arm" in platform.uname()[-1], reason="no ARM for Catboost ...")
+def test_train_model_in_series_CatboostClassifier(mocker, freqai_conf):
+    freqai_conf.update({"timerange": "20180110-20180130"})
+    freqai_conf.update({"freqaimodel": "CatboostClassifier"})
+    freqai_conf.update({"strategy": "freqai_test_classifier"})
+    strategy = get_patched_freqai_strategy(mocker, freqai_conf)
+    exchange = get_patched_exchange(mocker, freqai_conf)
+    strategy.dp = DataProvider(freqai_conf, exchange)
+
+    strategy.freqai_info = freqai_conf.get("freqai", {})
+    freqai = strategy.freqai
+    freqai.live = True
+    freqai.dk = FreqaiDataKitchen(freqai_conf)
+    timerange = TimeRange.parse_timerange("20180110-20180130")
+    freqai.dd.load_all_pair_histories(timerange, freqai.dk)
+
+    freqai.dd.pair_dict = MagicMock()
+
+    data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
+    new_timerange = TimeRange.parse_timerange("20180120-20180130")
+
+    freqai.train_model_in_series(new_timerange, "ADA/BTC",
+                                 strategy, freqai.dk, data_load_timerange)
+
+    assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_model.joblib").exists()
+    assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_metadata.json").exists()
+    assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_trained_df.pkl").exists()
+    assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_svm_model.joblib").exists()
+
+    shutil.rmtree(Path(freqai.dk.full_path))
+
+
+def test_train_model_in_series_LightGBMClassifier(mocker, freqai_conf):
+    freqai_conf.update({"timerange": "20180110-20180130"})
+    freqai_conf.update({"freqaimodel": "LightGBMClassifier"})
+    freqai_conf.update({"strategy": "freqai_test_classifier"})
+    strategy = get_patched_freqai_strategy(mocker, freqai_conf)
+    exchange = get_patched_exchange(mocker, freqai_conf)
+    strategy.dp = DataProvider(freqai_conf, exchange)
+
+    strategy.freqai_info = freqai_conf.get("freqai", {})
+    freqai = strategy.freqai
+    freqai.live = True
+    freqai.dk = FreqaiDataKitchen(freqai_conf)
+    timerange = TimeRange.parse_timerange("20180110-20180130")
+    freqai.dd.load_all_pair_histories(timerange, freqai.dk)
+
+    freqai.dd.pair_dict = MagicMock()
+
+    data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
+    new_timerange = TimeRange.parse_timerange("20180120-20180130")
+
+    freqai.train_model_in_series(new_timerange, "ADA/BTC",
+                                 strategy, freqai.dk, data_load_timerange)
+
+    assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_model.joblib").exists()
+    assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_metadata.json").exists()
+    assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_trained_df.pkl").exists()
+    assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_svm_model.joblib").exists()
+
+    shutil.rmtree(Path(freqai.dk.full_path))
+
+
 def test_start_backtesting(mocker, freqai_conf):
     freqai_conf.update({"timerange": "20180120-20180130"})
     strategy = get_patched_freqai_strategy(mocker, freqai_conf)
diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py
index e6b7c4dd2..2b66ed332 100644
--- a/tests/rpc/test_rpc_apiserver.py
+++ b/tests/rpc/test_rpc_apiserver.py
@@ -1403,6 +1403,7 @@ def test_api_strategies(botclient):
         'StrategyTestV2',
         'StrategyTestV3',
         'StrategyTestV3Futures',
+        'freqai_test_classifier',
         'freqai_test_multimodel_strat',
         'freqai_test_strat'
     ]}
diff --git a/tests/strategy/strats/freqai_test_classifier.py b/tests/strategy/strats/freqai_test_classifier.py
new file mode 100644
index 000000000..c333ac818
--- /dev/null
+++ b/tests/strategy/strats/freqai_test_classifier.py
@@ -0,0 +1,138 @@
+import logging
+from functools import reduce
+
+import pandas as pd
+import talib.abstract as ta
+from pandas import DataFrame
+import numpy as np
+from freqtrade.strategy import DecimalParameter, IntParameter, IStrategy, merge_informative_pair
+
+
+logger = logging.getLogger(__name__)
+
+
+class freqai_test_classifier(IStrategy):
+    """
+    Test strategy - used for testing freqAI functionalities.
+    DO not use in production.
+    """
+
+    minimal_roi = {"0": 0.1, "240": -1}
+
+    plot_config = {
+        "main_plot": {},
+        "subplots": {
+            "prediction": {"prediction": {"color": "blue"}},
+            "target_roi": {
+                "target_roi": {"color": "brown"},
+            },
+            "do_predict": {
+                "do_predict": {"color": "brown"},
+            },
+        },
+    }
+
+    process_only_new_candles = True
+    stoploss = -0.05
+    use_exit_signal = True
+    startup_candle_count: int = 300
+    can_short = False
+
+    linear_roi_offset = DecimalParameter(
+        0.00, 0.02, default=0.005, space="sell", optimize=False, load=True
+    )
+    max_roi_time_long = IntParameter(0, 800, default=400, space="sell", optimize=False, load=True)
+
+    def informative_pairs(self):
+        whitelist_pairs = self.dp.current_whitelist()
+        corr_pairs = self.config["freqai"]["feature_parameters"]["include_corr_pairlist"]
+        informative_pairs = []
+        for tf in self.config["freqai"]["feature_parameters"]["include_timeframes"]:
+            for pair in whitelist_pairs:
+                informative_pairs.append((pair, tf))
+            for pair in corr_pairs:
+                if pair in whitelist_pairs:
+                    continue  # avoid duplication
+                informative_pairs.append((pair, tf))
+        return informative_pairs
+
+    def populate_any_indicators(
+        self, pair, df, tf, informative=None, set_generalized_indicators=False
+    ):
+
+        coin = pair.split('/')[0]
+
+        with self.freqai.lock:
+            if informative is None:
+                informative = self.dp.get_pair_dataframe(pair, tf)
+
+            # first loop is automatically duplicating indicators for time periods
+            for t in self.freqai_info["feature_parameters"]["indicator_periods_candles"]:
+
+                t = int(t)
+                informative[f"%-{coin}rsi-period_{t}"] = ta.RSI(informative, timeperiod=t)
+                informative[f"%-{coin}mfi-period_{t}"] = ta.MFI(informative, timeperiod=t)
+                informative[f"%-{coin}adx-period_{t}"] = ta.ADX(informative, window=t)
+
+            informative[f"%-{coin}pct-change"] = informative["close"].pct_change()
+            informative[f"%-{coin}raw_volume"] = informative["volume"]
+            informative[f"%-{coin}raw_price"] = informative["close"]
+
+            indicators = [col for col in informative if col.startswith("%")]
+            # This loop duplicates and shifts all indicators to add a sense of recency to data
+            for n in range(self.freqai_info["feature_parameters"]["include_shifted_candles"] + 1):
+                if n == 0:
+                    continue
+                informative_shift = informative[indicators].shift(n)
+                informative_shift = informative_shift.add_suffix("_shift-" + str(n))
+                informative = pd.concat((informative, informative_shift), axis=1)
+
+            df = merge_informative_pair(df, informative, self.config["timeframe"], tf, ffill=True)
+            skip_columns = [
+                (s + "_" + tf) for s in ["date", "open", "high", "low", "close", "volume"]
+            ]
+            df = df.drop(columns=skip_columns)
+
+            # Add generalized indicators here (because in live, it will call this
+            # function to populate indicators during training). Notice how we ensure not to
+            # add them multiple times
+            if set_generalized_indicators:
+                df["%-day_of_week"] = (df["date"].dt.dayofweek + 1) / 7
+                df["%-hour_of_day"] = (df["date"].dt.hour + 1) / 25
+
+                # user adds targets here by prepending them with &- (see convention below)
+                # If user wishes to use multiple targets, a multioutput prediction model
+                # needs to be used such as templates/CatboostPredictionMultiModel.py
+            df['&s-up_or_down'] = np.where(df["close"].shift(-100) > df["close"], 'up', 'down')
+
+        return df
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+
+        self.freqai_info = self.config["freqai"]
+
+        dataframe = self.freqai.start(dataframe, metadata, self)
+
+        return dataframe
+
+    def populate_entry_trend(self, df: DataFrame, metadata: dict) -> DataFrame:
+
+        enter_long_conditions = [df['&s-up_or_down'] == 'up']
+
+        if enter_long_conditions:
+            df.loc[
+                reduce(lambda x, y: x & y, enter_long_conditions), ["enter_long", "enter_tag"]
+            ] = (1, "long")
+
+        enter_short_conditions = [df['&s-up_or_down'] == 'down']
+
+        if enter_short_conditions:
+            df.loc[
+                reduce(lambda x, y: x & y, enter_short_conditions), ["enter_short", "enter_tag"]
+            ] = (1, "short")
+
+        return df
+
+    def populate_exit_trend(self, df: DataFrame, metadata: dict) -> DataFrame:
+
+        return df
diff --git a/tests/strategy/test_strategy_loading.py b/tests/strategy/test_strategy_loading.py
index aaad26e5b..5b6f15d11 100644
--- a/tests/strategy/test_strategy_loading.py
+++ b/tests/strategy/test_strategy_loading.py
@@ -34,7 +34,7 @@ def test_search_all_strategies_no_failed():
     directory = Path(__file__).parent / "strats"
     strategies = StrategyResolver.search_all_objects(directory, enum_failed=False)
     assert isinstance(strategies, list)
-    assert len(strategies) == 8
+    assert len(strategies) == 9
     assert isinstance(strategies[0], dict)
 
 
@@ -42,10 +42,10 @@ def test_search_all_strategies_with_failed():
     directory = Path(__file__).parent / "strats"
     strategies = StrategyResolver.search_all_objects(directory, enum_failed=True)
     assert isinstance(strategies, list)
-    assert len(strategies) == 9
+    assert len(strategies) == 10
     # with enum_failed=True search_all_objects() shall find 2 good strategies
     # and 1 which fails to load
-    assert len([x for x in strategies if x['class'] is not None]) == 8
+    assert len([x for x in strategies if x['class'] is not None]) == 9
     assert len([x for x in strategies if x['class'] is None]) == 1
 
 

From 78e129034ee64cc60e2975a70338767d7206dc73 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 6 Aug 2022 17:59:08 +0200
Subject: [PATCH 084/132] Update docs to specify trading limit behaviour

closes #7183
---
 docs/backtesting.md | 20 +++++++++++++++++++-
 1 file changed, 19 insertions(+), 1 deletion(-)

diff --git a/docs/backtesting.md b/docs/backtesting.md
index 50fc96923..a7baf6932 100644
--- a/docs/backtesting.md
+++ b/docs/backtesting.md
@@ -514,6 +514,7 @@ You can then load the trades to perform further analysis as shown in the [data a
 
 Since backtesting lacks some detailed information about what happens within a candle, it needs to take a few assumptions:
 
+- Exchange [trading limits](#trading-limits-in-backtesting) are respected
 - Buys happen at open-price
 - All orders are filled at the requested price (no slippage, no unfilled orders)
 - Exit-signal exits happen at open-price of the consecutive candle
@@ -543,7 +544,24 @@ Also, keep in mind that past results don't guarantee future success.
 
 In addition to the above assumptions, strategy authors should carefully read the [Common Mistakes](strategy-customization.md#common-mistakes-when-developing-strategies) section, to avoid using data in backtesting which is not available in real market conditions.
 
-### Improved backtest accuracy
+### Trading limits in backtesting
+
+Exchanges have certain trading limits, like minimum base currency, or minimum stake (quote) currency.
+These limits are usually listed in the exchange documentation as "trading rules" or similar.
+
+Backtesting (as well as live and dry-run) does honor these limits, and will ensure that a stoploss can be placed below this value - so the value will be slightly higher than what the exchange specifies.
+Freqtrade has however no information about historic limits.
+
+This can lead to situations where trading-limits are inflated by using a historic price, resulting in minimum amounts > 50$.
+
+For example:
+
+BTC minimum tradable amount is 0.001.
+BTC trades at 22.000\$ today (0.001 BTC is related to this) - but the backtesting period includes prices as high as 50.000\$.
+Today's minimum would be `0.001 * 22_000` - or 22\$.  
+However the limit could also be 50$ - based on `0.001 * 50_000` in some historic setting.
+
+## Improved backtest accuracy
 
 One big limitation of backtesting is it's inability to know how prices moved intra-candle (was high before close, or viceversa?).
 So assuming you run backtesting with a 1h timeframe, there will be 4 prices for that candle (Open, High, Low, Close).

From 82aecc81f393e98b86115e9bdfa46dac1a143fad Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Tue, 2 Aug 2022 19:53:10 +0200
Subject: [PATCH 085/132] Accept parameters to forceexit

---
 freqtrade/rpc/api_server/api_schemas.py |  1 +
 freqtrade/rpc/api_server/api_v1.py      |  2 +-
 freqtrade/rpc/rpc.py                    | 22 +++++++++++++++++-----
 scripts/rest_client.py                  | 10 ++++++++--
 4 files changed, 27 insertions(+), 8 deletions(-)

diff --git a/freqtrade/rpc/api_server/api_schemas.py b/freqtrade/rpc/api_server/api_schemas.py
index 333f2fe6e..d2a584136 100644
--- a/freqtrade/rpc/api_server/api_schemas.py
+++ b/freqtrade/rpc/api_server/api_schemas.py
@@ -330,6 +330,7 @@ class ForceEnterPayload(BaseModel):
 class ForceExitPayload(BaseModel):
     tradeid: str
     ordertype: Optional[OrderTypeValues]
+    amount: Optional[float]
 
 
 class BlacklistPayload(BaseModel):
diff --git a/freqtrade/rpc/api_server/api_v1.py b/freqtrade/rpc/api_server/api_v1.py
index b3506409d..29e4fb75a 100644
--- a/freqtrade/rpc/api_server/api_v1.py
+++ b/freqtrade/rpc/api_server/api_v1.py
@@ -161,7 +161,7 @@ def force_entry(payload: ForceEnterPayload, rpc: RPC = Depends(get_rpc)):
 @router.post('/forcesell', response_model=ResultMsg, tags=['trading'])
 def forceexit(payload: ForceExitPayload, rpc: RPC = Depends(get_rpc)):
     ordertype = payload.ordertype.value if payload.ordertype else None
-    return rpc._rpc_force_exit(payload.tradeid, ordertype)
+    return rpc._rpc_force_exit(payload.tradeid, ordertype, amount=payload.amount)
 
 
 @router.get('/blacklist', response_model=BlacklistResponse, tags=['info', 'pairlist'])
diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py
index d848da546..340adea43 100644
--- a/freqtrade/rpc/rpc.py
+++ b/freqtrade/rpc/rpc.py
@@ -660,12 +660,15 @@ class RPC:
 
         return {'status': 'No more buy will occur from now. Run /reload_config to reset.'}
 
-    def _rpc_force_exit(self, trade_id: str, ordertype: Optional[str] = None) -> Dict[str, str]:
+    def _rpc_force_exit(self, trade_id: str, ordertype: Optional[str] = None, *,
+                        amount: Optional[float]) -> Dict[str, str]:
         """
         Handler for forceexit <id>.
         Sells the given trade at current price
         """
-        def _exec_force_exit(trade: Trade) -> None:
+
+        def _exec_force_exit(trade: Trade, ordertype: Optional[str],
+                             _amount: Optional[float] = None) -> None:
             # Check if there is there is an open order
             fully_canceled = False
             if trade.open_order_id:
@@ -686,10 +689,19 @@ class RPC:
                 exit_check = ExitCheckTuple(exit_type=ExitType.FORCE_EXIT)
                 order_type = ordertype or self._freqtrade.strategy.order_types.get(
                     "force_exit", self._freqtrade.strategy.order_types["exit"])
+                sub_amount: float = None
+                if _amount and _amount < trade.amount:
+                    # Partial exit ...
+                    min_exit_stake = self._freqtrade.exchange.get_min_pair_stake_amount(
+                        trade.pair, current_rate, trade.stop_loss_pct)
+                    remaining = (trade.amount - _amount) * current_rate
+                    if remaining < min_exit_stake:
+                        raise RPCException(f'Remaining amount of {remaining} would be too small.')
+                    sub_amount = _amount
 
                 self._freqtrade.execute_trade_exit(
-                    trade, current_rate, exit_check, ordertype=order_type)
-        # ---- EOF def _exec_forcesell ----
+                    trade, current_rate, exit_check, ordertype=order_type,
+                    sub_trade_amt=sub_amount)
 
         if self._freqtrade.state != State.RUNNING:
             raise RPCException('trader is not running')
@@ -711,7 +723,7 @@ class RPC:
                 logger.warning('force_exit: Invalid argument received')
                 raise RPCException('invalid argument')
 
-            _exec_force_exit(trade)
+            _exec_force_exit(trade, ordertype, amount)
             Trade.commit()
             self._freqtrade.wallets.update()
             return {'result': f'Created sell order for trade {trade_id}.'}
diff --git a/scripts/rest_client.py b/scripts/rest_client.py
index e5d358c98..989e6a50d 100755
--- a/scripts/rest_client.py
+++ b/scripts/rest_client.py
@@ -275,14 +275,20 @@ class FtRestClient():
                 }
         return self._post("forceenter", data=data)
 
-    def forceexit(self, tradeid):
+    def forceexit(self, tradeid, ordertype=None, amount=None):
         """Force-exit a trade.
 
         :param tradeid: Id of the trade (can be received via status command)
+        :param ordertype: Order type to use (must be market or limit)
+        :param amount: Amount to sell. Full sell if not given
         :return: json object
         """
 
-        return self._post("forceexit", data={"tradeid": tradeid})
+        return self._post("forceexit", data={
+            "tradeid": tradeid,
+            "ordertype": ordertype,
+            "amount": amount,
+            })
 
     def strategies(self):
         """Lists available strategies

From daf015d0077736ba94c0b3cc3302942c425a9357 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Tue, 2 Aug 2022 19:54:37 +0200
Subject: [PATCH 086/132] extract nested force_exit function to private
 instance function

---
 freqtrade/rpc/rpc.py | 76 ++++++++++++++++++++++----------------------
 1 file changed, 38 insertions(+), 38 deletions(-)

diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py
index 340adea43..36327f091 100644
--- a/freqtrade/rpc/rpc.py
+++ b/freqtrade/rpc/rpc.py
@@ -660,6 +660,42 @@ class RPC:
 
         return {'status': 'No more buy will occur from now. Run /reload_config to reset.'}
 
+    def __exec_force_exit(self, trade: Trade, ordertype: Optional[str],
+                          _amount: Optional[float] = None) -> None:
+        # Check if there is there is an open order
+        fully_canceled = False
+        if trade.open_order_id:
+            order = self._freqtrade.exchange.fetch_order(trade.open_order_id, trade.pair)
+
+            if order['side'] == trade.entry_side:
+                fully_canceled = self._freqtrade.handle_cancel_enter(
+                    trade, order, CANCEL_REASON['FORCE_EXIT'])
+
+            if order['side'] == trade.exit_side:
+                # Cancel order - so it is placed anew with a fresh price.
+                self._freqtrade.handle_cancel_exit(trade, order, CANCEL_REASON['FORCE_EXIT'])
+
+        if not fully_canceled:
+            # Get current rate and execute sell
+            current_rate = self._freqtrade.exchange.get_rate(
+                trade.pair, side='exit', is_short=trade.is_short, refresh=True)
+            exit_check = ExitCheckTuple(exit_type=ExitType.FORCE_EXIT)
+            order_type = ordertype or self._freqtrade.strategy.order_types.get(
+                "force_exit", self._freqtrade.strategy.order_types["exit"])
+            sub_amount: float = None
+            if _amount and _amount < trade.amount:
+                # Partial exit ...
+                min_exit_stake = self._freqtrade.exchange.get_min_pair_stake_amount(
+                    trade.pair, current_rate, trade.stop_loss_pct)
+                remaining = (trade.amount - _amount) * current_rate
+                if remaining < min_exit_stake:
+                    raise RPCException(f'Remaining amount of {remaining} would be too small.')
+                sub_amount = _amount
+
+            self._freqtrade.execute_trade_exit(
+                trade, current_rate, exit_check, ordertype=order_type,
+                sub_trade_amt=sub_amount)
+
     def _rpc_force_exit(self, trade_id: str, ordertype: Optional[str] = None, *,
                         amount: Optional[float]) -> Dict[str, str]:
         """
@@ -667,42 +703,6 @@ class RPC:
         Sells the given trade at current price
         """
 
-        def _exec_force_exit(trade: Trade, ordertype: Optional[str],
-                             _amount: Optional[float] = None) -> None:
-            # Check if there is there is an open order
-            fully_canceled = False
-            if trade.open_order_id:
-                order = self._freqtrade.exchange.fetch_order(trade.open_order_id, trade.pair)
-
-                if order['side'] == trade.entry_side:
-                    fully_canceled = self._freqtrade.handle_cancel_enter(
-                        trade, order, CANCEL_REASON['FORCE_EXIT'])
-
-                if order['side'] == trade.exit_side:
-                    # Cancel order - so it is placed anew with a fresh price.
-                    self._freqtrade.handle_cancel_exit(trade, order, CANCEL_REASON['FORCE_EXIT'])
-
-            if not fully_canceled:
-                # Get current rate and execute sell
-                current_rate = self._freqtrade.exchange.get_rate(
-                    trade.pair, side='exit', is_short=trade.is_short, refresh=True)
-                exit_check = ExitCheckTuple(exit_type=ExitType.FORCE_EXIT)
-                order_type = ordertype or self._freqtrade.strategy.order_types.get(
-                    "force_exit", self._freqtrade.strategy.order_types["exit"])
-                sub_amount: float = None
-                if _amount and _amount < trade.amount:
-                    # Partial exit ...
-                    min_exit_stake = self._freqtrade.exchange.get_min_pair_stake_amount(
-                        trade.pair, current_rate, trade.stop_loss_pct)
-                    remaining = (trade.amount - _amount) * current_rate
-                    if remaining < min_exit_stake:
-                        raise RPCException(f'Remaining amount of {remaining} would be too small.')
-                    sub_amount = _amount
-
-                self._freqtrade.execute_trade_exit(
-                    trade, current_rate, exit_check, ordertype=order_type,
-                    sub_trade_amt=sub_amount)
-
         if self._freqtrade.state != State.RUNNING:
             raise RPCException('trader is not running')
 
@@ -710,7 +710,7 @@ class RPC:
             if trade_id == 'all':
                 # Execute sell for all open orders
                 for trade in Trade.get_open_trades():
-                    _exec_force_exit(trade)
+                    self.__exec_force_exit(trade)
                 Trade.commit()
                 self._freqtrade.wallets.update()
                 return {'result': 'Created sell orders for all open trades.'}
@@ -723,7 +723,7 @@ class RPC:
                 logger.warning('force_exit: Invalid argument received')
                 raise RPCException('invalid argument')
 
-            _exec_force_exit(trade, ordertype, amount)
+            self.__exec_force_exit(trade, ordertype, amount)
             Trade.commit()
             self._freqtrade.wallets.update()
             return {'result': f'Created sell order for trade {trade_id}.'}

From eff8cd7ecbf2da8aea10a363a98aafa5f0bec480 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Tue, 2 Aug 2022 20:15:47 +0200
Subject: [PATCH 087/132] Add leverage to force_entry

---
 freqtrade/freqtradebot.py               | 27 +++++++++++++++----------
 freqtrade/rpc/api_server/api_schemas.py |  1 +
 freqtrade/rpc/api_server/api_v1.py      | 10 ++++-----
 freqtrade/rpc/rpc.py                    |  4 +++-
 4 files changed, 25 insertions(+), 17 deletions(-)

diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py
index 390c8e8f6..0dbeb2e44 100644
--- a/freqtrade/freqtradebot.py
+++ b/freqtrade/freqtradebot.py
@@ -624,7 +624,8 @@ class FreqtradeBot(LoggingMixin):
         ordertype: Optional[str] = None,
         enter_tag: Optional[str] = None,
         trade: Optional[Trade] = None,
-        order_adjust: bool = False
+        order_adjust: bool = False,
+        leverage_: Optional[float] = None,
     ) -> bool:
         """
         Executes a limit buy for the given pair
@@ -640,7 +641,7 @@ class FreqtradeBot(LoggingMixin):
         pos_adjust = trade is not None
 
         enter_limit_requested, stake_amount, leverage = self.get_valid_enter_price_and_stake(
-            pair, price, stake_amount, trade_side, enter_tag, trade, order_adjust)
+            pair, price, stake_amount, trade_side, enter_tag, trade, order_adjust, leverage_)
 
         if not stake_amount:
             return False
@@ -787,6 +788,7 @@ class FreqtradeBot(LoggingMixin):
         entry_tag: Optional[str],
         trade: Optional[Trade],
         order_adjust: bool,
+        leverage_: Optional[float],
     ) -> Tuple[float, float, float]:
 
         if price:
@@ -809,16 +811,19 @@ class FreqtradeBot(LoggingMixin):
         if not enter_limit_requested:
             raise PricingError('Could not determine entry price.')
 
-        if trade is None:
+        if self.trading_mode != TradingMode.SPOT and trade is None:
             max_leverage = self.exchange.get_max_leverage(pair, stake_amount)
-            leverage = strategy_safe_wrapper(self.strategy.leverage, default_retval=1.0)(
-                pair=pair,
-                current_time=datetime.now(timezone.utc),
-                current_rate=enter_limit_requested,
-                proposed_leverage=1.0,
-                max_leverage=max_leverage,
-                side=trade_side, entry_tag=entry_tag,
-            ) if self.trading_mode != TradingMode.SPOT else 1.0
+            if leverage_:
+                leverage = leverage_
+            else:
+                leverage = strategy_safe_wrapper(self.strategy.leverage, default_retval=1.0)(
+                    pair=pair,
+                    current_time=datetime.now(timezone.utc),
+                    current_rate=enter_limit_requested,
+                    proposed_leverage=1.0,
+                    max_leverage=max_leverage,
+                    side=trade_side, entry_tag=entry_tag,
+                )
             # Cap leverage between 1.0 and max_leverage.
             leverage = min(max(leverage, 1.0), max_leverage)
         else:
diff --git a/freqtrade/rpc/api_server/api_schemas.py b/freqtrade/rpc/api_server/api_schemas.py
index d2a584136..1641df384 100644
--- a/freqtrade/rpc/api_server/api_schemas.py
+++ b/freqtrade/rpc/api_server/api_schemas.py
@@ -325,6 +325,7 @@ class ForceEnterPayload(BaseModel):
     ordertype: Optional[OrderTypeValues]
     stakeamount: Optional[float]
     entry_tag: Optional[str]
+    leverage: Optional[float]
 
 
 class ForceExitPayload(BaseModel):
diff --git a/freqtrade/rpc/api_server/api_v1.py b/freqtrade/rpc/api_server/api_v1.py
index 29e4fb75a..54d7baf38 100644
--- a/freqtrade/rpc/api_server/api_v1.py
+++ b/freqtrade/rpc/api_server/api_v1.py
@@ -37,7 +37,8 @@ logger = logging.getLogger(__name__)
 # 2.14: Add entry/exit orders to trade response
 # 2.15: Add backtest history endpoints
 # 2.16: Additional daily metrics
-API_VERSION = 2.16
+# 2.16: Forceentry - leverage, partial force_exit
+API_VERSION = 2.17
 
 # Public API, requires no auth.
 router_public = APIRouter()
@@ -142,12 +143,11 @@ def show_config(rpc: Optional[RPC] = Depends(get_rpc_optional), config=Depends(g
 @router.post('/forcebuy', response_model=ForceEnterResponse, tags=['trading'])
 def force_entry(payload: ForceEnterPayload, rpc: RPC = Depends(get_rpc)):
     ordertype = payload.ordertype.value if payload.ordertype else None
-    stake_amount = payload.stakeamount if payload.stakeamount else None
-    entry_tag = payload.entry_tag if payload.entry_tag else 'force_entry'
 
     trade = rpc._rpc_force_entry(payload.pair, payload.price, order_side=payload.side,
-                                 order_type=ordertype, stake_amount=stake_amount,
-                                 enter_tag=entry_tag)
+                                 order_type=ordertype, stake_amount=payload.stakeamount,
+                                 enter_tag=payload.entry_tag or 'force_entry',
+                                 leverage=payload.leverage)
 
     if trade:
         return ForceEnterResponse.parse_obj(trade.to_json())
diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py
index 36327f091..22effb849 100644
--- a/freqtrade/rpc/rpc.py
+++ b/freqtrade/rpc/rpc.py
@@ -732,7 +732,8 @@ class RPC:
                          order_type: Optional[str] = None,
                          order_side: SignalDirection = SignalDirection.LONG,
                          stake_amount: Optional[float] = None,
-                         enter_tag: Optional[str] = 'force_entry') -> Optional[Trade]:
+                         enter_tag: Optional[str] = 'force_entry',
+                         leverage: Optional[float] = None) -> Optional[Trade]:
         """
         Handler for forcebuy <asset> <price>
         Buys a pair trade at the given or current price
@@ -774,6 +775,7 @@ class RPC:
                                          ordertype=order_type, trade=trade,
                                          is_short=is_short,
                                          enter_tag=enter_tag,
+                                         leverage_=leverage,
                                          ):
             Trade.commit()
             trade = Trade.get_trades([Trade.is_open.is_(True), Trade.pair == pair]).first()

From d1998f7ed0bf2f58daf439d367fa25b7319f3aa1 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Tue, 2 Aug 2022 20:16:01 +0200
Subject: [PATCH 088/132] Fix forceexit calling

---
 freqtrade/rpc/rpc.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py
index 22effb849..7694b2414 100644
--- a/freqtrade/rpc/rpc.py
+++ b/freqtrade/rpc/rpc.py
@@ -697,7 +697,7 @@ class RPC:
                 sub_trade_amt=sub_amount)
 
     def _rpc_force_exit(self, trade_id: str, ordertype: Optional[str] = None, *,
-                        amount: Optional[float]) -> Dict[str, str]:
+                        amount: Optional[float] = None) -> Dict[str, str]:
         """
         Handler for forceexit <id>.
         Sells the given trade at current price
@@ -710,7 +710,7 @@ class RPC:
             if trade_id == 'all':
                 # Execute sell for all open orders
                 for trade in Trade.get_open_trades():
-                    self.__exec_force_exit(trade)
+                    self.__exec_force_exit(trade, ordertype)
                 Trade.commit()
                 self._freqtrade.wallets.update()
                 return {'result': 'Created sell orders for all open trades.'}

From d3780b931c27a6cdede7d58d5814de7d1aa8ac05 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Tue, 2 Aug 2022 20:21:02 +0200
Subject: [PATCH 089/132] Add test passing  leverage to execute_entry

---
 tests/test_freqtradebot.py | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py
index f274e2119..fb5fd38d8 100644
--- a/tests/test_freqtradebot.py
+++ b/tests/test_freqtradebot.py
@@ -973,6 +973,14 @@ def test_execute_entry(mocker, default_conf_usdt, fee, limit_order,
     trade.is_short = is_short
     assert pytest.approx(trade.stake_amount) == 500
 
+    order['id'] = '55673'
+
+    freqtrade.strategy.leverage.reset_mock()
+    assert freqtrade.execute_entry(pair, 200, leverage_=3)
+    assert freqtrade.strategy.leverage.call_count == 0
+    trade = Trade.query.all()[10]
+    assert trade.leverage == 1 if trading_mode == 'spot' else 3
+
 
 @pytest.mark.parametrize("is_short", [False, True])
 def test_execute_entry_confirm_error(mocker, default_conf_usdt, fee, limit_order, is_short) -> None:

From 6ded2d5b7c442a5fd69d56ee63361df4f4a3db7e Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Thu, 4 Aug 2022 16:28:36 +0200
Subject: [PATCH 090/132] Improve forceexit API test

---
 freqtrade/rpc/rpc.py            |  2 +-
 tests/conftest_trades.py        |  6 ++++--
 tests/rpc/test_rpc_apiserver.py | 23 +++++++++++++++++++----
 3 files changed, 24 insertions(+), 7 deletions(-)

diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py
index 7694b2414..cda4fdc22 100644
--- a/freqtrade/rpc/rpc.py
+++ b/freqtrade/rpc/rpc.py
@@ -682,7 +682,7 @@ class RPC:
             exit_check = ExitCheckTuple(exit_type=ExitType.FORCE_EXIT)
             order_type = ordertype or self._freqtrade.strategy.order_types.get(
                 "force_exit", self._freqtrade.strategy.order_types["exit"])
-            sub_amount: float = None
+            sub_amount: Optional[float] = None
             if _amount and _amount < trade.amount:
                 # Partial exit ...
                 min_exit_stake = self._freqtrade.exchange.get_min_pair_stake_amount(
diff --git a/tests/conftest_trades.py b/tests/conftest_trades.py
index 1a8cf3183..9642435e5 100644
--- a/tests/conftest_trades.py
+++ b/tests/conftest_trades.py
@@ -214,7 +214,8 @@ def mock_trade_4(fee, is_short: bool):
         open_order_id=f'prod_buy_{direc(is_short)}_12345',
         strategy='StrategyTestV3',
         timeframe=5,
-        is_short=is_short
+        is_short=is_short,
+        stop_loss_pct=0.10
     )
     o = Order.parse_from_ccxt_object(mock_order_4(is_short), 'ETC/BTC', entry_side(is_short))
     trade.orders.append(o)
@@ -270,7 +271,8 @@ def mock_trade_5(fee, is_short: bool):
         enter_tag='TEST1',
         stoploss_order_id=f'prod_stoploss_{direc(is_short)}_3455',
         timeframe=5,
-        is_short=is_short
+        is_short=is_short,
+        stop_loss_pct=0.10,
     )
     o = Order.parse_from_ccxt_object(mock_order_5(is_short), 'XRP/BTC', entry_side(is_short))
     trade.orders.append(o)
diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py
index b7161e680..d2d9a73d5 100644
--- a/tests/rpc/test_rpc_apiserver.py
+++ b/tests/rpc/test_rpc_apiserver.py
@@ -1202,7 +1202,7 @@ def test_api_forceexit(botclient, mocker, ticker, fee, markets):
         fetch_ticker=ticker,
         get_fee=fee,
         markets=PropertyMock(return_value=markets),
-        _is_dry_limit_order_filled=MagicMock(return_value=False),
+        _is_dry_limit_order_filled=MagicMock(return_value=True),
     )
     patch_get_signal(ftbot)
 
@@ -1212,12 +1212,27 @@ def test_api_forceexit(botclient, mocker, ticker, fee, markets):
     assert rc.json() == {"error": "Error querying /api/v1/forceexit: invalid argument"}
     Trade.query.session.rollback()
 
-    ftbot.enter_positions()
+    create_mock_trades(fee)
+    trade = Trade.get_trades([Trade.id == 5]).first()
+    assert pytest.approx(trade.amount) == 123
+    rc = client_post(client, f"{BASE_URI}/forceexit",
+                     data='{"tradeid": "5", "ordertype": "market", "amount": 23}')
+    assert_response(rc)
+    assert rc.json() == {'result': 'Created sell order for trade 5.'}
+    Trade.query.session.rollback()
+
+    trade = Trade.get_trades([Trade.id == 5]).first()
+    assert pytest.approx(trade.amount) == 100
+    assert trade.is_open is True
 
     rc = client_post(client, f"{BASE_URI}/forceexit",
-                     data='{"tradeid": "1"}')
+                     data='{"tradeid": "5"}')
     assert_response(rc)
-    assert rc.json() == {'result': 'Created sell order for trade 1.'}
+    assert rc.json() == {'result': 'Created sell order for trade 5.'}
+    Trade.query.session.rollback()
+
+    trade = Trade.get_trades([Trade.id == 5]).first()
+    assert trade.is_open is False
 
 
 def test_api_pair_candles(botclient, ohlcv_history):

From 5182f755f1aa67bae976c5314e0a3fb2ab970662 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sun, 7 Aug 2022 10:08:35 +0200
Subject: [PATCH 091/132] Add debug setup documentation

closes #7167
---
 docs/developer.md | 30 ++++++++++++++++++++++++++++++
 1 file changed, 30 insertions(+)

diff --git a/docs/developer.md b/docs/developer.md
index 0209d220a..aca4ce4ed 100644
--- a/docs/developer.md
+++ b/docs/developer.md
@@ -68,6 +68,36 @@ def test_method_to_test(caplog):
 
 ```
 
+### Debug configuration
+
+To debug freqtrade, we recommend VSCode with the following launch configuration (located in `.vscode/launch.json`).
+Details will obviously vary between setups - but this should work to get you started.
+
+``` json
+{
+    "name": "freqtrade trade",
+    "type": "python",
+    "request": "launch",
+    "module": "freqtrade",
+    "console": "integratedTerminal",
+    "args": [
+        "trade",
+        // Optional:
+        // "--userdir", "user_data",
+        "--strategy", 
+        "MyAwesomeStrategy",
+    ]
+},
+```
+
+Command line arguments can be added in the `"args"` array.
+This method can also be used to debug a strategy, by setting the breakpoints within the strategy.
+
+A similar setup can also be taken for Pycharm - using `freqtrade` as module name, and setting the command line arguments as "parameters".
+
+!!! Note "Startup directory"
+    This assumes that you have the repository checked out, and the editor is started at the repository root level (so setup.py is at the top level of your repository).
+
 ## ErrorHandling
 
 Freqtrade Exceptions all inherit from `FreqtradeException`.

From 0b2104fc7a13e8034e051cf456dce25b30097f4a Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sun, 7 Aug 2022 10:13:22 +0200
Subject: [PATCH 092/132] Properly increment the api version

---
 freqtrade/rpc/api_server/api_v1.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/freqtrade/rpc/api_server/api_v1.py b/freqtrade/rpc/api_server/api_v1.py
index 54d7baf38..e0fef7be8 100644
--- a/freqtrade/rpc/api_server/api_v1.py
+++ b/freqtrade/rpc/api_server/api_v1.py
@@ -37,7 +37,7 @@ logger = logging.getLogger(__name__)
 # 2.14: Add entry/exit orders to trade response
 # 2.15: Add backtest history endpoints
 # 2.16: Additional daily metrics
-# 2.16: Forceentry - leverage, partial force_exit
+# 2.17: Forceentry - leverage, partial force_exit
 API_VERSION = 2.17
 
 # Public API, requires no auth.

From e48e82232d67695d412ba89df7dcea725a991f3d Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sun, 7 Aug 2022 10:42:56 +0200
Subject: [PATCH 093/132] Force response API to js to fix faulty system configs

closes #7147
---
 freqtrade/rpc/api_server/web_ui.py | 7 ++++++-
 tests/rpc/test_rpc_apiserver.py    | 3 +++
 2 files changed, 9 insertions(+), 1 deletion(-)

diff --git a/freqtrade/rpc/api_server/web_ui.py b/freqtrade/rpc/api_server/web_ui.py
index b04269c61..e1a277b30 100644
--- a/freqtrade/rpc/api_server/web_ui.py
+++ b/freqtrade/rpc/api_server/web_ui.py
@@ -1,4 +1,5 @@
 from pathlib import Path
+from typing import Optional
 
 from fastapi import APIRouter
 from fastapi.exceptions import HTTPException
@@ -50,8 +51,12 @@ async def index_html(rest_of_path: str):
     filename = uibase / rest_of_path
     # It's security relevant to check "relative_to".
     # Without this, Directory-traversal is possible.
+    media_type: Optional[str] = None
+    if filename.suffix == '.js':
+        # Force text/javascript for .js files - Circumvent faulty system configuration
+        media_type = 'application/javascript'
     if filename.is_file() and is_relative_to(filename, uibase):
-        return FileResponse(str(filename))
+        return FileResponse(str(filename), media_type=media_type)
 
     index_file = uibase / 'index.html'
     if not index_file.is_file():
diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py
index b7161e680..6bbf3cff6 100644
--- a/tests/rpc/test_rpc_apiserver.py
+++ b/tests/rpc/test_rpc_apiserver.py
@@ -109,6 +109,9 @@ def test_api_ui_fallback(botclient, mocker):
     rc = client_get(client, "/something")
     assert rc.status_code == 200
 
+    rc = client_get(client, "/something.js")
+    assert rc.status_code == 200
+
     # Test directory traversal without mock
     rc = client_get(client, '%2F%2F%2Fetc/passwd')
     assert rc.status_code == 200

From 67c722c9c8c932f1b712d2470f0aa35e0d1007b9 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Sun, 7 Aug 2022 14:48:39 +0200
Subject: [PATCH 094/132] fix asyncio bug

---
 freqtrade/exchange/exchange.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py
index 79bc769e6..f4959db3b 100644
--- a/freqtrade/exchange/exchange.py
+++ b/freqtrade/exchange/exchange.py
@@ -482,6 +482,7 @@ class Exchange:
 
     def reload_markets(self) -> None:
         """Reload markets both sync and async if refresh interval has passed """
+        asyncio.set_event_loop(self.loop)
         # Check whether markets have to be reloaded
         if (self._last_markets_refresh > 0) and (
                 self._last_markets_refresh + self.markets_refresh_interval

From ea64f43e52dac1bcebd083540527b17235cab6b1 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Mon, 8 Aug 2022 01:13:13 +0200
Subject: [PATCH 095/132] bring back auto DF resizing for okx

---
 freqtrade/freqai/data_drawer.py | 25 ++++++++++++-------------
 1 file changed, 12 insertions(+), 13 deletions(-)

diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py
index 6527eed98..1aecddb9d 100644
--- a/freqtrade/freqai/data_drawer.py
+++ b/freqtrade/freqai/data_drawer.py
@@ -279,15 +279,15 @@ class FreqaiDataDrawer:
         # own return array in the same shape, we need to figure out how the size has changed
         # and adapt our stored/returned info accordingly.
 
-        # length_difference = len(self.model_return_values[pair]) - len_df
-        # i = 0
+        length_difference = len(self.model_return_values[pair]) - len_df
+        i = 0
 
-        # if length_difference == 0:
-        #     i = 1
-        # elif length_difference > 0:
-        #     i = length_difference + 1
+        if length_difference == 0:
+            i = 1
+        elif length_difference > 0:
+            i = length_difference + 1
 
-        df = self.model_return_values[pair] = self.model_return_values[pair].shift(-1)
+        df = self.model_return_values[pair] = self.model_return_values[pair].shift(-i)
 
         if pair in self.historic_predictions:
             hp_df = self.historic_predictions[pair]
@@ -320,11 +320,11 @@ class FreqaiDataDrawer:
             for key in df.keys():
                 self.historic_predictions[pair][key].iloc[-1] = df[key].iloc[-1]
 
-        # if length_difference < 0:
-        #     prepend_df = pd.DataFrame(
-        #         np.zeros((abs(length_difference) - 1, len(df.columns))), columns=df.columns
-        #     )
-        #     df = pd.concat([prepend_df, df], axis=0)
+        if length_difference < 0:
+            prepend_df = pd.DataFrame(
+                np.zeros((abs(length_difference) - 1, len(df.columns))), columns=df.columns
+            )
+            df = pd.concat([prepend_df, df], axis=0)
 
     def attach_return_values_to_return_dataframe(
             self, pair: str, dataframe: DataFrame) -> DataFrame:
@@ -355,7 +355,6 @@ class FreqaiDataDrawer:
             dataframe[f"{label}_mean"] = 0
             dataframe[f"{label}_std"] = 0
 
-        # dataframe['prediction'] = 0
         dataframe["do_predict"] = 0
 
         if self.freqai_info["feature_parameters"].get("DI_threshold", 0) > 0:

From 11a2eb6cc5598f837478864fba9139b78a1603db Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 8 Aug 2022 03:01:16 +0000
Subject: [PATCH 096/132] Bump flake8 from 5.0.1 to 5.0.4

Bumps [flake8](https://github.com/pycqa/flake8) from 5.0.1 to 5.0.4.
- [Release notes](https://github.com/pycqa/flake8/releases)
- [Commits](https://github.com/pycqa/flake8/compare/5.0.1...5.0.4)

---
updated-dependencies:
- dependency-name: flake8
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 requirements-dev.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements-dev.txt b/requirements-dev.txt
index 79021e591..16fc1b046 100644
--- a/requirements-dev.txt
+++ b/requirements-dev.txt
@@ -5,7 +5,7 @@
 -r docs/requirements-docs.txt
 
 coveralls==3.3.1
-flake8==5.0.1
+flake8==5.0.4
 flake8-tidy-imports==4.8.0
 mypy==0.971
 pre-commit==2.20.0

From 7fd3f98ae8e730d964b10260e604d6b45592176a Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 8 Aug 2022 03:01:20 +0000
Subject: [PATCH 097/132] Bump scikit-learn from 1.1.1 to 1.1.2

Bumps [scikit-learn](https://github.com/scikit-learn/scikit-learn) from 1.1.1 to 1.1.2.
- [Release notes](https://github.com/scikit-learn/scikit-learn/releases)
- [Commits](https://github.com/scikit-learn/scikit-learn/compare/1.1.1...1.1.2)

---
updated-dependencies:
- dependency-name: scikit-learn
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 requirements-hyperopt.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements-hyperopt.txt b/requirements-hyperopt.txt
index cc659fc50..11b9511f2 100644
--- a/requirements-hyperopt.txt
+++ b/requirements-hyperopt.txt
@@ -3,7 +3,7 @@
 
 # Required for hyperopt
 scipy==1.9.0
-scikit-learn==1.1.1
+scikit-learn==1.1.2
 scikit-optimize==0.9.0
 filelock==3.7.1
 progressbar2==4.0.0

From a45a35f38c616acf2565816163d2f2bf50e15d84 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 8 Aug 2022 03:01:25 +0000
Subject: [PATCH 098/132] Bump jsonschema from 4.9.0 to 4.9.1

Bumps [jsonschema](https://github.com/python-jsonschema/jsonschema) from 4.9.0 to 4.9.1.
- [Release notes](https://github.com/python-jsonschema/jsonschema/releases)
- [Changelog](https://github.com/python-jsonschema/jsonschema/blob/main/CHANGELOG.rst)
- [Commits](https://github.com/python-jsonschema/jsonschema/compare/v4.9.0...v4.9.1)

---
updated-dependencies:
- dependency-name: jsonschema
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 requirements.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements.txt b/requirements.txt
index 4cb6519b3..202ded414 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -12,7 +12,7 @@ arrow==1.2.2
 cachetools==4.2.2
 requests==2.28.1
 urllib3==1.26.11
-jsonschema==4.9.0
+jsonschema==4.9.1
 TA-Lib==0.4.24
 technical==1.3.0
 tabulate==0.8.10

From 97c077171ac63b16839baf0651d8e526e02a8d88 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 8 Aug 2022 03:01:28 +0000
Subject: [PATCH 099/132] Bump types-requests from 2.28.6 to 2.28.8

Bumps [types-requests](https://github.com/python/typeshed) from 2.28.6 to 2.28.8.
- [Release notes](https://github.com/python/typeshed/releases)
- [Commits](https://github.com/python/typeshed/commits)

---
updated-dependencies:
- dependency-name: types-requests
  dependency-type: direct:development
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 requirements-dev.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements-dev.txt b/requirements-dev.txt
index 79021e591..b0533d415 100644
--- a/requirements-dev.txt
+++ b/requirements-dev.txt
@@ -24,6 +24,6 @@ nbconvert==6.5.0
 # mypy types
 types-cachetools==5.2.1
 types-filelock==3.2.7
-types-requests==2.28.6
+types-requests==2.28.8
 types-tabulate==0.8.11
 types-python-dateutil==2.8.19

From 71c88244fedae929b9189d2560d6a8c9c9528cec Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Mon, 8 Aug 2022 03:01:38 +0000
Subject: [PATCH 100/132] Bump ccxt from 1.91.55 to 1.91.93

Bumps [ccxt](https://github.com/ccxt/ccxt) from 1.91.55 to 1.91.93.
- [Release notes](https://github.com/ccxt/ccxt/releases)
- [Changelog](https://github.com/ccxt/ccxt/blob/master/exchanges.cfg)
- [Commits](https://github.com/ccxt/ccxt/compare/1.91.55...1.91.93)

---
updated-dependencies:
- dependency-name: ccxt
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 requirements.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements.txt b/requirements.txt
index 4cb6519b3..93c41c4c9 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -2,7 +2,7 @@ numpy==1.23.1
 pandas==1.4.3
 pandas-ta==0.3.14b
 
-ccxt==1.91.55
+ccxt==1.91.93
 # Pin cryptography for now due to rust build errors with piwheels
 cryptography==37.0.4
 aiohttp==3.8.1

From 0c7d862aae1d1b44d57af0177578edd586bc49bb Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Mon, 8 Aug 2022 06:54:00 +0200
Subject: [PATCH 101/132] types-requests bump pre-commit

---
 .pre-commit-config.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 398d09875..a205f24ec 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -15,7 +15,7 @@ repos:
         additional_dependencies:
           - types-cachetools==5.2.1
           - types-filelock==3.2.7
-          - types-requests==2.28.6
+          - types-requests==2.28.8
           - types-tabulate==0.8.11
           - types-python-dateutil==2.8.19
         # stages: [push]

From 20b41347879585de25ccad7a36514b037585c59a Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Mon, 8 Aug 2022 18:15:18 +0000
Subject: [PATCH 102/132] Properly exclude catboost in ARM

---
 tests/freqai/test_freqai_interface.py | 8 ++++++--
 1 file changed, 6 insertions(+), 2 deletions(-)

diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py
index 676f451ab..ec69a41c1 100644
--- a/tests/freqai/test_freqai_interface.py
+++ b/tests/freqai/test_freqai_interface.py
@@ -12,6 +12,10 @@ from tests.conftest import get_patched_exchange, log_has_re
 from tests.freqai.conftest import get_patched_freqai_strategy
 
 
+def is_arm() -> bool:
+    machine = platform.machine()
+    return "arm" in machine or "aarch64" in machine
+
 def test_train_model_in_series_LightGBM(mocker, freqai_conf):
     freqai_conf.update({"timerange": "20180110-20180130"})
 
@@ -70,7 +74,7 @@ def test_train_model_in_series_LightGBMMultiModel(mocker, freqai_conf):
     shutil.rmtree(Path(freqai.dk.full_path))
 
 
-@pytest.mark.skipif("arm" in platform.uname()[-1], reason="no ARM for Catboost ...")
+@pytest.mark.skipif(is_arm(), reason="no ARM for Catboost ...")
 def test_train_model_in_series_Catboost(mocker, freqai_conf):
     freqai_conf.update({"timerange": "20180110-20180130"})
     freqai_conf.update({"freqaimodel": "CatboostRegressor"})
@@ -103,7 +107,7 @@ def test_train_model_in_series_Catboost(mocker, freqai_conf):
     shutil.rmtree(Path(freqai.dk.full_path))
 
 
-@pytest.mark.skipif("arm" in platform.uname()[-1], reason="no ARM for Catboost ...")
+@pytest.mark.skipif(is_arm(), reason="no ARM for Catboost ...")
 def test_train_model_in_series_CatboostClassifier(mocker, freqai_conf):
     freqai_conf.update({"timerange": "20180110-20180130"})
     freqai_conf.update({"freqaimodel": "CatboostClassifier"})

From 77b3b8a13412dd5e33a8ad459d52495cb90080de Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Mon, 8 Aug 2022 18:34:11 +0000
Subject: [PATCH 103/132] Use main exchange instead of creating a separate
 instance.

---
 freqtrade/exchange/exchange.py        |  1 -
 freqtrade/freqai/data_kitchen.py      | 22 +++++++++-------------
 freqtrade/freqai/freqai_interface.py  |  2 +-
 tests/freqai/test_freqai_interface.py |  1 +
 4 files changed, 11 insertions(+), 15 deletions(-)

diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py
index f4959db3b..79bc769e6 100644
--- a/freqtrade/exchange/exchange.py
+++ b/freqtrade/exchange/exchange.py
@@ -482,7 +482,6 @@ class Exchange:
 
     def reload_markets(self) -> None:
         """Reload markets both sync and async if refresh interval has passed """
-        asyncio.set_event_loop(self.loop)
         # Check whether markets have to be reloaded
         if (self._last_markets_refresh > 0) and (
                 self._last_markets_refresh + self.markets_refresh_interval
diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index be9284c92..6735df02b 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -17,9 +17,9 @@ from sklearn.model_selection import train_test_split
 from sklearn.neighbors import NearestNeighbors
 
 from freqtrade.configuration import TimeRange
+from freqtrade.data.dataprovider import DataProvider
 from freqtrade.data.history.history_utils import refresh_backtest_ohlcv_data
 from freqtrade.exceptions import OperationalException
-from freqtrade.resolvers import ExchangeResolver
 from freqtrade.strategy.interface import IStrategy
 
 
@@ -895,22 +895,20 @@ class FreqaiDataKitchen:
 
         self.model_filename = f"cb_{coin.lower()}_{int(trained_timerange.stopts)}"
 
-    def download_all_data_for_training(self, timerange: TimeRange) -> None:
+    def download_all_data_for_training(self, timerange: TimeRange, dp: DataProvider) -> None:
         """
         Called only once upon start of bot to download the necessary data for
         populating indicators and training the model.
-        :params:
-        timerange: TimeRange = The full data timerange for populating the indicators
-        and training the model.
+        :param timerange: TimeRange = The full data timerange for populating the indicators
+                                      and training the model.
+        :param dp: DataProvider instance attached to the strategy
         """
-        exchange = ExchangeResolver.load_exchange(
-            self.config["exchange"]["name"], self.config, validate=False, load_leverage_tiers=False
-        )
-
         new_pairs_days = int((timerange.stopts - timerange.startts) / SECONDS_IN_DAY)
-
+        if not dp._exchange:
+            # Not realistic - this is only called in live mode.
+            raise OperationalException("Dataprovider did not have an exchange attached.")
         refresh_backtest_ohlcv_data(
-            exchange,
+            dp._exchange,
             pairs=self.all_pairs,
             timeframes=self.freqai_config["feature_parameters"].get("include_timeframes"),
             datadir=self.config["datadir"],
@@ -922,8 +920,6 @@ class FreqaiDataKitchen:
             prepend=self.config.get("prepend_data", False),
         )
 
-        exchange.close()
-
     def set_all_pairs(self) -> None:
 
         self.all_pairs = copy.deepcopy(
diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py
index 097ecf553..833fb50d6 100644
--- a/freqtrade/freqai/freqai_interface.py
+++ b/freqtrade/freqai/freqai_interface.py
@@ -273,7 +273,7 @@ class IFreqaiModel(ABC):
                     "corr_pairlist, this may take a while if you do not have the "
                     "data saved"
                 )
-                dk.download_all_data_for_training(data_load_timerange)
+                dk.download_all_data_for_training(data_load_timerange, strategy.dp)
                 self.dd.load_all_pair_histories(data_load_timerange, dk)
 
             if not self.scanning:
diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py
index ec69a41c1..a36f80280 100644
--- a/tests/freqai/test_freqai_interface.py
+++ b/tests/freqai/test_freqai_interface.py
@@ -16,6 +16,7 @@ def is_arm() -> bool:
     machine = platform.machine()
     return "arm" in machine or "aarch64" in machine
 
+
 def test_train_model_in_series_LightGBM(mocker, freqai_conf):
     freqai_conf.update({"timerange": "20180110-20180130"})
 

From 02646a4a08e02922d3a696872649a871562b05b9 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Tue, 9 Aug 2022 06:23:16 +0200
Subject: [PATCH 104/132] Update scikit-learn in freqai deps

---
 requirements-freqai.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements-freqai.txt b/requirements-freqai.txt
index e4f4a7c17..5e67a5539 100644
--- a/requirements-freqai.txt
+++ b/requirements-freqai.txt
@@ -2,7 +2,7 @@
 -r requirements.txt
 
 # Required for freqai
-scikit-learn==1.1.1
+scikit-learn==1.1.2
 joblib==1.1.0
 catboost==1.0.4; platform_machine != 'aarch64'
 lightgbm==3.3.2

From aef086b02e73bf426cf6f7e7079f1a7c0e0e76b9 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Tue, 9 Aug 2022 15:30:25 +0200
Subject: [PATCH 105/132] Improved dict typing, timeframe parser, collect dates
 associated with training data points

---
 freqtrade/freqai/data_drawer.py               | 56 +++++++++++-------
 freqtrade/freqai/data_kitchen.py              | 58 +++++++++----------
 .../strategy/strats/freqai_test_classifier.py |  3 +-
 3 files changed, 66 insertions(+), 51 deletions(-)

diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py
index 1aecddb9d..f8002a45f 100644
--- a/freqtrade/freqai/data_drawer.py
+++ b/freqtrade/freqai/data_drawer.py
@@ -5,10 +5,11 @@ import re
 import shutil
 import threading
 from pathlib import Path
-from typing import Any, Dict, Tuple
+from typing import Any, Dict, Tuple, TypedDict
 
 import numpy as np
 import pandas as pd
+import rapidjson
 from joblib import dump, load
 from joblib.externals import cloudpickle
 from numpy.typing import ArrayLike, NDArray
@@ -24,6 +25,14 @@ from freqtrade.strategy.interface import IStrategy
 logger = logging.getLogger(__name__)
 
 
+class pair_info(TypedDict):
+    model_filename: str
+    first: bool
+    trained_timestamp: int
+    priority: int
+    data_path: str
+
+
 class FreqaiDataDrawer:
     """
     Class aimed at holding all pair models/info in memory for better inferencing/retrainig/saving
@@ -54,14 +63,13 @@ class FreqaiDataDrawer:
         self.config = config
         self.freqai_info = config.get("freqai", {})
         # dictionary holding all pair metadata necessary to load in from disk
-        self.pair_dict: Dict[str, Any] = {}
+        self.pair_dict: Dict[str, pair_info] = {}
         # dictionary holding all actively inferenced models in memory given a model filename
         self.model_dictionary: Dict[str, Any] = {}
-        self.model_return_values: Dict[str, Any] = {}
-        self.pair_data_dict: Dict[str, Any] = {}
-        self.historic_data: Dict[str, Any] = {}
-        self.historic_predictions: Dict[str, Any] = {}
-        self.follower_dict: Dict[str, Any] = {}
+        self.model_return_values: Dict[str, DataFrame] = {}
+        self.historic_data: Dict[str, Dict[str, DataFrame]] = {}
+        self.historic_predictions: Dict[str, DataFrame] = {}
+        self.follower_dict: Dict[str, pair_info] = {}
         self.full_path = full_path
         self.follower_name: str = self.config.get("bot_name", "follower1")
         self.follower_dict_path = Path(
@@ -77,6 +85,9 @@ class FreqaiDataDrawer:
         self.training_queue: Dict[str, int] = {}
         self.history_lock = threading.Lock()
         self.old_DBSCAN_eps: Dict[str, float] = {}
+        self.empty_pair_dict: pair_info = {
+                "model_filename": "", "trained_timestamp": 0,
+                "priority": 1, "first": True, "data_path": ""}
 
     def load_drawer_from_disk(self):
         """
@@ -133,15 +144,17 @@ class FreqaiDataDrawer:
         """
         Save data drawer full of all pair model metadata in present model folder.
         """
-        with open(self.pair_dictionary_path, "w") as fp:
-            json.dump(self.pair_dict, fp, default=self.np_encoder)
+        with open(self.pair_dictionary_path, 'w') as fp:
+            rapidjson.dump(self.pair_dict, fp, default=self.np_encoder,
+                           number_mode=rapidjson.NM_NATIVE)
 
     def save_follower_dict_to_disk(self):
         """
         Save follower dictionary to disk (used by strategy for persistent prediction targets)
         """
         with open(self.follower_dict_path, "w") as fp:
-            json.dump(self.follower_dict, fp, default=self.np_encoder)
+            rapidjson.dump(self.follower_dict, fp, default=self.np_encoder,
+                           number_mode=rapidjson.NM_NATIVE)
 
     def create_follower_dict(self):
         """
@@ -175,18 +188,19 @@ class FreqaiDataDrawer:
             trained_timestamp: int = the last time the coin was trained
             return_null_array: bool = Follower could not find pair metadata
         """
+
         pair_dict = self.pair_dict.get(pair)
-        data_path_set = self.pair_dict.get(pair, {}).get("data_path", None)
+        data_path_set = self.pair_dict.get(pair, self.empty_pair_dict).get("data_path", "")
         return_null_array = False
 
         if pair_dict:
             model_filename = pair_dict["model_filename"]
             trained_timestamp = pair_dict["trained_timestamp"]
         elif not self.follow_mode:
-            pair_dict = self.pair_dict[pair] = {}
-            model_filename = pair_dict["model_filename"] = ""
-            trained_timestamp = pair_dict["trained_timestamp"] = 0
-            pair_dict["priority"] = len(self.pair_dict)
+            self.pair_dict[pair] = self.empty_pair_dict.copy()
+            model_filename = ""
+            trained_timestamp = 0
+            self.pair_dict[pair]["priority"] = len(self.pair_dict)
 
         if not data_path_set and self.follow_mode:
             logger.warning(
@@ -205,11 +219,9 @@ class FreqaiDataDrawer:
         if pair_in_dict:
             return
         else:
-            self.pair_dict[metadata["pair"]] = {}
-            self.pair_dict[metadata["pair"]]["model_filename"] = ""
-            self.pair_dict[metadata["pair"]]["first"] = True
-            self.pair_dict[metadata["pair"]]["trained_timestamp"] = 0
+            self.pair_dict[metadata["pair"]] = self.empty_pair_dict.copy()
             self.pair_dict[metadata["pair"]]["priority"] = len(self.pair_dict)
+
             return
 
     def pair_to_end_of_training_queue(self, pair: str) -> None:
@@ -440,13 +452,17 @@ class FreqaiDataDrawer:
         dk.data["label_list"] = dk.label_list
         # store the metadata
         with open(save_path / f"{dk.model_filename}_metadata.json", "w") as fp:
-            json.dump(dk.data, fp, default=dk.np_encoder)
+            rapidjson.dump(dk.data, fp, default=self.np_encoder, number_mode=rapidjson.NM_NATIVE)
 
         # save the train data to file so we can check preds for area of applicability later
         dk.data_dictionary["train_features"].to_pickle(
             save_path / f"{dk.model_filename}_trained_df.pkl"
         )
 
+        dk.data_dictionary["train_dates"].to_pickle(
+            save_path / f"{dk.model_filename}_trained_dates_df.pkl"
+        )
+
         if self.freqai_info["feature_parameters"].get("principal_component_analysis"):
             cloudpickle.dump(
                 dk.pca, open(dk.data_path / f"{dk.model_filename}_pca_object.pkl", "wb")
diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index 6735df02b..96479b87c 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -20,6 +20,7 @@ from freqtrade.configuration import TimeRange
 from freqtrade.data.dataprovider import DataProvider
 from freqtrade.data.history.history_utils import refresh_backtest_ohlcv_data
 from freqtrade.exceptions import OperationalException
+from freqtrade.exchange import timeframe_to_seconds
 from freqtrade.strategy.interface import IStrategy
 
 
@@ -58,8 +59,8 @@ class FreqaiDataKitchen:
         live: bool = False,
         pair: str = "",
     ):
-        self.data: Dict[Any, Any] = {}
-        self.data_dictionary: Dict[Any, Any] = {}
+        self.data: Dict[str, Any] = {}
+        self.data_dictionary: Dict[str, DataFrame] = {}
         self.config = config
         self.freqai_config: Dict[str, Any] = config["freqai"]
         self.full_df: DataFrame = DataFrame()
@@ -98,6 +99,7 @@ class FreqaiDataKitchen:
 
         self.data['extra_returns_per_train'] = self.freqai_config.get('extra_returns_per_train', {})
         self.thread_count = self.freqai_config.get("data_kitchen_thread_count", -1)
+        self.train_dates: DataFrame = pd.DataFrame()
 
     def set_paths(
         self,
@@ -206,16 +208,20 @@ class FreqaiDataKitchen:
         if (training_filter):
             # we don't care about total row number (total no. datapoints) in training, we only care
             # about removing any row with NaNs
-            # if labels has multiple columns (user wants to train multiple models), we detect here
+            # if labels has multiple columns (user wants to train multiple modelEs), we detect here
             labels = unfiltered_dataframe.filter(label_list, axis=1)
             drop_index_labels = pd.isnull(labels).any(1)
             drop_index_labels = drop_index_labels.replace(True, 1).replace(False, 0)
+            dates = unfiltered_dataframe.filter('date', axis=1)
             filtered_dataframe = filtered_dataframe[
                 (drop_index == 0) & (drop_index_labels == 0)
             ]  # dropping values
             labels = labels[
                 (drop_index == 0) & (drop_index_labels == 0)
             ]  # assuming the labels depend entirely on the dataframe here.
+            self.train_dates = dates[
+                (drop_index == 0) & (drop_index_labels == 0)
+            ]
             logger.info(
                 f"dropped {len(unfiltered_dataframe) - len(filtered_dataframe)} training points"
                 f" due to NaNs in populated dataset {len(unfiltered_dataframe)}."
@@ -266,6 +272,7 @@ class FreqaiDataKitchen:
             "test_labels": test_labels,
             "train_weights": train_weights,
             "test_weights": test_weights,
+            "train_dates": self.train_dates
         }
 
         return self.data_dictionary
@@ -351,7 +358,7 @@ class FreqaiDataKitchen:
         return df
 
     def split_timerange(
-        self, tr: str, train_split: int = 28, bt_split: int = 7
+        self, tr: str, train_split: int = 28, bt_split: float = 7
     ) -> Tuple[list, list]:
         """
         Function which takes a single time range (tr) and splits it
@@ -359,7 +366,7 @@ class FreqaiDataKitchen:
         tr: str, full timerange to train on
         train_split: the period length for the each training (days). Specified in user
         configuration file
-        bt_split: the backtesting length (dats). Specified in user configuration file
+        bt_split: the backtesting length (days). Specified in user configuration file
         """
 
         if not isinstance(train_split, int) or train_split < 1:
@@ -386,7 +393,7 @@ class FreqaiDataKitchen:
 
         while True:
             if not first:
-                timerange_train.startts = timerange_train.startts + bt_period
+                timerange_train.startts = timerange_train.startts + int(bt_period)
             timerange_train.stopts = timerange_train.startts + train_period_days
 
             first = False
@@ -399,7 +406,7 @@ class FreqaiDataKitchen:
 
             timerange_backtest.startts = timerange_train.stopts
 
-            timerange_backtest.stopts = timerange_backtest.startts + bt_period
+            timerange_backtest.stopts = timerange_backtest.startts + int(bt_period)
 
             if timerange_backtest.stopts > config_timerange.stopts:
                 timerange_backtest.stopts = config_timerange.stopts
@@ -820,30 +827,21 @@ class FreqaiDataKitchen:
         trained_timerange = TimeRange()
         data_load_timerange = TimeRange()
 
-        # find the max indicator length required
-        max_timeframe_chars = self.freqai_config["feature_parameters"].get(
-            "include_timeframes"
-        )[-1]
-        max_period = self.freqai_config["feature_parameters"].get(
-            "indicator_max_period_candles", 50
-        )
-        additional_seconds = 0
-        if max_timeframe_chars[-1] == "d":
-            additional_seconds = max_period * SECONDS_IN_DAY * int(max_timeframe_chars[-2])
-        elif max_timeframe_chars[-1] == "h":
-            additional_seconds = max_period * 3600 * int(max_timeframe_chars[-2])
-        elif max_timeframe_chars[-1] == "m":
-            if len(max_timeframe_chars) == 2:
-                additional_seconds = max_period * 60 * int(max_timeframe_chars[-2])
-            elif len(max_timeframe_chars) == 3:
-                additional_seconds = max_period * 60 * int(float(max_timeframe_chars[0:2]))
-            else:
-                logger.warning(
-                    "FreqAI could not detect max timeframe and therefore may not "
-                    "download the proper amount of data for training"
-                )
+        timeframes = self.freqai_config["feature_parameters"].get("include_timeframes")
 
-        # logger.info(f'Extending data download by {additional_seconds/SECONDS_IN_DAY:.2f} days')
+        max_tf_seconds = 0
+        for tf in timeframes:
+            secs = timeframe_to_seconds(tf)
+            if secs > max_tf_seconds:
+                max_tf_seconds = secs
+
+        # We notice that users like to use exotic indicators where
+        # they do not know the required timeperiod. Here we include a factor
+        # of safety by multiplying the user considered "max" by 2.
+        max_period = self.freqai_config["feature_parameters"].get(
+            "indicator_max_period_candles", 20
+        ) * 2
+        additional_seconds = max_period * max_tf_seconds
 
         if trained_timestamp != 0:
             elapsed_time = (time - trained_timestamp) / SECONDS_IN_HOUR
diff --git a/tests/strategy/strats/freqai_test_classifier.py b/tests/strategy/strats/freqai_test_classifier.py
index c333ac818..0a2ce793a 100644
--- a/tests/strategy/strats/freqai_test_classifier.py
+++ b/tests/strategy/strats/freqai_test_classifier.py
@@ -1,10 +1,11 @@
 import logging
 from functools import reduce
 
+import numpy as np
 import pandas as pd
 import talib.abstract as ta
 from pandas import DataFrame
-import numpy as np
+
 from freqtrade.strategy import DecimalParameter, IntParameter, IStrategy, merge_informative_pair
 
 

From e7de812948c87be1a5b5ccc82301d5e227c6bd97 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Tue, 9 Aug 2022 16:03:10 +0200
Subject: [PATCH 106/132] Allow user to user pair_dict for persistent storage
 of custom data

---
 freqtrade/freqai/data_drawer.py              | 3 ++-
 freqtrade/templates/FreqaiExampleStrategy.py | 8 ++++----
 2 files changed, 6 insertions(+), 5 deletions(-)

diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py
index f8002a45f..ec49c7050 100644
--- a/freqtrade/freqai/data_drawer.py
+++ b/freqtrade/freqai/data_drawer.py
@@ -31,6 +31,7 @@ class pair_info(TypedDict):
     trained_timestamp: int
     priority: int
     data_path: str
+    extras: dict
 
 
 class FreqaiDataDrawer:
@@ -87,7 +88,7 @@ class FreqaiDataDrawer:
         self.old_DBSCAN_eps: Dict[str, float] = {}
         self.empty_pair_dict: pair_info = {
                 "model_filename": "", "trained_timestamp": 0,
-                "priority": 1, "first": True, "data_path": ""}
+                "priority": 1, "first": True, "data_path": "", "extras": {}}
 
     def load_drawer_from_disk(self):
         """
diff --git a/freqtrade/templates/FreqaiExampleStrategy.py b/freqtrade/templates/FreqaiExampleStrategy.py
index ee1602725..01f947a6a 100644
--- a/freqtrade/templates/FreqaiExampleStrategy.py
+++ b/freqtrade/templates/FreqaiExampleStrategy.py
@@ -252,16 +252,16 @@ class FreqaiExampleStrategy(IStrategy):
 
         if (
             "prediction" + entry_tag not in pair_dict[pair]
-            or pair_dict[pair]["prediction" + entry_tag] == 0
+            or pair_dict[pair]['extras']["prediction" + entry_tag] == 0
         ):
             with self.freqai.lock:
-                pair_dict[pair]["prediction" + entry_tag] = abs(trade_candle["&-s_close"])
+                pair_dict[pair]['extras']["prediction" + entry_tag] = abs(trade_candle["&-s_close"])
                 if not follow_mode:
                     self.freqai.dd.save_drawer_to_disk()
                 else:
                     self.freqai.dd.save_follower_dict_to_disk()
 
-        roi_price = pair_dict[pair]["prediction" + entry_tag]
+        roi_price = pair_dict[pair]['extras']["prediction" + entry_tag]
         roi_time = self.max_roi_time_long.value
 
         roi_decay = roi_price * (
@@ -299,7 +299,7 @@ class FreqaiExampleStrategy(IStrategy):
             pair_dict = self.freqai.dd.follower_dict
 
         with self.freqai.lock:
-            pair_dict[pair]["prediction" + entry_tag] = 0
+            pair_dict[pair]['extras']["prediction" + entry_tag] = 0
             if not follow_mode:
                 self.freqai.dd.save_drawer_to_disk()
             else:

From 5a16d5a51276d7d77c5474068c1b25ec2729ec62 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Tue, 9 Aug 2022 16:36:22 +0200
Subject: [PATCH 107/132] Deactivate database analyzer if user does not use
 sqlite

---
 freqtrade/freqai/data_kitchen.py | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index 96479b87c..adfd68c84 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -93,7 +93,12 @@ class FreqaiDataKitchen:
         if self.live:
             db_url = self.config.get('db_url', None)
             self.database_path = Path(db_url)
-            self.database_name = Path(*self.database_path.parts[1:])
+            if 'sqlite' not in self.database_path.parts[0]:
+                self.database_path = None
+                logger.warning('FreqAI database analyzer only available for sqlite dbs. '
+                               ' FreqAI will still run, but user cannot use database analyzer.')
+            else:
+                self.database_name = Path(*self.database_path.parts[1:])
 
         self.trade_database_df: DataFrame = pd.DataFrame()
 

From 4289c5c684fb193d9822a4e5a0904e05c8be97df Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Tue, 9 Aug 2022 16:51:57 +0200
Subject: [PATCH 108/132] update freqai logo

---
 docs/assets/freqai_logo_no_md.svg | 277 ++++++++++++++----------------
 1 file changed, 127 insertions(+), 150 deletions(-)

diff --git a/docs/assets/freqai_logo_no_md.svg b/docs/assets/freqai_logo_no_md.svg
index 2d1305462..62c32217f 100644
--- a/docs/assets/freqai_logo_no_md.svg
+++ b/docs/assets/freqai_logo_no_md.svg
@@ -8,19 +8,22 @@
    xmlns:xlink="http://www.w3.org/1999/xlink"
    id="svg1557"
    version="1.1"
-   viewBox="0 0 454.73947 309.55279"
-   height="309.5528mm"
-   width="454.73947mm">
+   viewBox="0 0 316.36553 184.36865"
+   height="184.36865mm"
+   width="316.36554mm">
   <defs
      id="defs1551">
     <linearGradient
-       y2="26.575241"
-       x2="249.15274"
-       y1="57.745811"
-       x1="174.20145"
-       gradientUnits="userSpaceOnUse"
-       id="linearGradient1312"
-       xlink:href="#linearGradient1142" />
+       id="linearGradient1933">
+      <stop
+         style="stop-color:#800080;stop-opacity:1"
+         offset="0"
+         id="stop1929" />
+      <stop
+         style="stop-color:#c83737;stop-opacity:1"
+         offset="1"
+         id="stop1931" />
+    </linearGradient>
     <linearGradient
        id="linearGradient1142">
       <stop
@@ -41,29 +44,45 @@
        id="linearGradient1147"
        xlink:href="#linearGradient1142" />
     <linearGradient
-       y2="26.575241"
-       x2="249.15274"
-       y1="57.745811"
-       x1="174.20145"
+       y2="81.289787"
+       x2="301.36768"
+       y1="131.64389"
+       x1="293.50531"
        gradientUnits="userSpaceOnUse"
        id="linearGradient2187"
        xlink:href="#linearGradient1142" />
     <linearGradient
-       y2="26.575241"
-       x2="249.15274"
-       y1="57.745811"
-       x1="174.20145"
+       y2="-63.514065"
+       x2="229.03004"
+       y1="168.38782"
+       x1="78.344269"
        gradientUnits="userSpaceOnUse"
        id="linearGradient2189"
        xlink:href="#linearGradient1142" />
     <linearGradient
-       y2="26.575241"
-       x2="249.15274"
-       y1="56.015697"
-       x1="153.87447"
+       y2="75.905518"
+       x2="378.23627"
+       y1="104.48698"
+       x1="371.62622"
        gradientUnits="userSpaceOnUse"
        id="linearGradient2481"
        xlink:href="#linearGradient1142" />
+    <linearGradient
+       gradientUnits="userSpaceOnUse"
+       y2="-40.816475"
+       x2="304.21649"
+       y1="336.74393"
+       x1="94.333183"
+       id="linearGradient1917"
+       xlink:href="#linearGradient1142" />
+    <linearGradient
+       y2="-0.12421786"
+       x2="317.15186"
+       y1="223.87135"
+       x1="192.64189"
+       gradientUnits="userSpaceOnUse"
+       id="linearGradient1927"
+       xlink:href="#linearGradient1933" />
   </defs>
   <metadata
      id="metadata1554">
@@ -78,144 +97,102 @@
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   </metadata>
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+     transform="translate(7.2313488,-24.26963)"
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-     transform="translate(95.042874,-2.128963)"
-     id="layer1">
     <text
-       x="100.8474"
-       y="237.30298"
+       x="-11.907605"
+       y="196.59839"
        font-size="96.8px"
-       style="font-size:85.28913879px;line-height:1.25;font-family:sans-serif;display:inline;fill:#000000;stroke:#000000;stroke-width:2.13222837"
+       style="font-size:54.6007576px;line-height:1.25;font-family:sans-serif;display:inline;fill:#000000;stroke:#000000;stroke-width:1.36501884"
        xml:space="preserve"
        id="text1366"><tspan
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          id="tspan1364">FreqAI</tspan></text>
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+     style="display:inline"
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+     id="layer1" />
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From b5c5a95b64f8c35b2606da65114d6c65d66ec758 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Tue, 9 Aug 2022 20:09:35 +0200
Subject: [PATCH 109/132] FTX: Use conditionalOrders endpoint to get proper
 stop-market order id

closes #7165
---
 freqtrade/exchange/ftx.py  | 14 +++++++++++---
 tests/exchange/test_ftx.py | 18 +++++++++++++++---
 2 files changed, 26 insertions(+), 6 deletions(-)

diff --git a/freqtrade/exchange/ftx.py b/freqtrade/exchange/ftx.py
index 9ee6894f1..b3c219542 100644
--- a/freqtrade/exchange/ftx.py
+++ b/freqtrade/exchange/ftx.py
@@ -1,6 +1,6 @@
 """ FTX exchange subclass """
 import logging
-from typing import Any, Dict, List, Tuple
+from typing import Any, Dict, List, Optional, Tuple
 
 import ccxt
 
@@ -116,9 +116,17 @@ class Ftx(Exchange):
             if len(order) == 1:
                 if order[0].get('status') == 'closed':
                     # Trigger order was triggered ...
-                    real_order_id = order[0].get('info', {}).get('orderId')
+                    real_order_id: Optional[str] = order[0].get('info', {}).get('orderId')
                     # OrderId may be None for stoploss-market orders
-                    # But contains "average" in these cases.
+                    # So we need to get it through the endpoint
+                    # /conditional_orders/{conditional_order_id}/triggers
+                    if not real_order_id:
+                        res = self._api.privateGetConditionalOrdersConditionalOrderIdTriggers(
+                            params={'conditional_order_id': order_id})
+                        self._log_exchange_response('fetch_stoploss_order2', res)
+                        real_order_id = res['result'][0]['orderId'] if res.get(
+                            'result', []) else None
+
                     if real_order_id:
                         order1 = self._api.fetch_order(real_order_id, pair)
                         self._log_exchange_response('fetch_stoploss_order1', order1)
diff --git a/tests/exchange/test_ftx.py b/tests/exchange/test_ftx.py
index 5a83b964a..5213c1b36 100644
--- a/tests/exchange/test_ftx.py
+++ b/tests/exchange/test_ftx.py
@@ -203,7 +203,7 @@ def test_fetch_stoploss_order_ftx(default_conf, mocker, limit_sell_order, limit_
          'info': {
              'orderId': 'mocked_limit_sell',
          }}])
-    api_mock.fetch_order = MagicMock(return_value=limit_sell_order)
+    api_mock.fetch_order = MagicMock(return_value=limit_sell_order.copy())
 
     # No orderId field - no call to fetch_order
     resp = exchange.fetch_stoploss_order('X', 'TKN/BTC')
@@ -219,11 +219,23 @@ def test_fetch_stoploss_order_ftx(default_conf, mocker, limit_sell_order, limit_
     order = {'id': 'X', 'status': 'closed', 'info': {'orderId': None}, 'average': 0.254}
     api_mock.fetch_orders = MagicMock(return_value=[order])
     api_mock.fetch_order.reset_mock()
+    api_mock.privateGetConditionalOrdersConditionalOrderIdTriggers = MagicMock(
+        return_value={'result': [
+            {'orderId': 'mocked_market_sell', 'type': 'market', 'side': 'sell', 'price': 0.254}
+        ]})
     resp = exchange.fetch_stoploss_order('X', 'TKN/BTC')
     assert resp
     # fetch_order not called (no regular order ID)
-    assert api_mock.fetch_order.call_count == 0
-    assert order == order
+    assert api_mock.fetch_order.call_count == 1
+    api_mock.privateGetConditionalOrdersConditionalOrderIdTriggers.call_count == 1
+    expected_resp = limit_sell_order.copy()
+    expected_resp.update({
+        'id_stop': 'X',
+        'id': 'X',
+        'type': 'stop',
+        'status_stop': 'triggered',
+    })
+    assert expected_resp == resp
 
     with pytest.raises(InvalidOrderException):
         api_mock.fetch_orders = MagicMock(side_effect=ccxt.InvalidOrder("Order not found"))

From 736884c5a909b22a98428a2c2953413820d2840d Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Tue, 9 Aug 2022 20:43:58 +0200
Subject: [PATCH 110/132] Orders should be allowed to have empty fill/remaining
 values

---
 freqtrade/rpc/api_server/api_schemas.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/freqtrade/rpc/api_server/api_schemas.py b/freqtrade/rpc/api_server/api_schemas.py
index 333f2fe6e..8f4066ac7 100644
--- a/freqtrade/rpc/api_server/api_schemas.py
+++ b/freqtrade/rpc/api_server/api_schemas.py
@@ -194,11 +194,11 @@ class OrderSchema(BaseModel):
     pair: str
     order_id: str
     status: str
-    remaining: float
+    remaining: Optional[float]
     amount: float
     safe_price: float
     cost: float
-    filled: float
+    filled: Optional[float]
     ft_order_side: str
     order_type: str
     is_open: bool

From ce2c9bf26dd54c5cee3864edf60fa496e5711922 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Wed, 10 Aug 2022 06:44:41 +0200
Subject: [PATCH 111/132] Slight renaming of variable

---
 freqtrade/rpc/rpc.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py
index cda4fdc22..9f2c8cf37 100644
--- a/freqtrade/rpc/rpc.py
+++ b/freqtrade/rpc/rpc.py
@@ -661,7 +661,7 @@ class RPC:
         return {'status': 'No more buy will occur from now. Run /reload_config to reset.'}
 
     def __exec_force_exit(self, trade: Trade, ordertype: Optional[str],
-                          _amount: Optional[float] = None) -> None:
+                          amount: Optional[float] = None) -> None:
         # Check if there is there is an open order
         fully_canceled = False
         if trade.open_order_id:
@@ -683,14 +683,14 @@ class RPC:
             order_type = ordertype or self._freqtrade.strategy.order_types.get(
                 "force_exit", self._freqtrade.strategy.order_types["exit"])
             sub_amount: Optional[float] = None
-            if _amount and _amount < trade.amount:
+            if amount and amount < trade.amount:
                 # Partial exit ...
                 min_exit_stake = self._freqtrade.exchange.get_min_pair_stake_amount(
                     trade.pair, current_rate, trade.stop_loss_pct)
-                remaining = (trade.amount - _amount) * current_rate
+                remaining = (trade.amount - amount) * current_rate
                 if remaining < min_exit_stake:
                     raise RPCException(f'Remaining amount of {remaining} would be too small.')
-                sub_amount = _amount
+                sub_amount = amount
 
             self._freqtrade.execute_trade_exit(
                 trade, current_rate, exit_check, ordertype=order_type,

From 573964b19fc38daec4a8c8ce7387453c5eb03c01 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Wed, 10 Aug 2022 07:12:56 +0200
Subject: [PATCH 112/132] Dry Market orders should update "remaining"

---
 freqtrade/exchange/exchange.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py
index b6996211f..7eb71351e 100644
--- a/freqtrade/exchange/exchange.py
+++ b/freqtrade/exchange/exchange.py
@@ -849,6 +849,7 @@ class Exchange:
             dry_order.update({
                 'average': average,
                 'filled': _amount,
+                'remaining': 0.0,
                 'cost': (dry_order['amount'] * average) / leverage
             })
             # market orders will always incurr taker fees

From adc8ee88e2ec72aafe8c02af591127512dbf7ef8 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Wed, 10 Aug 2022 08:57:19 +0000
Subject: [PATCH 113/132] Move periodicCache to Utils package

---
 freqtrade/configuration/__init__.py                             | 1 -
 freqtrade/data/dataprovider.py                                  | 2 +-
 freqtrade/plugins/pairlist/AgeFilter.py                         | 2 +-
 freqtrade/util/__init__.py                                      | 2 ++
 .../{configuration/PeriodicCache.py => util/periodic_cache.py}  | 0
 tests/test_periodiccache.py                                     | 2 +-
 6 files changed, 5 insertions(+), 4 deletions(-)
 create mode 100644 freqtrade/util/__init__.py
 rename freqtrade/{configuration/PeriodicCache.py => util/periodic_cache.py} (100%)

diff --git a/freqtrade/configuration/__init__.py b/freqtrade/configuration/__init__.py
index cf41c0ca9..730a4e47f 100644
--- a/freqtrade/configuration/__init__.py
+++ b/freqtrade/configuration/__init__.py
@@ -4,5 +4,4 @@ from freqtrade.configuration.check_exchange import check_exchange
 from freqtrade.configuration.config_setup import setup_utils_configuration
 from freqtrade.configuration.config_validation import validate_config_consistency
 from freqtrade.configuration.configuration import Configuration
-from freqtrade.configuration.PeriodicCache import PeriodicCache
 from freqtrade.configuration.timerange import TimeRange
diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py
index e21f10193..21cead77f 100644
--- a/freqtrade/data/dataprovider.py
+++ b/freqtrade/data/dataprovider.py
@@ -12,12 +12,12 @@ from typing import Any, Dict, List, Optional, Tuple
 from pandas import DataFrame
 
 from freqtrade.configuration import TimeRange
-from freqtrade.configuration.PeriodicCache import PeriodicCache
 from freqtrade.constants import ListPairsWithTimeframes, PairWithTimeframe
 from freqtrade.data.history import load_pair_history
 from freqtrade.enums import CandleType, RunMode
 from freqtrade.exceptions import ExchangeError, OperationalException
 from freqtrade.exchange import Exchange, timeframe_to_seconds
+from freqtrade.util import PeriodicCache
 
 
 logger = logging.getLogger(__name__)
diff --git a/freqtrade/plugins/pairlist/AgeFilter.py b/freqtrade/plugins/pairlist/AgeFilter.py
index 786f32e88..13c992c87 100644
--- a/freqtrade/plugins/pairlist/AgeFilter.py
+++ b/freqtrade/plugins/pairlist/AgeFilter.py
@@ -8,11 +8,11 @@ from typing import Any, Dict, List, Optional
 import arrow
 from pandas import DataFrame
 
-from freqtrade.configuration import PeriodicCache
 from freqtrade.constants import ListPairsWithTimeframes
 from freqtrade.exceptions import OperationalException
 from freqtrade.misc import plural
 from freqtrade.plugins.pairlist.IPairList import IPairList
+from freqtrade.util import PeriodicCache
 
 
 logger = logging.getLogger(__name__)
diff --git a/freqtrade/util/__init__.py b/freqtrade/util/__init__.py
new file mode 100644
index 000000000..fc4d66380
--- /dev/null
+++ b/freqtrade/util/__init__.py
@@ -0,0 +1,2 @@
+# flake8: noqa: F401
+from freqtrade.util.periodic_cache import PeriodicCache
diff --git a/freqtrade/configuration/PeriodicCache.py b/freqtrade/util/periodic_cache.py
similarity index 100%
rename from freqtrade/configuration/PeriodicCache.py
rename to freqtrade/util/periodic_cache.py
diff --git a/tests/test_periodiccache.py b/tests/test_periodiccache.py
index b2bd8ba2b..df05de4ef 100644
--- a/tests/test_periodiccache.py
+++ b/tests/test_periodiccache.py
@@ -1,6 +1,6 @@
 import time_machine
 
-from freqtrade.configuration import PeriodicCache
+from freqtrade.util import PeriodicCache
 
 
 def test_ttl_cache():

From 91d0c91287120e3e3976402b390e2c532d382f16 Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Wed, 10 Aug 2022 11:56:42 +0200
Subject: [PATCH 114/132] improve docs

---
 docs/assets/freqai_doc_logo.svg   | 417 ++++++++++++++++++++++++++++++
 docs/assets/freqai_logo_no_md.svg | 198 --------------
 docs/freqai.md                    | 110 ++++----
 3 files changed, 476 insertions(+), 249 deletions(-)
 create mode 100644 docs/assets/freqai_doc_logo.svg
 delete mode 100644 docs/assets/freqai_logo_no_md.svg

diff --git a/docs/assets/freqai_doc_logo.svg b/docs/assets/freqai_doc_logo.svg
new file mode 100644
index 000000000..61561a4ae
--- /dev/null
+++ b/docs/assets/freqai_doc_logo.svg
@@ -0,0 +1,417 @@
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-         id="path2269-6"
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-         d="m 335.4454,19.416852 c -9.20129,69.433777 11.24688,69.5371 24.38694,132.907968 C 312.28003,120.10418 255.52015,111.40061 210.12331,121.80192 250.42852,68.708729 313.52349,31.065403 335.4454,19.416852 Z"
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diff --git a/docs/freqai.md b/docs/freqai.md
index b3682127c..9b2377557 100644
--- a/docs/freqai.md
+++ b/docs/freqai.md
@@ -1,21 +1,37 @@
-![freqai-logo](assets/freqai_logo_no_md.svg)
+![freqai-logo](assets/freqai_doc_logo.svg)
 
 # FreqAI
 
-FreqAI is a module designed to automate a variety of tasks associated with
-training a predictive model to provide signals based on input features.
+FreqAI is a module designed to automate a variety of tasks associated with training a predictive model to generate market forecasts given a set of input features.
 
 Among the the features included:
 
-* Create large rich feature sets (10k+ features) based on simple user created strategies.
-* Sweep model training and backtesting to simulate consistent model retraining through time.
-* Remove outliers automatically from training and prediction sets using a Dissimilarity Index and Support Vector Machines.
-* Reduce the dimensionality of the data with Principal Component Analysis.
-* Store models to disk to make reloading from a crash fast and easy (and purge obsolete files automatically for sustained dry/live runs).
-* Normalize the data automatically in a smart and statistically safe way.
-* Automated data download and data handling.
-* Clean the incoming data of NaNs in a safe way before training and prediction.
-* Retrain live automatically so that the model self-adapts to the market in an unsupervised manner.
+* **Self-adaptive retraining**: automatically retrain models during live deployments to self-adapt to the market in an unsupervised manner.
+* **Rapid feature engineering**: create large rich feature sets (10k+ features) based on simple user created strategies.
+* **High performance**: adaptive retraining occurs on separate thread (or on GPU if available) from inferencing and bot trade operations. Keep newest models and data in memory for rapid inferencing. 
+* **Realistic backtesting**: emulate self-adaptive retraining with backtesting module that automates past retraining.
+* **Modifiable**: use the generalized and robust architecture for incorporating any machine learning library/method available in Python. Seven examples available.
+* **Smart outlier removal**: remove outliers automatically from training and prediction sets using a variety of outlier detection techniques.
+* **Crash resilience**: automatic model storage to disk to make reloading from a crash fast and easy (and purge obsolete files automatically for sustained dry/live runs).
+* **Automated data normalization**: automatically normalize the data automatically in a smart and statistically safe way.
+* **Automatic data download**: automatically compute the data download timerange and downloads data accordingly (in live deployments).
+* **Clean the incoming data of NaNs in a safe way before training and prediction.
+* **Dimensionality reduction**: reduce the size of the training data via Principal Component Analysis.
+* **Deploy bot fleets**: set one bot to train models while a fleet of other bots inference into the models and handle trades.
+
+## Quick start
+
+The easiest way to quickly test FreqAI is to run it in dry run with the following command
+
+```bash
+freqtrade trade --config config_examples/config_freqai.example.json --strategy FreqaiExampleStrategy --freqaimodel LightGBMRegressor --strategy-path freqtrade/templates
+```
+
+where the user will see the boot-up process of auto-data downloading, followed by simultaneous training and trading.
+
+The example strategy, example prediction model, and example config can all be found in
+`freqtrade/templates/FreqaiExampleStrategy.py`, `freqtrade/freqai/prediction_models/LightGBMRegressor.py`,
+`config_examples/config_freqai.example.json`, respectively.
 
 ## General approach
 
@@ -30,7 +46,7 @@ An overview of the algorithm is shown here to help users understand the data pro
 ## Background and vocabulary
 
 **Features** are the quantities with which a model is trained. $X_i$ represents the
-vector of all features for a single candle. In Freqai, the user
+vector of all features for a single candle. In FreqAI, the user
 builds the features from anything they can construct in the strategy.
 
 **Labels** are the target values with which the weights inside a model are trained
@@ -50,7 +66,7 @@ directly influence nodal weights within the model.
 
 ## Install prerequisites
 
-Use `pip` to install the prerequisites with:
+The normal Freqtrade install process will ask the user if they wish to install `FreqAI` dependencies. The user should reply "yes" to this question if they wish to use FreqAI. If the user did not reply yes, they can manually install these dependencies after the install with:
 
 ``` bash
 pip install -r requirements-freqai.txt
@@ -59,18 +75,6 @@ pip install -r requirements-freqai.txt
 !!! Note
     Catboost will not be installed on arm devices (raspberry, Mac M1, ARM based VPS, ...), since Catboost does not provide wheels for this platform.
 
-## Running from the example files
-
-An example strategy, an example prediction model, and example config can all be found in
-`freqtrade/templates/FreqaiExampleStrategy.py`, `freqtrade/freqai/prediction_models/LightGBMRegressor.py`,
-`config_examples/config_freqai.example.json`, respectively.
-
-Assuming the user has downloaded the necessary data, Freqai can be executed from these templates with:
-
-```bash
-freqtrade backtesting --config config_examples/config_freqai.example.json --strategy FreqaiExampleStrategy --freqaimodel LightGBMRegressor --strategy-path freqtrade/templates --timerange 20220101-20220201
-```
-
 ## Configuring the bot
 
 ### Parameter table
@@ -92,13 +96,13 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `purge_old_models` | Tell FreqAI to delete obsolete models. Otherwise, all historic models will remain on disk. Defaults to `False`. <br> **Datatype:** boolean.
 | `expiration_hours` | Ask FreqAI to avoid making predictions if a model is more than `expiration_hours` old. Defaults to 0 which means models never expire. <br> **Datatype:** positive integer.
 |  |  **Feature Parameters**
-| `feature_parameters` | A dictionary containing the parameters used to engineer the feature set. Details and examples shown [here](#building-the-feature-set) <br> **Datatype:** dictionary.
+| `feature_parameters` | A dictionary containing the parameters used to engineer the feature set. Details and examples shown [here](#feature-engineering) <br> **Datatype:** dictionary.
 | `include_corr_pairlist` | A list of correlated coins that FreqAI will add as additional features to all `pair_whitelist` coins. All indicators set in `populate_any_indicators` will be created for each coin in this list, and that set of features is added to the base asset feature set. <br> **Datatype:** list of assets (strings).
 | `include_timeframes` | A list of timeframes that all indicators in `populate_any_indicators` will be created for and added as features to the base asset feature set. <br> **Datatype:** list of timeframes (strings).
 | `label_period_candles` | Number of candles into the future that the labels are created for. This is used in `populate_any_indicators`, refer to `templates/FreqaiExampleStrategy.py` for detailed usage. The user can create custom labels, making use of this parameter not. <br> **Datatype:** positive integer.
 | `include_shifted_candles` | Parameter used to add a sense of temporal recency to flattened regression type input data. `include_shifted_candles` takes all features, duplicates and shifts them by the number indicated by user. <br> **Datatype:** positive integer.
 | `DI_threshold` | Activates the Dissimilarity Index for outlier detection when above 0, explained more [here](#removing-outliers-with-the-dissimilarity-index). <br> **Datatype:** positive float (typically below 1).
-| `weight_factor` | Used to set weights for training data points according to their recency, see details and a figure of how it works [here](##controlling-the-model-learning-process). <br> **Datatype:** positive float (typically below 1).
+| `weight_factor` | Used to set weights for training data points according to their recency, see details and a figure of how it works [here](#controlling-the-model-learning-process). <br> **Datatype:** positive float (typically below 1).
 | `principal_component_analysis` | Ask FreqAI to automatically reduce the dimensionality of the data set using PCA. <br> **Datatype:** boolean.
 | `use_SVM_to_remove_outliers` | Ask FreqAI to train a support vector machine to detect and remove outliers from the training data set as well as from incoming data points. <br> **Datatype:** boolean.
 | `svm_params` | All parameters available in Sklearn's `SGDOneClassSVM()`. E.g. `nu` *Very* broadly, is the percentage of data points that should be considered outliers. `shuffle` is by default false to maintain reprodicibility. But these and all others can be added/changed in this dictionary. <br> **Datatype:** dictionary.
@@ -133,8 +137,8 @@ Here are the values the user can expect to include/use inside the typical strate
 
 ### Example config file
 
-The user interface is isolated to the typical config file. A typical Freqai
-config setup includes:
+The user interface is isolated to the typical config file. A typical FreqAI
+config setup could include:
 
 ```json
     "freqai": {
@@ -169,7 +173,7 @@ config setup includes:
         }
 ```
 
-### Building the feature set
+### Feature engineering
 
 Features are added by the user inside the `populate_any_indicators()` method of the strategy 
 by prepending indicators with `%` and labels are added by prepending `&`.  
@@ -182,7 +186,7 @@ various configuration parameters which multiply the feature set such as `include
 
 ```python
     def populate_any_indicators(
-        self, metadata, pair, df, tf, informative=None, coin="", set_generalized_indicators=False
+        self, pair, df, tf, informative=None, set_generalized_indicators=False
     ):
         """
         Function designed to automatically generate, name and merge features
@@ -198,6 +202,8 @@ various configuration parameters which multiply the feature set such as `include
         :param coin: the name of the coin which will modify the feature names.
         """
 
+        coint = pair.split('/')[0]
+
         with self.freqai.lock:
             if informative is None:
                 informative = self.dp.get_pair_dataframe(pair, tf)
@@ -265,7 +271,7 @@ various configuration parameters which multiply the feature set such as `include
         return df
 ```
 
-The user of the present example does not want to pass the `bb_lowerband` as a feature to the model,
+The user of the present example does not wish to pass the `bb_lowerband` as a feature to the model,
 and has therefore not prepended it with `%`. The user does, however, wish to pass `bb_width` to the
 model for training/prediction and has therefore prepended it with `%`.
 
@@ -313,7 +319,7 @@ set will include all the features from `populate_any_indicators` on all the `inc
 
 `include_shifted_candles` is another user controlled parameter which indicates the number of previous
 candles to include in the present feature set. In other words, `include_shifted_candles: 2`, tells
-Freqai to include the the past 2 candles for each of the features included in the dataset.
+FreqAI to include the the past 2 candles for each of the features included in the dataset.
 
 In total, the number of features the present user has created is:
 
@@ -326,12 +332,12 @@ Users define the backtesting timerange with the typical `--timerange` parameter
 configuration file. `train_period_days` is the duration of the sliding training window, while
 `backtest_period_days` is the sliding backtesting window, both in number of days (`backtest_period_days` can be
 a float to indicate sub daily retraining in live/dry mode). In the present example,
-the user is asking Freqai to use a training period of 30 days and backtest the subsequent 7 days.
+the user is asking FreqAI to use a training period of 30 days and backtest the subsequent 7 days.
 This means that if the user sets `--timerange 20210501-20210701`,
-Freqai will train 8 separate models (because the full range comprises 8 weeks),
+FreqAI will train 8 separate models (because the full range comprises 8 weeks),
 and then backtest the subsequent week associated with each of the 8 training
 data set timerange months. Users can think of this as a "sliding window" which
-emulates Freqai retraining itself once per week in live using the previous
+emulates FreqAI retraining itself once per week in live using the previous
 month of data.
 
 In live, the required training data is automatically computed and downloaded. However, in backtesting
@@ -349,16 +355,18 @@ and adding this to the `train_period_days`. The units need to be in the base can
 !!! Note
     Although fractional `backtest_period_days` is allowed, the user should be ware that the `--timerange` is divided by this value to determine the number of models that FreqAI will need to train in order to backtest the full range. For example, if the user wants to set a `--timerange` of 10 days, and asks for a `backtest_period_days` of 0.1, FreqAI will need to train 100 models per pair to complete the full backtest. This is why it is physically impossible to truly backtest FreqAI adaptive training. The best way to fully test a model is to run it dry and let it constantly train. In this case, backtesting would take the exact same amount of time as a dry run.
 
-## Running Freqai
+## Running FreqAI
 
-### Training and backtesting
+### Backtesting
 
-The freqai training/backtesting module can be executed with the following command:
+The FreqAI backtesting module can be executed with the following command:
 
 ```bash
 freqtrade backtesting --strategy FreqaiExampleStrategy --config config_freqai.example.json --freqaimodel LightGBMRegressor --timerange 20210501-20210701
 ```
 
+Backtesting mode requires the user to have the data pre-downloaded (unlike dry/live, where FreqAI automatically downloads the necessary data). The user should be careful to consider that the range of the downloaded data is more than the backtesting range. This is because FreqAI needs data prior to the desired backtesting range in order to train a model to be ready to make predictions on the first candle of the user set backtesting range. More details on how to calculate the data download timerange can be found [here](#deciding-the-sliding-training-window-and-backtesting-duration).
+
 If this command has never been executed with the existing config file, then it will train a new model
 for each pair, for each backtesting window within the bigger `--timerange`.
 
@@ -374,7 +382,7 @@ for each pair, for each backtesting window within the bigger `--timerange`.
 
 ### Building a freqai strategy
 
-The Freqai strategy requires the user to include the following lines of code in the strategy:
+The FreqAI strategy requires the user to include the following lines of code in the strategy:
 
 ```python
 
@@ -419,21 +427,16 @@ FreqAI includes a the `CatboostClassifier` via the flag `--freqaimodel CatboostC
 df['&s-up_or_down'] = np.where( df["close"].shift(-100) > df["close"], 'up', 'down')
 ```
 
-### Building an IFreqaiModel
-
-FreqAI has multiple example prediction model based libraries such as `Catboost` regression (`freqai/prediction_models/CatboostRegressor.py`) and `LightGBM` regression. 
-However, users can customize and create their own prediction models using the `IFreqaiModel` class.
-Users are encouraged to inherit `train()` and `predict()` to let them customize various aspects of their training procedures.
 
 ### Running the model live
 
-Freqai can be run dry/live using the following command
+FreqAI can be run dry/live using the following command
 
 ```bash
-freqtrade trade --strategy FreqaiExampleStrategy --config config_freqai.example.json --freqaimodel ExamplePredictionModel
+freqtrade trade --strategy FreqaiExampleStrategy --config config_freqai.example.json --freqaimodel LightGBMRegressor
 ```
 
-By default, Freqai will not find find any existing models and will start by training a new one 
+By default, FreqAI will not find find any existing models and will start by training a new one 
 given the user configuration settings. Following training, it will use that model to make predictions on incoming candles until a new model is available. New models are typically generated as often as possible, with FreqAI managing an internal queue of the pairs to try and keep all models equally "young." FreqAI will always use the newest trained model to make predictions on incoming live data. If users do not want FreqAI to retrain new models as often as possible, they can set `live_retrain_hours` to tell FreqAI to wait at least that number of hours before retraining a new model. Additionally, users can set `expired_hours` to tell FreqAI to avoid making predictions on models aged over this number of hours. 
 
 If the user wishes to start dry/live from a backtested saved model, the user only needs to reuse
@@ -446,7 +449,7 @@ the same `identifier` parameter
     }
 ```
 
-In this case, although Freqai will initiate with a
+In this case, although FreqAI will initiate with a
 pre-trained model, it will still check to see how much time has elapsed since the model was trained,
 and if a full `live_retrain_hours` has elapsed since the end of the loaded model, FreqAI will self retrain. 
 
@@ -473,7 +476,7 @@ the user is asking for `labels` that are 24 candles in the future.
 ### Removing outliers with the Dissimilarity Index
 
 The Dissimilarity Index (DI) aims to quantify the uncertainty associated with each
-prediction by the model. To do so, Freqai measures the distance between each training
+prediction by the model. To do so, FreqAI measures the distance between each training
 data point and all other training data points:
 
 $$ d_{ab} = \sqrt{\sum_{j=1}^p(X_{a,j}-X_{b,j})^2} $$
@@ -679,6 +682,11 @@ database setup in a pandas dataframe and ready to be analyzed. Here is an exampl
 
         return
 ```
+## Building an IFreqaiModel
+
+FreqAI has multiple example prediction model based libraries such as `Catboost` regression (`freqai/prediction_models/CatboostRegressor.py`) and `LightGBM` regression. 
+However, users can customize and create their own prediction models using the `IFreqaiModel` class.
+Users are encouraged to inherit `train()` and `predict()` to let them customize various aspects of their training procedures.
 
 <!-- ## Dynamic target expectation
 

From e7cb1b73753ad412d20e2cad58b76326c15e7ce7 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Wed, 10 Aug 2022 11:26:06 +0000
Subject: [PATCH 115/132] Wrap Precise into  FtPecise

---
 freqtrade/exchange/exchange.py      |  9 ++---
 freqtrade/util/__init__.py          |  1 +
 freqtrade/util/ft_precise.py        |  9 +++++
 tests/exchange/test_ccxt_precise.py | 52 ++++++++++++++---------------
 4 files changed, 41 insertions(+), 30 deletions(-)
 create mode 100644 freqtrade/util/ft_precise.py

diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py
index 7eb71351e..2806a4f42 100644
--- a/freqtrade/exchange/exchange.py
+++ b/freqtrade/exchange/exchange.py
@@ -16,7 +16,7 @@ import arrow
 import ccxt
 import ccxt.async_support as ccxt_async
 from cachetools import TTLCache
-from ccxt import ROUND_DOWN, ROUND_UP, TICK_SIZE, TRUNCATE, Precise, decimal_to_precision
+from ccxt import ROUND_DOWN, ROUND_UP, TICK_SIZE, TRUNCATE, decimal_to_precision
 from pandas import DataFrame
 
 from freqtrade.constants import (DEFAULT_AMOUNT_RESERVE_PERCENT, NON_OPEN_EXCHANGE_STATES, BuySell,
@@ -32,6 +32,7 @@ from freqtrade.exchange.common import (API_FETCH_ORDER_RETRY_COUNT, BAD_EXCHANGE
                                        retrier_async)
 from freqtrade.misc import chunks, deep_merge_dicts, safe_value_fallback2
 from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
+from freqtrade.util import FtPrecise
 
 
 CcxtModuleType = Any
@@ -708,10 +709,10 @@ class Exchange:
             #                                    counting_mode=self.precisionMode,
             #                                    ))
             if self.precisionMode == TICK_SIZE:
-                precision = Precise(str(self.markets[pair]['precision']['price']))
-                price_str = Precise(str(price))
+                precision = FtPrecise(str(self.markets[pair]['precision']['price']))
+                price_str = FtPrecise(str(price))
                 missing = price_str % precision
-                if not missing == Precise("0"):
+                if not missing == FtPrecise("0"):
                     price = round(float(str(price_str - missing + precision)), 14)
             else:
                 symbol_prec = self.markets[pair]['precision']['price']
diff --git a/freqtrade/util/__init__.py b/freqtrade/util/__init__.py
index fc4d66380..7980b7ca2 100644
--- a/freqtrade/util/__init__.py
+++ b/freqtrade/util/__init__.py
@@ -1,2 +1,3 @@
 # flake8: noqa: F401
+from freqtrade.util.ft_precise import FtPrecise
 from freqtrade.util.periodic_cache import PeriodicCache
diff --git a/freqtrade/util/ft_precise.py b/freqtrade/util/ft_precise.py
new file mode 100644
index 000000000..9c79552c2
--- /dev/null
+++ b/freqtrade/util/ft_precise.py
@@ -0,0 +1,9 @@
+"""
+Slim wrapper around ccxt's Precise (string math)
+To have imports from freqtrade
+"""
+from ccxt import Precise
+
+
+class FtPrecise(Precise):
+    pass
diff --git a/tests/exchange/test_ccxt_precise.py b/tests/exchange/test_ccxt_precise.py
index 026adb4c1..770dde13c 100644
--- a/tests/exchange/test_ccxt_precise.py
+++ b/tests/exchange/test_ccxt_precise.py
@@ -1,14 +1,14 @@
-from ccxt import Precise
+from freqtrade.util import FtPrecise
 
 
-ws = Precise('-1.123e-6')
-ws = Precise('-1.123e-6')
-xs = Precise('0.00000002')
-ys = Precise('69696900000')
-zs = Precise('0')
+ws = FtPrecise('-1.123e-6')
+ws = FtPrecise('-1.123e-6')
+xs = FtPrecise('0.00000002')
+ys = FtPrecise('69696900000')
+zs = FtPrecise('0')
 
 
-def test_precise():
+def test_FtPrecise():
     assert ys * xs == '1393.938'
     assert xs * ys == '1393.938'
 
@@ -45,31 +45,31 @@ def test_precise():
     assert xs + zs == '0.00000002'
     assert ys + zs == '69696900000'
 
-    assert abs(Precise('-500.1')) == '500.1'
-    assert abs(Precise('213')) == '213'
+    assert abs(FtPrecise('-500.1')) == '500.1'
+    assert abs(FtPrecise('213')) == '213'
 
-    assert abs(Precise('-500.1')) == '500.1'
-    assert -Precise('213') == '-213'
+    assert abs(FtPrecise('-500.1')) == '500.1'
+    assert -FtPrecise('213') == '-213'
 
-    assert Precise('10.1') % Precise('0.5') == '0.1'
-    assert Precise('5550') % Precise('120') == '30'
+    assert FtPrecise('10.1') % FtPrecise('0.5') == '0.1'
+    assert FtPrecise('5550') % FtPrecise('120') == '30'
 
-    assert Precise('-0.0') == Precise('0')
-    assert Precise('5.534000') == Precise('5.5340')
+    assert FtPrecise('-0.0') == FtPrecise('0')
+    assert FtPrecise('5.534000') == FtPrecise('5.5340')
 
-    assert min(Precise('-3.1415'), Precise('-2')) == '-3.1415'
+    assert min(FtPrecise('-3.1415'), FtPrecise('-2')) == '-3.1415'
 
-    assert max(Precise('3.1415'), Precise('-2')) == '3.1415'
+    assert max(FtPrecise('3.1415'), FtPrecise('-2')) == '3.1415'
 
-    assert Precise('2') > Precise('1.2345')
-    assert not Precise('-3.1415') > Precise('-2')
-    assert not Precise('3.1415') > Precise('3.1415')
-    assert Precise.string_gt('3.14150000000000000000001', '3.1415')
+    assert FtPrecise('2') > FtPrecise('1.2345')
+    assert not FtPrecise('-3.1415') > FtPrecise('-2')
+    assert not FtPrecise('3.1415') > FtPrecise('3.1415')
+    assert FtPrecise.string_gt('3.14150000000000000000001', '3.1415')
 
-    assert Precise('3.1415') >= Precise('3.1415')
-    assert Precise('3.14150000000000000000001') >= Precise('3.1415')
+    assert FtPrecise('3.1415') >= FtPrecise('3.1415')
+    assert FtPrecise('3.14150000000000000000001') >= FtPrecise('3.1415')
 
-    assert not Precise('3.1415') < Precise('3.1415')
+    assert not FtPrecise('3.1415') < FtPrecise('3.1415')
 
-    assert Precise('3.1415') <= Precise('3.1415')
-    assert Precise('3.1415') <= Precise('3.14150000000000000000001')
+    assert FtPrecise('3.1415') <= FtPrecise('3.1415')
+    assert FtPrecise('3.1415') <= FtPrecise('3.14150000000000000000001')

From ed004236ce8310a722b5737c5647ee4232a45068 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Wed, 10 Aug 2022 11:29:04 +0000
Subject: [PATCH 116/132] Add float initializer to FtPrecise

---
 freqtrade/exchange/exchange.py      | 4 ++--
 freqtrade/util/ft_precise.py        | 7 +++++--
 tests/exchange/test_ccxt_precise.py | 5 +++++
 3 files changed, 12 insertions(+), 4 deletions(-)

diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py
index 2806a4f42..18598e92d 100644
--- a/freqtrade/exchange/exchange.py
+++ b/freqtrade/exchange/exchange.py
@@ -709,8 +709,8 @@ class Exchange:
             #                                    counting_mode=self.precisionMode,
             #                                    ))
             if self.precisionMode == TICK_SIZE:
-                precision = FtPrecise(str(self.markets[pair]['precision']['price']))
-                price_str = FtPrecise(str(price))
+                precision = FtPrecise(self.markets[pair]['precision']['price'])
+                price_str = FtPrecise(price)
                 missing = price_str % precision
                 if not missing == FtPrecise("0"):
                     price = round(float(str(price_str - missing + precision)), 14)
diff --git a/freqtrade/util/ft_precise.py b/freqtrade/util/ft_precise.py
index 9c79552c2..aba0517a9 100644
--- a/freqtrade/util/ft_precise.py
+++ b/freqtrade/util/ft_precise.py
@@ -1,9 +1,12 @@
 """
 Slim wrapper around ccxt's Precise (string math)
-To have imports from freqtrade
+To have imports from freqtrade - and support float initializers
 """
 from ccxt import Precise
 
 
 class FtPrecise(Precise):
-    pass
+    def __init__(self, number, decimals=None):
+        if not isinstance(number, str):
+            number = str(number)
+        super().__init__(number, decimals)
diff --git a/tests/exchange/test_ccxt_precise.py b/tests/exchange/test_ccxt_precise.py
index 770dde13c..8b599093f 100644
--- a/tests/exchange/test_ccxt_precise.py
+++ b/tests/exchange/test_ccxt_precise.py
@@ -73,3 +73,8 @@ def test_FtPrecise():
 
     assert FtPrecise('3.1415') <= FtPrecise('3.1415')
     assert FtPrecise('3.1415') <= FtPrecise('3.14150000000000000000001')
+
+    assert FtPrecise(213) == '213'
+    assert FtPrecise(-213) == '-213'
+    assert str(FtPrecise(-213)) == '-213'
+    assert FtPrecise(213.2) == '213.2'

From 2cae3c42e60f78502f120e5a3ccd662ee4b7c9ca Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Wed, 10 Aug 2022 17:43:06 +0200
Subject: [PATCH 117/132] remove trade database analyzer, clean up a bit

---
 docs/freqai.md                       |  66 ---------
 freqtrade/freqai/data_kitchen.py     | 202 +--------------------------
 freqtrade/freqai/freqai_interface.py |  20 ---
 3 files changed, 1 insertion(+), 287 deletions(-)

diff --git a/docs/freqai.md b/docs/freqai.md
index 9b2377557..c495ba24b 100644
--- a/docs/freqai.md
+++ b/docs/freqai.md
@@ -663,79 +663,13 @@ The user needs to set the standard dictionary in the config so FreqAI can return
 These values will likely be overridden by the user prediction model, but in the case where the user model has yet to set them, or needs
 a default initial value - this is the value that will be returned.
 
-## Analyzing the trade live database
 
-Users can analyze the live trade database by calling `analyze_trade_database()` in their custom prediction model. FreqAI already has the
-database setup in a pandas dataframe and ready to be analyzed. Here is an example usecase:
-
-```python
-    def analyze_trade_database(self, dk: FreqaiDataKitchen, pair: str) -> None:
-        """
-        User analyzes the trade database here and returns summary stats which will be passed back
-        to the strategy for reinforcement learning or for additional adaptive metrics for use
-        in entry/exit signals. Store these metrics in dk.data['extra_returns_per_train'] and
-        they will format themselves into the dataframe as an additional column in the user
-        strategy. User has access to the current trade database in dk.trade_database_df.
-        """
-        total_profit = dk.trade_database_df['close_profit_abs'].sum()
-        dk.data['extra_returns_per_train']['total_profit'] = total_profit
-
-        return
-```
 ## Building an IFreqaiModel
 
 FreqAI has multiple example prediction model based libraries such as `Catboost` regression (`freqai/prediction_models/CatboostRegressor.py`) and `LightGBM` regression. 
 However, users can customize and create their own prediction models using the `IFreqaiModel` class.
 Users are encouraged to inherit `train()` and `predict()` to let them customize various aspects of their training procedures.
 
-<!-- ## Dynamic target expectation
-
-The labels used for model training have a unique statistical distribution for each separate model training. 
-We can use this information to know if our current prediction is in the realm of what the model was trained on, 
-and if so, what is the statistical probability of the current prediction. With this information, we can
-make more informed prediction.
-FreqAI builds this label distribution and provides a quantile to the strategy, which can be optionally used as a
-dynamic threshold. The `target_quantile: X` means that X% of the labels are below this value. So setting:
-
-```json
-    "freqai": {
-        "feature_parameters" : {
-            "target_quantile": 0.9
-        }
-    }
-```
-
-Means the user will get back in the strategy the label threshold at which 90% of the labels were 
-below this value. An example usage in the strategy may look something like:
-
-```python
-
-    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-
-        # ... #
-
-        (
-            dataframe["prediction"],
-            dataframe["do_predict"],
-            dataframe["target_upper_quantile"],
-            dataframe["target_lower_quantile"],
-        ) = self.freqai.start(dataframe, metadata, self)
-
-        return dataframe
-
-    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-
-        buy_conditions = [
-            (dataframe["prediction"] > dataframe["target_upper_quantile"]) & (dataframe["do_predict"] == 1)
-        ]
-
-        if buy_conditions:
-            dataframe.loc[reduce(lambda x, y: x | y, buy_conditions), "buy"] = 1
-
-        return dataframe
-
-``` -->
-
 ## Additional information
 
 ### Common pitfalls
diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index adfd68c84..5e64d165d 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -2,9 +2,8 @@ import copy
 import datetime
 import logging
 import shutil
-import sqlite3
 from pathlib import Path
-from typing import Any, Dict, List, Optional, Tuple
+from typing import Any, Dict, List, Tuple
 
 import numpy as np
 import numpy.typing as npt
@@ -88,20 +87,6 @@ class FreqaiDataKitchen:
                 config["freqai"]["backtest_period_days"],
             )
 
-        self.database_path: Optional[Path] = None
-
-        if self.live:
-            db_url = self.config.get('db_url', None)
-            self.database_path = Path(db_url)
-            if 'sqlite' not in self.database_path.parts[0]:
-                self.database_path = None
-                logger.warning('FreqAI database analyzer only available for sqlite dbs. '
-                               ' FreqAI will still run, but user cannot use database analyzer.')
-            else:
-                self.database_name = Path(*self.database_path.parts[1:])
-
-        self.trade_database_df: DataFrame = pd.DataFrame()
-
         self.data['extra_returns_per_train'] = self.freqai_config.get('extra_returns_per_train', {})
         self.thread_count = self.freqai_config.get("data_kitchen_thread_count", -1)
         self.train_dates: DataFrame = pd.DataFrame()
@@ -1007,13 +992,6 @@ class FreqaiDataKitchen:
             f = spy.stats.norm.fit(self.data_dictionary["train_labels"][label])
             self.data["labels_mean"][label], self.data["labels_std"][label] = f[0], f[1]
 
-        # KEEPME incase we want to let user start to grab quantiles.
-        # upper_q = spy.stats.norm.ppf(self.freqai_config['feature_parameters'][
-        #                                                   'target_quantile'], *f)
-        # lower_q = spy.stats.norm.ppf(1 - self.freqai_config['feature_parameters'][
-        #                                                       'target_quantile'], *f)
-        # self.data["upper_quantile"] = upper_q
-        # self.data["lower_quantile"] = lower_q
         return
 
     def remove_features_from_df(self, dataframe: DataFrame) -> DataFrame:
@@ -1025,181 +1003,3 @@ class FreqaiDataKitchen:
             col for col in dataframe.columns if not col.startswith("%") or col.startswith("%%")
         ]
         return dataframe[to_keep]
-
-    def get_current_trade_database(self) -> None:
-
-        if self.database_path is None:
-            logger.warning('No trade database found. Skipping analysis.')
-            return
-
-        data = sqlite3.connect(self.database_name)
-        query = data.execute("SELECT * From trades")
-        cols = [column[0] for column in query.description]
-        df = pd.DataFrame.from_records(data=query.fetchall(), columns=cols)
-        self.trade_database_df = df.dropna(subset='close_date')
-        data.close()
-
-    def np_encoder(self, object):
-        if isinstance(object, np.generic):
-            return object.item()
-
-    # Functions containing useful data manipulation examples. but not actively in use.
-
-    # Possibly phasing these outlier removal methods below out in favor of
-    # use_SVM_to_remove_outliers (computationally more efficient and apparently higher performance).
-    # But these have good data manipulation examples, so keep them commented here for now.
-
-    # def determine_statistical_distributions(self) -> None:
-    #     from fitter import Fitter
-
-    #     logger.info('Determining best model for all features, may take some time')
-
-    #     def compute_quantiles(ft):
-    #         f = Fitter(self.data_dictionary["train_features"][ft],
-    #                    distributions=['gamma', 'cauchy', 'laplace',
-    #                                   'beta', 'uniform', 'lognorm'])
-    #         f.fit()
-    #         # f.summary()
-    #         dist = list(f.get_best().items())[0][0]
-    #         params = f.get_best()[dist]
-    #         upper_q = getattr(spy.stats, list(f.get_best().items())[0][0]).ppf(0.999, **params)
-    #         lower_q = getattr(spy.stats, list(f.get_best().items())[0][0]).ppf(0.001, **params)
-
-    #         return ft, upper_q, lower_q, dist
-
-    #     quantiles_tuple = Parallel(n_jobs=-1)(
-    #         delayed(compute_quantiles)(ft) for ft in self.data_dictionary[
-    #                                                       'train_features'].columns)
-
-    #     df = pd.DataFrame(quantiles_tuple, columns=['features', 'upper_quantiles',
-    #                                                 'lower_quantiles', 'dist'])
-    #     self.data_dictionary['upper_quantiles'] = df['upper_quantiles']
-    #     self.data_dictionary['lower_quantiles'] = df['lower_quantiles']
-
-    #     return
-
-    # def remove_outliers(self, predict: bool) -> None:
-    #     """
-    #     Remove data that looks like an outlier based on the distribution of each
-    #     variable.
-    #     :params:
-    #     :predict: boolean which tells the function if this is prediction data or
-    #     training data coming in.
-    #     """
-
-    #     lower_quantile = self.data_dictionary["lower_quantiles"].to_numpy()
-    #     upper_quantile = self.data_dictionary["upper_quantiles"].to_numpy()
-
-    #     if predict:
-
-    #         df = self.data_dictionary["prediction_features"][
-    #             (self.data_dictionary["prediction_features"] < upper_quantile)
-    #             & (self.data_dictionary["prediction_features"] > lower_quantile)
-    #         ]
-    #         drop_index = pd.isnull(df).any(1)
-    #         self.data_dictionary["prediction_features"].fillna(0, inplace=True)
-    #         drop_index = ~drop_index
-    #         do_predict = np.array(drop_index.replace(True, 1).replace(False, 0))
-
-    #         logger.info(
-    #             "remove_outliers() tossed %s predictions",
-    #             len(do_predict) - do_predict.sum(),
-    #         )
-    #         self.do_predict += do_predict
-    #         self.do_predict -= 1
-
-    #     else:
-
-    #         filter_train_df = self.data_dictionary["train_features"][
-    #             (self.data_dictionary["train_features"] < upper_quantile)
-    #             & (self.data_dictionary["train_features"] > lower_quantile)
-    #         ]
-    #         drop_index = pd.isnull(filter_train_df).any(1)
-    #         drop_index = drop_index.replace(True, 1).replace(False, 0)
-    #         self.data_dictionary["train_features"] = self.data_dictionary["train_features"][
-    #             (drop_index == 0)
-    #         ]
-    #         self.data_dictionary["train_labels"] = self.data_dictionary["train_labels"][
-    #             (drop_index == 0)
-    #         ]
-    #         self.data_dictionary["train_weights"] = self.data_dictionary["train_weights"][
-    #             (drop_index == 0)
-    #         ]
-
-    #         logger.info(
-    #             f'remove_outliers() tossed {drop_index.sum()}'
-    #             f' training points from {len(filter_train_df)}'
-    #         )
-
-    #         # do the same for the test data
-    #         filter_test_df = self.data_dictionary["test_features"][
-    #             (self.data_dictionary["test_features"] < upper_quantile)
-    #             & (self.data_dictionary["test_features"] > lower_quantile)
-    #         ]
-    #         drop_index = pd.isnull(filter_test_df).any(1)
-    #         drop_index = drop_index.replace(True, 1).replace(False, 0)
-    #         self.data_dictionary["test_labels"] = self.data_dictionary["test_labels"][
-    #             (drop_index == 0)
-    #         ]
-    #         self.data_dictionary["test_features"] = self.data_dictionary["test_features"][
-    #             (drop_index == 0)
-    #         ]
-    #         self.data_dictionary["test_weights"] = self.data_dictionary["test_weights"][
-    #             (drop_index == 0)
-    #         ]
-
-    #         logger.info(
-    #             f'remove_outliers() tossed {drop_index.sum()}'
-    #             f' test points from {len(filter_test_df)}'
-    #         )
-
-    #     return
-
-    # def standardize_data(self, data_dictionary: Dict) -> Dict[Any, Any]:
-    #     """
-    #     standardize all data in the data_dictionary according to the training dataset
-    #     :params:
-    #     :data_dictionary: dictionary containing the cleaned and split training/test data/labels
-    #     :returns:
-    #     :data_dictionary: updated dictionary with standardized values.
-    #     """
-    #     # standardize the data by training stats
-    #     train_mean = data_dictionary["train_features"].mean()
-    #     train_std = data_dictionary["train_features"].std()
-    #     data_dictionary["train_features"] = (
-    #         data_dictionary["train_features"] - train_mean
-    #     ) / train_std
-    #     data_dictionary["test_features"] = (
-    #         data_dictionary["test_features"] - train_mean
-    #     ) / train_std
-
-    #     train_labels_std = data_dictionary["train_labels"].std()
-    #     train_labels_mean = data_dictionary["train_labels"].mean()
-    #     data_dictionary["train_labels"] = (
-    #         data_dictionary["train_labels"] - train_labels_mean
-    #     ) / train_labels_std
-    #     data_dictionary["test_labels"] = (
-    #         data_dictionary["test_labels"] - train_labels_mean
-    #     ) / train_labels_std
-
-    #     for item in train_std.keys():
-    #         self.data[item + "_std"] = train_std[item]
-    #         self.data[item + "_mean"] = train_mean[item]
-
-    #     self.data["labels_std"] = train_labels_std
-    #     self.data["labels_mean"] = train_labels_mean
-
-    #     return data_dictionary
-
-    # def standardize_data_from_metadata(self, df: DataFrame) -> DataFrame:
-    # """
-    # Normalizes a set of data using the mean and standard deviation from
-    # the associated training data.
-    # :params:
-    # :df: Dataframe to be standardized
-    # """
-
-    # for item in df.keys():
-    #     df[item] = (df[item] - self.data[item + "_mean"]) / self.data[item + "_std"]
-
-    # return df
diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py
index 833fb50d6..0c32a625d 100644
--- a/freqtrade/freqai/freqai_interface.py
+++ b/freqtrade/freqai/freqai_interface.py
@@ -491,9 +491,6 @@ class IFreqaiModel(ABC):
 
         model = self.train(unfiltered_dataframe, pair, dk)
 
-        dk.get_current_trade_database()
-        self.analyze_trade_database(dk, pair)
-
         self.dd.pair_dict[pair]["trained_timestamp"] = new_trained_timerange.stopts
         dk.set_new_model_names(pair, new_trained_timerange)
         self.dd.pair_dict[pair]["first"] = False
@@ -612,20 +609,3 @@ class IFreqaiModel(ABC):
         :do_predict: np.array of 1s and 0s to indicate places where freqai needed to remove
         data (NaNs) or felt uncertain about data (i.e. SVM and/or DI index)
         """
-
-    def analyze_trade_database(self, dk: FreqaiDataKitchen, pair: str) -> None:
-        """
-        User analyzes the trade database here and returns summary stats which will be passed back
-        to the strategy for reinforcement learning or for additional adaptive metrics for use
-        in entry/exit signals. Store these metrics in dk.data['extra_returns_per_train'] and
-        they will format themselves into the dataframe as an additional column in the user
-        strategy. User has access to the current trade database in dk.trade_database_df.
-        """
-        # if dk.trade_database_df.empty:
-        #     logger.warning(f'No trades found for {pair} to analyze DB')
-        #     return
-
-        # total_profit = dk.trade_database_df['close_profit_abs'].sum()
-        # dk.data['extra_returns_per_train']['total_profit'] = total_profit
-
-        return

From f7502bcc923044a60d2bad31d5c3cd25ef12f56d Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Thu, 11 Aug 2022 11:35:24 +0000
Subject: [PATCH 118/132] slightly update dca_short test

---
 tests/test_integration.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/tests/test_integration.py b/tests/test_integration.py
index 40fdb4277..6a11b13f4 100644
--- a/tests/test_integration.py
+++ b/tests/test_integration.py
@@ -291,7 +291,7 @@ def test_dca_short(default_conf_usdt, ticker_usdt, fee, mocker) -> None:
         'freqtrade.exchange.Exchange',
         fetch_ticker=ticker_usdt,
         get_fee=fee,
-        amount_to_precision=lambda s, x, y: y,
+        amount_to_precision=lambda s, x, y: round(y, 4),
         price_to_precision=lambda s, x, y: y,
     )
 
@@ -303,6 +303,7 @@ def test_dca_short(default_conf_usdt, ticker_usdt, fee, mocker) -> None:
     assert len(trade.orders) == 1
     assert pytest.approx(trade.stake_amount) == 60
     assert trade.open_rate == 2.02
+    assert trade.orders[0].amount == trade.amount
     # No adjustment
     freqtrade.process()
     trade = Trade.get_trades().first()
@@ -331,8 +332,7 @@ def test_dca_short(default_conf_usdt, ticker_usdt, fee, mocker) -> None:
     trade = Trade.get_trades().first()
     assert len(trade.orders) == 2
     assert pytest.approx(trade.stake_amount) == 120
-    # assert trade.orders[0].amount == 30
-    assert trade.orders[1].amount == 60 / ticker_usdt_modif['ask']
+    assert trade.orders[1].amount == round(60 / ticker_usdt_modif['ask'], 4)
 
     assert trade.amount == trade.orders[0].amount + trade.orders[1].amount
     assert trade.nr_of_successful_entries == 2
@@ -344,7 +344,7 @@ def test_dca_short(default_conf_usdt, ticker_usdt, fee, mocker) -> None:
     assert trade.is_open is False
     # assert trade.orders[0].amount == 30
     assert trade.orders[0].side == 'sell'
-    assert trade.orders[1].amount == 60 / ticker_usdt_modif['ask']
+    assert trade.orders[1].amount == round(60 / ticker_usdt_modif['ask'], 4)
     # Sold everything
     assert trade.orders[-1].side == 'buy'
     assert trade.orders[2].amount == trade.amount

From dd4e44931e9a909ed5a6d04ab6e51ff26beb37c0 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Thu, 11 Aug 2022 15:02:52 +0000
Subject: [PATCH 119/132] Improve NAN handling in RPC module

---
 freqtrade/rpc/rpc.py  | 25 +++++++++++++++----------
 tests/rpc/test_rpc.py | 40 ----------------------------------------
 2 files changed, 15 insertions(+), 50 deletions(-)

diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py
index 9f2c8cf37..ede8a9d3c 100644
--- a/freqtrade/rpc/rpc.py
+++ b/freqtrade/rpc/rpc.py
@@ -239,12 +239,15 @@ class RPC:
                         trade.pair, side='exit', is_short=trade.is_short, refresh=False)
                 except (PricingError, ExchangeError):
                     current_rate = NAN
-                if len(trade.select_filled_orders(trade.entry_side)) > 0:
-                    trade_profit = trade.calc_profit(current_rate)
-                    profit_str = f'{trade.calc_profit_ratio(current_rate):.2%}'
+                    trade_profit = NAN
+                    profit_str = f'{NAN:.2%}'
                 else:
-                    trade_profit = 0.0
-                    profit_str = f'{0.0:.2f}'
+                    if trade.nr_of_successful_entries > 0:
+                        trade_profit = trade.calc_profit(current_rate)
+                        profit_str = f'{trade.calc_profit_ratio(current_rate):.2%}'
+                    else:
+                        trade_profit = 0.0
+                        profit_str = f'{0.0:.2f}'
                 direction_str = ('S' if trade.is_short else 'L') if nonspot else ''
                 if self._fiat_converter:
                     fiat_profit = self._fiat_converter.convert_amount(
@@ -424,8 +427,6 @@ class RPC:
         for trade in trades:
             current_rate: float = 0.0
 
-            if not trade.open_rate:
-                continue
             if trade.close_date:
                 durations.append((trade.close_date - trade.open_date).total_seconds())
 
@@ -447,9 +448,13 @@ class RPC:
                         trade.pair, side='exit', is_short=trade.is_short, refresh=False)
                 except (PricingError, ExchangeError):
                     current_rate = NAN
-                profit_ratio = trade.calc_profit_ratio(rate=current_rate)
-                profit_abs = trade.calc_profit(
-                    rate=trade.close_rate or current_rate) + trade.realized_profit
+                if isnan(current_rate):
+                    profit_ratio = NAN
+                    profit_abs = NAN
+                else:
+                    profit_ratio = trade.calc_profit_ratio(rate=current_rate)
+                    profit_abs = trade.calc_profit(
+                        rate=trade.close_rate or current_rate) + trade.realized_profit
 
             profit_all_coin.append(profit_abs)
             profit_all_ratio.append(profit_ratio)
diff --git a/tests/rpc/test_rpc.py b/tests/rpc/test_rpc.py
index 4c580c3c2..1a2428fe7 100644
--- a/tests/rpc/test_rpc.py
+++ b/tests/rpc/test_rpc.py
@@ -461,46 +461,6 @@ def test_rpc_trade_statistics(default_conf_usdt, ticker, fee, mocker) -> None:
     assert isnan(stats['profit_all_coin'])
 
 
-# Test that rpc_trade_statistics can handle trades that lacks
-# trade.open_rate (it is set to None)
-def test_rpc_trade_statistics_closed(mocker, default_conf_usdt, ticker, fee):
-    mocker.patch('freqtrade.rpc.fiat_convert.CryptoToFiatConverter._find_price',
-                 return_value=1.1)
-    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
-        get_fee=fee,
-    )
-
-    freqtradebot = get_patched_freqtradebot(mocker, default_conf_usdt)
-    patch_get_signal(freqtradebot)
-    stake_currency = default_conf_usdt['stake_currency']
-    fiat_display_currency = default_conf_usdt['fiat_display_currency']
-
-    rpc = RPC(freqtradebot)
-
-    # Create some test data
-    create_mock_trades_usdt(fee)
-
-    for trade in Trade.query.order_by(Trade.id).all():
-        trade.open_rate = None
-
-    stats = rpc._rpc_trade_statistics(stake_currency, fiat_display_currency)
-    assert stats['profit_closed_coin'] == 0
-    assert stats['profit_closed_percent_mean'] == 0
-    assert stats['profit_closed_fiat'] == 0
-    assert stats['profit_all_coin'] == 0
-    assert stats['profit_all_percent_mean'] == 0
-    assert stats['profit_all_fiat'] == 0
-    assert stats['trade_count'] == 7
-    assert stats['first_trade_date'] == '2 days ago'
-    assert stats['latest_trade_date'] == '17 minutes ago'
-    assert stats['avg_duration'] == '0:00:00'
-    assert stats['best_pair'] == 'XRP/USDT'
-    assert stats['best_rate'] == 10.0
-
-
 def test_rpc_balance_handle_error(default_conf, mocker):
     mock_balance = {
         'BTC': {

From de690b0a698f6c65ce1e4cebb6b2fc673df9b3af Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Thu, 11 Aug 2022 20:08:40 +0200
Subject: [PATCH 120/132] Use PEP440 compatible versioning

---
 freqtrade/__init__.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/freqtrade/__init__.py b/freqtrade/__init__.py
index f8be8f66f..2572c03f1 100644
--- a/freqtrade/__init__.py
+++ b/freqtrade/__init__.py
@@ -1,5 +1,5 @@
 """ Freqtrade bot """
-__version__ = 'develop'
+__version__ = '2022.8.dev'
 
 if 'dev' in __version__:
     try:

From cc885e25ac048cba4df69b8a2bd8787d728dd69d Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Thu, 11 Aug 2022 20:16:07 +0200
Subject: [PATCH 121/132] Improve NAN Handling in RPC

---
 freqtrade/rpc/rpc.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py
index ede8a9d3c..ed7f13a96 100644
--- a/freqtrade/rpc/rpc.py
+++ b/freqtrade/rpc/rpc.py
@@ -179,8 +179,10 @@ class RPC:
                 else:
                     current_rate = trade.close_rate
                 if len(trade.select_filled_orders(trade.entry_side)) > 0:
-                    current_profit = trade.calc_profit_ratio(current_rate)
-                    current_profit_abs = trade.calc_profit(current_rate)
+                    current_profit = trade.calc_profit_ratio(
+                        current_rate) if not isnan(current_rate) else NAN
+                    current_profit_abs = trade.calc_profit(
+                        current_rate) if not isnan(current_rate) else NAN
                     current_profit_fiat: Optional[float] = None
                     # Calculate fiat profit
                     if self._fiat_converter:

From aa1bf2adbd0b0f1796b7ad734123cea173bd43aa Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Fri, 12 Aug 2022 06:43:34 +0200
Subject: [PATCH 122/132] Try fix windows testfailure

---
 tests/plugins/test_protections.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/tests/plugins/test_protections.py b/tests/plugins/test_protections.py
index 4cebb6492..07541735d 100644
--- a/tests/plugins/test_protections.py
+++ b/tests/plugins/test_protections.py
@@ -335,6 +335,7 @@ def test_LowProfitPairs(mocker, default_conf, fee, caplog, only_per_side):
         'XRP/BTC', fee.return_value, False, exit_reason=ExitType.STOP_LOSS.value,
         min_ago_open=110, min_ago_close=20, profit_rate=0.8,
     ))
+    Trade.commit()
 
     # Locks due to 2nd trade
     assert freqtrade.protections.global_stop() != only_per_side
@@ -342,6 +343,7 @@ def test_LowProfitPairs(mocker, default_conf, fee, caplog, only_per_side):
     assert PairLocks.is_pair_locked('XRP/BTC', side='long')
     assert PairLocks.is_pair_locked('XRP/BTC', side='*') != only_per_side
     assert not PairLocks.is_global_lock()
+    Trade.commit()
 
 
 @pytest.mark.usefixtures("init_persistence")

From d93bb82193fed27d255bb5386e2c6b31c7702bca Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Fri, 12 Aug 2022 08:19:40 +0200
Subject: [PATCH 123/132] Add more Commits to failing test

---
 tests/plugins/test_protections.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/tests/plugins/test_protections.py b/tests/plugins/test_protections.py
index 07541735d..7a21b2ed6 100644
--- a/tests/plugins/test_protections.py
+++ b/tests/plugins/test_protections.py
@@ -305,6 +305,7 @@ def test_LowProfitPairs(mocker, default_conf, fee, caplog, only_per_side):
         min_ago_open=800, min_ago_close=450, profit_rate=0.9,
     ))
 
+    Trade.commit()
     # Not locked with 1 trade
     assert not freqtrade.protections.global_stop()
     assert not freqtrade.protections.stop_per_pair('XRP/BTC')
@@ -316,6 +317,7 @@ def test_LowProfitPairs(mocker, default_conf, fee, caplog, only_per_side):
         min_ago_open=200, min_ago_close=120, profit_rate=0.9,
     ))
 
+    Trade.commit()
     # Not locked with 1 trade (first trade is outside of lookback_period)
     assert not freqtrade.protections.global_stop()
     assert not freqtrade.protections.stop_per_pair('XRP/BTC')
@@ -327,6 +329,7 @@ def test_LowProfitPairs(mocker, default_conf, fee, caplog, only_per_side):
         'XRP/BTC', fee.return_value, False, exit_reason=ExitType.ROI.value,
         min_ago_open=20, min_ago_close=10, profit_rate=1.15, is_short=True
     ))
+    Trade.commit()
     assert freqtrade.protections.stop_per_pair('XRP/BTC') != only_per_side
     assert not PairLocks.is_pair_locked('XRP/BTC', side='*')
     assert PairLocks.is_pair_locked('XRP/BTC', side='long') == only_per_side

From b427c7ff136fb017d75eb5f59b8adf98dfb306ac Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Fri, 12 Aug 2022 07:28:19 +0000
Subject: [PATCH 124/132] Use diff. close time to avoid buggy behavior

---
 tests/plugins/test_protections.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/plugins/test_protections.py b/tests/plugins/test_protections.py
index 7a21b2ed6..8a5356b3e 100644
--- a/tests/plugins/test_protections.py
+++ b/tests/plugins/test_protections.py
@@ -336,7 +336,7 @@ def test_LowProfitPairs(mocker, default_conf, fee, caplog, only_per_side):
 
     Trade.query.session.add(generate_mock_trade(
         'XRP/BTC', fee.return_value, False, exit_reason=ExitType.STOP_LOSS.value,
-        min_ago_open=110, min_ago_close=20, profit_rate=0.8,
+        min_ago_open=110, min_ago_close=21, profit_rate=0.8,
     ))
     Trade.commit()
 

From fb4b73ce8961dd9db34ad5b94d7484ca80ffc06b Mon Sep 17 00:00:00 2001
From: robcaulk <rob.caulk@gmail.com>
Date: Fri, 12 Aug 2022 12:03:44 +0200
Subject: [PATCH 125/132] ensure dates are saved

---
 freqtrade/freqai/data_kitchen.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index 5e64d165d..0cff9c90e 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -202,7 +202,7 @@ class FreqaiDataKitchen:
             labels = unfiltered_dataframe.filter(label_list, axis=1)
             drop_index_labels = pd.isnull(labels).any(1)
             drop_index_labels = drop_index_labels.replace(True, 1).replace(False, 0)
-            dates = unfiltered_dataframe.filter('date', axis=1)
+            dates = unfiltered_dataframe['date']
             filtered_dataframe = filtered_dataframe[
                 (drop_index == 0) & (drop_index_labels == 0)
             ]  # dropping values

From f6545ebdb8a82cedce065779873d395631aff07f Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 13 Aug 2022 09:10:03 +0200
Subject: [PATCH 126/132] Disallow backtesting with --strategy-list for now.

---
 freqtrade/optimize/backtesting.py      |  3 +++
 tests/freqai/test_freqai_backtsting.py | 33 ++++++++++++++++++++++++++
 2 files changed, 36 insertions(+)
 create mode 100644 tests/freqai/test_freqai_backtsting.py

diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py
index 86c1822f7..c00f30686 100644
--- a/freqtrade/optimize/backtesting.py
+++ b/freqtrade/optimize/backtesting.py
@@ -89,6 +89,9 @@ class Backtesting:
         self.dataprovider = DataProvider(self.config, self.exchange)
 
         if self.config.get('strategy_list'):
+            if self.config.get('freqai'):
+                raise OperationalException(
+                    "You can't use strategy_list and freqai at the same time.")
             for strat in list(self.config['strategy_list']):
                 stratconf = deepcopy(self.config)
                 stratconf['strategy'] = strat
diff --git a/tests/freqai/test_freqai_backtsting.py b/tests/freqai/test_freqai_backtsting.py
new file mode 100644
index 000000000..bb0a71e2c
--- /dev/null
+++ b/tests/freqai/test_freqai_backtsting.py
@@ -0,0 +1,33 @@
+from pathlib import Path
+from unittest.mock import PropertyMock
+
+import pytest
+
+from freqtrade.commands.optimize_commands import start_backtesting
+from freqtrade.exceptions import OperationalException
+from tests.conftest import (CURRENT_TEST_STRATEGY, get_args, patch_exchange,
+                            patched_configuration_load_config_file)
+
+
+def test_backtest_start_backtest_list_freqai(freqai_conf, mocker, testdatadir):
+    # Tests detail-data loading
+    patch_exchange(mocker)
+
+    mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist',
+                 PropertyMock(return_value=['HULUMULU/USDT', 'XRP/USDT']))
+    # mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', backtestmock)
+
+    patched_configuration_load_config_file(mocker, freqai_conf)
+
+    args = [
+        'backtesting',
+        '--config', 'config.json',
+        '--datadir', str(testdatadir),
+        '--strategy-path', str(Path(__file__).parents[1] / 'strategy/strats'),
+        '--timeframe', '1h',
+        '--strategy-list', CURRENT_TEST_STRATEGY
+    ]
+    args = get_args(args)
+    with pytest.raises(OperationalException,
+                       match=r"You can't use strategy_list and freqai at the same time\."):
+        start_backtesting(args)

From 49989012abae22740a6a65ccc5ba2685c036aa91 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 13 Aug 2022 09:20:58 +0200
Subject: [PATCH 127/132] Bump catboost requirement to latest

---
 requirements-freqai.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements-freqai.txt b/requirements-freqai.txt
index 5e67a5539..26e4617af 100644
--- a/requirements-freqai.txt
+++ b/requirements-freqai.txt
@@ -4,5 +4,5 @@
 # Required for freqai
 scikit-learn==1.1.2
 joblib==1.1.0
-catboost==1.0.4; platform_machine != 'aarch64'
+catboost==1.0.6; platform_machine != 'aarch64'
 lightgbm==3.3.2

From 3b827ee60a6f9194c825a7ee472bfbc4815e4fe6 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 13 Aug 2022 09:24:04 +0200
Subject: [PATCH 128/132] Add "freqai.enabled" flag to disable freqAI via
 config flag

aligns with how other optional modules work in freqtrade.
---
 config_examples/config_freqai.example.json     |  1 +
 freqtrade/constants.py                         | 16 ++++++++++------
 freqtrade/optimize/backtesting.py              |  4 ++--
 freqtrade/plugins/pairlist/pairlist_helpers.py |  2 +-
 freqtrade/strategy/interface.py                |  2 +-
 tests/freqai/conftest.py                       |  1 +
 6 files changed, 16 insertions(+), 10 deletions(-)

diff --git a/config_examples/config_freqai.example.json b/config_examples/config_freqai.example.json
index e9fc50a4a..aeb1cb13d 100644
--- a/config_examples/config_freqai.example.json
+++ b/config_examples/config_freqai.example.json
@@ -52,6 +52,7 @@
         }
     ],
     "freqai": {
+        "enabled": true,
         "startup_candles": 10000,
         "purge_old_models": true,
         "train_period_days": 15,
diff --git a/freqtrade/constants.py b/freqtrade/constants.py
index b5d6b4b8e..ddbc84fa9 100644
--- a/freqtrade/constants.py
+++ b/freqtrade/constants.py
@@ -486,6 +486,7 @@ CONF_SCHEMA = {
         "freqai": {
             "type": "object",
             "properties": {
+                "enabled": {"type": "boolean", "default": False},
                 "keras": {"type": "boolean", "default": False},
                 "conv_width": {"type": "integer", "default": 2},
                 "train_period_days": {"type": "integer", "default": 0},
@@ -525,12 +526,15 @@ CONF_SCHEMA = {
                     },
                 },
             },
-            "required": ["train_period_days",
-                         "backtest_period_days",
-                         "identifier",
-                         "feature_parameters",
-                         "data_split_parameters",
-                         "model_training_parameters"]
+            "required": [
+                "enabled",
+                "train_period_days",
+                "backtest_period_days",
+                "identifier",
+                "feature_parameters",
+                "data_split_parameters",
+                "model_training_parameters"
+                ]
         },
     },
 }
diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py
index c00f30686..7691b96f1 100644
--- a/freqtrade/optimize/backtesting.py
+++ b/freqtrade/optimize/backtesting.py
@@ -89,7 +89,7 @@ class Backtesting:
         self.dataprovider = DataProvider(self.config, self.exchange)
 
         if self.config.get('strategy_list'):
-            if self.config.get('freqai'):
+            if self.config.get('freqai', {}).get('enabled', False):
                 raise OperationalException(
                     "You can't use strategy_list and freqai at the same time.")
             for strat in list(self.config['strategy_list']):
@@ -210,7 +210,7 @@ class Backtesting:
         """
         self.progress.init_step(BacktestState.DATALOAD, 1)
 
-        if self.config.get('freqai') is not None:
+        if self.config.get('freqai', {}).get('enabled', False):
             startup_candles = int(self.config.get('freqai', {}).get('startup_candles', 0))
             if not startup_candles:
                 raise OperationalException('FreqAI backtesting module requires user set '
diff --git a/freqtrade/plugins/pairlist/pairlist_helpers.py b/freqtrade/plugins/pairlist/pairlist_helpers.py
index a07a0f783..f1eca6df0 100644
--- a/freqtrade/plugins/pairlist/pairlist_helpers.py
+++ b/freqtrade/plugins/pairlist/pairlist_helpers.py
@@ -44,7 +44,7 @@ def expand_pairlist(wildcardpl: List[str], available_pairs: List[str],
 
 def dynamic_expand_pairlist(config: dict, markets: list) -> List[str]:
     expanded_pairs = expand_pairlist(config['pairs'], markets)
-    if config.get('freqai', {}):
+    if config.get('freqai', {}).get('enabled', False):
         corr_pairlist = config['freqai']['feature_parameters']['include_corr_pairlist']
         expanded_pairs += [pair for pair in corr_pairlist
                            if pair not in config['pairs']]
diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py
index cda8a1cbc..d10699e3b 100644
--- a/freqtrade/strategy/interface.py
+++ b/freqtrade/strategy/interface.py
@@ -146,7 +146,7 @@ class IStrategy(ABC, HyperStrategyMixin):
                 self._ft_informative.append((informative_data, cls_method))
 
     def load_freqAI_model(self) -> None:
-        if self.config.get('freqai', None):
+        if self.config.get('freqai', {}).get('enabled', False):
             # Import here to avoid importing this if freqAI is disabled
             from freqtrade.resolvers.freqaimodel_resolver import FreqaiModelResolver
 
diff --git a/tests/freqai/conftest.py b/tests/freqai/conftest.py
index ee02cc097..63f3ef2c7 100644
--- a/tests/freqai/conftest.py
+++ b/tests/freqai/conftest.py
@@ -17,6 +17,7 @@ def freqai_conf(default_conf, tmpdir):
     freqaiconf = deepcopy(default_conf)
     freqaiconf.update(
         {
+            "enabled": True,
             "datadir": Path(default_conf["datadir"]),
             "strategy": "freqai_test_strat",
             "user_data_dir": Path(tmpdir),

From 3918f4abbd7ed975e113477f09bd231ceb8f2fab Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 13 Aug 2022 09:27:56 +0200
Subject: [PATCH 129/132] Simplify strategy interface by removing explicit
 self.freqai_info assignment

---
 docs/freqai.md                               | 2 --
 freqtrade/strategy/interface.py              | 1 +
 freqtrade/templates/FreqaiExampleStrategy.py | 2 --
 3 files changed, 1 insertion(+), 4 deletions(-)

diff --git a/docs/freqai.md b/docs/freqai.md
index c495ba24b..eb76ab1a4 100644
--- a/docs/freqai.md
+++ b/docs/freqai.md
@@ -401,8 +401,6 @@ The FreqAI strategy requires the user to include the following lines of code in
 
     def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
 
-        self.freqai_info = self.config["freqai"]
-
         # All indicators must be populated by populate_any_indicators() for live functionality
         # to work correctly.
 
diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py
index d10699e3b..760d852c4 100644
--- a/freqtrade/strategy/interface.py
+++ b/freqtrade/strategy/interface.py
@@ -151,6 +151,7 @@ class IStrategy(ABC, HyperStrategyMixin):
             from freqtrade.resolvers.freqaimodel_resolver import FreqaiModelResolver
 
             self.freqai = FreqaiModelResolver.load_freqaimodel(self.config)
+            self.freqai_info = self.config["freqai"]
 
     def ft_bot_start(self, **kwargs) -> None:
         """
diff --git a/freqtrade/templates/FreqaiExampleStrategy.py b/freqtrade/templates/FreqaiExampleStrategy.py
index 01f947a6a..d8584d5f9 100644
--- a/freqtrade/templates/FreqaiExampleStrategy.py
+++ b/freqtrade/templates/FreqaiExampleStrategy.py
@@ -180,8 +180,6 @@ class FreqaiExampleStrategy(IStrategy):
 
     def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
 
-        self.freqai_info = self.config["freqai"]
-
         # All indicators must be populated by populate_any_indicators() for live functionality
         # to work correctly.
 

From c190d57f1a67ffd3a6735365bbe3ee592c445a6e Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 13 Aug 2022 09:48:59 +0200
Subject: [PATCH 130/132] Test populate_any_indicator interface

---
 tests/strategy/test_interface.py | 12 ++++++++++++
 1 file changed, 12 insertions(+)

diff --git a/tests/strategy/test_interface.py b/tests/strategy/test_interface.py
index 4257b2cf9..8b4ba5f03 100644
--- a/tests/strategy/test_interface.py
+++ b/tests/strategy/test_interface.py
@@ -290,6 +290,18 @@ def test_advise_all_indicators(default_conf, testdatadir) -> None:
     assert len(processed['UNITTEST/BTC']) == 102  # partial candle was removed
 
 
+def test_populate_any_indicators(default_conf, testdatadir) -> None:
+    strategy = StrategyResolver.load_strategy(default_conf)
+
+    timerange = TimeRange.parse_timerange('1510694220-1510700340')
+    data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], timerange=timerange,
+                     fill_up_missing=True)
+    processed = strategy.populate_any_indicators('UNITTEST/BTC', data, '5m')
+    assert processed == data
+    assert id(processed) == id(data)
+    assert len(processed['UNITTEST/BTC']) == 102  # partial candle was removed
+
+
 def test_advise_all_indicators_copy(mocker, default_conf, testdatadir) -> None:
     strategy = StrategyResolver.load_strategy(default_conf)
     aimock = mocker.patch('freqtrade.strategy.interface.IStrategy.advise_indicators')

From b682fc446e10c3df0aee91776df7a6e0ccebf851 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 13 Aug 2022 09:53:18 +0200
Subject: [PATCH 131/132] Graciously fail if strategy has freqAI code, but
 freqAI is not enabled.

---
 freqtrade/strategy/interface.py  | 7 +++++++
 tests/strategy/test_interface.py | 7 +++++++
 2 files changed, 14 insertions(+)

diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py
index 760d852c4..45609beaa 100644
--- a/freqtrade/strategy/interface.py
+++ b/freqtrade/strategy/interface.py
@@ -152,6 +152,13 @@ class IStrategy(ABC, HyperStrategyMixin):
 
             self.freqai = FreqaiModelResolver.load_freqaimodel(self.config)
             self.freqai_info = self.config["freqai"]
+        else:
+            # Gracious failures if freqAI is disabled but "start" is called.
+            class DummyClass():
+                def start(self, *args, **kwargs):
+                    raise OperationalException(
+                        'freqAI is not enabled. Please enable it in your config to use this strategy.')
+            self.freqai = DummyClass()  # type: ignore
 
     def ft_bot_start(self, **kwargs) -> None:
         """
diff --git a/tests/strategy/test_interface.py b/tests/strategy/test_interface.py
index 8b4ba5f03..83f7d19b7 100644
--- a/tests/strategy/test_interface.py
+++ b/tests/strategy/test_interface.py
@@ -302,6 +302,13 @@ def test_populate_any_indicators(default_conf, testdatadir) -> None:
     assert len(processed['UNITTEST/BTC']) == 102  # partial candle was removed
 
 
+def test_freqai_not_initialized(default_conf) -> None:
+    strategy = StrategyResolver.load_strategy(default_conf)
+    strategy.ft_bot_start()
+    with pytest.raises(OperationalException, match=r'freqAI is not enabled\.'):
+        strategy.freqai.start()
+
+
 def test_advise_all_indicators_copy(mocker, default_conf, testdatadir) -> None:
     strategy = StrategyResolver.load_strategy(default_conf)
     aimock = mocker.patch('freqtrade.strategy.interface.IStrategy.advise_indicators')

From 1ac6ec1446a02a30d0a840e2181fcd2dcf6de932 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 13 Aug 2022 09:56:21 +0200
Subject: [PATCH 132/132] Fix failing test...

---
 tests/freqai/conftest.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/freqai/conftest.py b/tests/freqai/conftest.py
index 63f3ef2c7..6ace13677 100644
--- a/tests/freqai/conftest.py
+++ b/tests/freqai/conftest.py
@@ -17,7 +17,6 @@ def freqai_conf(default_conf, tmpdir):
     freqaiconf = deepcopy(default_conf)
     freqaiconf.update(
         {
-            "enabled": True,
             "datadir": Path(default_conf["datadir"]),
             "strategy": "freqai_test_strat",
             "user_data_dir": Path(tmpdir),
@@ -26,6 +25,7 @@ def freqai_conf(default_conf, tmpdir):
             "freqaimodel_path": "freqai/prediction_models",
             "timerange": "20180110-20180115",
             "freqai": {
+                "enabled": True,
                 "startup_candles": 10000,
                 "purge_old_models": True,
                 "train_period_days": 5,