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Merge remote-tracking branch 'origin/develop' into add-metric-tracker

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robcaulk
2022-10-14 19:00:49 +02:00
parent 88b8f18639 4a8cb3359b
commit b236e362ba
72 changed files with 570 additions and 341 deletions
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11
freqtrade/commands/list_commands.py
View File

@@ -1,7 +1,6 @@
import csv
import logging
import sys
from pathlib import Path
from typing import Any, Dict, List
import rapidjson
@@ -10,7 +9,6 @@ from colorama import init as colorama_init
from tabulate import tabulate
from freqtrade.configuration import setup_utils_configuration
from freqtrade.constants import USERPATH_STRATEGIES
from freqtrade.enums import RunMode
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import market_is_active, validate_exchanges
@@ -41,7 +39,7 @@ def start_list_exchanges(args: Dict[str, Any]) -> None:
print(tabulate(exchanges, headers=['Exchange name', 'Valid', 'reason']))
def _print_objs_tabular(objs: List, print_colorized: bool, base_dir: Path) -> None:
def _print_objs_tabular(objs: List, print_colorized: bool) -> None:
if print_colorized:
colorama_init(autoreset=True)
red = Fore.RED
@@ -55,7 +53,7 @@ def _print_objs_tabular(objs: List, print_colorized: bool, base_dir: Path) -> No
names = [s['name'] for s in objs]
objs_to_print = [{
'name': s['name'] if s['name'] else "--",
'location': s['location'].relative_to(base_dir),
'location': s['location_rel'],
'status': (red + "LOAD FAILED" + reset if s['class'] is None
else "OK" if names.count(s['name']) == 1
else yellow + "DUPLICATE NAME" + reset)
@@ -76,9 +74,8 @@ def start_list_strategies(args: Dict[str, Any]) -> None:
"""
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
directory = Path(config.get('strategy_path', config['user_data_dir'] / USERPATH_STRATEGIES))
strategy_objs = StrategyResolver.search_all_objects(
directory, not args['print_one_column'], config.get('recursive_strategy_search', False))
config, not args['print_one_column'], config.get('recursive_strategy_search', False))
# Sort alphabetically
strategy_objs = sorted(strategy_objs, key=lambda x: x['name'])
for obj in strategy_objs:
@@ -90,7 +87,7 @@ def start_list_strategies(args: Dict[str, Any]) -> None:
if args['print_one_column']:
print('\n'.join([s['name'] for s in strategy_objs]))
else:
_print_objs_tabular(strategy_objs, config.get('print_colorized', False), directory)
_print_objs_tabular(strategy_objs, config.get('print_colorized', False))
def start_list_timeframes(args: Dict[str, Any]) -> None:

7
freqtrade/configuration/directory_operations.py
View File

@@ -3,7 +3,8 @@ import shutil
from pathlib import Path
from typing import Optional
from freqtrade.constants import USER_DATA_FILES, Config
from freqtrade.constants import (USER_DATA_FILES, USERPATH_FREQAIMODELS, USERPATH_HYPEROPTS,
USERPATH_NOTEBOOKS, USERPATH_STRATEGIES, Config)
from freqtrade.exceptions import OperationalException
@@ -49,8 +50,8 @@ def create_userdata_dir(directory: str, create_dir: bool = False) -> Path:
:param create_dir: Create directory if it does not exist.
:return: Path object containing the directory
"""
sub_dirs = ["backtest_results", "data", "hyperopts", "hyperopt_results", "logs",
"notebooks", "plot", "strategies", ]
sub_dirs = ["backtest_results", "data", USERPATH_HYPEROPTS, "hyperopt_results", "logs",
USERPATH_NOTEBOOKS, "plot", USERPATH_STRATEGIES, USERPATH_FREQAIMODELS]
folder = Path(directory)
chown_user_directory(folder)
if not folder.is_dir():

6
freqtrade/constants.py
View File

@@ -5,7 +5,7 @@ bot constants
"""
from typing import Any, Dict, List, Literal, Tuple
from freqtrade.enums import CandleType
from freqtrade.enums import CandleType, RPCMessageType
DEFAULT_CONFIG = 'config.json'
@@ -282,6 +282,7 @@ CONF_SCHEMA = {
'enabled': {'type': 'boolean'},
'token': {'type': 'string'},
'chat_id': {'type': 'string'},
'allow_custom_messages': {'type': 'boolean', 'default': True},
'balance_dust_level': {'type': 'number', 'minimum': 0.0},
'notification_settings': {
'type': 'object',
@@ -344,6 +345,8 @@ CONF_SCHEMA = {
'format': {'type': 'string', 'enum': WEBHOOK_FORMAT_OPTIONS, 'default': 'form'},
'retries': {'type': 'integer', 'minimum': 0},
'retry_delay': {'type': 'number', 'minimum': 0},
**dict([(x, {'type': 'object'}) for x in RPCMessageType]),
# Below -> Deprecated
'webhookentry': {'type': 'object'},
'webhookentrycancel': {'type': 'object'},
'webhookentryfill': {'type': 'object'},
@@ -655,5 +658,6 @@ LongShort = Literal['long', 'short']
EntryExit = Literal['entry', 'exit']
BuySell = Literal['buy', 'sell']
MakerTaker = Literal['maker', 'taker']
BidAsk = Literal['bid', 'ask']
Config = Dict[str, Any]

3
freqtrade/exchange/binance.py
View File

@@ -11,6 +11,7 @@ from freqtrade.enums import CandleType, MarginMode, TradingMode
from freqtrade.exceptions import DDosProtection, OperationalException, TemporaryError
from freqtrade.exchange import Exchange
from freqtrade.exchange.common import retrier
from freqtrade.exchange.types import Tickers
from freqtrade.misc import deep_merge_dicts, json_load
@@ -59,7 +60,7 @@ class Binance(Exchange):
)
))
def get_tickers(self, symbols: Optional[List[str]] = None, cached: bool = False) -> Dict:
def get_tickers(self, symbols: Optional[List[str]] = None, cached: bool = False) -> Tickers:
tickers = super().get_tickers(symbols=symbols, cached=cached)
if self.trading_mode == TradingMode.FUTURES:
# Binance's future result has no bid/ask values.

20
freqtrade/exchange/exchange.py
View File

@@ -20,8 +20,8 @@ from ccxt import ROUND_DOWN, ROUND_UP, TICK_SIZE, TRUNCATE, decimal_to_precision
from dateutil import parser
from pandas import DataFrame, concat
from freqtrade.constants import (DEFAULT_AMOUNT_RESERVE_PERCENT, NON_OPEN_EXCHANGE_STATES, BuySell,
Config, EntryExit, ListPairsWithTimeframes, MakerTaker,
from freqtrade.constants import (DEFAULT_AMOUNT_RESERVE_PERCENT, NON_OPEN_EXCHANGE_STATES, BidAsk,
BuySell, Config, EntryExit, ListPairsWithTimeframes, MakerTaker,
PairWithTimeframe)
from freqtrade.data.converter import clean_ohlcv_dataframe, ohlcv_to_dataframe, trades_dict_to_list
from freqtrade.enums import OPTIMIZE_MODES, CandleType, MarginMode, TradingMode
@@ -31,6 +31,7 @@ from freqtrade.exceptions import (DDosProtection, ExchangeError, InsufficientFun
from freqtrade.exchange.common import (API_FETCH_ORDER_RETRY_COUNT, BAD_EXCHANGES,
EXCHANGE_HAS_OPTIONAL, EXCHANGE_HAS_REQUIRED,
remove_credentials, retrier, retrier_async)
from freqtrade.exchange.types import Ticker, Tickers
from freqtrade.misc import (chunks, deep_merge_dicts, file_dump_json, file_load_json,
safe_value_fallback2)
from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
@@ -1420,14 +1421,17 @@ class Exchange:
raise OperationalException(e) from e
@retrier
def get_tickers(self, symbols: Optional[List[str]] = None, cached: bool = False) -> Dict:
def get_tickers(self, symbols: Optional[List[str]] = None, cached: bool = False) -> Tickers:
"""
:param cached: Allow cached result
:return: fetch_tickers result
"""
tickers: Tickers
if not self.exchange_has('fetchTickers'):
return {}
if cached:
with self._cache_lock:
tickers = self._fetch_tickers_cache.get('fetch_tickers')
tickers = self._fetch_tickers_cache.get('fetch_tickers') # type: ignore
if tickers:
return tickers
try:
@@ -1450,12 +1454,12 @@ class Exchange:
# Pricing info
@retrier
def fetch_ticker(self, pair: str) -> dict:
def fetch_ticker(self, pair: str) -> Ticker:
try:
if (pair not in self.markets or
self.markets[pair].get('active', False) is False):
raise ExchangeError(f"Pair {pair} not available")
data = self._api.fetch_ticker(pair)
data: Ticker = self._api.fetch_ticker(pair)
return data
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
@@ -1506,7 +1510,7 @@ class Exchange:
except ccxt.BaseError as e:
raise OperationalException(e) from e
def _get_price_side(self, side: str, is_short: bool, conf_strategy: Dict) -> str:
def _get_price_side(self, side: str, is_short: bool, conf_strategy: Dict) -> BidAsk:
price_side = conf_strategy['price_side']
if price_side in ('same', 'other'):
@@ -1525,7 +1529,7 @@ class Exchange:
def get_rate(self, pair: str, refresh: bool,
side: EntryExit, is_short: bool,
order_book: Optional[dict] = None, ticker: Optional[dict] = None) -> float:
order_book: Optional[dict] = None, ticker: Optional[Ticker] = None) -> float:
"""
Calculates bid/ask target
bid rate - between current ask price and last price

3
freqtrade/exchange/kraken.py
View File

@@ -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.types import Tickers
logger = logging.getLogger(__name__)
@@ -45,7 +46,7 @@ class Kraken(Exchange):
return (parent_check and
market.get('darkpool', False) is False)
def get_tickers(self, symbols: Optional[List[str]] = None, cached: bool = False) -> Dict:
def get_tickers(self, symbols: Optional[List[str]] = None, cached: bool = False) -> Tickers:
# Only fetch tickers for current stake currency
# Otherwise the request for kraken becomes too large.
symbols = list(self.get_markets(quote_currencies=[self._config['stake_currency']]))

16
freqtrade/exchange/types.py Normal file
View File

@@ -0,0 +1,16 @@
from typing import Dict, Optional, TypedDict
class Ticker(TypedDict):
symbol: str
ask: Optional[float]
askVolume: Optional[float]
bid: Optional[float]
bidVolume: Optional[float]
last: Optional[float]
quoteVolume: Optional[float]
baseVolume: Optional[float]
# Several more - only listing required.
Tickers = Dict[str, Ticker]

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

@@ -78,7 +78,7 @@ class BaseClassifierModel(IFreqaiModel):
) -> Tuple[DataFrame, npt.NDArray[np.int_]]:
"""
Filter the prediction features data and predict with it.
:param: unfiltered_df: Full dataframe for the current backtest period.
:param unfiltered_df: Full dataframe for the current backtest period.
:return:
:pred_df: dataframe containing the predictions
:do_predict: np.array of 1s and 0s to indicate places where freqai needed to remove

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

@@ -77,7 +77,7 @@ class BaseRegressionModel(IFreqaiModel):
) -> Tuple[DataFrame, npt.NDArray[np.int_]]:
"""
Filter the prediction features data and predict with it.
:param: unfiltered_df: Full dataframe for the current backtest period.
:param unfiltered_df: Full dataframe for the current backtest period.
:return:
:pred_df: dataframe containing the predictions
:do_predict: np.array of 1s and 0s to indicate places where freqai needed to remove

20
freqtrade/freqai/data_drawer.py
View File

@@ -461,9 +461,8 @@ class FreqaiDataDrawer:
def save_data(self, model: Any, coin: str, dk: FreqaiDataKitchen) -> None:
"""
Saves all data associated with a model for a single sub-train time range
:params:
:model: User trained model which can be reused for inferencing to generate
predictions
:param model: User trained model which can be reused for inferencing to generate
predictions
"""
if not dk.data_path.is_dir():
@@ -581,8 +580,7 @@ class FreqaiDataDrawer:
Append new candles to our stores historic data (in memory) so that
we do not need to load candle history from disk and we dont need to
pinging exchange multiple times for the same candle.
:params:
dataframe: DataFrame = strategy provided dataframe
:param dataframe: DataFrame = strategy provided dataframe
"""
feat_params = self.freqai_info["feature_parameters"]
with self.history_lock:
@@ -628,9 +626,8 @@ class FreqaiDataDrawer:
"""
Load pair histories for all whitelist and corr_pairlist pairs.
Only called once upon startup of bot.
:params:
timerange: TimeRange = full timerange required to populate all indicators
for training according to user defined train_period_days
:param timerange: TimeRange = full timerange required to populate all indicators
for training according to user defined train_period_days
"""
history_data = self.historic_data
@@ -653,10 +650,9 @@ class FreqaiDataDrawer:
"""
Searches through our historic_data in memory and returns the dataframes relevant
to the present pair.
:params:
timerange: TimeRange = full timerange required to populate all indicators
for training according to user defined train_period_days
metadata: dict = strategy furnished pair metadata
:param timerange: TimeRange = full timerange required to populate all indicators
for training according to user defined train_period_days
:param metadata: dict = strategy furnished pair metadata
"""
with self.history_lock:
corr_dataframes: Dict[Any, Any] = {}

79
freqtrade/freqai/data_kitchen.py
View File

@@ -107,9 +107,8 @@ class FreqaiDataKitchen:
) -> None:
"""
Set the paths to the data for the present coin/botloop
:params:
metadata: dict = strategy furnished pair metadata
trained_timestamp: int = timestamp of most recent training
:param metadata: dict = strategy furnished pair metadata
:param trained_timestamp: int = timestamp of most recent training
"""
self.full_path = Path(
self.config["user_data_dir"] / "models" / str(self.freqai_config.get("identifier"))
@@ -129,8 +128,8 @@ class FreqaiDataKitchen:
Given the dataframe for the full history for training, split the data into
training and test data according to user specified parameters in configuration
file.
:filtered_dataframe: cleaned dataframe ready to be split.
:labels: cleaned labels ready to be split.
:param filtered_dataframe: cleaned dataframe ready to be split.
:param labels: cleaned labels ready to be split.
"""
feat_dict = self.freqai_config["feature_parameters"]
@@ -189,13 +188,14 @@ class FreqaiDataKitchen:
remove all NaNs. Any row with a NaN is removed from training dataset or replaced with
0s in the prediction dataset. However, prediction dataset do_predict will reflect any
row that had a NaN and will shield user from that prediction.
:params:
:unfiltered_df: the full dataframe for the present training period
:training_feature_list: list, the training feature list constructed by
self.build_feature_list() according to user specified parameters in the configuration file.
:labels: the labels for the dataset
:training_filter: boolean which lets the function know if it is training data or
prediction data to be filtered.
:param unfiltered_df: the full dataframe for the present training period
:param training_feature_list: list, the training feature list constructed by
self.build_feature_list() according to user specified
parameters in the configuration file.
:param labels: the labels for the dataset
:param training_filter: boolean which lets the function know if it is training data or
prediction data to be filtered.
:returns:
:filtered_df: dataframe cleaned of NaNs and only containing the user
requested feature set.
@@ -241,6 +241,7 @@ class FreqaiDataKitchen:
self.data["filter_drop_index_training"] = drop_index
else:
filtered_df = self.check_pred_labels(filtered_df)
# 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(axis=1)
@@ -285,8 +286,8 @@ class FreqaiDataKitchen:
def normalize_data(self, data_dictionary: Dict) -> Dict[Any, Any]:
"""
Normalize all data in the data_dictionary according to the training dataset
:params:
:data_dictionary: dictionary containing the cleaned and split training/test data/labels
:param data_dictionary: dictionary containing the cleaned and
split training/test data/labels
:returns:
:data_dictionary: updated dictionary with standardized values.
"""
@@ -460,6 +461,24 @@ class FreqaiDataKitchen:
return df
def check_pred_labels(self, df_predictions: DataFrame) -> DataFrame:
"""
Check that prediction feature labels match training feature labels.
:params:
:df_predictions: incoming predictions
"""
train_labels = self.data_dictionary["train_features"].columns
pred_labels = df_predictions.columns
num_diffs = len(pred_labels.difference(train_labels))
if num_diffs != 0:
df_predictions = df_predictions[train_labels]
logger.warning(
f"Removed {num_diffs} features from prediction features, "
f"these were likely considered constant values during most recent training."
)
return df_predictions
def principal_component_analysis(self) -> None:
"""
Performs Principal Component Analysis on the data for dimensionality reduction
@@ -516,8 +535,7 @@ class FreqaiDataKitchen:
def pca_transform(self, filtered_dataframe: DataFrame) -> None:
"""
Use an existing pca transform to transform data into components
:params:
filtered_dataframe: DataFrame = the cleaned dataframe
:param filtered_dataframe: DataFrame = the cleaned dataframe
"""
pca_components = self.pca.transform(filtered_dataframe)
self.data_dictionary["prediction_features"] = pd.DataFrame(
@@ -561,8 +579,7 @@ class FreqaiDataKitchen:
"""
Build/inference a Support Vector Machine to detect outliers
in training data and prediction
:params:
predict: bool = If true, inference an existing SVM model, else construct one
:param predict: bool = If true, inference an existing SVM model, else construct one
"""
if self.keras:
@@ -647,11 +664,11 @@ class FreqaiDataKitchen:
Use DBSCAN to cluster training data and remove "noisy" data (read outliers).
User controls this via the config param `DBSCAN_outlier_pct` which indicates the
pct of training data that they want to be considered outliers.
:params:
predict: bool = If False (training), iterate to find the best hyper parameters to match
user requested outlier percent target. If True (prediction), use the parameters
determined from the previous training to estimate if the current prediction point
is an outlier.
:param predict: bool = If False (training), iterate to find the best hyper parameters
to match user requested outlier percent target.
If True (prediction), use the parameters determined from
the previous training to estimate if the current prediction point
is an outlier.
"""
if predict:
@@ -1118,15 +1135,13 @@ class FreqaiDataKitchen:
prediction_dataframe: DataFrame = pd.DataFrame(),
) -> DataFrame:
"""
Use the user defined strategy for populating indicators during
retrain
:params:
strategy: IStrategy = user defined strategy object
corr_dataframes: dict = dict containing the informative pair dataframes
(for user defined timeframes)
base_dataframes: dict = dict containing the current pair dataframes
(for user defined timeframes)
metadata: dict = strategy furnished pair metadata
Use the user defined strategy for populating indicators during retrain
:param strategy: IStrategy = user defined strategy object
:param corr_dataframes: dict = dict containing the informative pair dataframes
(for user defined timeframes)
:param base_dataframes: dict = dict containing the current pair dataframes
(for user defined timeframes)
:param metadata: dict = strategy furnished pair metadata
:returns:
dataframe: DataFrame = dataframe containing populated indicators
"""

17
freqtrade/freqai/freqai_interface.py
View File

@@ -196,16 +196,15 @@ class IFreqaiModel(ABC):
(_, trained_timestamp, _) = self.dd.get_pair_dict_info(pair)
dk = FreqaiDataKitchen(self.config, self.live, pair)
dk.set_paths(pair, trained_timestamp)
(
retrain,
new_trained_timerange,
data_load_timerange,
) = dk.check_if_new_training_required(trained_timestamp)
dk.set_paths(pair, new_trained_timerange.stopts)
if retrain:
self.train_timer('start')
dk.set_paths(pair, new_trained_timerange.stopts)
try:
self.extract_data_and_train_model(
new_trained_timerange, pair, strategy, dk, data_load_timerange
@@ -270,9 +269,7 @@ class IFreqaiModel(ABC):
)
trained_timestamp_int = int(trained_timestamp.stopts)
dk.data_path = Path(
dk.full_path / f"sub-train-{pair.split('/')[0]}_{trained_timestamp_int}"
)
dk.set_paths(pair, trained_timestamp_int)
dk.set_new_model_names(pair, trained_timestamp)
@@ -605,11 +602,11 @@ class IFreqaiModel(ABC):
If the user reuses an identifier on a subsequent instance,
this function will not be called. In that case, "real" predictions
will be appended to the loaded set of historic predictions.
:param: df: DataFrame = the dataframe containing the training feature data
:param: model: Any = A model which was `fit` using a common library such as
catboost or lightgbm
:param: dk: FreqaiDataKitchen = object containing methods for data analysis
:param: pair: str = current pair
:param df: DataFrame = the dataframe containing the training feature data
:param model: Any = A model which was `fit` using a common library such as
catboost or lightgbm
:param dk: FreqaiDataKitchen = object containing methods for data analysis
:param pair: str = current pair
"""
self.dd.historic_predictions[pair] = pred_df

9
freqtrade/freqai/prediction_models/CatboostClassifier.py
View File

@@ -1,4 +1,5 @@
import logging
from pathlib import Path
from typing import Any, Dict
from catboost import CatBoostClassifier, Pool
@@ -20,9 +21,8 @@ class CatboostClassifier(BaseClassifierModel):
def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen, **kwargs) -> Any:
"""
User sets up the training and test data to fit their desired model here
:params:
:data_dictionary: the dictionary constructed by DataHandler to hold
all the training and test data/labels.
:param data_dictionary: the dictionary constructed by DataHandler to hold
all the training and test data/labels.
"""
train_data = Pool(
@@ -32,8 +32,9 @@ class CatboostClassifier(BaseClassifierModel):
)
cbr = CatBoostClassifier(
allow_writing_files=False,
allow_writing_files=True,
loss_function='MultiClass',
train_dir=Path(dk.data_path),
**self.model_training_parameters,
)

4
freqtrade/freqai/prediction_models/CatboostRegressor.py
View File

@@ -1,4 +1,5 @@
import logging
from pathlib import Path
from typing import Any, Dict
from catboost import CatBoostRegressor, Pool
@@ -41,7 +42,8 @@ class CatboostRegressor(BaseRegressionModel):
init_model = self.get_init_model(dk.pair)
model = CatBoostRegressor(
allow_writing_files=False,
allow_writing_files=True,
train_dir=Path(dk.data_path),
**self.model_training_parameters,
)

4
freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py
View File

@@ -1,4 +1,5 @@
import logging
from pathlib import Path
from typing import Any, Dict
from catboost import CatBoostRegressor, Pool
@@ -26,7 +27,8 @@ class CatboostRegressorMultiTarget(BaseRegressionModel):
"""
cbr = CatBoostRegressor(
allow_writing_files=False,
allow_writing_files=True,
train_dir=Path(dk.data_path),
**self.model_training_parameters,
)

5
freqtrade/freqai/prediction_models/LightGBMClassifier.py
View File

@@ -20,9 +20,8 @@ class LightGBMClassifier(BaseClassifierModel):
def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen, **kwargs) -> Any:
"""
User sets up the training and test data to fit their desired model here
:params:
:data_dictionary: the dictionary constructed by DataHandler to hold
all the training and test data/labels.
:param data_dictionary: the dictionary constructed by DataHandler to hold
all the training and test data/labels.
"""
if self.freqai_info.get('data_split_parameters', {}).get('test_size', 0.1) == 0:

7
freqtrade/freqai/prediction_models/XGBoostClassifier.py
View File

@@ -26,9 +26,8 @@ class XGBoostClassifier(BaseClassifierModel):
def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen, **kwargs) -> Any:
"""
User sets up the training and test data to fit their desired model here
:params:
:data_dictionary: the dictionary constructed by DataHandler to hold
all the training and test data/labels.
:param data_dictionary: the dictionary constructed by DataHandler to hold
all the training and test data/labels.
"""
X = data_dictionary["train_features"].to_numpy()
@@ -65,7 +64,7 @@ class XGBoostClassifier(BaseClassifierModel):
) -> Tuple[DataFrame, npt.NDArray[np.int_]]:
"""
Filter the prediction features data and predict with it.
:param: unfiltered_df: Full dataframe for the current backtest period.
:param unfiltered_df: Full dataframe for the current backtest period.
:return:
:pred_df: dataframe containing the predictions
:do_predict: np.array of 1s and 0s to indicate places where freqai needed to remove

7
freqtrade/misc.py
View File

@@ -6,7 +6,7 @@ import logging
import re
from datetime import datetime
from pathlib import Path
from typing import Any, Iterator, List
from typing import Any, Dict, Iterator, List, Mapping, Union
from typing.io import IO
from urllib.parse import urlparse
@@ -186,7 +186,10 @@ def safe_value_fallback(obj: dict, key1: str, key2: str, default_value=None):
return default_value
def safe_value_fallback2(dict1: dict, dict2: dict, key1: str, key2: str, default_value=None):
dictMap = Union[Dict[str, Any], Mapping[str, Any]]
def safe_value_fallback2(dict1: dictMap, dict2: dictMap, key1: str, key2: str, default_value=None):
"""
Search a value in dict1, return this if it's not None.
Fall back to dict2 - return key2 from dict2 if it's not None.

29
freqtrade/optimize/backtesting.py
View File

@@ -617,13 +617,16 @@ class Backtesting:
exit_reason = row[EXIT_TAG_IDX]
# Custom exit pricing only for exit-signals
if order_type == 'limit':
close_rate = strategy_safe_wrapper(self.strategy.custom_exit_price,
default_retval=close_rate)(
rate = strategy_safe_wrapper(self.strategy.custom_exit_price,
default_retval=close_rate)(
pair=trade.pair,
trade=trade, # type: ignore[arg-type]
current_time=exit_candle_time,
proposed_rate=close_rate, current_profit=current_profit,
exit_tag=exit_reason)
if rate != close_rate:
close_rate = price_to_precision(rate, trade.price_precision,
self.precision_mode)
# We can't place orders lower than current low.
# freqtrade does not support this in live, and the order would fill immediately
if trade.is_short:
@@ -660,7 +663,6 @@ class Backtesting:
# amount = amount or trade.amount
amount = amount_to_contract_precision(amount or trade.amount, trade.amount_precision,
self.precision_mode, trade.contract_size)
rate = price_to_precision(close_rate, trade.price_precision, self.precision_mode)
order = Order(
id=self.order_id_counter,
ft_trade_id=trade.id,
@@ -674,12 +676,12 @@ class Backtesting:
side=trade.exit_side,
order_type=order_type,
status="open",
price=rate,
average=rate,
price=close_rate,
average=close_rate,
amount=amount,
filled=0,
remaining=amount,
cost=amount * rate,
cost=amount * close_rate,
)
trade.orders.append(order)
return trade
@@ -726,18 +728,21 @@ class Backtesting:
def get_valid_price_and_stake(
self, pair: str, row: Tuple, propose_rate: float, stake_amount: float,
direction: LongShort, current_time: datetime, entry_tag: Optional[str],
trade: Optional[LocalTrade], order_type: str
trade: Optional[LocalTrade], order_type: str, price_precision: Optional[float]
) -> Tuple[float, float, float, float]:
if order_type == 'limit':
propose_rate = strategy_safe_wrapper(self.strategy.custom_entry_price,
default_retval=propose_rate)(
new_rate = strategy_safe_wrapper(self.strategy.custom_entry_price,
default_retval=propose_rate)(
pair=pair, current_time=current_time,
proposed_rate=propose_rate, entry_tag=entry_tag,
side=direction,
) # default value is the open rate
# We can't place orders higher than current high (otherwise it'd be a stop limit entry)
# which freqtrade does not support in live.
if new_rate != propose_rate:
propose_rate = price_to_precision(new_rate, price_precision,
self.precision_mode)
if direction == "short":
propose_rate = max(propose_rate, row[LOW_IDX])
else:
@@ -799,9 +804,11 @@ class Backtesting:
pos_adjust = trade is not None and requested_rate is None
stake_amount_ = stake_amount or (trade.stake_amount if trade else 0.0)
precision_price = self.exchange.get_precision_price(pair)
propose_rate, stake_amount, leverage, min_stake_amount = self.get_valid_price_and_stake(
pair, row, row[OPEN_IDX], stake_amount_, direction, current_time, entry_tag, trade,
order_type
order_type, precision_price,
)
# replace proposed rate if another rate was requested
@@ -817,8 +824,6 @@ class Backtesting:
if stake_amount and (not min_stake_amount or stake_amount > min_stake_amount):
self.order_id_counter += 1
base_currency = self.exchange.get_pair_base_currency(pair)
precision_price = self.exchange.get_precision_price(pair)
propose_rate = price_to_precision(propose_rate, precision_price, self.precision_mode)
amount_p = (stake_amount / propose_rate) * leverage
contract_size = self.exchange.get_contract_size(pair)

5
freqtrade/optimize/hyperopt_tools.py
View File

@@ -12,7 +12,7 @@ import tabulate
from colorama import Fore, Style
from pandas import isna, json_normalize
from freqtrade.constants import FTHYPT_FILEVERSION, USERPATH_STRATEGIES, Config
from freqtrade.constants import FTHYPT_FILEVERSION, Config
from freqtrade.enums import HyperoptState
from freqtrade.exceptions import OperationalException
from freqtrade.misc import deep_merge_dicts, round_coin_value, round_dict, safe_value_fallback2
@@ -50,9 +50,8 @@ class HyperoptTools():
Get Strategy-location (filename) from strategy_name
"""
from freqtrade.resolvers.strategy_resolver import StrategyResolver
directory = Path(config.get('strategy_path', config['user_data_dir'] / USERPATH_STRATEGIES))
strategy_objs = StrategyResolver.search_all_objects(
directory, False, config.get('recursive_strategy_search', False))
config, False, config.get('recursive_strategy_search', False))
strategies = [s for s in strategy_objs if s['name'] == strategy_name]
if strategies:
strategy = strategies[0]

5
freqtrade/plugins/pairlist/AgeFilter.py
View File

@@ -10,6 +10,7 @@ from pandas import DataFrame
from freqtrade.constants import Config, ListPairsWithTimeframes
from freqtrade.exceptions import OperationalException
from freqtrade.exchange.types import Tickers
from freqtrade.misc import plural
from freqtrade.plugins.pairlist.IPairList import IPairList
from freqtrade.util import PeriodicCache
@@ -67,10 +68,10 @@ class AgeFilter(IPairList):
f"{self._max_days_listed} {plural(self._max_days_listed, 'day')}"
) if self._max_days_listed else '')
def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
def filter_pairlist(self, pairlist: List[str], tickers: Tickers) -> List[str]:
"""
:param pairlist: pairlist to filter or sort
:param tickers: Tickers (from exchange.get_tickers()). May be cached.
:param tickers: Tickers (from exchange.get_tickers). May be cached.
:return: new allowlist
"""
needed_pairs: ListPairsWithTimeframes = [

17
freqtrade/plugins/pairlist/IPairList.py
View File

@@ -4,11 +4,12 @@ PairList Handler base class
import logging
from abc import ABC, abstractmethod, abstractproperty
from copy import deepcopy
from typing import Any, Dict, List
from typing import Any, Dict, List, Optional
from freqtrade.constants import Config
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import Exchange, market_is_active
from freqtrade.exchange.types import Ticker, Tickers
from freqtrade.mixins import LoggingMixin
@@ -61,7 +62,7 @@ class IPairList(LoggingMixin, ABC):
-> Please overwrite in subclasses
"""
def _validate_pair(self, pair: str, ticker: Dict[str, Any]) -> bool:
def _validate_pair(self, pair: str, ticker: Optional[Ticker]) -> bool:
"""
Check one pair against Pairlist Handler's specific conditions.
@@ -69,12 +70,12 @@ class IPairList(LoggingMixin, ABC):
filter_pairlist() method.
:param pair: Pair that's currently validated
:param ticker: ticker dict as returned from ccxt.fetch_tickers()
:param ticker: ticker dict as returned from ccxt.fetch_ticker
:return: True if the pair can stay, false if it should be removed
"""
raise NotImplementedError()
def gen_pairlist(self, tickers: Dict) -> List[str]:
def gen_pairlist(self, tickers: Tickers) -> List[str]:
"""
Generate the pairlist.
@@ -85,13 +86,13 @@ class IPairList(LoggingMixin, ABC):
it will raise the exception if a Pairlist Handler is used at the first
position in the chain.
:param tickers: Tickers (from exchange.get_tickers()). May be cached.
:param tickers: Tickers (from exchange.get_tickers). May be cached.
:return: List of pairs
"""
raise OperationalException("This Pairlist Handler should not be used "
"at the first position in the list of Pairlist Handlers.")
def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
def filter_pairlist(self, pairlist: List[str], tickers: Tickers) -> List[str]:
"""
Filters and sorts pairlist and returns the whitelist again.
@@ -103,14 +104,14 @@ class IPairList(LoggingMixin, ABC):
own filtration.
:param pairlist: pairlist to filter or sort
:param tickers: Tickers (from exchange.get_tickers()). May be cached.
:param tickers: Tickers (from exchange.get_tickers). May be cached.
:return: new whitelist
"""
if self._enabled:
# Copy list since we're modifying this list
for p in deepcopy(pairlist):
# Filter out assets
if not self._validate_pair(p, tickers[p] if p in tickers else {}):
if not self._validate_pair(p, tickers[p] if p in tickers else None):
pairlist.remove(p)
return pairlist

5
freqtrade/plugins/pairlist/OffsetFilter.py
View File

@@ -6,6 +6,7 @@ from typing import Any, Dict, List
from freqtrade.constants import Config
from freqtrade.exceptions import OperationalException
from freqtrade.exchange.types import Tickers
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -42,12 +43,12 @@ class OffsetFilter(IPairList):
return f"{self.name} - Taking {self._number_pairs} Pairs, starting from {self._offset}."
return f"{self.name} - Offsetting pairs by {self._offset}."
def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
def filter_pairlist(self, pairlist: List[str], tickers: Tickers) -> 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.
:param tickers: Tickers (from exchange.get_tickers). May be cached.
:return: new whitelist
"""
if self._offset > len(pairlist):

5
freqtrade/plugins/pairlist/PerformanceFilter.py
View File

@@ -7,6 +7,7 @@ from typing import Any, Dict, List
import pandas as pd
from freqtrade.constants import Config
from freqtrade.exchange.types import Tickers
from freqtrade.persistence import Trade
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -39,12 +40,12 @@ class PerformanceFilter(IPairList):
"""
return f"{self.name} - Sorting pairs by performance."
def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
def filter_pairlist(self, pairlist: List[str], tickers: Tickers) -> List[str]:
"""
Filters and sorts pairlist and returns the allowlist 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.
:param tickers: Tickers (from exchange.get_tickers). May be cached.
:return: new allowlist
"""
# Get the trading performance for pairs from database

9
freqtrade/plugins/pairlist/PrecisionFilter.py
View File

@@ -2,10 +2,11 @@
Precision pair list filter
"""
import logging
from typing import Any, Dict
from typing import Any, Dict, Optional
from freqtrade.constants import Config
from freqtrade.exceptions import OperationalException
from freqtrade.exchange.types import Ticker
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -44,15 +45,15 @@ class PrecisionFilter(IPairList):
"""
return f"{self.name} - Filtering untradable pairs."
def _validate_pair(self, pair: str, ticker: Dict[str, Any]) -> bool:
def _validate_pair(self, pair: str, ticker: Optional[Ticker]) -> bool:
"""
Check if pair has enough room to add a stoploss to avoid "unsellable" buys of very
low value pairs.
:param pair: Pair that's currently validated
:param ticker: ticker dict as returned from ccxt.fetch_tickers()
:param ticker: ticker dict as returned from ccxt.fetch_ticker
:return: True if the pair can stay, false if it should be removed
"""
if ticker.get('last', None) is None:
if not ticker or ticker.get('last', None) is None:
self.log_once(f"Removed {pair} from whitelist, because "
"ticker['last'] is empty (Usually no trade in the last 24h).",
logger.info)

20
freqtrade/plugins/pairlist/PriceFilter.py
View File

@@ -2,10 +2,11 @@
Price pair list filter
"""
import logging
from typing import Any, Dict
from typing import Any, Dict, Optional
from freqtrade.constants import Config
from freqtrade.exceptions import OperationalException
from freqtrade.exchange.types import Ticker
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -64,14 +65,16 @@ class PriceFilter(IPairList):
return f"{self.name} - No price filters configured."
def _validate_pair(self, pair: str, ticker: Dict[str, Any]) -> bool:
def _validate_pair(self, pair: str, ticker: Optional[Ticker]) -> bool:
"""
Check if if one price-step (pip) is > than a certain barrier.
:param pair: Pair that's currently validated
:param ticker: ticker dict as returned from ccxt.fetch_tickers()
:param ticker: ticker dict as returned from ccxt.fetch_ticker
:return: True if the pair can stay, false if it should be removed
"""
if ticker.get('last', None) is None or ticker.get('last') == 0:
if ticker and 'last' in ticker and ticker['last'] is not None and ticker.get('last') != 0:
price: float = ticker['last']
else:
self.log_once(f"Removed {pair} from whitelist, because "
"ticker['last'] is empty (Usually no trade in the last 24h).",
logger.info)
@@ -79,8 +82,8 @@ class PriceFilter(IPairList):
# Perform low_price_ratio check.
if self._low_price_ratio != 0:
compare = self._exchange.price_get_one_pip(pair, ticker['last'])
changeperc = compare / ticker['last']
compare = self._exchange.price_get_one_pip(pair, price)
changeperc = compare / price
if changeperc > self._low_price_ratio:
self.log_once(f"Removed {pair} from whitelist, "
f"because 1 unit is {changeperc:.3%}", logger.info)
@@ -88,7 +91,6 @@ class PriceFilter(IPairList):
# Perform low_amount check
if self._max_value != 0:
price = ticker['last']
market = self._exchange.markets[pair]
limits = market['limits']
if (limits['amount']['min'] is not None):
@@ -113,14 +115,14 @@ class PriceFilter(IPairList):
# Perform min_price check.
if self._min_price != 0:
if ticker['last'] < self._min_price:
if price < self._min_price:
self.log_once(f"Removed {pair} from whitelist, "
f"because last price < {self._min_price:.8f}", logger.info)
return False
# Perform max_price check.
if self._max_price != 0:
if ticker['last'] > self._max_price:
if price > self._max_price:
self.log_once(f"Removed {pair} from whitelist, "
f"because last price > {self._max_price:.8f}", logger.info)
return False

9
freqtrade/plugins/pairlist/ProducerPairList.py
View File

@@ -7,6 +7,7 @@ import logging
from typing import Any, Dict, List, Optional
from freqtrade.exceptions import OperationalException
from freqtrade.exchange.types import Tickers
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -68,10 +69,10 @@ class ProducerPairList(IPairList):
return pairs
def gen_pairlist(self, tickers: Dict) -> List[str]:
def gen_pairlist(self, tickers: Tickers) -> List[str]:
"""
Generate the pairlist
:param tickers: Tickers (from exchange.get_tickers()). May be cached.
:param tickers: Tickers (from exchange.get_tickers). May be cached.
:return: List of pairs
"""
pairs = self._filter_pairlist(None)
@@ -79,12 +80,12 @@ class ProducerPairList(IPairList):
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]:
def filter_pairlist(self, pairlist: List[str], tickers: Tickers) -> 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.
:param tickers: Tickers (from exchange.get_tickers). May be cached.
:return: new whitelist
"""
return self._filter_pairlist(pairlist)

5
freqtrade/plugins/pairlist/ShuffleFilter.py
View File

@@ -7,6 +7,7 @@ from typing import Any, Dict, List
from freqtrade.constants import Config
from freqtrade.enums import RunMode
from freqtrade.exchange.types import Tickers
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -47,12 +48,12 @@ class ShuffleFilter(IPairList):
return (f"{self.name} - Shuffling pairs" +
(f", seed = {self._seed}." if self._seed is not None else "."))
def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
def filter_pairlist(self, pairlist: List[str], tickers: Tickers) -> 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.
:param tickers: Tickers (from exchange.get_tickers). May be cached.
:return: new whitelist
"""
# Shuffle is done inplace

16
freqtrade/plugins/pairlist/SpreadFilter.py
View File

@@ -2,10 +2,10 @@
Spread pair list filter
"""
import logging
from typing import Any, Dict
from typing import Any, Dict, Optional
from freqtrade.constants import Config
from freqtrade.exceptions import OperationalException
from freqtrade.exchange.types import Ticker
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -22,12 +22,6 @@ class SpreadFilter(IPairList):
self._max_spread_ratio = pairlistconfig.get('max_spread_ratio', 0.005)
self._enabled = self._max_spread_ratio != 0
if not self._exchange.exchange_has('fetchTickers'):
raise OperationalException(
'Exchange does not support fetchTickers, therefore SpreadFilter cannot be used.'
'Please edit your config and restart the bot.'
)
@property
def needstickers(self) -> bool:
"""
@@ -44,14 +38,14 @@ class SpreadFilter(IPairList):
return (f"{self.name} - Filtering pairs with ask/bid diff above "
f"{self._max_spread_ratio:.2%}.")
def _validate_pair(self, pair: str, ticker: Dict[str, Any]) -> bool:
def _validate_pair(self, pair: str, ticker: Optional[Ticker]) -> bool:
"""
Validate spread for the ticker
:param pair: Pair that's currently validated
:param ticker: ticker dict as returned from ccxt.fetch_tickers()
:param ticker: ticker dict as returned from ccxt.fetch_ticker
:return: True if the pair can stay, false if it should be removed
"""
if 'bid' in ticker and 'ask' in ticker and ticker['ask'] and ticker['bid']:
if ticker and 'bid' in ticker and 'ask' in ticker and ticker['ask'] and ticker['bid']:
spread = 1 - ticker['bid'] / ticker['ask']
if spread > self._max_spread_ratio:
self.log_once(f"Removed {pair} from whitelist, because spread "

9
freqtrade/plugins/pairlist/StaticPairList.py
View File

@@ -8,6 +8,7 @@ from copy import deepcopy
from typing import Any, Dict, List
from freqtrade.constants import Config
from freqtrade.exchange.types import Tickers
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -39,10 +40,10 @@ class StaticPairList(IPairList):
"""
return f"{self.name}"
def gen_pairlist(self, tickers: Dict) -> List[str]:
def gen_pairlist(self, tickers: Tickers) -> List[str]:
"""
Generate the pairlist
:param tickers: Tickers (from exchange.get_tickers()). May be cached.
:param tickers: Tickers (from exchange.get_tickers). May be cached.
:return: List of pairs
"""
if self._allow_inactive:
@@ -53,12 +54,12 @@ class StaticPairList(IPairList):
return self._whitelist_for_active_markets(
self.verify_whitelist(self._config['exchange']['pair_whitelist'], logger.info))
def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
def filter_pairlist(self, pairlist: List[str], tickers: Tickers) -> 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.
:param tickers: Tickers (from exchange.get_tickers). May be cached.
:return: new whitelist
"""
pairlist_ = deepcopy(pairlist)

5
freqtrade/plugins/pairlist/VolatilityFilter.py
View File

@@ -13,6 +13,7 @@ from pandas import DataFrame
from freqtrade.constants import Config, ListPairsWithTimeframes
from freqtrade.exceptions import OperationalException
from freqtrade.exchange.types import Tickers
from freqtrade.misc import plural
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -62,11 +63,11 @@ class VolatilityFilter(IPairList):
f"{self._min_volatility}-{self._max_volatility} "
f" the last {self._days} {plural(self._days, 'day')}.")
def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
def filter_pairlist(self, pairlist: List[str], tickers: Tickers) -> List[str]:
"""
Validate trading range
:param pairlist: pairlist to filter or sort
:param tickers: Tickers (from exchange.get_tickers()). May be cached.
:param tickers: Tickers (from exchange.get_tickers). May be cached.
:return: new allowlist
"""
needed_pairs: ListPairsWithTimeframes = [

11
freqtrade/plugins/pairlist/VolumePairList.py
View File

@@ -5,13 +5,14 @@ Provides dynamic pair list based on trade volumes
"""
import logging
from datetime import datetime, timedelta, timezone
from typing import Any, Dict, List
from typing import Any, Dict, List, Literal
from cachetools import TTLCache
from freqtrade.constants import Config, ListPairsWithTimeframes
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_prev_date
from freqtrade.exchange.types import Tickers
from freqtrade.misc import format_ms_time
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -36,7 +37,7 @@ class VolumePairList(IPairList):
self._stake_currency = config['stake_currency']
self._number_pairs = self._pairlistconfig['number_assets']
self._sort_key = self._pairlistconfig.get('sort_key', 'quoteVolume')
self._sort_key: Literal['quoteVolume'] = self._pairlistconfig.get('sort_key', 'quoteVolume')
self._min_value = self._pairlistconfig.get('min_value', 0)
self._refresh_period = self._pairlistconfig.get('refresh_period', 1800)
self._pair_cache: TTLCache = TTLCache(maxsize=1, ttl=self._refresh_period)
@@ -110,10 +111,10 @@ class VolumePairList(IPairList):
"""
return f"{self.name} - top {self._pairlistconfig['number_assets']} volume pairs."
def gen_pairlist(self, tickers: Dict) -> List[str]:
def gen_pairlist(self, tickers: Tickers) -> List[str]:
"""
Generate the pairlist
:param tickers: Tickers (from exchange.get_tickers()). May be cached.
:param tickers: Tickers (from exchange.get_tickers). May be cached.
:return: List of pairs
"""
# Generate dynamic whitelist
@@ -150,7 +151,7 @@ class VolumePairList(IPairList):
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.
:param tickers: Tickers (from exchange.get_tickers). May be cached.
:return: new whitelist
"""
if self._use_range:

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

@@ -12,7 +12,7 @@ def expand_pairlist(wildcardpl: List[str], available_pairs: List[str],
:param wildcardpl: List of Pairlists, which may contain regex
:param available_pairs: List of all available pairs (`exchange.get_markets().keys()`)
:param keep_invalid: If sets to True, drops invalid pairs silently while expanding regexes
:return expanded pairlist, with Regexes from wildcardpl applied to match all available pairs.
:return: expanded pairlist, with Regexes from wildcardpl applied to match all available pairs.
:raises: ValueError if a wildcard is invalid (like '*/BTC' - which should be `.*/BTC`)
"""
result = []

5
freqtrade/plugins/pairlist/rangestabilityfilter.py
View File

@@ -11,6 +11,7 @@ from pandas import DataFrame
from freqtrade.constants import Config, ListPairsWithTimeframes
from freqtrade.exceptions import OperationalException
from freqtrade.exchange.types import Tickers
from freqtrade.misc import plural
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -60,11 +61,11 @@ class RangeStabilityFilter(IPairList):
f"{self._min_rate_of_change}{max_rate_desc} over the "
f"last {plural(self._days, 'day')}.")
def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
def filter_pairlist(self, pairlist: List[str], tickers: Tickers) -> List[str]:
"""
Validate trading range
:param pairlist: pairlist to filter or sort
:param tickers: Tickers (from exchange.get_tickers()). May be cached.
:param tickers: Tickers (from exchange.get_tickers). May be cached.
:return: new allowlist
"""
needed_pairs: ListPairsWithTimeframes = [

12
freqtrade/plugins/pairlistmanager.py
View File

@@ -11,6 +11,7 @@ from freqtrade.constants import Config, ListPairsWithTimeframes
from freqtrade.data.dataprovider import DataProvider
from freqtrade.enums import CandleType
from freqtrade.exceptions import OperationalException
from freqtrade.exchange.types import Tickers
from freqtrade.mixins import LoggingMixin
from freqtrade.plugins.pairlist.IPairList import IPairList
from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
@@ -45,6 +46,15 @@ class PairListManager(LoggingMixin):
if not self._pairlist_handlers:
raise OperationalException("No Pairlist Handlers defined")
if self._tickers_needed and not self._exchange.exchange_has('fetchTickers'):
invalid = ". ".join([p.name for p in self._pairlist_handlers if p.needstickers])
raise OperationalException(
"Exchange does not support fetchTickers, therefore the following pairlists "
"cannot be used. Please edit your config and restart the bot.\n"
f"{invalid}."
)
refresh_period = config.get('pairlist_refresh_period', 3600)
LoggingMixin.__init__(self, logger, refresh_period)
@@ -76,7 +86,7 @@ class PairListManager(LoggingMixin):
return [{p.name: p.short_desc()} for p in self._pairlist_handlers]
@cached(TTLCache(maxsize=1, ttl=1800))
def _get_cached_tickers(self):
def _get_cached_tickers(self) -> Tickers:
return self._exchange.get_tickers()
def refresh_pairlist(self) -> None:

32
freqtrade/resolvers/iresolver.py
View File

@@ -183,9 +183,35 @@ class IResolver:
)
@classmethod
def search_all_objects(cls, directory: Path, enum_failed: bool,
def search_all_objects(cls, config: Config, enum_failed: bool,
recursive: bool = False) -> List[Dict[str, Any]]:
"""
Searches for valid objects
:param config: Config object
:param enum_failed: If True, will return None for modules which fail.
Otherwise, failing modules are skipped.
:param recursive: Recursively walk directory tree searching for strategies
:return: List of dicts containing 'name', 'class' and 'location' entries
"""
result = []
abs_paths = cls.build_search_paths(config, user_subdir=cls.user_subdir)
for path in abs_paths:
result.extend(cls._search_all_objects(path, enum_failed, recursive))
return result
@classmethod
def _build_rel_location(cls, directory: Path, entry: Path) -> str:
builtin = cls.initial_search_path == directory
return f"<builtin>/{entry.relative_to(directory)}" if builtin else str(
entry.relative_to(directory))
@classmethod
def _search_all_objects(
cls, directory: Path, enum_failed: bool, recursive: bool = False,
basedir: Optional[Path] = None) -> List[Dict[str, Any]]:
"""
Searches a directory for valid objects
:param directory: Path to search
:param enum_failed: If True, will return None for modules which fail.
@@ -204,7 +230,8 @@ class IResolver:
and not entry.name.startswith('__')
and not entry.name.startswith('.')
):
objects.extend(cls.search_all_objects(entry, enum_failed, recursive=recursive))
objects.extend(cls._search_all_objects(
entry, enum_failed, recursive, basedir or directory))
# Only consider python files
if entry.suffix != '.py':
logger.debug('Ignoring %s', entry)
@@ -217,5 +244,6 @@ class IResolver:
{'name': obj[0].__name__ if obj is not None else '',
'class': obj[0] if obj is not None else None,
'location': entry,
'location_rel': cls._build_rel_location(basedir or directory, entry),
})
return objects

8
freqtrade/resolvers/strategy_resolver.py
View File

@@ -268,6 +268,14 @@ class StrategyResolver(IResolver):
"or contains Python code errors."
)
@classmethod
def build_search_paths(cls, config: Config, user_subdir: Optional[str] = None,
extra_dirs: List[str] = []) -> List[Path]:
if 'strategy_path' in config and config['strategy_path'] not in extra_dirs:
extra_dirs = [config['strategy_path']] + extra_dirs
return super().build_search_paths(config, user_subdir, extra_dirs)
def warn_deprecated_setting(strategy: IStrategy, old: str, new: str, error=False):
if hasattr(strategy, old):

6
freqtrade/rpc/api_server/api_v1.py
View File

@@ -1,13 +1,11 @@
import logging
from copy import deepcopy
from pathlib import Path
from typing import List, Optional
from fastapi import APIRouter, Depends, Query
from fastapi.exceptions import HTTPException
from freqtrade import __version__
from freqtrade.constants import USERPATH_STRATEGIES
from freqtrade.data.history import get_datahandler
from freqtrade.enums import CandleType, TradingMode
from freqtrade.exceptions import OperationalException
@@ -253,11 +251,9 @@ def plot_config(rpc: RPC = Depends(get_rpc)):
@router.get('/strategies', response_model=StrategyListResponse, tags=['strategy'])
def list_strategies(config=Depends(get_config)):
directory = Path(config.get(
'strategy_path', config['user_data_dir'] / USERPATH_STRATEGIES))
from freqtrade.resolvers.strategy_resolver import StrategyResolver
strategies = StrategyResolver.search_all_objects(
directory, False, config.get('recursive_strategy_search', False))
config, False, config.get('recursive_strategy_search', False))
strategies = sorted(strategies, key=lambda x: x['name'])
return {'strategies': [x['name'] for x in strategies]}

21
freqtrade/rpc/api_server/api_ws.py
View File

@@ -4,6 +4,7 @@ from typing import Any, Dict
from fastapi import APIRouter, Depends, WebSocketDisconnect
from fastapi.websockets import WebSocket, WebSocketState
from pydantic import ValidationError
from websockets.exceptions import WebSocketException
from freqtrade.enums import RPCMessageType, RPCRequestType
from freqtrade.rpc.api_server.api_auth import validate_ws_token
@@ -102,7 +103,6 @@ async def message_endpoint(
"""
try:
channel = await channel_manager.on_connect(ws)
if await is_websocket_alive(ws):
logger.info(f"Consumer connected - {channel}")
@@ -115,26 +115,31 @@ async def message_endpoint(
# Process the request here
await _process_consumer_request(request, channel, rpc)
except WebSocketDisconnect:
except (WebSocketDisconnect, WebSocketException):
# Handle client disconnects
logger.info(f"Consumer disconnected - {channel}")
await channel_manager.on_disconnect(ws)
except Exception as e:
logger.info(f"Consumer connection failed - {channel}")
logger.exception(e)
except RuntimeError:
# Handle cases like -
# RuntimeError('Cannot call "send" once a closed message has been sent')
pass
except Exception as e:
logger.info(f"Consumer connection failed - {channel}: {e}")
logger.debug(e, exc_info=e)
finally:
await channel_manager.on_disconnect(ws)
else:
if channel:
await channel_manager.on_disconnect(ws)
await ws.close()
except RuntimeError:
# WebSocket was closed
await channel_manager.on_disconnect(ws)
# Do nothing
pass
except Exception as e:
logger.error(f"Failed to serve - {ws.client}")
# Log tracebacks to keep track of what errors are happening
logger.exception(e)
finally:
await channel_manager.on_disconnect(ws)

5
freqtrade/rpc/api_server/webserver.py
View File

@@ -198,10 +198,6 @@ class ApiServer(RPCHandler):
logger.debug(f"Found message of type: {message.get('type')}")
# Broadcast it
await self._ws_channel_manager.broadcast(message)
# 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
@@ -245,6 +241,7 @@ class ApiServer(RPCHandler):
use_colors=False,
log_config=None,
access_log=True if verbosity != 'error' else False,
ws_ping_interval=None # We do this explicitly ourselves
)
try:
self._server = UvicornServer(uvconfig)

44
freqtrade/rpc/api_server/ws/channel.py
View File

@@ -1,6 +1,7 @@
import asyncio
import logging
from threading import RLock
from typing import List, Optional, Type
from typing import Any, Dict, List, Optional, Type
from uuid import uuid4
from fastapi import WebSocket as FastAPIWebSocket
@@ -34,6 +35,8 @@ class WebSocketChannel:
self._serializer_cls = serializer_cls
self._subscriptions: List[str] = []
self.queue: asyncio.Queue[Dict[str, Any]] = asyncio.Queue(maxsize=32)
self._relay_task = asyncio.create_task(self.relay())
# Internal event to signify a closed websocket
self._closed = False
@@ -48,12 +51,18 @@ class WebSocketChannel:
def remote_addr(self):
return self._websocket.remote_addr
async def send(self, data):
async def _send(self, data):
"""
Send data on the wrapped websocket
"""
await self._wrapped_ws.send(data)
async def send(self, data):
"""
Add the data to the queue to be sent
"""
self.queue.put_nowait(data)
async def recv(self):
"""
Receive data on the wrapped websocket
@@ -72,6 +81,7 @@ class WebSocketChannel:
"""
self._closed = True
self._relay_task.cancel()
def is_closed(self) -> bool:
"""
@@ -95,6 +105,26 @@ class WebSocketChannel:
"""
return message_type in self._subscriptions
async def relay(self):
"""
Relay messages from the channel's queue and send them out. This is started
as a task.
"""
while True:
message = await self.queue.get()
try:
await self._send(message)
self.queue.task_done()
# Limit messages per sec.
# Could cause problems with queue size if too low, and
# problems with network traffik if too high.
# 0.001 = 1000/s
await asyncio.sleep(0.001)
except RuntimeError:
# The connection was closed, just exit the task
return
class ChannelManager:
def __init__(self):
@@ -155,12 +185,12 @@ class ChannelManager:
with self._lock:
message_type = data.get('type')
for websocket, channel in self.channels.copy().items():
try:
if channel.subscribed_to(message_type):
if channel.subscribed_to(message_type):
if not channel.queue.full():
await channel.send(data)
except RuntimeError:
# Handle cannot send after close cases
await self.on_disconnect(websocket)
else:
logger.info(f"Channel {channel} is too far behind, disconnecting")
await self.on_disconnect(websocket)
async def send_direct(self, channel, data):
"""

17
freqtrade/rpc/discord.py
View File

@@ -11,13 +11,12 @@ logger = logging.getLogger(__name__)
class Discord(Webhook):
def __init__(self, rpc: 'RPC', config: Config):
# super().__init__(rpc, config)
self._config = config
self.rpc = rpc
self.config = config
self.strategy = config.get('strategy', '')
self.timeframe = config.get('timeframe', '')
self._url = self.config['discord']['webhook_url']
self._url = config['discord']['webhook_url']
self._format = 'json'
self._retries = 1
self._retry_delay = 0.1
@@ -31,19 +30,21 @@ class Discord(Webhook):
def send_msg(self, msg) -> None:
if msg['type'].value in self.config['discord']:
if msg['type'].value in self._config['discord']:
logger.info(f"Sending discord message: {msg}")
msg['strategy'] = self.strategy
msg['timeframe'] = self.timeframe
fields = self.config['discord'].get(msg['type'].value)
fields = self._config['discord'].get(msg['type'].value)
color = 0x0000FF
if msg['type'] in (RPCMessageType.EXIT, RPCMessageType.EXIT_FILL):
profit_ratio = msg.get('profit_ratio')
color = (0x00FF00 if profit_ratio > 0 else 0xFF0000)
title = msg['type'].value
if 'pair' in msg:
title = f"Trade: {msg['pair']} {msg['type'].value}"
embeds = [{
'title': f"Trade: {msg['pair']} {msg['type'].value}",
'title': title,
'color': color,
'fields': [],
@@ -51,7 +52,7 @@ class Discord(Webhook):
for f in fields:
for k, v in f.items():
v = v.format(**msg)
embeds[0]['fields'].append( # type: ignore
embeds[0]['fields'].append(
{'name': k, 'value': v, 'inline': True})
# Send the message to discord channel

13
freqtrade/rpc/external_message_consumer.py
View File

@@ -62,7 +62,7 @@ class ExternalMessageConsumer:
self.enabled = self._emc_config.get('enabled', False)
self.producers: List[Producer] = self._emc_config.get('producers', [])
self.wait_timeout = self._emc_config.get('wait_timeout', 300) # in seconds
self.wait_timeout = self._emc_config.get('wait_timeout', 30) # in seconds
self.ping_timeout = self._emc_config.get('ping_timeout', 10) # in seconds
self.sleep_time = self._emc_config.get('sleep_time', 10) # in seconds
@@ -174,6 +174,7 @@ class ExternalMessageConsumer:
:param producer: Dictionary containing producer info
:param lock: An asyncio Lock
"""
channel = None
while self._running:
try:
host, port = producer['host'], producer['port']
@@ -182,7 +183,11 @@ class ExternalMessageConsumer:
ws_url = f"ws://{host}:{port}/api/v1/message/ws?token={token}"
# This will raise InvalidURI if the url is bad
async with websockets.connect(ws_url, max_size=self.message_size_limit) as ws:
async with websockets.connect(
ws_url,
max_size=self.message_size_limit,
ping_interval=None
) as ws:
channel = WebSocketChannel(ws, channel_id=name)
logger.info(f"Producer connection success - {channel}")
@@ -224,6 +229,10 @@ class ExternalMessageConsumer:
logger.exception(e)
continue
finally:
if channel:
await channel.close()
async def _receive_messages(
self,
channel: WebSocketChannel,

11
freqtrade/rpc/rpc_manager.py
View File

@@ -88,10 +88,13 @@ class RPCManager:
"""
while queue:
msg = queue.popleft()
self.send_msg({
'type': RPCMessageType.STRATEGY_MSG,
'msg': msg,
})
logger.info('Sending rpc strategy_msg: %s', msg)
for mod in self.registered_modules:
if mod._config.get(mod.name, {}).get('allow_custom_messages', False):
mod.send_msg({
'type': RPCMessageType.STRATEGY_MSG,
'msg': msg,
})
def startup_messages(self, config: Config, pairlist, protections) -> None:
if config['dry_run']:

64
freqtrade/rpc/webhook.py
View File

@@ -3,7 +3,7 @@ This module manages webhook communication
"""
import logging
import time
from typing import Any, Dict
from typing import Any, Dict, Optional
from requests import RequestException, post
@@ -41,36 +41,44 @@ class Webhook(RPCHandler):
"""
pass
def _get_value_dict(self, msg: Dict[str, Any]) -> Optional[Dict[str, Any]]:
whconfig = self._config['webhook']
# Deprecated 2022.10 - only keep generic method.
if msg['type'] in [RPCMessageType.ENTRY]:
valuedict = whconfig.get('webhookentry')
elif msg['type'] in [RPCMessageType.ENTRY_CANCEL]:
valuedict = whconfig.get('webhookentrycancel')
elif msg['type'] in [RPCMessageType.ENTRY_FILL]:
valuedict = whconfig.get('webhookentryfill')
elif msg['type'] == RPCMessageType.EXIT:
valuedict = whconfig.get('webhookexit')
elif msg['type'] == RPCMessageType.EXIT_FILL:
valuedict = whconfig.get('webhookexitfill')
elif msg['type'] == RPCMessageType.EXIT_CANCEL:
valuedict = whconfig.get('webhookexitcancel')
elif msg['type'] in (RPCMessageType.STATUS,
RPCMessageType.STARTUP,
RPCMessageType.WARNING):
valuedict = whconfig.get('webhookstatus')
elif msg['type'].value in whconfig:
# Allow all types ...
valuedict = whconfig.get(msg['type'].value)
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 None
return valuedict
def send_msg(self, msg: Dict[str, Any]) -> None:
""" Send a message to telegram channel """
try:
whconfig = self._config['webhook']
if msg['type'] in [RPCMessageType.ENTRY]:
valuedict = whconfig.get('webhookentry')
elif msg['type'] in [RPCMessageType.ENTRY_CANCEL]:
valuedict = whconfig.get('webhookentrycancel')
elif msg['type'] in [RPCMessageType.ENTRY_FILL]:
valuedict = whconfig.get('webhookentryfill')
elif msg['type'] == RPCMessageType.EXIT:
valuedict = whconfig.get('webhookexit')
elif msg['type'] == RPCMessageType.EXIT_FILL:
valuedict = whconfig.get('webhookexitfill')
elif msg['type'] == RPCMessageType.EXIT_CANCEL:
valuedict = whconfig.get('webhookexitcancel')
elif msg['type'] in (RPCMessageType.STATUS,
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']))
valuedict = self._get_value_dict(msg)
if not valuedict:
logger.info("Message type '%s' not configured for webhooks", msg['type'])
return

2
freqtrade/strategy/interface.py
View File

@@ -49,7 +49,7 @@ class IStrategy(ABC, HyperStrategyMixin):
_ft_params_from_file: Dict
# associated minimal roi
minimal_roi: Dict = {}
minimal_roi: Dict = {"0": 10.0}
# associated stoploss
stoploss: float