Bump python-telegram-bot from 13.15 to 20.2

Bumps [python-telegram-bot](https://github.com/python-telegram-bot/python-telegram-bot) from 13.15 to 20.2.
- [Release notes](https://github.com/python-telegram-bot/python-telegram-bot/releases)
- [Changelog](https://github.com/python-telegram-bot/python-telegram-bot/blob/master/CHANGES.rst)
- [Commits](https://github.com/python-telegram-bot/python-telegram-bot/compare/v13.15...v20.2)

---
updated-dependencies:
- dependency-name: python-telegram-bot
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>

.github/workflows/ci.yml

@@ -425,7 +425,7 @@ jobs:
         python setup.py sdist bdist_wheel
 
     - name: Publish to PyPI (Test)
-      uses: pypa/gh-action-pypi-publish@v1.8.3
+      uses: pypa/gh-action-pypi-publish@v1.8.5
       if: (github.event_name == 'release')
       with:
         user: __token__
@@ -433,7 +433,7 @@ jobs:
         repository_url: https://test.pypi.org/legacy/
 
     - name: Publish to PyPI
-      uses: pypa/gh-action-pypi-publish@v1.8.3
+      uses: pypa/gh-action-pypi-publish@v1.8.5
       if: (github.event_name == 'release')
       with:
         user: __token__

.pre-commit-config.yaml

@@ -13,12 +13,12 @@ repos:
       - id: mypy
         exclude: build_helpers
         additional_dependencies:
-          - types-cachetools==5.3.0.4
+          - types-cachetools==5.3.0.5
           - types-filelock==3.2.7
-          - types-requests==2.28.11.16
-          - types-tabulate==0.9.0.1
-          - types-python-dateutil==2.8.19.10
-          - SQLAlchemy==2.0.7
+          - types-requests==2.28.11.17
+          - types-tabulate==0.9.0.2
+          - types-python-dateutil==2.8.19.12
+          - SQLAlchemy==2.0.9
         # stages: [push]
 
   - repo: https://github.com/pycqa/isort

Dockerfile

@@ -1,4 +1,4 @@
-FROM python:3.10.10-slim-bullseye as base
+FROM python:3.10.11-slim-bullseye as base
 
 # Setup env
 ENV LANG C.UTF-8

build_helpers/publish_docker_arm64.sh

@@ -42,9 +42,9 @@ if [ $? -ne 0 ]; then
     return 1
 fi
 
-docker build --cache-from freqtrade:${TAG_ARM} --build-arg sourceimage=${CACHE_IMAGE} --build-arg sourcetag=${TAG_ARM} -t freqtrade:${TAG_PLOT_ARM} -f docker/Dockerfile.plot .
-docker build --cache-from freqtrade:${TAG_ARM} --build-arg sourceimage=${CACHE_IMAGE} --build-arg sourcetag=${TAG_ARM} -t freqtrade:${TAG_FREQAI_ARM} -f docker/Dockerfile.freqai .
-docker build --cache-from freqtrade:${TAG_ARM} --build-arg sourceimage=${CACHE_IMAGE} --build-arg sourcetag=${TAG_ARM} -t freqtrade:${TAG_FREQAI_RL_ARM} -f docker/Dockerfile.freqai_rl .
+docker build --build-arg sourceimage=freqtrade --build-arg sourcetag=${TAG_ARM} -t freqtrade:${TAG_PLOT_ARM} -f docker/Dockerfile.plot .
+docker build --build-arg sourceimage=freqtrade --build-arg sourcetag=${TAG_ARM} -t freqtrade:${TAG_FREQAI_ARM} -f docker/Dockerfile.freqai .
+docker build --build-arg sourceimage=freqtrade --build-arg sourcetag=${TAG_FREQAI_ARM} -t freqtrade:${TAG_FREQAI_RL_ARM} -f docker/Dockerfile.freqai_rl .
 
 # Tag image for upload and next build step
 docker tag freqtrade:$TAG_ARM ${CACHE_IMAGE}:$TAG_ARM

build_helpers/publish_docker_multi.sh

@@ -58,9 +58,9 @@ fi
 # Tag image for upload and next build step
 docker tag freqtrade:$TAG ${CACHE_IMAGE}:$TAG
 
-docker build --cache-from freqtrade:${TAG} --build-arg sourceimage=${CACHE_IMAGE} --build-arg sourcetag=${TAG} -t freqtrade:${TAG_PLOT} -f docker/Dockerfile.plot .
-docker build --cache-from freqtrade:${TAG} --build-arg sourceimage=${CACHE_IMAGE} --build-arg sourcetag=${TAG} -t freqtrade:${TAG_FREQAI} -f docker/Dockerfile.freqai .
-docker build --cache-from freqtrade:${TAG_FREQAI} --build-arg sourceimage=${CACHE_IMAGE} --build-arg sourcetag=${TAG_FREQAI} -t freqtrade:${TAG_FREQAI_RL} -f docker/Dockerfile.freqai_rl .
+docker build --build-arg sourceimage=freqtrade --build-arg sourcetag=${TAG} -t freqtrade:${TAG_PLOT} -f docker/Dockerfile.plot .
+docker build --build-arg sourceimage=freqtrade --build-arg sourcetag=${TAG} -t freqtrade:${TAG_FREQAI} -f docker/Dockerfile.freqai .
+docker build --build-arg sourceimage=freqtrade --build-arg sourcetag=${TAG_FREQAI} -t freqtrade:${TAG_FREQAI_RL} -f docker/Dockerfile.freqai_rl .
 
 docker tag freqtrade:$TAG_PLOT ${CACHE_IMAGE}:$TAG_PLOT
 docker tag freqtrade:$TAG_FREQAI ${CACHE_IMAGE}:$TAG_FREQAI

docs/backtesting.md

@@ -274,19 +274,20 @@ A backtesting result will look like that:
 | XRP/BTC  |      35 |           0.66 |          22.96 |       0.00114897 |          11.48 | 3:49:00      |    12     0    23   34.3 |
 | ZEC/BTC  |      22 |          -0.46 |         -10.18 |      -0.00050971 |          -5.09 | 2:22:00      |     7     0    15   31.8 |
 | TOTAL    |     429 |           0.36 |         152.41 |       0.00762792 |          76.20 | 4:12:00      |   186     0   243   43.4 |
-========================================================= EXIT REASON STATS ==========================================================
-| Exit Reason        |   Exits |  Wins |  Draws |  Losses |
-|:-------------------|--------:|------:|-------:|--------:|
-| trailing_stop_loss |     205 |   150 |      0 |      55 |
-| stop_loss          |     166 |     0 |      0 |     166 |
-| exit_signal        |      56 |    36 |      0 |      20 |
-| force_exit         |       2 |     0 |      0 |       2 |
 ====================================================== LEFT OPEN TRADES REPORT ======================================================
 | Pair     |  Entries |   Avg Profit % |   Cum Profit % |   Tot Profit BTC |   Tot Profit % | Avg Duration   |  Win Draw Loss Win% |
 |:---------|---------:|---------------:|---------------:|-----------------:|---------------:|:---------------|--------------------:|
 | ADA/BTC  |        1 |           0.89 |           0.89 |       0.00004434 |           0.44 | 6:00:00        |    1    0    0  100 |
 | LTC/BTC  |        1 |           0.68 |           0.68 |       0.00003421 |           0.34 | 2:00:00        |    1    0    0  100 |
 | TOTAL    |        2 |           0.78 |           1.57 |       0.00007855 |           0.78 | 4:00:00        |    2    0    0  100 |
+==================== EXIT REASON STATS ====================
+| Exit Reason        |   Exits |  Wins |  Draws |  Losses |
+|:-------------------|--------:|------:|-------:|--------:|
+| trailing_stop_loss |     205 |   150 |      0 |      55 |
+| stop_loss          |     166 |     0 |      0 |     166 |
+| exit_signal        |      56 |    36 |      0 |      20 |
+| force_exit         |       2 |     0 |      0 |       2 |
+
 ================== SUMMARY METRICS ==================
 | Metric                      | Value               |
 |-----------------------------+---------------------|

docs/freqai-feature-engineering.md

@@ -6,8 +6,8 @@ Low level feature engineering is performed in the user strategy within a set of
 
 |  Function | Description |
 |---------------|-------------|
-| `feature_engineering__expand_all()` | This optional function will automatically expand the defined features on the config defined `indicator_periods_candles`, `include_timeframes`, `include_shifted_candles`, and `include_corr_pairs`.
-| `feature_engineering__expand_basic()` | This optional function will automatically expand the defined features on the config defined `include_timeframes`, `include_shifted_candles`, and `include_corr_pairs`. Note: this function does *not* expand across `include_periods_candles`.
+| `feature_engineering_expand_all()` | This optional function will automatically expand the defined features on the config defined `indicator_periods_candles`, `include_timeframes`, `include_shifted_candles`, and `include_corr_pairs`.
+| `feature_engineering_expand_basic()` | This optional function will automatically expand the defined features on the config defined `include_timeframes`, `include_shifted_candles`, and `include_corr_pairs`. Note: this function does *not* expand across `include_periods_candles`.
 | `feature_engineering_standard()` | This optional function will be called once with the dataframe of the base timeframe. This is the final function to be called, which means that the dataframe entering this function will contain all the features and columns from the base asset created by the other `feature_engineering_expand` functions. This function is a good place to do custom exotic feature extractions (e.g. tsfresh). This function is also a good place for any feature that should not be auto-expanded upon (e.g., day of the week).
 | `set_freqai_targets()` | Required function to set the targets for the model. All targets must be prepended with `&` to be recognized by the FreqAI internals.
 
@@ -182,11 +182,11 @@ In total, the number of features the user of the presented example strat has cre
  $= 3 * 3 * 3 * 2 * 2 = 108$.
 
 
- ### Gain finer control over `feature_engineering_*` functions with `metadata`
+### Gain finer control over `feature_engineering_*` functions with `metadata`
 
  All `feature_engineering_*` and `set_freqai_targets()` functions are passed a `metadata` dictionary which contains information about the `pair`, `tf` (timeframe), and `period` that FreqAI is automating for feature building. As such, a user can use `metadata` inside `feature_engineering_*` functions as criteria for blocking/reserving features for certain timeframes, periods, pairs etc.
 
- ```py
+ ```python
 def feature_engineering_expand_all(self, dataframe, period, metadata, **kwargs):
  if metadata["tf"] == "1h":
     dataframe["%-roc-period"] = ta.ROC(dataframe, timeperiod=period)

docs/freqai-reinforcement-learning.md

@@ -180,7 +180,7 @@ As you begin to modify the strategy and the prediction model, you will quickly r
 
                 # you can use feature values from dataframe
                 # Assumes the shifted RSI indicator has been generated in the strategy.
-                rsi_now = self.raw_features[f"%-rsi-period-10_shift-1_{pair}_"
+                rsi_now = self.raw_features[f"%-rsi-period_10_shift-1_{pair}_"
                                 f"{self.config['timeframe']}"].iloc[self._current_tick]
 
                 # reward agent for entering trades

docs/requirements-docs.txt

@@ -1,6 +1,6 @@
 markdown==3.3.7
 mkdocs==1.4.2
-mkdocs-material==9.1.4
+mkdocs-material==9.1.6
 mdx_truly_sane_lists==1.3
-pymdown-extensions==9.10
+pymdown-extensions==9.11
 jinja2==3.1.2

docs/rest-api.md

@@ -9,9 +9,6 @@ This same command can also be used to update freqUI, should there be a new relea
 
 Once the bot is started in trade / dry-run mode (with `freqtrade trade`) - the UI will be available under the configured port below (usually `http://127.0.0.1:8080`).
 
-!!! info "Alpha release"
-    FreqUI is still considered an alpha release - if you encounter bugs or inconsistencies please open a [FreqUI issue](https://github.com/freqtrade/frequi/issues/new/choose).
-
 !!! Note "developers"
     Developers should not use this method, but instead use the method described in the [freqUI repository](https://github.com/freqtrade/frequi) to get the source-code of freqUI.
 

docs/telegram-usage.md

@@ -279,6 +279,7 @@ Return a summary of your profit/loss and performance.
 >   ∙ `33.095 EUR`
 >
 > **Total Trade Count:** `138`
+> **Bot started:** `2022-07-11 18:40:44`
 > **First Trade opened:** `3 days ago`
 > **Latest Trade opened:** `2 minutes ago`
 > **Avg. Duration:** `2:33:45`
@@ -292,6 +293,7 @@ The relative profit of `15.2 Σ%` is be based on the starting capital - so in th
 Starting capital is either taken from the `available_capital` setting, or calculated by using current wallet size - profits.
 Profit Factor is calculated as gross profits / gross losses - and should serve as an overall metric for the strategy.
 Max drawdown corresponds to the backtesting metric `Absolute Drawdown (Account)` - calculated as `(Absolute Drawdown) / (DrawdownHigh + startingBalance)`.
+Bot started date will refer to the date the bot was first started. For older bots, this will default to the first trade's open date.
 
 ### /forceexit <trade_id>
 

freqtrade/__init__.py

@@ -1,5 +1,5 @@
 """ Freqtrade bot """
-__version__ = '2023.3'
+__version__ = '2023.4.dev'
 
 if 'dev' in __version__:
     from pathlib import Path

freqtrade/constants.py

@@ -598,7 +598,7 @@ CONF_SCHEMA = {
                         "model_type": {"type": "string", "default": "PPO"},
                         "policy_type": {"type": "string", "default": "MlpPolicy"},
                         "net_arch": {"type": "array", "default": [128, 128]},
-                        "randomize_startinng_position": {"type": "boolean", "default": False},
+                        "randomize_starting_position": {"type": "boolean", "default": False},
                         "model_reward_parameters": {
                             "type": "object",
                             "properties": {

freqtrade/data/btanalysis.py

@@ -246,14 +246,8 @@ def _load_backtest_data_df_compatibility(df: pd.DataFrame) -> pd.DataFrame:
     """
     Compatibility support for older backtest data.
     """
-    df['open_date'] = pd.to_datetime(df['open_date'],
-                                     utc=True,
-                                     infer_datetime_format=True
-                                     )
-    df['close_date'] = pd.to_datetime(df['close_date'],
-                                      utc=True,
-                                      infer_datetime_format=True
-                                      )
+    df['open_date'] = pd.to_datetime(df['open_date'], utc=True)
+    df['close_date'] = pd.to_datetime(df['close_date'], utc=True)
     # Compatibility support for pre short Columns
     if 'is_short' not in df.columns:
         df['is_short'] = False

freqtrade/data/converter.py

@@ -34,7 +34,7 @@ def ohlcv_to_dataframe(ohlcv: list, timeframe: str, pair: str, *,
     cols = DEFAULT_DATAFRAME_COLUMNS
     df = DataFrame(ohlcv, columns=cols)
 
-    df['date'] = to_datetime(df['date'], unit='ms', utc=True, infer_datetime_format=True)
+    df['date'] = to_datetime(df['date'], unit='ms', utc=True)
 
     # Some exchanges return int values for Volume and even for OHLC.
     # Convert them since TA-LIB indicators used in the strategy assume floats

freqtrade/data/history/featherdatahandler.py

@@ -63,10 +63,7 @@ class FeatherDataHandler(IDataHandler):
         pairdata.columns = self._columns
         pairdata = pairdata.astype(dtype={'open': 'float', 'high': 'float',
                                           'low': 'float', 'close': 'float', 'volume': 'float'})
-        pairdata['date'] = to_datetime(pairdata['date'],
-                                       unit='ms',
-                                       utc=True,
-                                       infer_datetime_format=True)
+        pairdata['date'] = to_datetime(pairdata['date'], unit='ms', utc=True)
         return pairdata
 
     def ohlcv_append(

freqtrade/data/history/jsondatahandler.py

@@ -75,10 +75,7 @@ class JsonDataHandler(IDataHandler):
             return DataFrame(columns=self._columns)
         pairdata = pairdata.astype(dtype={'open': 'float', 'high': 'float',
                                           'low': 'float', 'close': 'float', 'volume': 'float'})
-        pairdata['date'] = to_datetime(pairdata['date'],
-                                       unit='ms',
-                                       utc=True,
-                                       infer_datetime_format=True)
+        pairdata['date'] = to_datetime(pairdata['date'], unit='ms', utc=True)
         return pairdata
 
     def ohlcv_append(

freqtrade/data/history/parquetdatahandler.py

@@ -62,10 +62,7 @@ class ParquetDataHandler(IDataHandler):
         pairdata.columns = self._columns
         pairdata = pairdata.astype(dtype={'open': 'float', 'high': 'float',
                                           'low': 'float', 'close': 'float', 'volume': 'float'})
-        pairdata['date'] = to_datetime(pairdata['date'],
-                                       unit='ms',
-                                       utc=True,
-                                       infer_datetime_format=True)
+        pairdata['date'] = to_datetime(pairdata['date'], unit='ms', utc=True)
         return pairdata
 
     def ohlcv_append(

freqtrade/exchange/__init__.py

@@ -8,15 +8,15 @@ from freqtrade.exchange.bitpanda import Bitpanda
 from freqtrade.exchange.bittrex import Bittrex
 from freqtrade.exchange.bybit import Bybit
 from freqtrade.exchange.coinbasepro import Coinbasepro
-from freqtrade.exchange.exchange_utils import (amount_to_contract_precision, amount_to_contracts,
-                                               amount_to_precision, available_exchanges,
-                                               ccxt_exchanges, contracts_to_amount,
-                                               date_minus_candles, is_exchange_known_ccxt,
-                                               market_is_active, price_to_precision,
-                                               timeframe_to_minutes, timeframe_to_msecs,
-                                               timeframe_to_next_date, timeframe_to_prev_date,
-                                               timeframe_to_seconds, validate_exchange,
-                                               validate_exchanges)
+from freqtrade.exchange.exchange_utils import (ROUND_DOWN, ROUND_UP, amount_to_contract_precision,
+                                               amount_to_contracts, amount_to_precision,
+                                               available_exchanges, ccxt_exchanges,
+                                               contracts_to_amount, date_minus_candles,
+                                               is_exchange_known_ccxt, market_is_active,
+                                               price_to_precision, timeframe_to_minutes,
+                                               timeframe_to_msecs, timeframe_to_next_date,
+                                               timeframe_to_prev_date, timeframe_to_seconds,
+                                               validate_exchange, validate_exchanges)
 from freqtrade.exchange.gate import Gate
 from freqtrade.exchange.hitbtc import Hitbtc
 from freqtrade.exchange.huobi import Huobi

freqtrade/exchange/exchange.py

@@ -30,13 +30,14 @@ from freqtrade.exceptions import (DDosProtection, ExchangeError, InsufficientFun
                                   RetryableOrderError, TemporaryError)
 from freqtrade.exchange.common import (API_FETCH_ORDER_RETRY_COUNT, remove_credentials, retrier,
                                        retrier_async)
-from freqtrade.exchange.exchange_utils import (CcxtModuleType, amount_to_contract_precision,
-                                               amount_to_contracts, amount_to_precision,
-                                               contracts_to_amount, date_minus_candles,
-                                               is_exchange_known_ccxt, market_is_active,
-                                               price_to_precision, timeframe_to_minutes,
-                                               timeframe_to_msecs, timeframe_to_next_date,
-                                               timeframe_to_prev_date, timeframe_to_seconds)
+from freqtrade.exchange.exchange_utils import (ROUND, ROUND_DOWN, ROUND_UP, CcxtModuleType,
+                                               amount_to_contract_precision, amount_to_contracts,
+                                               amount_to_precision, contracts_to_amount,
+                                               date_minus_candles, is_exchange_known_ccxt,
+                                               market_is_active, price_to_precision,
+                                               timeframe_to_minutes, timeframe_to_msecs,
+                                               timeframe_to_next_date, timeframe_to_prev_date,
+                                               timeframe_to_seconds)
 from freqtrade.exchange.types import OHLCVResponse, OrderBook, Ticker, Tickers
 from freqtrade.misc import (chunks, deep_merge_dicts, file_dump_json, file_load_json,
                             safe_value_fallback2)
@@ -59,6 +60,7 @@ class Exchange:
     # or by specifying them in the configuration.
     _ft_has_default: Dict = {
         "stoploss_on_exchange": False,
+        "stop_price_param": "stopPrice",
         "order_time_in_force": ["GTC"],
         "ohlcv_params": {},
         "ohlcv_candle_limit": 500,
@@ -734,12 +736,14 @@ class Exchange:
         """
         return amount_to_precision(amount, self.get_precision_amount(pair), self.precisionMode)
 
-    def price_to_precision(self, pair: str, price: float) -> float:
+    def price_to_precision(self, pair: str, price: float, *, rounding_mode: int = ROUND) -> float:
         """
-        Returns the price rounded up to the precision the Exchange accepts.
-        Rounds up
+        Returns the price rounded to the precision the Exchange accepts.
+        The default price_rounding_mode in conf is ROUND.
+        For stoploss calculations, must use ROUND_UP for longs, and ROUND_DOWN for shorts.
         """
-        return price_to_precision(price, self.get_precision_price(pair), self.precisionMode)
+        return price_to_precision(price, self.get_precision_price(pair),
+                                  self.precisionMode, rounding_mode=rounding_mode)
 
     def price_get_one_pip(self, pair: str, price: float) -> float:
         """
@@ -762,12 +766,12 @@ class Exchange:
         return self._get_stake_amount_limit(pair, price, stoploss, 'min', leverage)
 
     def get_max_pair_stake_amount(self, pair: str, price: float, leverage: float = 1.0) -> float:
-        max_stake_amount = self._get_stake_amount_limit(pair, price, 0.0, 'max')
+        max_stake_amount = self._get_stake_amount_limit(pair, price, 0.0, 'max', leverage)
         if max_stake_amount is None:
             # * Should never be executed
             raise OperationalException(f'{self.name}.get_max_pair_stake_amount should'
                                        'never set max_stake_amount to None')
-        return max_stake_amount / leverage
+        return max_stake_amount
 
     def _get_stake_amount_limit(
         self,
@@ -785,43 +789,41 @@ class Exchange:
         except KeyError:
             raise ValueError(f"Can't get market information for symbol {pair}")
 
+        if isMin:
+            # reserve some percent defined in config (5% default) + stoploss
+            margin_reserve: float = 1.0 + self._config.get('amount_reserve_percent',
+                                                           DEFAULT_AMOUNT_RESERVE_PERCENT)
+            stoploss_reserve = (
+                margin_reserve / (1 - abs(stoploss)) if abs(stoploss) != 1 else 1.5
+            )
+            # it should not be more than 50%
+            stoploss_reserve = max(min(stoploss_reserve, 1.5), 1)
+        else:
+            margin_reserve = 1.0
+            stoploss_reserve = 1.0
+
         stake_limits = []
         limits = market['limits']
         if (limits['cost'][limit] is not None):
             stake_limits.append(
-                self._contracts_to_amount(
-                    pair,
-                    limits['cost'][limit]
-                )
+                self._contracts_to_amount(pair, limits['cost'][limit]) * stoploss_reserve
             )
 
         if (limits['amount'][limit] is not None):
             stake_limits.append(
-                self._contracts_to_amount(
-                    pair,
-                    limits['amount'][limit] * price
-                )
+                self._contracts_to_amount(pair, limits['amount'][limit]) * price * margin_reserve
             )
 
         if not stake_limits:
             return None if isMin else float('inf')
 
-        # reserve some percent defined in config (5% default) + stoploss
-        amount_reserve_percent = 1.0 + self._config.get('amount_reserve_percent',
-                                                        DEFAULT_AMOUNT_RESERVE_PERCENT)
-        amount_reserve_percent = (
-            amount_reserve_percent / (1 - abs(stoploss)) if abs(stoploss) != 1 else 1.5
-        )
-        # it should not be more than 50%
-        amount_reserve_percent = max(min(amount_reserve_percent, 1.5), 1)
-
         # The value returned should satisfy both limits: for amount (base currency) and
         # for cost (quote, stake currency), so max() is used here.
         # See also #2575 at github.
         return self._get_stake_amount_considering_leverage(
-            max(stake_limits) * amount_reserve_percent,
+            max(stake_limits) if isMin else min(stake_limits),
             leverage or 1.0
-        ) if isMin else min(stake_limits)
+        )
 
     def _get_stake_amount_considering_leverage(self, stake_amount: float, leverage: float) -> float:
         """
@@ -1114,11 +1116,11 @@ class Exchange:
         """
         if not self._ft_has.get('stoploss_on_exchange'):
             raise OperationalException(f"stoploss is not implemented for {self.name}.")
-
+        price_param = self._ft_has['stop_price_param']
         return (
-            order.get('stopPrice', None) is None
-            or ((side == "sell" and stop_loss > float(order['stopPrice'])) or
-                (side == "buy" and stop_loss < float(order['stopPrice'])))
+            order.get(price_param, None) is None
+            or ((side == "sell" and stop_loss > float(order[price_param])) or
+                (side == "buy" and stop_loss < float(order[price_param])))
         )
 
     def _get_stop_order_type(self, user_order_type) -> Tuple[str, str]:
@@ -1158,8 +1160,8 @@ class Exchange:
 
     def _get_stop_params(self, side: BuySell, ordertype: str, stop_price: float) -> Dict:
         params = self._params.copy()
-        # Verify if stopPrice works for your exchange!
-        params.update({'stopPrice': stop_price})
+        # Verify if stopPrice works for your exchange, else configure stop_price_param
+        params.update({self._ft_has['stop_price_param']: stop_price})
         return params
 
     @retrier(retries=0)
@@ -1185,12 +1187,12 @@ class Exchange:
 
         user_order_type = order_types.get('stoploss', 'market')
         ordertype, user_order_type = self._get_stop_order_type(user_order_type)
-
-        stop_price_norm = self.price_to_precision(pair, stop_price)
+        round_mode = ROUND_DOWN if side == 'buy' else ROUND_UP
+        stop_price_norm = self.price_to_precision(pair, stop_price, rounding_mode=round_mode)
         limit_rate = None
         if user_order_type == 'limit':
             limit_rate = self._get_stop_limit_rate(stop_price, order_types, side)
-            limit_rate = self.price_to_precision(pair, limit_rate)
+            limit_rate = self.price_to_precision(pair, limit_rate, rounding_mode=round_mode)
 
         if self._config['dry_run']:
             dry_order = self.create_dry_run_order(

freqtrade/exchange/exchange_utils.py

@@ -2,11 +2,12 @@
 Exchange support utils
 """
 from datetime import datetime, timedelta, timezone
-from math import ceil
+from math import ceil, floor
 from typing import Any, Dict, List, Optional, Tuple
 
 import ccxt
-from ccxt import ROUND_DOWN, ROUND_UP, TICK_SIZE, TRUNCATE, decimal_to_precision
+from ccxt import (DECIMAL_PLACES, ROUND, ROUND_DOWN, ROUND_UP, SIGNIFICANT_DIGITS, TICK_SIZE,
+                  TRUNCATE, decimal_to_precision)
 
 from freqtrade.exchange.common import BAD_EXCHANGES, EXCHANGE_HAS_OPTIONAL, EXCHANGE_HAS_REQUIRED
 from freqtrade.util import FtPrecise
@@ -219,35 +220,51 @@ def amount_to_contract_precision(
     return amount
 
 
-def price_to_precision(price: float, price_precision: Optional[float],
-                       precisionMode: Optional[int]) -> float:
+def price_to_precision(
+    price: float,
+    price_precision: Optional[float],
+    precisionMode: Optional[int],
+    *,
+    rounding_mode: int = ROUND,
+) -> float:
     """
-    Returns the price rounded up to the precision the Exchange accepts.
+    Returns the price rounded to the precision the Exchange accepts.
     Partial Re-implementation of ccxt internal method decimal_to_precision(),
-    which does not support rounding up
+    which does not support rounding up.
+    For stoploss calculations, must use ROUND_UP for longs, and ROUND_DOWN for shorts.
+
     TODO: If ccxt supports ROUND_UP for decimal_to_precision(), we could remove this and
     align with amount_to_precision().
-    !!! Rounds up
     :param price: price to convert
     :param price_precision: price precision to use. Used from markets[pair]['precision']['price']
     :param precisionMode: precision mode to use. Should be used from precisionMode
                           one of ccxt's DECIMAL_PLACES, SIGNIFICANT_DIGITS, or TICK_SIZE
+    :param rounding_mode: rounding mode to use. Defaults to ROUND
     :return: price rounded up to the precision the Exchange accepts
-
     """
     if price_precision is not None and precisionMode is not None:
-        # price = float(decimal_to_precision(price, rounding_mode=ROUND,
-        #                                    precision=price_precision,
-        #                                    counting_mode=self.precisionMode,
-        #                                    ))
         if precisionMode == TICK_SIZE:
+            if rounding_mode == ROUND:
+                ticks = price / price_precision
+                rounded_ticks = round(ticks)
+                return rounded_ticks * price_precision
             precision = FtPrecise(price_precision)
             price_str = FtPrecise(price)
             missing = price_str % precision
             if not missing == FtPrecise("0"):
-                price = round(float(str(price_str - missing + precision)), 14)
-        else:
-            symbol_prec = price_precision
-            big_price = price * pow(10, symbol_prec)
-            price = ceil(big_price) / pow(10, symbol_prec)
+                return round(float(str(price_str - missing + precision)), 14)
+            return price
+        elif precisionMode in (SIGNIFICANT_DIGITS, DECIMAL_PLACES):
+            ndigits = round(price_precision)
+            if rounding_mode == ROUND:
+                return round(price, ndigits)
+            ticks = price * (10**ndigits)
+            if rounding_mode == ROUND_UP:
+                return ceil(ticks) / (10**ndigits)
+            if rounding_mode == TRUNCATE:
+                return int(ticks) / (10**ndigits)
+            if rounding_mode == ROUND_DOWN:
+                return floor(ticks) / (10**ndigits)
+            raise ValueError(f"Unknown rounding_mode {rounding_mode}")
+        raise ValueError(f"Unknown precisionMode {precisionMode}")
     return price

freqtrade/exchange/kraken.py

@@ -12,6 +12,7 @@ from freqtrade.exceptions import (DDosProtection, InsufficientFundsError, Invali
                                   OperationalException, TemporaryError)
 from freqtrade.exchange import Exchange
 from freqtrade.exchange.common import retrier
+from freqtrade.exchange.exchange_utils import ROUND_DOWN, ROUND_UP
 from freqtrade.exchange.types import Tickers
 
 
@@ -109,6 +110,7 @@ class Kraken(Exchange):
         if self.trading_mode == TradingMode.FUTURES:
             params.update({'reduceOnly': True})
 
+        round_mode = ROUND_DOWN if side == 'buy' else ROUND_UP
         if order_types.get('stoploss', 'market') == 'limit':
             ordertype = "stop-loss-limit"
             limit_price_pct = order_types.get('stoploss_on_exchange_limit_ratio', 0.99)
@@ -116,11 +118,11 @@ class Kraken(Exchange):
                 limit_rate = stop_price * limit_price_pct
             else:
                 limit_rate = stop_price * (2 - limit_price_pct)
-            params['price2'] = self.price_to_precision(pair, limit_rate)
+            params['price2'] = self.price_to_precision(pair, limit_rate, rounding_mode=round_mode)
         else:
             ordertype = "stop-loss"
 
-        stop_price = self.price_to_precision(pair, stop_price)
+        stop_price = self.price_to_precision(pair, stop_price, rounding_mode=round_mode)
 
         if self._config['dry_run']:
             dry_order = self.create_dry_run_order(

freqtrade/exchange/okx.py

@@ -28,6 +28,7 @@ class Okx(Exchange):
         "funding_fee_timeframe": "8h",
         "stoploss_order_types": {"limit": "limit"},
         "stoploss_on_exchange": True,
+        "stop_price_param": "stopLossPrice",
     }
     _ft_has_futures: Dict = {
         "tickers_have_quoteVolume": False,
@@ -162,29 +163,12 @@ class Okx(Exchange):
         return pair_tiers[-1]['maxNotional'] / leverage
 
     def _get_stop_params(self, side: BuySell, ordertype: str, stop_price: float) -> Dict:
-
-        params = self._params.copy()
-        # Verify if stopPrice works for your exchange!
-        params.update({'stopLossPrice': stop_price})
-
+        params = super()._get_stop_params(side, ordertype, stop_price)
         if self.trading_mode == TradingMode.FUTURES and self.margin_mode:
             params['tdMode'] = self.margin_mode.value
             params['posSide'] = self._get_posSide(side, True)
         return params
 
-    def stoploss_adjust(self, stop_loss: float, order: Dict, side: str) -> bool:
-        """
-        OKX uses non-default stoploss price naming.
-        """
-        if not self._ft_has.get('stoploss_on_exchange'):
-            raise OperationalException(f"stoploss is not implemented for {self.name}.")
-
-        return (
-            order.get('stopLossPrice', None) is None
-            or ((side == "sell" and stop_loss > float(order['stopLossPrice'])) or
-                (side == "buy" and stop_loss < float(order['stopLossPrice'])))
-        )
-
     def fetch_stoploss_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
         if self._config['dry_run']:
             return self.fetch_dry_run_order(order_id)

freqtrade/freqai/RL/Base3ActionRLEnv.py

@@ -66,7 +66,7 @@ class Base3ActionRLEnv(BaseEnvironment):
             elif action == Actions.Sell.value and not self.can_short:
                 self._update_total_profit()
                 self._position = Positions.Neutral
-                trade_type = "neutral"
+                trade_type = "exit"
                 self._last_trade_tick = None
             else:
                 print("case not defined")
@@ -74,7 +74,7 @@ class Base3ActionRLEnv(BaseEnvironment):
             if trade_type is not None:
                 self.trade_history.append(
                     {'price': self.current_price(), 'index': self._current_tick,
-                     'type': trade_type})
+                     'type': trade_type, 'profit': self.get_unrealized_profit()})
 
         if (self._total_profit < self.max_drawdown or
                 self._total_unrealized_profit < self.max_drawdown):

freqtrade/freqai/RL/Base4ActionRLEnv.py

@@ -52,16 +52,6 @@ class Base4ActionRLEnv(BaseEnvironment):
 
         trade_type = None
         if self.is_tradesignal(action):
-            """
-            Action: Neutral, position: Long ->  Close Long
-            Action: Neutral, position: Short -> Close Short
-
-            Action: Long, position: Neutral -> Open Long
-            Action: Long, position: Short -> Close Short and Open Long
-
-            Action: Short, position: Neutral -> Open Short
-            Action: Short, position: Long -> Close Long and Open Short
-            """
 
             if action == Actions.Neutral.value:
                 self._position = Positions.Neutral
@@ -69,16 +59,16 @@ class Base4ActionRLEnv(BaseEnvironment):
                 self._last_trade_tick = None
             elif action == Actions.Long_enter.value:
                 self._position = Positions.Long
-                trade_type = "long"
+                trade_type = "enter_long"
                 self._last_trade_tick = self._current_tick
             elif action == Actions.Short_enter.value:
                 self._position = Positions.Short
-                trade_type = "short"
+                trade_type = "enter_short"
                 self._last_trade_tick = self._current_tick
             elif action == Actions.Exit.value:
                 self._update_total_profit()
                 self._position = Positions.Neutral
-                trade_type = "neutral"
+                trade_type = "exit"
                 self._last_trade_tick = None
             else:
                 print("case not defined")
@@ -86,7 +76,7 @@ class Base4ActionRLEnv(BaseEnvironment):
             if trade_type is not None:
                 self.trade_history.append(
                     {'price': self.current_price(), 'index': self._current_tick,
-                     'type': trade_type})
+                     'type': trade_type, 'profit': self.get_unrealized_profit()})
 
         if (self._total_profit < self.max_drawdown or
                 self._total_unrealized_profit < self.max_drawdown):

freqtrade/freqai/RL/Base5ActionRLEnv.py

@@ -53,16 +53,6 @@ class Base5ActionRLEnv(BaseEnvironment):
 
         trade_type = None
         if self.is_tradesignal(action):
-            """
-            Action: Neutral, position: Long ->  Close Long
-            Action: Neutral, position: Short -> Close Short
-
-            Action: Long, position: Neutral -> Open Long
-            Action: Long, position: Short -> Close Short and Open Long
-
-            Action: Short, position: Neutral -> Open Short
-            Action: Short, position: Long -> Close Long and Open Short
-            """
 
             if action == Actions.Neutral.value:
                 self._position = Positions.Neutral
@@ -70,21 +60,21 @@ class Base5ActionRLEnv(BaseEnvironment):
                 self._last_trade_tick = None
             elif action == Actions.Long_enter.value:
                 self._position = Positions.Long
-                trade_type = "long"
+                trade_type = "enter_long"
                 self._last_trade_tick = self._current_tick
             elif action == Actions.Short_enter.value:
                 self._position = Positions.Short
-                trade_type = "short"
+                trade_type = "enter_short"
                 self._last_trade_tick = self._current_tick
             elif action == Actions.Long_exit.value:
                 self._update_total_profit()
                 self._position = Positions.Neutral
-                trade_type = "neutral"
+                trade_type = "exit_long"
                 self._last_trade_tick = None
             elif action == Actions.Short_exit.value:
                 self._update_total_profit()
                 self._position = Positions.Neutral
-                trade_type = "neutral"
+                trade_type = "exit_short"
                 self._last_trade_tick = None
             else:
                 print("case not defined")
@@ -92,7 +82,7 @@ class Base5ActionRLEnv(BaseEnvironment):
             if trade_type is not None:
                 self.trade_history.append(
                     {'price': self.current_price(), 'index': self._current_tick,
-                     'type': trade_type})
+                     'type': trade_type, 'profit': self.get_unrealized_profit()})
 
         if (self._total_profit < self.max_drawdown or
                 self._total_unrealized_profit < self.max_drawdown):

freqtrade/freqai/data_kitchen.py

@@ -1291,7 +1291,7 @@ class FreqaiDataKitchen:
 
         return dataframe
 
-    def use_strategy_to_populate_indicators(
+    def use_strategy_to_populate_indicators(  # noqa: C901
         self,
         strategy: IStrategy,
         corr_dataframes: dict = {},
@@ -1362,12 +1362,12 @@ class FreqaiDataKitchen:
                 dataframe = self.populate_features(dataframe.copy(), corr_pair, strategy,
                                                    corr_dataframes, base_dataframes, True)
 
-        dataframe = strategy.set_freqai_targets(dataframe.copy(), metadata=metadata)
+        if self.live:
+            dataframe = strategy.set_freqai_targets(dataframe.copy(), metadata=metadata)
+            dataframe = self.remove_special_chars_from_feature_names(dataframe)
 
         self.get_unique_classes_from_labels(dataframe)
 
-        dataframe = self.remove_special_chars_from_feature_names(dataframe)
-
         if self.config.get('reduce_df_footprint', False):
             dataframe = reduce_dataframe_footprint(dataframe)
 

freqtrade/freqai/freqai_interface.py

@@ -306,7 +306,7 @@ class IFreqaiModel(ABC):
                 if check_features:
                     self.dd.load_metadata(dk)
                     dataframe_dummy_features = self.dk.use_strategy_to_populate_indicators(
-                        strategy, prediction_dataframe=dataframe.tail(1), pair=metadata["pair"]
+                        strategy, prediction_dataframe=dataframe.tail(1), pair=pair
                     )
                     dk.find_features(dataframe_dummy_features)
                     self.check_if_feature_list_matches_strategy(dk)
@@ -316,7 +316,7 @@ class IFreqaiModel(ABC):
             else:
                 if populate_indicators:
                     dataframe = self.dk.use_strategy_to_populate_indicators(
-                        strategy, prediction_dataframe=dataframe, pair=metadata["pair"]
+                        strategy, prediction_dataframe=dataframe, pair=pair
                     )
                     populate_indicators = False
 
@@ -332,6 +332,10 @@ class IFreqaiModel(ABC):
                 dataframe_train = dk.slice_dataframe(tr_train, dataframe_base_train)
                 dataframe_backtest = dk.slice_dataframe(tr_backtest, dataframe_base_backtest)
 
+                dataframe_train = dk.remove_special_chars_from_feature_names(dataframe_train)
+                dataframe_backtest = dk.remove_special_chars_from_feature_names(dataframe_backtest)
+                dk.get_unique_classes_from_labels(dataframe_train)
+
                 if not self.model_exists(dk):
                     dk.find_features(dataframe_train)
                     dk.find_labels(dataframe_train)

freqtrade/freqtradebot.py

@@ -21,10 +21,12 @@ from freqtrade.enums import (ExitCheckTuple, ExitType, RPCMessageType, RunMode,
                              State, TradingMode)
 from freqtrade.exceptions import (DependencyException, ExchangeError, InsufficientFundsError,
                                   InvalidOrderException, PricingError)
-from freqtrade.exchange import timeframe_to_minutes, timeframe_to_next_date, timeframe_to_seconds
+from freqtrade.exchange import (ROUND_DOWN, ROUND_UP, timeframe_to_minutes, timeframe_to_next_date,
+                                timeframe_to_seconds)
 from freqtrade.misc import safe_value_fallback, safe_value_fallback2
 from freqtrade.mixins import LoggingMixin
 from freqtrade.persistence import Order, PairLocks, Trade, init_db
+from freqtrade.persistence.key_value_store import set_startup_time
 from freqtrade.plugins.pairlistmanager import PairListManager
 from freqtrade.plugins.protectionmanager import ProtectionManager
 from freqtrade.resolvers import ExchangeResolver, StrategyResolver
@@ -181,6 +183,7 @@ class FreqtradeBot(LoggingMixin):
         performs startup tasks
         """
         migrate_binance_futures_names(self.config)
+        set_startup_time()
 
         self.rpc.startup_messages(self.config, self.pairlists, self.protections)
         # Update older trades with precision and precision mode
@@ -853,7 +856,8 @@ class FreqtradeBot(LoggingMixin):
                 logger.info(f"Canceling stoploss on exchange for {trade}")
                 co = self.exchange.cancel_stoploss_order_with_result(
                     trade.stoploss_order_id, trade.pair, trade.amount)
-                trade.update_order(co)
+                self.update_trade_state(trade, trade.stoploss_order_id, co, stoploss_order=True)
+
                 # Reset stoploss order id.
                 trade.stoploss_order_id = None
             except InvalidOrderException:
@@ -945,7 +949,7 @@ class FreqtradeBot(LoggingMixin):
 
         return enter_limit_requested, stake_amount, leverage
 
-    def _notify_enter(self, trade: Trade, order: Order, order_type: Optional[str] = None,
+    def _notify_enter(self, trade: Trade, order: Order, order_type: str,
                       fill: bool = False, sub_trade: bool = False) -> None:
         """
         Sends rpc notification when a entry order occurred.
@@ -1171,7 +1175,8 @@ class FreqtradeBot(LoggingMixin):
             logger.warning('Unable to fetch stoploss order: %s', exception)
 
         if stoploss_order:
-            trade.update_order(stoploss_order)
+            self.update_trade_state(trade, trade.stoploss_order_id, stoploss_order,
+                                    stoploss_order=True)
 
         # We check if stoploss order is fulfilled
         if stoploss_order and stoploss_order['status'] in ('closed', 'triggered'):
@@ -1235,7 +1240,9 @@ class FreqtradeBot(LoggingMixin):
         :param order: Current on exchange stoploss order
         :return: None
         """
-        stoploss_norm = self.exchange.price_to_precision(trade.pair, trade.stoploss_or_liquidation)
+        stoploss_norm = self.exchange.price_to_precision(
+            trade.pair, trade.stoploss_or_liquidation,
+            rounding_mode=ROUND_DOWN if trade.is_short else ROUND_UP)
 
         if self.exchange.stoploss_adjust(stoploss_norm, order, side=trade.exit_side):
             # we check if the update is necessary
@@ -1478,8 +1485,8 @@ class FreqtradeBot(LoggingMixin):
                     return False
 
             try:
-                order = self.exchange.cancel_order_with_result(order['id'], trade.pair,
-                                                               trade.amount)
+                order = self.exchange.cancel_order_with_result(
+                    order['id'], trade.pair, trade.amount)
             except InvalidOrderException:
                 logger.exception(
                     f"Could not cancel {trade.exit_side} order {trade.open_order_id}")
@@ -1491,17 +1498,18 @@ class FreqtradeBot(LoggingMixin):
             # Order might be filled above in odd timing issues.
             if order.get('status') in ('canceled', 'cancelled'):
                 trade.exit_reason = None
+                trade.open_order_id = None
             else:
                 trade.exit_reason = exit_reason_prev
             cancelled = True
         else:
             reason = constants.CANCEL_REASON['CANCELLED_ON_EXCHANGE']
             trade.exit_reason = None
+            trade.open_order_id = None
 
         self.update_trade_state(trade, trade.open_order_id, order)
 
         logger.info(f'{trade.exit_side.capitalize()} order {reason} for {trade}.')
-        trade.open_order_id = None
         trade.close_rate = None
         trade.close_rate_requested = None
 
@@ -1778,11 +1786,11 @@ class FreqtradeBot(LoggingMixin):
             return False
 
         # Update trade with order values
-        logger.info(f'Found open order for {trade}')
+        if not stoploss_order:
+            logger.info(f'Found open order for {trade}')
         try:
-            order = action_order or self.exchange.fetch_order_or_stoploss_order(order_id,
-                                                                                trade.pair,
-                                                                                stoploss_order)
+            order = action_order or self.exchange.fetch_order_or_stoploss_order(
+                order_id, trade.pair, stoploss_order)
         except InvalidOrderException as exception:
             logger.warning('Unable to fetch order %s: %s', order_id, exception)
             return False
@@ -1847,7 +1855,7 @@ class FreqtradeBot(LoggingMixin):
                 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)
+            self._notify_enter(trade, order, order.order_type, fill=True, sub_trade=sub_trade)
 
     def handle_protections(self, pair: str, side: LongShort) -> None:
         # Lock pair for one candle to prevent immediate rebuys

freqtrade/optimize/hyperopt_tools.py

@@ -23,6 +23,8 @@ logger = logging.getLogger(__name__)
 
 NON_OPT_PARAM_APPENDIX = "  # value loaded from strategy"
 
+HYPER_PARAMS_FILE_FORMAT = rapidjson.NM_NATIVE | rapidjson.NM_NAN
+
 
 def hyperopt_serializer(x):
     if isinstance(x, np.integer):
@@ -76,9 +78,18 @@ class HyperoptTools():
         with filename.open('w') as f:
             rapidjson.dump(final_params, f, indent=2,
                            default=hyperopt_serializer,
-                           number_mode=rapidjson.NM_NATIVE | rapidjson.NM_NAN
+                           number_mode=HYPER_PARAMS_FILE_FORMAT
                            )
 
+    @staticmethod
+    def load_params(filename: Path) -> Dict:
+        """
+        Load parameters from file
+        """
+        with filename.open('r') as f:
+            params = rapidjson.load(f, number_mode=HYPER_PARAMS_FILE_FORMAT)
+        return params
+
     @staticmethod
     def try_export_params(config: Config, strategy_name: str, params: Dict):
         if params.get(FTHYPT_FILEVERSION, 1) >= 2 and not config.get('disableparamexport', False):
@@ -189,7 +200,7 @@ class HyperoptTools():
             for s in ['buy', 'sell', 'protection',
                       'roi', 'stoploss', 'trailing', 'max_open_trades']:
                 HyperoptTools._params_update_for_json(result_dict, params, non_optimized, s)
-            print(rapidjson.dumps(result_dict, default=str, number_mode=rapidjson.NM_NATIVE))
+            print(rapidjson.dumps(result_dict, default=str, number_mode=HYPER_PARAMS_FILE_FORMAT))
 
         else:
             HyperoptTools._params_pretty_print(params, 'buy', "Buy hyperspace params:",

freqtrade/optimize/optimize_reports.py

@@ -865,6 +865,11 @@ def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency:
         print(' BACKTESTING REPORT '.center(len(table.splitlines()[0]), '='))
     print(table)
 
+    table = text_table_bt_results(results['left_open_trades'], stake_currency=stake_currency)
+    if isinstance(table, str) and len(table) > 0:
+        print(' LEFT OPEN TRADES REPORT '.center(len(table.splitlines()[0]), '='))
+    print(table)
+
     if (results.get('results_per_enter_tag') is not None
             or results.get('results_per_buy_tag') is not None):
         # results_per_buy_tag is deprecated and should be removed 2 versions after short golive.
@@ -884,11 +889,6 @@ def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency:
         print(' EXIT REASON STATS '.center(len(table.splitlines()[0]), '='))
     print(table)
 
-    table = text_table_bt_results(results['left_open_trades'], stake_currency=stake_currency)
-    if isinstance(table, str) and len(table) > 0:
-        print(' LEFT OPEN TRADES REPORT '.center(len(table.splitlines()[0]), '='))
-    print(table)
-
     for period in backtest_breakdown:
         days_breakdown_stats = generate_periodic_breakdown_stats(
             trade_list=results['trades'], period=period)
@@ -917,11 +917,11 @@ def show_backtest_results(config: Config, backtest_stats: Dict):
             strategy, results, stake_currency,
             config.get('backtest_breakdown', []))
 
-    if len(backtest_stats['strategy']) > 1:
+    if len(backtest_stats['strategy']) > 0:
         # Print Strategy summary table
 
         table = text_table_strategy(backtest_stats['strategy_comparison'], stake_currency)
-        print(f"{results['backtest_start']} -> {results['backtest_end']} |"
+        print(f"Backtested {results['backtest_start']} -> {results['backtest_end']} |"
               f" Max open trades : {results['max_open_trades']}")
         print(' STRATEGY SUMMARY '.center(len(table.splitlines()[0]), '='))
         print(table)

freqtrade/persistence/__init__.py

@@ -1,5 +1,6 @@
 # flake8: noqa: F401
 
+from freqtrade.persistence.key_value_store import KeyStoreKeys, KeyValueStore
 from freqtrade.persistence.models import init_db
 from freqtrade.persistence.pairlock_middleware import PairLocks
 from freqtrade.persistence.trade_model import LocalTrade, Order, Trade

freqtrade/persistence/key_value_store.py

@@ -0,0 +1,179 @@
+from datetime import datetime, timezone
+from enum import Enum
+from typing import ClassVar, Optional, Union
+
+from sqlalchemy import String
+from sqlalchemy.orm import Mapped, mapped_column
+
+from freqtrade.persistence.base import ModelBase, SessionType
+
+
+ValueTypes = Union[str, datetime, float, int]
+
+
+class ValueTypesEnum(str, Enum):
+    STRING = 'str'
+    DATETIME = 'datetime'
+    FLOAT = 'float'
+    INT = 'int'
+
+
+class KeyStoreKeys(str, Enum):
+    BOT_START_TIME = 'bot_start_time'
+    STARTUP_TIME = 'startup_time'
+
+
+class _KeyValueStoreModel(ModelBase):
+    """
+    Pair Locks database model.
+    """
+    __tablename__ = 'KeyValueStore'
+    session: ClassVar[SessionType]
+
+    id: Mapped[int] = mapped_column(primary_key=True)
+
+    key: Mapped[KeyStoreKeys] = mapped_column(String(25), nullable=False, index=True)
+
+    value_type: Mapped[ValueTypesEnum] = mapped_column(String(20), nullable=False)
+
+    string_value: Mapped[Optional[str]]
+    datetime_value: Mapped[Optional[datetime]]
+    float_value: Mapped[Optional[float]]
+    int_value: Mapped[Optional[int]]
+
+
+class KeyValueStore():
+    """
+    Generic bot-wide, persistent key-value store
+    Can be used to store generic values, e.g. very first bot startup time.
+    Supports the types str, datetime, float and int.
+    """
+
+    @staticmethod
+    def store_value(key: KeyStoreKeys, value: ValueTypes) -> None:
+        """
+        Store the given value for the given key.
+        :param key: Key to store the value for - can be used in get-value to retrieve the key
+        :param value: Value to store - can be str, datetime, float or int
+        """
+        kv = _KeyValueStoreModel.session.query(_KeyValueStoreModel).filter(
+            _KeyValueStoreModel.key == key).first()
+        if kv is None:
+            kv = _KeyValueStoreModel(key=key)
+        if isinstance(value, str):
+            kv.value_type = ValueTypesEnum.STRING
+            kv.string_value = value
+        elif isinstance(value, datetime):
+            kv.value_type = ValueTypesEnum.DATETIME
+            kv.datetime_value = value
+        elif isinstance(value, float):
+            kv.value_type = ValueTypesEnum.FLOAT
+            kv.float_value = value
+        elif isinstance(value, int):
+            kv.value_type = ValueTypesEnum.INT
+            kv.int_value = value
+        else:
+            raise ValueError(f'Unknown value type {kv.value_type}')
+        _KeyValueStoreModel.session.add(kv)
+        _KeyValueStoreModel.session.commit()
+
+    @staticmethod
+    def delete_value(key: KeyStoreKeys) -> None:
+        """
+        Delete the value for the given key.
+        :param key: Key to delete the value for
+        """
+        kv = _KeyValueStoreModel.session.query(_KeyValueStoreModel).filter(
+            _KeyValueStoreModel.key == key).first()
+        if kv is not None:
+            _KeyValueStoreModel.session.delete(kv)
+            _KeyValueStoreModel.session.commit()
+
+    @staticmethod
+    def get_value(key: KeyStoreKeys) -> Optional[ValueTypes]:
+        """
+        Get the value for the given key.
+        :param key: Key to get the value for
+        """
+        kv = _KeyValueStoreModel.session.query(_KeyValueStoreModel).filter(
+            _KeyValueStoreModel.key == key).first()
+        if kv is None:
+            return None
+        if kv.value_type == ValueTypesEnum.STRING:
+            return kv.string_value
+        if kv.value_type == ValueTypesEnum.DATETIME and kv.datetime_value is not None:
+            return kv.datetime_value.replace(tzinfo=timezone.utc)
+        if kv.value_type == ValueTypesEnum.FLOAT:
+            return kv.float_value
+        if kv.value_type == ValueTypesEnum.INT:
+            return kv.int_value
+        # This should never happen unless someone messed with the database manually
+        raise ValueError(f'Unknown value type {kv.value_type}')  # pragma: no cover
+
+    @staticmethod
+    def get_string_value(key: KeyStoreKeys) -> Optional[str]:
+        """
+        Get the value for the given key.
+        :param key: Key to get the value for
+        """
+        kv = _KeyValueStoreModel.session.query(_KeyValueStoreModel).filter(
+            _KeyValueStoreModel.key == key,
+            _KeyValueStoreModel.value_type == ValueTypesEnum.STRING).first()
+        if kv is None:
+            return None
+        return kv.string_value
+
+    @staticmethod
+    def get_datetime_value(key: KeyStoreKeys) -> Optional[datetime]:
+        """
+        Get the value for the given key.
+        :param key: Key to get the value for
+        """
+        kv = _KeyValueStoreModel.session.query(_KeyValueStoreModel).filter(
+            _KeyValueStoreModel.key == key,
+            _KeyValueStoreModel.value_type == ValueTypesEnum.DATETIME).first()
+        if kv is None or kv.datetime_value is None:
+            return None
+        return kv.datetime_value.replace(tzinfo=timezone.utc)
+
+    @staticmethod
+    def get_float_value(key: KeyStoreKeys) -> Optional[float]:
+        """
+        Get the value for the given key.
+        :param key: Key to get the value for
+        """
+        kv = _KeyValueStoreModel.session.query(_KeyValueStoreModel).filter(
+            _KeyValueStoreModel.key == key,
+            _KeyValueStoreModel.value_type == ValueTypesEnum.FLOAT).first()
+        if kv is None:
+            return None
+        return kv.float_value
+
+    @staticmethod
+    def get_int_value(key: KeyStoreKeys) -> Optional[int]:
+        """
+        Get the value for the given key.
+        :param key: Key to get the value for
+        """
+        kv = _KeyValueStoreModel.session.query(_KeyValueStoreModel).filter(
+            _KeyValueStoreModel.key == key,
+            _KeyValueStoreModel.value_type == ValueTypesEnum.INT).first()
+        if kv is None:
+            return None
+        return kv.int_value
+
+
+def set_startup_time():
+    """
+    sets bot_start_time to the first trade open date - or "now" on new databases.
+    sets startup_time to "now"
+    """
+    st = KeyValueStore.get_value('bot_start_time')
+    if st is None:
+        from freqtrade.persistence import Trade
+        t = Trade.session.query(Trade).order_by(Trade.open_date.asc()).first()
+        if t is not None:
+            KeyValueStore.store_value('bot_start_time', t.open_date_utc)
+        else:
+            KeyValueStore.store_value('bot_start_time', datetime.now(timezone.utc))
+    KeyValueStore.store_value('startup_time', datetime.now(timezone.utc))

freqtrade/persistence/models.py

@@ -13,6 +13,7 @@ from sqlalchemy.pool import StaticPool
 
 from freqtrade.exceptions import OperationalException
 from freqtrade.persistence.base import ModelBase
+from freqtrade.persistence.key_value_store import _KeyValueStoreModel
 from freqtrade.persistence.migrations import check_migrate
 from freqtrade.persistence.pairlock import PairLock
 from freqtrade.persistence.trade_model import Order, Trade
@@ -76,6 +77,7 @@ def init_db(db_url: str) -> None:
         bind=engine, autoflush=False), scopefunc=get_request_or_thread_id)
     Order.session = Trade.session
     PairLock.session = Trade.session
+    _KeyValueStoreModel.session = Trade.session
 
     previous_tables = inspect(engine).get_table_names()
     ModelBase.metadata.create_all(engine)

freqtrade/persistence/trade_model.py

@@ -15,7 +15,8 @@ from freqtrade.constants import (DATETIME_PRINT_FORMAT, MATH_CLOSE_PREC, NON_OPE
                                  BuySell, LongShort)
 from freqtrade.enums import ExitType, TradingMode
 from freqtrade.exceptions import DependencyException, OperationalException
-from freqtrade.exchange import amount_to_contract_precision, price_to_precision
+from freqtrade.exchange import (ROUND_DOWN, ROUND_UP, amount_to_contract_precision,
+                                price_to_precision)
 from freqtrade.leverage import interest
 from freqtrade.persistence.base import ModelBase, SessionType
 from freqtrade.util import FtPrecise
@@ -597,7 +598,8 @@ class LocalTrade():
         """
         Method used internally to set self.stop_loss.
         """
-        stop_loss_norm = price_to_precision(stop_loss, self.price_precision, self.precision_mode)
+        stop_loss_norm = price_to_precision(stop_loss, self.price_precision, self.precision_mode,
+                                            rounding_mode=ROUND_DOWN if self.is_short else ROUND_UP)
         if not self.stop_loss:
             self.initial_stop_loss = stop_loss_norm
         self.stop_loss = stop_loss_norm
@@ -628,7 +630,8 @@ class LocalTrade():
         if self.initial_stop_loss_pct is None or refresh:
             self.__set_stop_loss(new_loss, stoploss)
             self.initial_stop_loss = price_to_precision(
-                new_loss, self.price_precision, self.precision_mode)
+                new_loss, self.price_precision, self.precision_mode,
+                rounding_mode=ROUND_DOWN if self.is_short else ROUND_UP)
             self.initial_stop_loss_pct = -1 * abs(stoploss)
 
         # evaluate if the stop loss needs to be updated
@@ -692,21 +695,24 @@ class LocalTrade():
             else:
                 logger.warning(
                     f'Got different open_order_id {self.open_order_id} != {order.order_id}')
+
+        elif order.ft_order_side == 'stoploss' and order.status not in ('open', ):
+            self.stoploss_order_id = None
+            self.close_rate_requested = self.stop_loss
+            self.exit_reason = ExitType.STOPLOSS_ON_EXCHANGE.value
+            if self.is_open:
+                logger.info(f'{order.order_type.upper()} is hit for {self}.')
+        else:
+            raise ValueError(f'Unknown order type: {order.order_type}')
+
+        if order.ft_order_side != self.entry_side:
             amount_tr = amount_to_contract_precision(self.amount, self.amount_precision,
                                                      self.precision_mode, self.contract_size)
             if isclose(order.safe_amount_after_fee, amount_tr, abs_tol=MATH_CLOSE_PREC):
                 self.close(order.safe_price)
             else:
                 self.recalc_trade_from_orders()
-        elif order.ft_order_side == 'stoploss' and order.status not in ('canceled', 'open'):
-            self.stoploss_order_id = None
-            self.close_rate_requested = self.stop_loss
-            self.exit_reason = ExitType.STOPLOSS_ON_EXCHANGE.value
-            if self.is_open:
-                logger.info(f'{order.order_type.upper()} is hit for {self}.')
-            self.close(order.safe_price)
-        else:
-            raise ValueError(f'Unknown order type: {order.order_type}')
+
         Trade.commit()
 
     def close(self, rate: float, *, show_msg: bool = True) -> None:

freqtrade/plugins/pairlist/PrecisionFilter.py

@@ -6,6 +6,7 @@ from typing import Any, Dict, Optional
 
 from freqtrade.constants import Config
 from freqtrade.exceptions import OperationalException
+from freqtrade.exchange import ROUND_UP
 from freqtrade.exchange.types import Ticker
 from freqtrade.plugins.pairlist.IPairList import IPairList
 
@@ -61,9 +62,10 @@ class PrecisionFilter(IPairList):
         stop_price = ticker['last'] * self._stoploss
 
         # Adjust stop-prices to precision
-        sp = self._exchange.price_to_precision(pair, stop_price)
+        sp = self._exchange.price_to_precision(pair, stop_price, rounding_mode=ROUND_UP)
 
-        stop_gap_price = self._exchange.price_to_precision(pair, stop_price * 0.99)
+        stop_gap_price = self._exchange.price_to_precision(pair, stop_price * 0.99,
+                                                           rounding_mode=ROUND_UP)
         logger.debug(f"{pair} - {sp} : {stop_gap_price}")
 
         if sp <= stop_gap_price:

freqtrade/rpc/api_server/api_schemas.py

@@ -108,6 +108,8 @@ class Profit(BaseModel):
     max_drawdown: float
     max_drawdown_abs: float
     trading_volume: Optional[float]
+    bot_start_timestamp: int
+    bot_start_date: str
 
 
 class SellReason(BaseModel):

freqtrade/rpc/api_server/uvicorn_threaded.py

@@ -55,7 +55,7 @@ class UvicornServer(uvicorn.Server):
 
     @contextlib.contextmanager
     def run_in_thread(self):
-        self.thread = threading.Thread(target=self.run)
+        self.thread = threading.Thread(target=self.run, name='FTUvicorn')
         self.thread.start()
         while not self.started:
             time.sleep(1e-3)

freqtrade/rpc/rpc.py

@@ -26,7 +26,7 @@ from freqtrade.exceptions import ExchangeError, PricingError
 from freqtrade.exchange import timeframe_to_minutes, timeframe_to_msecs
 from freqtrade.loggers import bufferHandler
 from freqtrade.misc import decimals_per_coin, shorten_date
-from freqtrade.persistence import Order, PairLocks, Trade
+from freqtrade.persistence import KeyStoreKeys, KeyValueStore, Order, PairLocks, Trade
 from freqtrade.persistence.models import PairLock
 from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
 from freqtrade.rpc.fiat_convert import CryptoToFiatConverter
@@ -543,6 +543,7 @@ class RPC:
         first_date = trades[0].open_date if trades else None
         last_date = trades[-1].open_date if trades else None
         num = float(len(durations) or 1)
+        bot_start = KeyValueStore.get_datetime_value(KeyStoreKeys.BOT_START_TIME)
         return {
             'profit_closed_coin': profit_closed_coin_sum,
             'profit_closed_percent_mean': round(profit_closed_ratio_mean * 100, 2),
@@ -576,6 +577,8 @@ class RPC:
             'max_drawdown': max_drawdown,
             'max_drawdown_abs': max_drawdown_abs,
             'trading_volume': trading_volume,
+            'bot_start_timestamp': int(bot_start.timestamp() * 1000) if bot_start else 0,
+            'bot_start_date': bot_start.strftime(DATETIME_PRINT_FORMAT) if bot_start else '',
         }
 
     def _rpc_balance(self, stake_currency: str, fiat_display_currency: str) -> Dict:
@@ -1193,6 +1196,7 @@ class RPC:
         from freqtrade.resolvers.strategy_resolver import StrategyResolver
         strategy = StrategyResolver.load_strategy(config)
         strategy.dp = DataProvider(config, exchange=exchange, pairlists=None)
+        strategy.ft_bot_start()
 
         df_analyzed = strategy.analyze_ticker(_data[pair], {'pair': pair})
 

freqtrade/rpc/rpc_types.py

@@ -52,7 +52,7 @@ class __RPCBuyMsgBase(RPCSendMsgBase):
     direction: str
     limit: float
     open_rate: float
-    order_type: Optional[str]  # TODO: why optional??
+    order_type: str
     stake_amount: float
     stake_currency: str
     fiat_currency: Optional[str]

freqtrade/rpc/telegram.py

@@ -819,7 +819,7 @@ class Telegram(RPCHandler):
         best_pair = stats['best_pair']
         best_pair_profit_ratio = stats['best_pair_profit_ratio']
         if stats['trade_count'] == 0:
-            markdown_msg = 'No trades yet.'
+            markdown_msg = f"No trades yet.\n*Bot started:* `{stats['bot_start_date']}`"
         else:
             # Message to display
             if stats['closed_trade_count'] > 0:
@@ -838,6 +838,7 @@ class Telegram(RPCHandler):
                 f"({profit_all_percent} \N{GREEK CAPITAL LETTER SIGMA}%)`\n"
                 f"∙ `{round_coin_value(profit_all_fiat, fiat_disp_cur)}`\n"
                 f"*Total Trade Count:* `{trade_count}`\n"
+                f"*Bot started:* `{stats['bot_start_date']}`\n"
                 f"*{'First Trade opened' if not timescale else 'Showing Profit since'}:* "
                 f"`{first_trade_date}`\n"
                 f"*Latest Trade opened:* `{latest_trade_date}`\n"

freqtrade/strategy/hyper.py

@@ -8,7 +8,7 @@ from typing import Any, Dict, Iterator, List, Optional, Tuple, Type, Union
 
 from freqtrade.constants import Config
 from freqtrade.exceptions import OperationalException
-from freqtrade.misc import deep_merge_dicts, json_load
+from freqtrade.misc import deep_merge_dicts
 from freqtrade.optimize.hyperopt_tools import HyperoptTools
 from freqtrade.strategy.parameters import BaseParameter
 
@@ -124,8 +124,7 @@ class HyperStrategyMixin:
         if filename.is_file():
             logger.info(f"Loading parameters from file {filename}")
             try:
-                with filename.open('r') as f:
-                    params = json_load(f)
+                params = HyperoptTools.load_params(filename)
                 if params.get('strategy_name') != self.__class__.__name__:
                     raise OperationalException('Invalid parameter file provided.')
                 return params

requirements-dev.txt

@@ -7,10 +7,10 @@
 -r docs/requirements-docs.txt
 
 coveralls==3.3.1
-ruff==0.0.259
-mypy==1.1.1
-pre-commit==3.2.1
-pytest==7.2.2
+ruff==0.0.261
+mypy==1.2.0
+pre-commit==3.2.2
+pytest==7.3.0
 pytest-asyncio==0.21.0
 pytest-cov==4.0.0
 pytest-mock==3.10.0
@@ -22,11 +22,11 @@ time-machine==2.9.0
 httpx==0.23.3
 
 # Convert jupyter notebooks to markdown documents
-nbconvert==7.2.10
+nbconvert==7.3.1
 
 # mypy types
-types-cachetools==5.3.0.4
+types-cachetools==5.3.0.5
 types-filelock==3.2.7
-types-requests==2.28.11.16
-types-tabulate==0.9.0.1
-types-python-dateutil==2.8.19.10
+types-requests==2.28.11.17
+types-tabulate==0.9.0.2
+types-python-dateutil==2.8.19.12

requirements-freqai.txt

@@ -7,5 +7,5 @@ scikit-learn==1.1.3
 joblib==1.2.0
 catboost==1.1.1; platform_machine != 'aarch64' and 'arm' not in platform_machine and python_version < '3.11'
 lightgbm==3.3.5
-xgboost==1.7.4
-tensorboard==2.12.0
+xgboost==1.7.5
+tensorboard==2.12.1

requirements-hyperopt.txt

@@ -5,5 +5,5 @@
 scipy==1.10.1
 scikit-learn==1.1.3
 scikit-optimize==0.9.0
-filelock==3.10.6
+filelock==3.11.0
 progressbar2==4.2.0

requirements-plot.txt

@@ -1,4 +1,4 @@
 # Include all requirements to run the bot.
 -r requirements.txt
 
-plotly==5.13.1
+plotly==5.14.1

requirements.txt

@@ -2,11 +2,11 @@ numpy==1.24.2
 pandas==1.5.3
 pandas-ta==0.3.14b
 
-ccxt==3.0.37
+ccxt==3.0.59
 cryptography==40.0.1
 aiohttp==3.8.4
-SQLAlchemy==2.0.7
-python-telegram-bot==13.15
+SQLAlchemy==2.0.9
+python-telegram-bot==20.2
 arrow==1.2.3
 cachetools==4.2.2
 requests==2.28.2
@@ -28,7 +28,7 @@ py_find_1st==1.1.5
 # Load ticker files 30% faster
 python-rapidjson==1.10
 # Properly format api responses
-orjson==3.8.8
+orjson==3.8.10
 
 # Notify systemd
 sdnotify==0.3.2
@@ -50,10 +50,10 @@ prompt-toolkit==3.0.38
 python-dateutil==2.8.2
 
 #Futures
-schedule==1.1.0
+schedule==1.2.0
 
 #WS Messages
-websockets==10.4
+websockets==11.0.1
 janus==1.0.0
 
 ast-comments==1.0.1

setup.py

@@ -59,7 +59,7 @@ setup(
     install_requires=[
         # from requirements.txt
         'ccxt>=2.6.26',
-        'SQLAlchemy',
+        'SQLAlchemy>=2.0.6',
         'python-telegram-bot>=13.4',
         'arrow>=0.17.0',
         'cachetools',

tests/exchange/test_binance.py

@@ -48,7 +48,7 @@ def test_create_stoploss_order_binance(default_conf, mocker, limitratio, expecte
     default_conf['margin_mode'] = MarginMode.ISOLATED
     default_conf['trading_mode'] = trademode
     mocker.patch(f'{EXMS}.amount_to_precision', lambda s, x, y: y)
-    mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y: y)
+    mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y, **kwargs: y)
 
     exchange = get_patched_exchange(mocker, default_conf, api_mock, 'binance')
 
@@ -127,7 +127,7 @@ def test_create_stoploss_order_dry_run_binance(default_conf, mocker):
     order_type = 'stop_loss_limit'
     default_conf['dry_run'] = True
     mocker.patch(f'{EXMS}.amount_to_precision', lambda s, x, y: y)
-    mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y: y)
+    mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y, **kwargs: y)
 
     exchange = get_patched_exchange(mocker, default_conf, api_mock, 'binance')
 

tests/exchange/test_exchange.py

@@ -8,6 +8,7 @@ from unittest.mock import MagicMock, Mock, PropertyMock, patch
 import arrow
 import ccxt
 import pytest
+from ccxt import DECIMAL_PLACES, ROUND, ROUND_UP, TICK_SIZE, TRUNCATE
 from pandas import DataFrame
 
 from freqtrade.enums import CandleType, MarginMode, TradingMode
@@ -315,35 +316,54 @@ def test_amount_to_precision(amount, precision_mode, precision, expected,):
     assert amount_to_precision(amount, precision, precision_mode) == expected
 
 
-@pytest.mark.parametrize("price,precision_mode,precision,expected", [
-    (2.34559, 2, 4, 2.3456),
-    (2.34559, 2, 5, 2.34559),
-    (2.34559, 2, 3, 2.346),
-    (2.9999, 2, 3, 3.000),
-    (2.9909, 2, 3, 2.991),
-    # Tests for Tick_size
-    (2.34559, 4, 0.0001, 2.3456),
-    (2.34559, 4, 0.00001, 2.34559),
-    (2.34559, 4, 0.001, 2.346),
-    (2.9999, 4, 0.001, 3.000),
-    (2.9909, 4, 0.001, 2.991),
-    (2.9909, 4, 0.005, 2.995),
-    (2.9973, 4, 0.005, 3.0),
-    (2.9977, 4, 0.005, 3.0),
-    (234.43, 4, 0.5, 234.5),
-    (234.53, 4, 0.5, 235.0),
-    (0.891534, 4, 0.0001, 0.8916),
-    (64968.89, 4, 0.01, 64968.89),
-    (0.000000003483, 4, 1e-12, 0.000000003483),
-
+@pytest.mark.parametrize("price,precision_mode,precision,expected,rounding_mode", [
+    # Tests for DECIMAL_PLACES, ROUND_UP
+    (2.34559, 2, 4, 2.3456, ROUND_UP),
+    (2.34559, 2, 5, 2.34559, ROUND_UP),
+    (2.34559, 2, 3, 2.346, ROUND_UP),
+    (2.9999, 2, 3, 3.000, ROUND_UP),
+    (2.9909, 2, 3, 2.991, ROUND_UP),
+    # Tests for DECIMAL_PLACES, ROUND
+    (2.345600000000001, DECIMAL_PLACES, 4, 2.3456, ROUND),
+    (2.345551, DECIMAL_PLACES, 4, 2.3456, ROUND),
+    (2.49, DECIMAL_PLACES, 0, 2., ROUND),
+    (2.51, DECIMAL_PLACES, 0, 3., ROUND),
+    (5.1, DECIMAL_PLACES, -1, 10., ROUND),
+    (4.9, DECIMAL_PLACES, -1, 0., ROUND),
+    # Tests for TICK_SIZE, ROUND_UP
+    (2.34559, TICK_SIZE, 0.0001, 2.3456, ROUND_UP),
+    (2.34559, TICK_SIZE, 0.00001, 2.34559, ROUND_UP),
+    (2.34559, TICK_SIZE, 0.001, 2.346, ROUND_UP),
+    (2.9999, TICK_SIZE, 0.001, 3.000, ROUND_UP),
+    (2.9909, TICK_SIZE, 0.001, 2.991, ROUND_UP),
+    (2.9909, TICK_SIZE, 0.005, 2.995, ROUND_UP),
+    (2.9973, TICK_SIZE, 0.005, 3.0, ROUND_UP),
+    (2.9977, TICK_SIZE, 0.005, 3.0, ROUND_UP),
+    (234.43, TICK_SIZE, 0.5, 234.5, ROUND_UP),
+    (234.53, TICK_SIZE, 0.5, 235.0, ROUND_UP),
+    (0.891534, TICK_SIZE, 0.0001, 0.8916, ROUND_UP),
+    (64968.89, TICK_SIZE, 0.01, 64968.89, ROUND_UP),
+    (0.000000003483, TICK_SIZE, 1e-12, 0.000000003483, ROUND_UP),
+    # Tests for TICK_SIZE, ROUND
+    (2.49, TICK_SIZE, 1., 2., ROUND),
+    (2.51, TICK_SIZE, 1., 3., ROUND),
+    (2.000000051, TICK_SIZE, 0.0000001, 2.0000001, ROUND),
+    (2.000000049, TICK_SIZE, 0.0000001, 2., ROUND),
+    (2.9909, TICK_SIZE, 0.005, 2.990, ROUND),
+    (2.9973, TICK_SIZE, 0.005, 2.995, ROUND),
+    (2.9977, TICK_SIZE, 0.005, 3.0, ROUND),
+    (234.24, TICK_SIZE, 0.5, 234., ROUND),
+    (234.26, TICK_SIZE, 0.5, 234.5, ROUND),
+    # Tests for TRUNCATTE
+    (2.34559, 2, 4, 2.3455, TRUNCATE),
+    (2.34559, 2, 5, 2.34559, TRUNCATE),
+    (2.34559, 2, 3, 2.345, TRUNCATE),
+    (2.9999, 2, 3, 2.999, TRUNCATE),
+    (2.9909, 2, 3, 2.990, TRUNCATE),
 ])
-def test_price_to_precision(price, precision_mode, precision, expected):
-    # digits counting mode
-    # DECIMAL_PLACES = 2
-    # SIGNIFICANT_DIGITS = 3
-    # TICK_SIZE = 4
-
-    assert price_to_precision(price, precision, precision_mode) == expected
+def test_price_to_precision(price, precision_mode, precision, expected, rounding_mode):
+    assert price_to_precision(
+        price, precision, precision_mode, rounding_mode=rounding_mode) == expected
 
 
 @pytest.mark.parametrize("price,precision_mode,precision,expected", [
@@ -417,7 +437,7 @@ def test__get_stake_amount_limit(mocker, default_conf) -> None:
     }
     mocker.patch(f'{EXMS}.markets', PropertyMock(return_value=markets))
     result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss)
-    expected_result = 2 * 2 * (1 + 0.05) / (1 - abs(stoploss))
+    expected_result = 2 * 2 * (1 + 0.05)
     assert pytest.approx(result) == expected_result
     # With Leverage
     result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss, 5.0)
@@ -426,14 +446,14 @@ def test__get_stake_amount_limit(mocker, default_conf) -> None:
     result = exchange.get_max_pair_stake_amount('ETH/BTC', 2)
     assert result == 20000
 
-    # min amount and cost are set (cost is minimal)
+    # min amount and cost are set (cost is minimal and therefore ignored)
     markets["ETH/BTC"]["limits"] = {
         'cost': {'min': 2, 'max': None},
         'amount': {'min': 2, 'max': None},
     }
     mocker.patch(f'{EXMS}.markets', PropertyMock(return_value=markets))
     result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss)
-    expected_result = max(2, 2 * 2) * (1 + 0.05) / (1 - abs(stoploss))
+    expected_result = max(2, 2 * 2) * (1 + 0.05)
     assert pytest.approx(result) == expected_result
     # With Leverage
     result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss, 10)
@@ -476,6 +496,9 @@ def test__get_stake_amount_limit(mocker, default_conf) -> None:
     result = exchange.get_max_pair_stake_amount('ETH/BTC', 2)
     assert result == 1000
 
+    result = exchange.get_max_pair_stake_amount('ETH/BTC', 2, 12.0)
+    assert result == 1000 / 12
+
     markets["ETH/BTC"]["contractSize"] = '0.01'
     default_conf['trading_mode'] = 'futures'
     default_conf['margin_mode'] = 'isolated'
@@ -5281,7 +5304,7 @@ def test_stoploss_contract_size(mocker, default_conf, contract_size, order_amoun
     })
     default_conf['dry_run'] = False
     mocker.patch(f'{EXMS}.amount_to_precision', lambda s, x, y: y)
-    mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y: y)
+    mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y, **kwargs: y)
 
     exchange = get_patched_exchange(mocker, default_conf, api_mock)
     exchange.get_contract_size = MagicMock(return_value=contract_size)
@@ -5301,3 +5324,10 @@ def test_stoploss_contract_size(mocker, default_conf, contract_size, order_amoun
     assert order['cost'] == 100
     assert order['filled'] == 100
     assert order['remaining'] == 100
+
+
+def test_price_to_precision_with_default_conf(default_conf, mocker):
+    conf = copy.deepcopy(default_conf)
+    patched_ex = get_patched_exchange(mocker, conf)
+    prec_price = patched_ex.price_to_precision("XRP/USDT", 1.0000000101)
+    assert prec_price == 1.00000001

tests/exchange/test_huobi.py

@@ -27,7 +27,7 @@ def test_create_stoploss_order_huobi(default_conf, mocker, limitratio, expected,
     })
     default_conf['dry_run'] = False
     mocker.patch(f'{EXMS}.amount_to_precision', lambda s, x, y: y)
-    mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y: y)
+    mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y, **kwargs: y)
 
     exchange = get_patched_exchange(mocker, default_conf, api_mock, 'huobi')
 
@@ -80,7 +80,7 @@ def test_create_stoploss_order_dry_run_huobi(default_conf, mocker):
     order_type = 'stop-limit'
     default_conf['dry_run'] = True
     mocker.patch(f'{EXMS}.amount_to_precision', lambda s, x, y: y)
-    mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y: y)
+    mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y, **kwargs: y)
 
     exchange = get_patched_exchange(mocker, default_conf, api_mock, 'huobi')
 

tests/exchange/test_kraken.py

@@ -29,7 +29,7 @@ def test_buy_kraken_trading_agreement(default_conf, mocker):
     default_conf['dry_run'] = False
 
     mocker.patch(f'{EXMS}.amount_to_precision', lambda s, x, y: y)
-    mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y: y)
+    mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y, **kwargs: y)
     exchange = get_patched_exchange(mocker, default_conf, api_mock, id="kraken")
 
     order = exchange.create_order(
@@ -192,7 +192,7 @@ def test_create_stoploss_order_kraken(default_conf, mocker, ordertype, side, adj
 
     default_conf['dry_run'] = False
     mocker.patch(f'{EXMS}.amount_to_precision', lambda s, x, y: y)
-    mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y: y)
+    mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y, **kwargs: y)
 
     exchange = get_patched_exchange(mocker, default_conf, api_mock, 'kraken')
 
@@ -263,7 +263,7 @@ def test_create_stoploss_order_dry_run_kraken(default_conf, mocker, side):
     api_mock = MagicMock()
     default_conf['dry_run'] = True
     mocker.patch(f'{EXMS}.amount_to_precision', lambda s, x, y: y)
-    mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y: y)
+    mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y, **kwargs: y)
 
     exchange = get_patched_exchange(mocker, default_conf, api_mock, 'kraken')
 

tests/exchange/test_kucoin.py

@@ -27,7 +27,7 @@ def test_create_stoploss_order_kucoin(default_conf, mocker, limitratio, expected
     })
     default_conf['dry_run'] = False
     mocker.patch(f'{EXMS}.amount_to_precision', lambda s, x, y: y)
-    mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y: y)
+    mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y, **kwargs: y)
 
     exchange = get_patched_exchange(mocker, default_conf, api_mock, 'kucoin')
     if order_type == 'limit':
@@ -88,7 +88,7 @@ def test_stoploss_order_dry_run_kucoin(default_conf, mocker):
     order_type = 'market'
     default_conf['dry_run'] = True
     mocker.patch(f'{EXMS}.amount_to_precision', lambda s, x, y: y)
-    mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y: y)
+    mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y, **kwargs: y)
 
     exchange = get_patched_exchange(mocker, default_conf, api_mock, 'kucoin')
 

tests/freqai/conftest.py

@@ -119,6 +119,7 @@ def make_unfiltered_dataframe(mocker, freqai_conf):
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     freqai.dk.pair = "ADA/BTC"
     data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
     freqai.dd.load_all_pair_histories(data_load_timerange, freqai.dk)
@@ -152,6 +153,7 @@ def make_data_dictionary(mocker, freqai_conf):
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     freqai.dk.pair = "ADA/BTC"
     data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
     freqai.dd.load_all_pair_histories(data_load_timerange, freqai.dk)

tests/freqai/test_freqai_datadrawer.py

@@ -19,6 +19,7 @@ def test_update_historic_data(mocker, freqai_conf):
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     timerange = TimeRange.parse_timerange("20180110-20180114")
 
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
@@ -41,6 +42,7 @@ def test_load_all_pairs_histories(mocker, freqai_conf):
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     timerange = TimeRange.parse_timerange("20180110-20180114")
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
 
@@ -60,6 +62,7 @@ def test_get_base_and_corr_dataframes(mocker, freqai_conf):
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     timerange = TimeRange.parse_timerange("20180110-20180114")
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
     sub_timerange = TimeRange.parse_timerange("20180111-20180114")
@@ -87,6 +90,7 @@ def test_use_strategy_to_populate_indicators(mocker, freqai_conf):
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     timerange = TimeRange.parse_timerange("20180110-20180114")
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
     sub_timerange = TimeRange.parse_timerange("20180111-20180114")
@@ -103,8 +107,9 @@ def test_get_timerange_from_live_historic_predictions(mocker, freqai_conf):
     exchange = get_patched_exchange(mocker, freqai_conf)
     strategy.dp = DataProvider(freqai_conf, exchange)
     freqai = strategy.freqai
-    freqai.live = True
+    freqai.live = False
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = False
     timerange = TimeRange.parse_timerange("20180126-20180130")
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
     sub_timerange = TimeRange.parse_timerange("20180128-20180130")

tests/freqai/test_freqai_datakitchen.py

@@ -180,6 +180,7 @@ def test_get_full_model_path(mocker, freqai_conf, model):
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     timerange = TimeRange.parse_timerange("20180110-20180130")
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
 

tests/freqai/test_freqai_interface.py

@@ -87,6 +87,7 @@ def test_extract_data_and_train_model_Standard(mocker, freqai_conf, model, pca,
     freqai.live = True
     freqai.can_short = can_short
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     freqai.dk.set_paths('ADA/BTC', 10000)
     timerange = TimeRange.parse_timerange("20180110-20180130")
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
@@ -135,6 +136,7 @@ def test_extract_data_and_train_model_MultiTargets(mocker, freqai_conf, model, s
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     timerange = TimeRange.parse_timerange("20180110-20180130")
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
 
@@ -178,6 +180,7 @@ def test_extract_data_and_train_model_Classifiers(mocker, freqai_conf, model):
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     timerange = TimeRange.parse_timerange("20180110-20180130")
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
 
@@ -371,6 +374,9 @@ def test_backtesting_fit_live_predictions(mocker, freqai_conf, caplog):
     sub_timerange = TimeRange.parse_timerange("20180129-20180130")
     corr_df, base_df = freqai.dd.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC", freqai.dk)
     df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, "LTC/BTC")
+    df = strategy.set_freqai_targets(df.copy(), metadata={"pair": "LTC/BTC"})
+    df = freqai.dk.remove_special_chars_from_feature_names(df)
+    freqai.dk.get_unique_classes_from_labels(df)
     freqai.dk.pair = "ADA/BTC"
     freqai.dk.full_df = df.fillna(0)
     freqai.dk.full_df
@@ -394,6 +400,7 @@ def test_principal_component_analysis(mocker, freqai_conf):
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     timerange = TimeRange.parse_timerange("20180110-20180130")
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
 
@@ -425,10 +432,12 @@ def test_plot_feature_importance(mocker, freqai_conf):
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     timerange = TimeRange.parse_timerange("20180110-20180130")
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
 
-    freqai.dd.pair_dict = MagicMock()
+    freqai.dd.pair_dict = {"ADA/BTC": {"model_filename": "fake_name",
+                                       "trained_timestamp": 1, "data_path": "", "extras": {}}}
 
     data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
     new_timerange = TimeRange.parse_timerange("20180120-20180130")

tests/persistence/test_key_value_store.py

@@ -0,0 +1,69 @@
+from datetime import datetime, timedelta, timezone
+
+import pytest
+
+from freqtrade.persistence.key_value_store import KeyValueStore, set_startup_time
+from tests.conftest import create_mock_trades_usdt
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_key_value_store(time_machine):
+    start = datetime(2023, 1, 1, 4, tzinfo=timezone.utc)
+    time_machine.move_to(start, tick=False)
+
+    KeyValueStore.store_value("test", "testStringValue")
+    KeyValueStore.store_value("test_dt", datetime.now(timezone.utc))
+    KeyValueStore.store_value("test_float", 22.51)
+    KeyValueStore.store_value("test_int", 15)
+
+    assert KeyValueStore.get_value("test") == "testStringValue"
+    assert KeyValueStore.get_value("test") == "testStringValue"
+    assert KeyValueStore.get_string_value("test") == "testStringValue"
+    assert KeyValueStore.get_value("test_dt") == datetime.now(timezone.utc)
+    assert KeyValueStore.get_datetime_value("test_dt") == datetime.now(timezone.utc)
+    assert KeyValueStore.get_string_value("test_dt") is None
+    assert KeyValueStore.get_float_value("test_dt") is None
+    assert KeyValueStore.get_int_value("test_dt") is None
+    assert KeyValueStore.get_value("test_float") == 22.51
+    assert KeyValueStore.get_float_value("test_float") == 22.51
+    assert KeyValueStore.get_value("test_int") == 15
+    assert KeyValueStore.get_int_value("test_int") == 15
+    assert KeyValueStore.get_datetime_value("test_int") is None
+
+    time_machine.move_to(start + timedelta(days=20, hours=5), tick=False)
+    assert KeyValueStore.get_value("test_dt") != datetime.now(timezone.utc)
+    assert KeyValueStore.get_value("test_dt") == start
+    # Test update works
+    KeyValueStore.store_value("test_dt", datetime.now(timezone.utc))
+    assert KeyValueStore.get_value("test_dt") == datetime.now(timezone.utc)
+
+    KeyValueStore.store_value("test_float", 23.51)
+    assert KeyValueStore.get_value("test_float") == 23.51
+    # test deleting
+    KeyValueStore.delete_value("test_float")
+    assert KeyValueStore.get_value("test_float") is None
+    # Delete same value again (should not fail)
+    KeyValueStore.delete_value("test_float")
+
+    with pytest.raises(ValueError, match=r"Unknown value type"):
+        KeyValueStore.store_value("test_float", {'some': 'dict'})
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_set_startup_time(fee, time_machine):
+    create_mock_trades_usdt(fee)
+    start = datetime.now(timezone.utc)
+    time_machine.move_to(start, tick=False)
+    set_startup_time()
+
+    assert KeyValueStore.get_value("startup_time") == start
+    initial_time = KeyValueStore.get_value("bot_start_time")
+    assert initial_time <= start
+
+    # Simulate bot restart
+    new_start = start + timedelta(days=5)
+    time_machine.move_to(new_start, tick=False)
+    set_startup_time()
+
+    assert KeyValueStore.get_value("startup_time") == new_start
+    assert KeyValueStore.get_value("bot_start_time") == initial_time

tests/rpc/test_rpc_apiserver.py

@@ -883,6 +883,8 @@ def test_api_profit(botclient, mocker, ticker, fee, markets, is_short, expected)
         'max_drawdown': ANY,
         'max_drawdown_abs': ANY,
         'trading_volume': expected['trading_volume'],
+        'bot_start_timestamp': 0,
+        'bot_start_date': '',
     }
 
 
@@ -1403,10 +1405,10 @@ def test_api_pair_candles(botclient, ohlcv_history):
              ])
 
 
-def test_api_pair_history(botclient, ohlcv_history):
+def test_api_pair_history(botclient, mocker):
     ftbot, client = botclient
     timeframe = '5m'
-
+    lfm = mocker.patch('freqtrade.strategy.interface.IStrategy.load_freqAI_model')
     # No pair
     rc = client_get(client,
                     f"{BASE_URI}/pair_history?timeframe={timeframe}"
@@ -1440,6 +1442,7 @@ def test_api_pair_history(botclient, ohlcv_history):
     assert len(rc.json()['data']) == rc.json()['length']
     assert 'columns' in rc.json()
     assert 'data' in rc.json()
+    assert lfm.call_count == 1
     assert rc.json()['pair'] == 'UNITTEST/BTC'
     assert rc.json()['strategy'] == CURRENT_TEST_STRATEGY
     assert rc.json()['data_start'] == '2018-01-11 00:00:00+00:00'

tests/strategy/test_interface.py

@@ -986,7 +986,8 @@ def test_auto_hyperopt_interface_loadparams(default_conf, mocker, caplog):
             }
         }
     }
-    mocker.patch('freqtrade.strategy.hyper.json_load', return_value=expected_result)
+    mocker.patch('freqtrade.strategy.hyper.HyperoptTools.load_params',
+                 return_value=expected_result)
     PairLocks.timeframe = default_conf['timeframe']
     strategy = StrategyResolver.load_strategy(default_conf)
     assert strategy.stoploss == -0.05
@@ -1005,11 +1006,13 @@ def test_auto_hyperopt_interface_loadparams(default_conf, mocker, caplog):
         }
     }
 
-    mocker.patch('freqtrade.strategy.hyper.json_load', return_value=expected_result)
+    mocker.patch('freqtrade.strategy.hyper.HyperoptTools.load_params',
+                 return_value=expected_result)
     with pytest.raises(OperationalException, match="Invalid parameter file provided."):
         StrategyResolver.load_strategy(default_conf)
 
-    mocker.patch('freqtrade.strategy.hyper.json_load', MagicMock(side_effect=ValueError()))
+    mocker.patch('freqtrade.strategy.hyper.HyperoptTools.load_params',
+                 MagicMock(side_effect=ValueError()))
 
     StrategyResolver.load_strategy(default_conf)
     assert log_has("Invalid parameter file format.", caplog)

tests/test_freqtradebot.py

@@ -356,7 +356,7 @@ def test_create_trade_no_stake_amount(default_conf_usdt, ticker_usdt, fee, mocke
 @pytest.mark.parametrize("is_short", [False, True])
 @pytest.mark.parametrize('stake_amount,create,amount_enough,max_open_trades', [
     (5.0, True, True, 99),
-    (0.049, True, False, 99),  # Amount will be adjusted to min - which is 0.051
+    (0.042, True, False, 99),  # Amount will be adjusted to min - which is 0.051
     (0, False, True, 99),
     (UNLIMITED_STAKE_AMOUNT, False, True, 0),
 ])
@@ -1290,6 +1290,137 @@ def test_handle_stoploss_on_exchange(mocker, default_conf_usdt, fee, caplog, is_
     assert trade.exit_reason == str(ExitType.EMERGENCY_EXIT)
 
 
+@pytest.mark.parametrize("is_short", [False, True])
+def test_handle_stoploss_on_exchange_partial(
+        mocker, default_conf_usdt, fee, is_short, limit_order) -> None:
+    stop_order_dict = {'id': "101", "status": "open"}
+    stoploss = MagicMock(return_value=stop_order_dict)
+    enter_order = limit_order[entry_side(is_short)]
+    exit_order = limit_order[exit_side(is_short)]
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        EXMS,
+        fetch_ticker=MagicMock(return_value={
+            'bid': 1.9,
+            'ask': 2.2,
+            'last': 1.9
+        }),
+        create_order=MagicMock(side_effect=[
+            enter_order,
+            exit_order,
+        ]),
+        get_fee=fee,
+        create_stoploss=stoploss
+    )
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
+
+    freqtrade.enter_positions()
+    trade = Trade.session.scalars(select(Trade)).first()
+    trade.is_short = is_short
+    trade.is_open = True
+    trade.open_order_id = None
+    trade.stoploss_order_id = None
+
+    assert freqtrade.handle_stoploss_on_exchange(trade) is False
+    assert stoploss.call_count == 1
+    assert trade.stoploss_order_id == "101"
+    assert trade.amount == 30
+    stop_order_dict.update({'id': "102"})
+    # Stoploss on exchange is cancelled on exchange, but filled partially.
+    # Must update trade amount to guarantee successful exit.
+    stoploss_order_hit = MagicMock(return_value={
+        'id': "101",
+        'status': 'canceled',
+        'type': 'stop_loss_limit',
+        'price': 3,
+        'average': 2,
+        'filled': trade.amount / 2,
+        'remaining': trade.amount / 2,
+        'amount': enter_order['amount'],
+    })
+    mocker.patch(f'{EXMS}.fetch_stoploss_order', stoploss_order_hit)
+    assert freqtrade.handle_stoploss_on_exchange(trade) is False
+    # Stoploss filled partially ...
+    assert trade.amount == 15
+
+    assert trade.stoploss_order_id == "102"
+
+
+@pytest.mark.parametrize("is_short", [False, True])
+def test_handle_stoploss_on_exchange_partial_cancel_here(
+        mocker, default_conf_usdt, fee, is_short, limit_order, caplog) -> None:
+    stop_order_dict = {'id': "101", "status": "open"}
+    default_conf_usdt['trailing_stop'] = True
+    stoploss = MagicMock(return_value=stop_order_dict)
+    enter_order = limit_order[entry_side(is_short)]
+    exit_order = limit_order[exit_side(is_short)]
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        EXMS,
+        fetch_ticker=MagicMock(return_value={
+            'bid': 1.9,
+            'ask': 2.2,
+            'last': 1.9
+        }),
+        create_order=MagicMock(side_effect=[
+            enter_order,
+            exit_order,
+        ]),
+        get_fee=fee,
+        create_stoploss=stoploss
+    )
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
+
+    freqtrade.enter_positions()
+    trade = Trade.session.scalars(select(Trade)).first()
+    trade.is_short = is_short
+    trade.is_open = True
+    trade.open_order_id = None
+    trade.stoploss_order_id = None
+
+    assert freqtrade.handle_stoploss_on_exchange(trade) is False
+    assert stoploss.call_count == 1
+    assert trade.stoploss_order_id == "101"
+    assert trade.amount == 30
+    stop_order_dict.update({'id': "102"})
+    # Stoploss on exchange is open.
+    # Freqtrade cancels the stop - but cancel returns a partial filled order.
+    stoploss_order_hit = MagicMock(return_value={
+        'id': "101",
+        'status': 'open',
+        'type': 'stop_loss_limit',
+        'price': 3,
+        'average': 2,
+        'filled': 0,
+        'remaining': trade.amount,
+        'amount': enter_order['amount'],
+    })
+    stoploss_order_cancel = MagicMock(return_value={
+        'id': "101",
+        'status': 'canceled',
+        'type': 'stop_loss_limit',
+        'price': 3,
+        'average': 2,
+        'filled': trade.amount / 2,
+        'remaining': trade.amount / 2,
+        'amount': enter_order['amount'],
+    })
+    mocker.patch(f'{EXMS}.fetch_stoploss_order', stoploss_order_hit)
+    mocker.patch(f'{EXMS}.cancel_stoploss_order_with_result', stoploss_order_cancel)
+    trade.stoploss_last_update = arrow.utcnow().shift(minutes=-10).datetime
+
+    assert freqtrade.handle_stoploss_on_exchange(trade) is False
+    # Canceled Stoploss filled partially ...
+    assert log_has_re('Cancelling current stoploss on exchange.*', caplog)
+
+    assert trade.stoploss_order_id == "102"
+    assert trade.amount == 15
+
+
 @pytest.mark.parametrize("is_short", [False, True])
 def test_handle_sle_cancel_cant_recreate(mocker, default_conf_usdt, fee, caplog, is_short,
                                          limit_order) -> None:
@@ -1671,7 +1802,7 @@ def test_stoploss_on_exchange_price_rounding(
         EXMS,
         get_fee=fee,
     )
-    price_mock = MagicMock(side_effect=lambda p, s: int(s))
+    price_mock = MagicMock(side_effect=lambda p, s, **kwargs: int(s))
     stoploss_mock = MagicMock(return_value={'id': '13434334'})
     adjust_mock = MagicMock(return_value=False)
     mocker.patch.multiple(
@@ -2824,6 +2955,9 @@ def test_manage_open_orders_exit_usercustom(
     assert rpc_mock.call_count == 2
     assert freqtrade.strategy.check_exit_timeout.call_count == 1
     assert freqtrade.strategy.check_entry_timeout.call_count == 0
+    trade = Trade.session.scalars(select(Trade)).first()
+    # cancelling didn't succeed - order-id remains open.
+    assert trade.open_order_id is not None
 
     # 2nd canceled trade - Fail execute exit
     caplog.clear()
@@ -3334,6 +3468,7 @@ def test_handle_cancel_exit_cancel_exception(mocker, default_conf_usdt) -> None:
 
     # TODO: should not be magicmock
     trade = MagicMock()
+    trade.open_order_id = '125'
     reason = CANCEL_REASON['TIMEOUT']
     order = {'remaining': 1,
              'id': '125',
@@ -3341,6 +3476,10 @@ def test_handle_cancel_exit_cancel_exception(mocker, default_conf_usdt) -> None:
              'status': "open"}
     assert not freqtrade.handle_cancel_exit(trade, order, reason)
 
+    # mocker.patch(f'{EXMS}.cancel_order_with_result', return_value=order)
+    # assert not freqtrade.handle_cancel_exit(trade, order, reason)
+    # assert trade.open_order_id == '125'
+
 
 @pytest.mark.parametrize("is_short, open_rate, amt", [
     (False, 2.0, 30.0),