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Merge branch 'feat/freqai' of https://github.com/freqtrade/freqtrade into feat/freqai

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This commit is contained in:
longyu
2022-07-04 09:01:34 +02:00
parent 769bd44d35 eda9464d30
commit 3f1ada81d5
143 changed files with 12472 additions and 10183 deletions
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76
freqtrade/templates/FreqaiExampleStrategy.py
View File

@@ -70,7 +70,9 @@ class FreqaiExampleStrategy(IStrategy):
def bot_start(self):
self.model = CustomModel(self.config)
def populate_any_indicators(self, metadata, pair, df, tf, informative=None, coin=""):
def populate_any_indicators(
self, metadata, pair, df, tf, informative=None, coin="", set_generalized_indicators=False
):
"""
Function designed to automatically generate, name and merge features
from user indicated timeframes in the configuration file. User controls the indicators
@@ -120,9 +122,7 @@ class FreqaiExampleStrategy(IStrategy):
informative["close"] / informative[f"{coin}bb_lowerband-period_{t}"]
)
informative[f"%-{coin}roc-period_{t}"] = ta.ROC(
informative, timeperiod=t
)
informative[f"%-{coin}roc-period_{t}"] = ta.ROC(informative, timeperiod=t)
macd = ta.MACD(informative, timeperiod=t)
informative[f"%-{coin}macd-period_{t}"] = macd["macd"]
@@ -152,17 +152,17 @@ class FreqaiExampleStrategy(IStrategy):
# Add generalized indicators here (because in live, it will call this
# function to populate indicators during training). Notice how we ensure not to
# add them multiple times
if pair == self.freqai_info['corr_pairlist'][0] and tf == self.timeframe:
if set_generalized_indicators:
df["%-day_of_week"] = (df["date"].dt.dayofweek + 1) / 7
df["%-hour_of_day"] = (df["date"].dt.hour + 1) / 25
# user adds targets here by prepending them with &- (see convention below)
# If user wishes to use multiple targets, a multioutput prediction model
# needs to be used such as templates/CatboostPredictionMultiModel.py
df['&-s_close'] = (
df["&-s_close"] = (
df["close"]
.shift(-self.freqai_info['feature_parameters']["period"])
.rolling(self.freqai_info['feature_parameters']["period"])
.shift(-self.freqai_info["feature_parameters"]["period"])
.rolling(self.freqai_info["feature_parameters"]["period"])
.mean()
/ df["close"]
- 1
@@ -174,15 +174,21 @@ class FreqaiExampleStrategy(IStrategy):
self.freqai_info = self.config["freqai"]
self.pair = metadata["pair"]
sgi = True
# the following loops are necessary for building the features
# indicated by the user in the configuration file.
# All indicators must be populated by populate_any_indicators() for live functionality
# to work correctly.
for tf in self.freqai_info["timeframes"]:
dataframe = self.populate_any_indicators(
metadata, self.pair, dataframe.copy(), tf, coin=self.pair.split("/")[0] + "-"
metadata,
self.pair,
dataframe.copy(),
tf,
coin=self.pair.split("/")[0] + "-",
set_generalized_indicators=sgi,
)
sgi = False
for pair in self.freqai_info["corr_pairlist"]:
if metadata["pair"] in pair:
continue # do not include whitelisted pair twice if it is in corr_pairlist
@@ -231,51 +237,55 @@ class FreqaiExampleStrategy(IStrategy):
def get_ticker_indicator(self):
return int(self.config["timeframe"][:-1])
def custom_exit(self, pair: str, trade: Trade, current_time, current_rate,
current_profit, **kwargs):
def custom_exit(
self, pair: str, trade: Trade, current_time, current_rate, current_profit, **kwargs
):
dataframe, _ = self.dp.get_analyzed_dataframe(pair=pair, timeframe=self.timeframe)
trade_date = timeframe_to_prev_date(self.config['timeframe'], trade.open_date_utc)
trade_candle = dataframe.loc[(dataframe['date'] == trade_date)]
trade_date = timeframe_to_prev_date(self.config["timeframe"], trade.open_date_utc)
trade_candle = dataframe.loc[(dataframe["date"] == trade_date)]
if trade_candle.empty:
return None
trade_candle = trade_candle.squeeze()
follow_mode = self.config.get('freqai', {}).get('follow_mode', False)
follow_mode = self.config.get("freqai", {}).get("follow_mode", False)
if not follow_mode:
pair_dict = self.model.bridge.data_drawer.pair_dict
pair_dict = self.model.bridge.dd.pair_dict
else:
pair_dict = self.model.bridge.data_drawer.follower_dict
pair_dict = self.model.bridge.dd.follower_dict
entry_tag = trade.enter_tag
if ('prediction' + entry_tag not in pair_dict[pair] or
pair_dict[pair]['prediction' + entry_tag] > 0):
if (
"prediction" + entry_tag not in pair_dict[pair]
or pair_dict[pair]["prediction" + entry_tag] > 0
):
with self.model.bridge.lock:
pair_dict[pair]['prediction' + entry_tag] = abs(trade_candle['&-s_close'])
pair_dict[pair]["prediction" + entry_tag] = abs(trade_candle["&-s_close"])
if not follow_mode:
self.model.bridge.data_drawer.save_drawer_to_disk()
self.model.bridge.dd.save_drawer_to_disk()
else:
self.model.bridge.data_drawer.save_follower_dict_to_disk()
self.model.bridge.dd.save_follower_dict_to_disk()
roi_price = pair_dict[pair]['prediction' + entry_tag]
roi_price = pair_dict[pair]["prediction" + entry_tag]
roi_time = self.max_roi_time_long.value
roi_decay = roi_price * (1 - ((current_time - trade.open_date_utc).seconds) /
(roi_time * 60))
roi_decay = roi_price * (
1 - ((current_time - trade.open_date_utc).seconds) / (roi_time * 60)
)
if roi_decay < 0:
roi_decay = self.linear_roi_offset.value
else:
roi_decay += self.linear_roi_offset.value
if current_profit > roi_decay:
return 'roi_custom_win'
return "roi_custom_win"
if current_profit < -roi_decay:
return 'roi_custom_loss'
return "roi_custom_loss"
def confirm_trade_exit(
self,
@@ -287,22 +297,22 @@ class FreqaiExampleStrategy(IStrategy):
time_in_force: str,
exit_reason: str,
current_time,
**kwargs
**kwargs,
) -> bool:
entry_tag = trade.enter_tag
follow_mode = self.config.get("freqai", {}).get("follow_mode", False)
if not follow_mode:
pair_dict = self.model.bridge.data_drawer.pair_dict
pair_dict = self.model.bridge.dd.pair_dict
else:
pair_dict = self.model.bridge.data_drawer.follower_dict
pair_dict = self.model.bridge.dd.follower_dict
with self.model.bridge.lock:
pair_dict[pair]["prediction" + entry_tag] = 0
if not follow_mode:
self.model.bridge.data_drawer.save_drawer_to_disk()
self.model.bridge.dd.save_drawer_to_disk()
else:
self.model.bridge.data_drawer.save_follower_dict_to_disk()
self.model.bridge.dd.save_follower_dict_to_disk()
return True
@@ -316,7 +326,7 @@ class FreqaiExampleStrategy(IStrategy):
current_time,
entry_tag,
side: str,
**kwargs
**kwargs,
) -> bool:
df, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)

4
freqtrade/templates/base_strategy.py.j2
View File

@@ -6,7 +6,7 @@ import numpy as np # noqa
import pandas as pd # noqa
from pandas import DataFrame # noqa
from datetime import datetime # noqa
from typing import Optional # noqa
from typing import Optional, Union # noqa
from freqtrade.strategy import (BooleanParameter, CategoricalParameter, DecimalParameter,
IStrategy, IntParameter)
@@ -64,7 +64,7 @@ class {{ strategy }}(IStrategy):
# trailing_stop_positive_offset = 0.0 # Disabled / not configured
# Run "populate_indicators()" only for new candle.
process_only_new_candles = False
process_only_new_candles = True
# These values can be overridden in the config.
use_exit_signal = True

2
freqtrade/templates/sample_strategy.py
View File

@@ -62,7 +62,7 @@ class SampleStrategy(IStrategy):
timeframe = '5m'
# Run "populate_indicators()" only for new candle.
process_only_new_candles = False
process_only_new_candles = True
# These values can be overridden in the config.
use_exit_signal = True

27
freqtrade/templates/subtemplates/strategy_methods_advanced.j2
View File

@@ -13,7 +13,7 @@ def bot_loop_start(self, **kwargs) -> None:
pass
def custom_entry_price(self, pair: str, current_time: 'datetime', proposed_rate: float,
entry_tag: Optional[str], **kwargs) -> float:
entry_tag: 'Optional[str]', side: str, **kwargs) -> float:
"""
Custom entry price logic, returning the new entry price.
@@ -80,8 +80,8 @@ def custom_exit_price(self, pair: str, trade: 'Trade',
return proposed_rate
def custom_stake_amount(self, pair: str, current_time: 'datetime', current_rate: float,
proposed_stake: float, min_stake: float, max_stake: float,
side: str, entry_tag: Optional[str], **kwargs) -> float:
proposed_stake: float, min_stake: Optional[float], max_stake: float,
entry_tag: 'Optional[str]', side: str, **kwargs) -> float:
"""
Customize stake size for each new trade.
@@ -159,8 +159,9 @@ def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: f
:param pair: Pair that's about to be bought/shorted.
:param order_type: Order type (as configured in order_types). usually limit or market.
:param amount: Amount in target (quote) currency that's going to be traded.
:param amount: Amount in target (base) currency that's going to be traded.
:param rate: Rate that's going to be used when using limit orders
or current rate for market orders.
:param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
:param current_time: datetime object, containing the current datetime
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
@@ -175,7 +176,7 @@ def confirm_trade_exit(self, pair: str, trade: 'Trade', order_type: str, amount:
rate: float, time_in_force: str, exit_reason: str,
current_time: 'datetime', **kwargs) -> bool:
"""
Called right before placing a regular sell order.
Called right before placing a regular exit order.
Timing for this function is critical, so avoid doing heavy computations or
network requests in this method.
@@ -183,18 +184,19 @@ def confirm_trade_exit(self, pair: str, trade: 'Trade', order_type: str, amount:
When not implemented by a strategy, returns True (always confirming).
:param pair: Pair that's currently analyzed
:param pair: Pair for trade that's about to be exited.
:param trade: trade object.
:param order_type: Order type (as configured in order_types). usually limit or market.
:param amount: Amount in quote currency.
:param amount: Amount in base currency.
:param rate: Rate that's going to be used when using limit orders
or current rate for market orders.
:param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
:param exit_reason: Exit reason.
Can be any of ['roi', 'stop_loss', 'stoploss_on_exchange', 'trailing_stop_loss',
'exit_signal', 'force_exit', 'emergency_exit']
:param current_time: datetime object, containing the current datetime
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return bool: When True is returned, then the exit-order is placed on the exchange.
:return bool: When True, then the exit-order is placed on the exchange.
False aborts the process
"""
return True
@@ -244,8 +246,8 @@ def check_exit_timeout(self, pair: str, trade: 'Trade', order: 'Order',
return False
def adjust_trade_position(self, trade: 'Trade', current_time: 'datetime',
current_rate: float, current_profit: float, min_stake: float,
max_stake: float, **kwargs) -> Optional[float]:
current_rate: float, current_profit: float, min_stake: Optional[float],
max_stake: float, **kwargs) -> 'Optional[float]':
"""
Custom trade adjustment logic, returning the stake amount that a trade should be increased.
This means extra buy orders with additional fees.
@@ -267,8 +269,8 @@ def adjust_trade_position(self, trade: 'Trade', current_time: 'datetime',
return None
def leverage(self, pair: str, current_time: datetime, current_rate: float,
proposed_leverage: float, max_leverage: float, side: str,
**kwargs) -> float:
proposed_leverage: float, max_leverage: float, entry_tag: Optional[str],
side: str, **kwargs) -> float:
"""
Customize leverage for each new trade. This method is only called in futures mode.
@@ -277,6 +279,7 @@ def leverage(self, pair: str, current_time: datetime, current_rate: float,
:param current_rate: Rate, calculated based on pricing settings in exit_pricing.
:param proposed_leverage: A leverage proposed by the bot.
:param max_leverage: Max leverage allowed on this pair
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
:param side: 'long' or 'short' - indicating the direction of the proposed trade
:return: A leverage amount, which is between 1.0 and max_leverage.
"""