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Merge branch 'freqtrade:develop' into develop

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This commit is contained in:
smarmau
2022-10-02 21:03:35 +11:00
committed by GitHub
parent a0b7e4d4c8 e686faf1bc
commit a17c32577f
45 changed files with 467 additions and 180 deletions
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3
freqtrade/constants.py
View File

@@ -31,7 +31,7 @@ HYPEROPT_LOSS_BUILTIN = ['ShortTradeDurHyperOptLoss', 'OnlyProfitHyperOptLoss',
'CalmarHyperOptLoss',
'MaxDrawDownHyperOptLoss', 'MaxDrawDownRelativeHyperOptLoss',
'ProfitDrawDownHyperOptLoss']
AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList',
AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList', 'ProducerPairList',
'AgeFilter', 'OffsetFilter', 'PerformanceFilter',
'PrecisionFilter', 'PriceFilter', 'RangeStabilityFilter',
'ShuffleFilter', 'SpreadFilter', 'VolatilityFilter']
@@ -568,6 +568,7 @@ CONF_SCHEMA = {
"properties": {
"test_size": {"type": "number"},
"random_state": {"type": "integer"},
"shuffle": {"type": "boolean", "default": False}
},
},
"model_training_parameters": {

3
freqtrade/data/converter.py
View File

@@ -47,8 +47,7 @@ def ohlcv_to_dataframe(ohlcv: list, timeframe: str, pair: str, *,
def clean_ohlcv_dataframe(data: DataFrame, timeframe: str, pair: str, *,
fill_missing: bool = True,
drop_incomplete: bool = True) -> DataFrame:
fill_missing: bool, drop_incomplete: bool) -> DataFrame:
"""
Cleanse a OHLCV dataframe by
* Grouping it by date (removes duplicate tics)

2
freqtrade/data/history/history_utils.py
View File

@@ -26,7 +26,7 @@ def load_pair_history(pair: str,
datadir: Path, *,
timerange: Optional[TimeRange] = None,
fill_up_missing: bool = True,
drop_incomplete: bool = True,
drop_incomplete: bool = False,
startup_candles: int = 0,
data_format: str = None,
data_handler: IDataHandler = None,

2
freqtrade/data/history/idatahandler.py
View File

@@ -275,7 +275,7 @@ class IDataHandler(ABC):
candle_type: CandleType, *,
timerange: Optional[TimeRange] = None,
fill_missing: bool = True,
drop_incomplete: bool = True,
drop_incomplete: bool = False,
startup_candles: int = 0,
warn_no_data: bool = True,
) -> DataFrame:

31
freqtrade/exchange/binance.py
View File

@@ -68,6 +68,37 @@ class Binance(Exchange):
tickers = deep_merge_dicts(bidsasks, tickers, allow_null_overrides=False)
return tickers
@retrier
def additional_exchange_init(self) -> None:
"""
Additional exchange initialization logic.
.api will be available at this point.
Must be overridden in child methods if required.
"""
try:
if self.trading_mode == TradingMode.FUTURES and not self._config['dry_run']:
position_side = self._api.fapiPrivateGetPositionsideDual()
self._log_exchange_response('position_side_setting', position_side)
assets_margin = self._api.fapiPrivateGetMultiAssetsMargin()
self._log_exchange_response('multi_asset_margin', assets_margin)
msg = ""
if position_side.get('dualSidePosition') is True:
msg += (
"\nHedge Mode is not supported by freqtrade. "
"Please change 'Position Mode' on your binance futures account.")
if assets_margin.get('multiAssetsMargin') is True:
msg += ("\nMulti-Asset Mode is not supported by freqtrade. "
"Please change 'Asset Mode' on your binance futures account.")
if msg:
raise OperationalException(msg)
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not set leverage due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
@retrier
def _set_leverage(
self,

2
freqtrade/exchange/exchange.py
View File

@@ -1292,7 +1292,7 @@ class Exchange:
order = self.fetch_order(order_id, pair)
except InvalidOrderException:
logger.warning(f"Could not fetch cancelled order {order_id}.")
order = {'fee': {}, 'status': 'canceled', 'amount': amount, 'info': {}}
order = {'id': order_id, 'fee': {}, 'status': 'canceled', 'amount': amount, 'info': {}}
return order

3
freqtrade/exchange/okx.py
View File

@@ -78,7 +78,8 @@ class Okx(Exchange):
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not set leverage due to {e.__class__.__name__}. Message: {e}') from e
f'Error in additional_exchange_init due to {e.__class__.__name__}. Message: {e}'
) from e
except ccxt.BaseError as e:
raise OperationalException(e) from e

2
freqtrade/freqai/base_models/BaseClassifierModel.py
View File

@@ -92,7 +92,7 @@ class BaseClassifierModel(IFreqaiModel):
filtered_df = dk.normalize_data_from_metadata(filtered_df)
dk.data_dictionary["prediction_features"] = filtered_df
self.data_cleaning_predict(dk, filtered_df)
self.data_cleaning_predict(dk)
predictions = self.model.predict(dk.data_dictionary["prediction_features"])
pred_df = DataFrame(predictions, columns=dk.label_list)

2
freqtrade/freqai/base_models/BaseRegressionModel.py
View File

@@ -92,7 +92,7 @@ class BaseRegressionModel(IFreqaiModel):
dk.data_dictionary["prediction_features"] = filtered_df
# optional additional data cleaning/analysis
self.data_cleaning_predict(dk, filtered_df)
self.data_cleaning_predict(dk)
predictions = self.model.predict(dk.data_dictionary["prediction_features"])
pred_df = DataFrame(predictions, columns=dk.label_list)

2
freqtrade/freqai/data_drawer.py
View File

@@ -423,7 +423,7 @@ class FreqaiDataDrawer:
dk.data["data_path"] = str(dk.data_path)
dk.data["model_filename"] = str(dk.model_filename)
dk.data["training_features_list"] = list(dk.data_dictionary["train_features"].columns)
dk.data["training_features_list"] = dk.training_features_list
dk.data["label_list"] = dk.label_list
# store the metadata
with open(save_path / f"{dk.model_filename}_metadata.json", "w") as fp:

21
freqtrade/freqai/data_kitchen.py
View File

@@ -134,20 +134,15 @@ class FreqaiDataKitchen:
"""
feat_dict = self.freqai_config["feature_parameters"]
if 'shuffle' not in self.freqai_config['data_split_parameters']:
self.freqai_config["data_split_parameters"].update({'shuffle': False})
weights: npt.ArrayLike
if feat_dict.get("weight_factor", 0) > 0:
weights = self.set_weights_higher_recent(len(filtered_dataframe))
else:
weights = np.ones(len(filtered_dataframe))
if feat_dict.get("stratify_training_data", 0) > 0:
stratification = np.zeros(len(filtered_dataframe))
for i in range(1, len(stratification)):
if i % feat_dict.get("stratify_training_data", 0) == 0:
stratification[i] = 1
else:
stratification = None
if self.freqai_config.get('data_split_parameters', {}).get('test_size', 0.1) != 0:
(
train_features,
@@ -160,7 +155,6 @@ class FreqaiDataKitchen:
filtered_dataframe[: filtered_dataframe.shape[0]],
labels,
weights,
stratify=stratification,
**self.config["freqai"]["data_split_parameters"],
)
else:
@@ -210,7 +204,7 @@ class FreqaiDataKitchen:
filtered_df = unfiltered_df.filter(training_feature_list, axis=1)
filtered_df = filtered_df.replace([np.inf, -np.inf], np.nan)
drop_index = pd.isnull(filtered_df).any(1) # get the rows that have NaNs,
drop_index = pd.isnull(filtered_df).any(axis=1) # get the rows that have NaNs,
drop_index = drop_index.replace(True, 1).replace(False, 0) # pep8 requirement.
if (training_filter):
const_cols = list((filtered_df.nunique() == 1).loc[lambda x: x].index)
@@ -221,7 +215,7 @@ class FreqaiDataKitchen:
# about removing any row with NaNs
# if labels has multiple columns (user wants to train multiple modelEs), we detect here
labels = unfiltered_df.filter(label_list, axis=1)
drop_index_labels = pd.isnull(labels).any(1)
drop_index_labels = pd.isnull(labels).any(axis=1)
drop_index_labels = drop_index_labels.replace(True, 1).replace(False, 0)
dates = unfiltered_df['date']
filtered_df = filtered_df[
@@ -249,7 +243,7 @@ class FreqaiDataKitchen:
else:
# we are backtesting so we need to preserve row number to send back to strategy,
# so now we use do_predict to avoid any prediction based on a NaN
drop_index = pd.isnull(filtered_df).any(1)
drop_index = pd.isnull(filtered_df).any(axis=1)
self.data["filter_drop_index_prediction"] = drop_index
filtered_df.fillna(0, inplace=True)
# replacing all NaNs with zeros to avoid issues in 'prediction', but any prediction
@@ -808,7 +802,7 @@ class FreqaiDataKitchen:
:, :no_prev_pts
]
distances = distances.replace([np.inf, -np.inf], np.nan)
drop_index = pd.isnull(distances).any(1)
drop_index = pd.isnull(distances).any(axis=1)
distances = distances[drop_index == 0]
inliers = pd.DataFrame(index=distances.index)
@@ -881,6 +875,7 @@ class FreqaiDataKitchen:
"""
column_names = dataframe.columns
features = [c for c in column_names if "%" in c]
if not features:
raise OperationalException("Could not find any features!")

17
freqtrade/freqai/freqai_interface.py
View File

@@ -275,7 +275,8 @@ class IFreqaiModel(ABC):
if dk.check_if_backtest_prediction_exists():
self.dd.load_metadata(dk)
self.check_if_feature_list_matches_strategy(dataframe_train, dk)
dk.find_features(dataframe_train)
self.check_if_feature_list_matches_strategy(dk)
append_df = dk.get_backtesting_prediction()
dk.append_predictions(append_df)
else:
@@ -296,7 +297,6 @@ class IFreqaiModel(ABC):
else:
self.model = self.dd.load_data(pair, dk)
# self.check_if_feature_list_matches_strategy(dataframe_train, dk)
pred_df, do_preds = self.predict(dataframe_backtest, dk)
append_df = dk.get_predictions_to_append(pred_df, do_preds)
dk.append_predictions(append_df)
@@ -420,7 +420,7 @@ class IFreqaiModel(ABC):
return
def check_if_feature_list_matches_strategy(
self, dataframe: DataFrame, dk: FreqaiDataKitchen
self, dk: FreqaiDataKitchen
) -> None:
"""
Ensure user is passing the proper feature set if they are reusing an `identifier` pointing
@@ -429,11 +429,12 @@ class IFreqaiModel(ABC):
:param dk: FreqaiDataKitchen = non-persistent data container/analyzer for
current coin/bot loop
"""
dk.find_features(dataframe)
if "training_features_list_raw" in dk.data:
feature_list = dk.data["training_features_list_raw"]
else:
feature_list = dk.data['training_features_list']
if dk.training_features_list != feature_list:
raise OperationalException(
"Trying to access pretrained model with `identifier` "
@@ -481,13 +482,16 @@ class IFreqaiModel(ABC):
if self.freqai_info["feature_parameters"].get('noise_standard_deviation', 0):
dk.add_noise_to_training_features()
def data_cleaning_predict(self, dk: FreqaiDataKitchen, dataframe: DataFrame) -> None:
def data_cleaning_predict(self, dk: FreqaiDataKitchen) -> None:
"""
Base data cleaning method for predict.
Functions here are complementary to the functions of data_cleaning_train.
"""
ft_params = self.freqai_info["feature_parameters"]
# ensure user is feeding the correct indicators to the model
self.check_if_feature_list_matches_strategy(dk)
if ft_params.get('inlier_metric_window', 0):
dk.compute_inlier_metric(set_='predict')
@@ -505,9 +509,6 @@ class IFreqaiModel(ABC):
if ft_params.get("use_DBSCAN_to_remove_outliers", False):
dk.use_DBSCAN_to_remove_outliers(predict=True)
# ensure user is feeding the correct indicators to the model
self.check_if_feature_list_matches_strategy(dk.data_dictionary['prediction_features'], dk)
def model_exists(self, dk: FreqaiDataKitchen) -> bool:
"""
Given a pair and path, check if a model already exists

35
freqtrade/freqtradebot.py
View File

@@ -82,7 +82,10 @@ class FreqtradeBot(LoggingMixin):
# Keep this at the end of this initialization method.
self.rpc: RPCManager = RPCManager(self)
self.dataprovider = DataProvider(self.config, self.exchange, self.pairlists, self.rpc)
self.dataprovider = DataProvider(self.config, self.exchange, rpc=self.rpc)
self.pairlists = PairListManager(self.exchange, self.config, self.dataprovider)
self.dataprovider.add_pairlisthandler(self.pairlists)
# Attach Dataprovider to strategy instance
self.strategy.dp = self.dataprovider
@@ -597,7 +600,7 @@ class FreqtradeBot(LoggingMixin):
# We should decrease our position
amount = self.exchange.amount_to_contract_precision(
trade.pair,
abs(float(FtPrecise(stake_amount) / FtPrecise(current_exit_rate))))
abs(float(FtPrecise(stake_amount * trade.leverage) / FtPrecise(current_exit_rate))))
if amount > trade.amount:
# This is currently ineffective as remaining would become < min tradable
# Fixing this would require checking for 0.0 there -
@@ -1340,11 +1343,12 @@ class FreqtradeBot(LoggingMixin):
replacing: Optional[bool] = False
) -> bool:
"""
Buy cancel - cancel order
entry cancel - cancel order
:param replacing: Replacing order - prevent trade deletion.
:return: True if order was fully cancelled
:return: True if trade was fully cancelled
"""
was_trade_fully_canceled = False
side = trade.entry_side.capitalize()
# Cancelled orders may have the status of 'canceled' or 'closed'
if order['status'] not in constants.NON_OPEN_EXCHANGE_STATES:
@@ -1371,7 +1375,6 @@ class FreqtradeBot(LoggingMixin):
corder = order
reason = constants.CANCEL_REASON['CANCELLED_ON_EXCHANGE']
side = trade.entry_side.capitalize()
logger.info('%s order %s for %s.', side, reason, trade)
# Using filled to determine the filled amount
@@ -1385,24 +1388,13 @@ class FreqtradeBot(LoggingMixin):
was_trade_fully_canceled = True
reason += f", {constants.CANCEL_REASON['FULLY_CANCELLED']}"
else:
# FIXME TODO: This could possibly reworked to not duplicate the code 15 lines below.
self.update_trade_state(trade, trade.open_order_id, corder)
trade.open_order_id = None
logger.info(f'{side} Order timeout for {trade}.')
else:
# if trade is partially complete, edit the stake details for the trade
# and close the order
# cancel_order may not contain the full order dict, so we need to fallback
# to the order dict acquired before cancelling.
# we need to fall back to the values from order if corder does not contain these keys.
trade.amount = filled_amount
# * Check edge cases, we don't want to make leverage > 1.0 if we don't have to
# * (for leverage modes which aren't isolated futures)
trade.stake_amount = trade.amount * trade.open_rate / trade.leverage
# update_trade_state (and subsequently recalc_trade_from_orders) will handle updates
# to the trade object
self.update_trade_state(trade, trade.open_order_id, corder)
trade.open_order_id = None
logger.info(f'Partial {trade.entry_side} order timeout for {trade}.')
reason += f", {constants.CANCEL_REASON['PARTIALLY_FILLED']}"
@@ -1439,8 +1431,6 @@ class FreqtradeBot(LoggingMixin):
trade.close_rate_requested = None
trade.close_profit = None
trade.close_profit_abs = None
trade.close_date = None
trade.is_open = True
trade.open_order_id = None
trade.exit_reason = None
cancelled = True
@@ -1700,11 +1690,6 @@ class FreqtradeBot(LoggingMixin):
'stake_amount': trade.stake_amount,
}
if 'fiat_display_currency' in self.config:
msg.update({
'fiat_currency': self.config['fiat_display_currency'],
})
# Send the message
self.rpc.send_msg(msg)

4
freqtrade/optimize/backtesting.py
View File

@@ -110,7 +110,7 @@ class Backtesting:
self.timeframe = str(self.config.get('timeframe'))
self.timeframe_min = timeframe_to_minutes(self.timeframe)
self.init_backtest_detail()
self.pairlists = PairListManager(self.exchange, self.config)
self.pairlists = PairListManager(self.exchange, self.config, self.dataprovider)
if 'VolumePairList' in self.pairlists.name_list:
raise OperationalException("VolumePairList not allowed for backtesting. "
"Please use StaticPairList instead.")
@@ -540,7 +540,7 @@ class Backtesting:
if stake_amount is not None and stake_amount < 0.0:
amount = amount_to_contract_precision(
abs(stake_amount) / current_rate, trade.amount_precision,
abs(stake_amount * trade.leverage) / current_rate, trade.amount_precision,
self.precision_mode, trade.contract_size)
if amount == 0.0:
return trade

90
freqtrade/plugins/pairlist/ProducerPairList.py Normal file
View File

@@ -0,0 +1,90 @@
"""
External Pair List provider
Provides pair list from Leader data
"""
import logging
from typing import Any, Dict, List, Optional
from freqtrade.exceptions import OperationalException
from freqtrade.plugins.pairlist.IPairList import IPairList
logger = logging.getLogger(__name__)
class ProducerPairList(IPairList):
"""
PairList plugin for use with external_message_consumer.
Will use pairs given from leader data.
Usage:
"pairlists": [
{
"method": "ProducerPairList",
"number_assets": 5,
"producer_name": "default",
}
],
"""
def __init__(self, exchange, pairlistmanager,
config: Dict[str, Any], pairlistconfig: Dict[str, Any],
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
self._num_assets: int = self._pairlistconfig.get('number_assets', 0)
self._producer_name = self._pairlistconfig.get('producer_name', 'default')
if not config.get('external_message_consumer', {}).get('enabled'):
raise OperationalException(
"ProducerPairList requires external_message_consumer to be enabled.")
@property
def needstickers(self) -> bool:
"""
Boolean property defining if tickers are necessary.
If no Pairlist requires tickers, an empty Dict is passed
as tickers argument to filter_pairlist
"""
return False
def short_desc(self) -> str:
"""
Short whitelist method description - used for startup-messages
-> Please overwrite in subclasses
"""
return f"{self.name} - {self._producer_name}"
def _filter_pairlist(self, pairlist: Optional[List[str]]):
upstream_pairlist = self._pairlistmanager._dataprovider.get_producer_pairs(
self._producer_name)
if pairlist is None:
pairlist = self._pairlistmanager._dataprovider.get_producer_pairs(self._producer_name)
pairs = list(dict.fromkeys(pairlist + upstream_pairlist))
if self._num_assets:
pairs = pairs[:self._num_assets]
return pairs
def gen_pairlist(self, tickers: Dict) -> List[str]:
"""
Generate the pairlist
:param tickers: Tickers (from exchange.get_tickers()). May be cached.
:return: List of pairs
"""
pairs = self._filter_pairlist(None)
self.log_once(f"Received pairs: {pairs}", logger.debug)
pairs = self._whitelist_for_active_markets(self.verify_whitelist(pairs, logger.info))
return pairs
def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
"""
Filters and sorts pairlist and returns the whitelist again.
Called on each bot iteration - please use internal caching if necessary
:param pairlist: pairlist to filter or sort
:param tickers: Tickers (from exchange.get_tickers()). May be cached.
:return: new whitelist
"""
return self._filter_pairlist(pairlist)

2
freqtrade/plugins/pairlist/VolumePairList.py
View File

@@ -232,6 +232,4 @@ class VolumePairList(IPairList):
# Limit pairlist to the requested number of pairs
pairs = pairs[:self._number_pairs]
self.log_once(f"Searching {self._number_pairs} pairs: {pairs}", logger.info)
return pairs

8
freqtrade/plugins/pairlistmanager.py
View File

@@ -3,11 +3,12 @@ PairList manager class
"""
import logging
from functools import partial
from typing import Dict, List
from typing import Dict, List, Optional
from cachetools import TTLCache, cached
from freqtrade.constants import Config, ListPairsWithTimeframes
from freqtrade.data.dataprovider import DataProvider
from freqtrade.enums import CandleType
from freqtrade.exceptions import OperationalException
from freqtrade.mixins import LoggingMixin
@@ -21,13 +22,14 @@ logger = logging.getLogger(__name__)
class PairListManager(LoggingMixin):
def __init__(self, exchange, config: Config) -> None:
def __init__(self, exchange, config: Config, dataprovider: DataProvider = None) -> None:
self._exchange = exchange
self._config = config
self._whitelist = self._config['exchange'].get('pair_whitelist')
self._blacklist = self._config['exchange'].get('pair_blacklist', [])
self._pairlist_handlers: List[IPairList] = []
self._tickers_needed = False
self._dataprovider: Optional[DataProvider] = dataprovider
for pairlist_handler_config in self._config.get('pairlists', []):
pairlist_handler = PairListResolver.load_pairlist(
pairlist_handler_config['method'],
@@ -96,6 +98,8 @@ class PairListManager(LoggingMixin):
# to ensure blacklist is respected.
pairlist = self.verify_blacklist(pairlist, logger.warning)
self.log_once(f"Whitelist with {len(pairlist)} pairs: {pairlist}", logger.info)
self._whitelist = pairlist
def verify_blacklist(self, pairlist: List[str], logmethod) -> List[str]:

6
freqtrade/rpc/api_server/webserver.py
View File

@@ -198,8 +198,10 @@ class ApiServer(RPCHandler):
logger.debug(f"Found message of type: {message.get('type')}")
# Broadcast it
await self._ws_channel_manager.broadcast(message)
# Sleep, make this configurable?
await asyncio.sleep(0.1)
# Limit messages per sec.
# Could cause problems with queue size if too low, and
# problems with network traffik if too high.
await asyncio.sleep(0.001)
except asyncio.CancelledError:
pass

2
freqtrade/rpc/discord.py
View File

@@ -30,9 +30,9 @@ class Discord(Webhook):
pass
def send_msg(self, msg) -> None:
logger.info(f"Sending discord message: {msg}")
if msg['type'].value in self.config['discord']:
logger.info(f"Sending discord message: {msg}")
msg['strategy'] = self.strategy
msg['timeframe'] = self.timeframe

8
freqtrade/rpc/webhook.py
View File

@@ -61,6 +61,14 @@ class Webhook(RPCHandler):
RPCMessageType.STARTUP,
RPCMessageType.WARNING):
valuedict = whconfig.get('webhookstatus')
elif msg['type'] in (
RPCMessageType.PROTECTION_TRIGGER,
RPCMessageType.PROTECTION_TRIGGER_GLOBAL,
RPCMessageType.WHITELIST,
RPCMessageType.ANALYZED_DF,
RPCMessageType.STRATEGY_MSG):
# Don't fail for non-implemented types
return
else:
raise NotImplementedError('Unknown message type: {}'.format(msg['type']))
if not valuedict: