Merge branch 'develop' into fix/pd-mem-leak

This commit is contained in:
Timothy Pogue 2022-11-17 12:04:49 -07:00
commit 49ecc83061
10 changed files with 85 additions and 53 deletions

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@ -3,11 +3,12 @@ This module contains the argument manager class
""" """
import logging import logging
import re import re
from datetime import datetime from datetime import datetime, timezone
from typing import Optional from typing import Optional
import arrow import arrow
from freqtrade.constants import DATETIME_PRINT_FORMAT
from freqtrade.exceptions import OperationalException from freqtrade.exceptions import OperationalException
@ -29,6 +30,52 @@ class TimeRange:
self.startts: int = startts self.startts: int = startts
self.stopts: int = stopts self.stopts: int = stopts
@property
def startdt(self) -> Optional[datetime]:
if self.startts:
return datetime.fromtimestamp(self.startts, tz=timezone.utc)
return None
@property
def stopdt(self) -> Optional[datetime]:
if self.stopts:
return datetime.fromtimestamp(self.stopts, tz=timezone.utc)
return None
@property
def timerange_str(self) -> str:
"""
Returns a string representation of the timerange as used by parse_timerange.
Follows the format yyyymmdd-yyyymmdd - leaving out the parts that are not set.
"""
start = ''
stop = ''
if startdt := self.startdt:
start = startdt.strftime('%Y%m%d')
if stopdt := self.stopdt:
stop = stopdt.strftime('%Y%m%d')
return f"{start}-{stop}"
@property
def start_fmt(self) -> str:
"""
Returns a string representation of the start date
"""
val = 'unbounded'
if (startdt := self.startdt) is not None:
val = startdt.strftime(DATETIME_PRINT_FORMAT)
return val
@property
def stop_fmt(self) -> str:
"""
Returns a string representation of the stop date
"""
val = 'unbounded'
if (stopdt := self.stopdt) is not None:
val = stopdt.strftime(DATETIME_PRINT_FORMAT)
return val
def __eq__(self, other): def __eq__(self, other):
"""Override the default Equals behavior""" """Override the default Equals behavior"""
return (self.starttype == other.starttype and self.stoptype == other.stoptype return (self.starttype == other.starttype and self.stoptype == other.stoptype

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@ -3,7 +3,6 @@ Functions to convert data from one format to another
""" """
import itertools import itertools
import logging import logging
from datetime import datetime, timezone
from operator import itemgetter from operator import itemgetter
from typing import Dict, List from typing import Dict, List
@ -138,11 +137,9 @@ def trim_dataframe(df: DataFrame, timerange, df_date_col: str = 'date',
df = df.iloc[startup_candles:, :] df = df.iloc[startup_candles:, :]
else: else:
if timerange.starttype == 'date': if timerange.starttype == 'date':
start = datetime.fromtimestamp(timerange.startts, tz=timezone.utc) df = df.loc[df[df_date_col] >= timerange.startdt, :]
df = df.loc[df[df_date_col] >= start, :]
if timerange.stoptype == 'date': if timerange.stoptype == 'date':
stop = datetime.fromtimestamp(timerange.stopts, tz=timezone.utc) df = df.loc[df[df_date_col] <= timerange.stopdt, :]
df = df.loc[df[df_date_col] <= stop, :]
return df return df

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@ -1,6 +1,6 @@
import logging import logging
import operator import operator
from datetime import datetime, timezone from datetime import datetime
from pathlib import Path from pathlib import Path
from typing import Dict, List, Optional, Tuple from typing import Dict, List, Optional, Tuple
@ -160,9 +160,9 @@ def _load_cached_data_for_updating(
end = None end = None
if timerange: if timerange:
if timerange.starttype == 'date': if timerange.starttype == 'date':
start = datetime.fromtimestamp(timerange.startts, tz=timezone.utc) start = timerange.startdt
if timerange.stoptype == 'date': if timerange.stoptype == 'date':
end = datetime.fromtimestamp(timerange.stopts, tz=timezone.utc) end = timerange.stopdt
# Intentionally don't pass timerange in - since we need to load the full dataset. # Intentionally don't pass timerange in - since we need to load the full dataset.
data = data_handler.ohlcv_load(pair, timeframe=timeframe, data = data_handler.ohlcv_load(pair, timeframe=timeframe,

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@ -366,13 +366,11 @@ class IDataHandler(ABC):
""" """
if timerange.starttype == 'date': if timerange.starttype == 'date':
start = datetime.fromtimestamp(timerange.startts, tz=timezone.utc) if pairdata.iloc[0]['date'] > timerange.startdt:
if pairdata.iloc[0]['date'] > start:
logger.warning(f"{pair}, {candle_type}, {timeframe}, " logger.warning(f"{pair}, {candle_type}, {timeframe}, "
f"data starts at {pairdata.iloc[0]['date']:%Y-%m-%d %H:%M:%S}") f"data starts at {pairdata.iloc[0]['date']:%Y-%m-%d %H:%M:%S}")
if timerange.stoptype == 'date': if timerange.stoptype == 'date':
stop = datetime.fromtimestamp(timerange.stopts, tz=timezone.utc) if pairdata.iloc[-1]['date'] < timerange.stopdt:
if pairdata.iloc[-1]['date'] < stop:
logger.warning(f"{pair}, {candle_type}, {timeframe}, " logger.warning(f"{pair}, {candle_type}, {timeframe}, "
f"data ends at {pairdata.iloc[-1]['date']:%Y-%m-%d %H:%M:%S}") f"data ends at {pairdata.iloc[-1]['date']:%Y-%m-%d %H:%M:%S}")

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@ -433,9 +433,7 @@ class FreqaiDataKitchen:
timerange_train.stopts = timerange_train.startts + train_period_days timerange_train.stopts = timerange_train.startts + train_period_days
first = False first = False
start = datetime.fromtimestamp(timerange_train.startts, tz=timezone.utc) tr_training_list.append(timerange_train.timerange_str)
stop = datetime.fromtimestamp(timerange_train.stopts, tz=timezone.utc)
tr_training_list.append(start.strftime("%Y%m%d") + "-" + stop.strftime("%Y%m%d"))
tr_training_list_timerange.append(copy.deepcopy(timerange_train)) tr_training_list_timerange.append(copy.deepcopy(timerange_train))
# associated backtest period # associated backtest period
@ -447,9 +445,7 @@ class FreqaiDataKitchen:
if timerange_backtest.stopts > config_timerange.stopts: if timerange_backtest.stopts > config_timerange.stopts:
timerange_backtest.stopts = config_timerange.stopts timerange_backtest.stopts = config_timerange.stopts
start = datetime.fromtimestamp(timerange_backtest.startts, tz=timezone.utc) tr_backtesting_list.append(timerange_backtest.timerange_str)
stop = datetime.fromtimestamp(timerange_backtest.stopts, tz=timezone.utc)
tr_backtesting_list.append(start.strftime("%Y%m%d") + "-" + stop.strftime("%Y%m%d"))
tr_backtesting_list_timerange.append(copy.deepcopy(timerange_backtest)) tr_backtesting_list_timerange.append(copy.deepcopy(timerange_backtest))
# ensure we are predicting on exactly same amount of data as requested by user defined # ensure we are predicting on exactly same amount of data as requested by user defined
@ -491,11 +487,9 @@ class FreqaiDataKitchen:
it is sliced down to just the present training period. it is sliced down to just the present training period.
""" """
start = datetime.fromtimestamp(timerange.startts, tz=timezone.utc) df = df.loc[df["date"] >= timerange.startdt, :]
stop = datetime.fromtimestamp(timerange.stopts, tz=timezone.utc)
df = df.loc[df["date"] >= start, :]
if not self.live: if not self.live:
df = df.loc[df["date"] < stop, :] df = df.loc[df["date"] < timerange.stopdt, :]
return df return df
@ -1058,9 +1052,7 @@ class FreqaiDataKitchen:
backtest_timerange.startts = ( backtest_timerange.startts = (
backtest_timerange.startts - backtest_period_days * SECONDS_IN_DAY backtest_timerange.startts - backtest_period_days * SECONDS_IN_DAY
) )
start = datetime.fromtimestamp(backtest_timerange.startts, tz=timezone.utc) full_timerange = backtest_timerange.timerange_str
stop = datetime.fromtimestamp(backtest_timerange.stopts, tz=timezone.utc)
full_timerange = start.strftime("%Y%m%d") + "-" + stop.strftime("%Y%m%d")
config_path = Path(self.config["config_files"][0]) config_path = Path(self.config["config_files"][0])
if not self.full_path.is_dir(): if not self.full_path.is_dir():

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@ -13,7 +13,7 @@ from numpy.typing import NDArray
from pandas import DataFrame from pandas import DataFrame
from freqtrade.configuration import TimeRange from freqtrade.configuration import TimeRange
from freqtrade.constants import DATETIME_PRINT_FORMAT, Config from freqtrade.constants import Config
from freqtrade.enums import RunMode from freqtrade.enums import RunMode
from freqtrade.exceptions import OperationalException from freqtrade.exceptions import OperationalException
from freqtrade.exchange import timeframe_to_seconds from freqtrade.exchange import timeframe_to_seconds
@ -788,14 +788,8 @@ class IFreqaiModel(ABC):
:return: if the data exists or not :return: if the data exists or not
""" """
if self.config.get("freqai_backtest_live_models", False) and len(dataframe_backtest) == 0: if self.config.get("freqai_backtest_live_models", False) and len(dataframe_backtest) == 0:
tr_backtest_startts_str = datetime.fromtimestamp( logger.info(f"No data found for pair {pair} from "
tr_backtest.startts, f"from { tr_backtest.start_fmt} to {tr_backtest.stop_fmt}. "
tz=timezone.utc).strftime(DATETIME_PRINT_FORMAT)
tr_backtest_stopts_str = datetime.fromtimestamp(
tr_backtest.stopts,
tz=timezone.utc).strftime(DATETIME_PRINT_FORMAT)
logger.info(f"No data found for pair {pair} from {tr_backtest_startts_str} "
f" from {tr_backtest_startts_str} to {tr_backtest_stopts_str}. "
"Probably more than one training within the same candle period.") "Probably more than one training within the same candle period.")
return False return False
return True return True
@ -810,18 +804,11 @@ class IFreqaiModel(ABC):
:param pair: the current pair :param pair: the current pair
:param total_trains: total trains (total number of slides for the sliding window) :param total_trains: total trains (total number of slides for the sliding window)
""" """
tr_train_startts_str = datetime.fromtimestamp(
tr_train.startts,
tz=timezone.utc).strftime(DATETIME_PRINT_FORMAT)
tr_train_stopts_str = datetime.fromtimestamp(
tr_train.stopts,
tz=timezone.utc).strftime(DATETIME_PRINT_FORMAT)
if not self.config.get("freqai_backtest_live_models", False): if not self.config.get("freqai_backtest_live_models", False):
logger.info( logger.info(
f"Training {pair}, {self.pair_it}/{self.total_pairs} pairs" f"Training {pair}, {self.pair_it}/{self.total_pairs} pairs"
f" from {tr_train_startts_str} " f" from {tr_train.start_fmt} "
f"to {tr_train_stopts_str}, {train_it}/{total_trains} " f"to {tr_train.stop_fmt}, {train_it}/{total_trains} "
"trains" "trains"
) )
# Following methods which are overridden by user made prediction models. # Following methods which are overridden by user made prediction models.

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@ -230,7 +230,4 @@ def get_timerange_backtest_live_models(config: Config) -> str:
dk = FreqaiDataKitchen(config) dk = FreqaiDataKitchen(config)
models_path = dk.get_full_models_path(config) models_path = dk.get_full_models_path(config)
timerange, _ = dk.get_timerange_and_assets_end_dates_from_ready_models(models_path) timerange, _ = dk.get_timerange_and_assets_end_dates_from_ready_models(models_path)
start_date = datetime.fromtimestamp(timerange.startts, tz=timezone.utc) return timerange.timerange_str
end_date = datetime.fromtimestamp(timerange.stopts, tz=timezone.utc)
tr = f"{start_date.strftime('%Y%m%d')}-{end_date.strftime('%Y%m%d')}"
return tr

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@ -1286,8 +1286,7 @@ class Backtesting:
def _get_min_cached_backtest_date(self): def _get_min_cached_backtest_date(self):
min_backtest_date = None min_backtest_date = None
backtest_cache_age = self.config.get('backtest_cache', constants.BACKTEST_CACHE_DEFAULT) backtest_cache_age = self.config.get('backtest_cache', constants.BACKTEST_CACHE_DEFAULT)
if self.timerange.stopts == 0 or datetime.fromtimestamp( if self.timerange.stopts == 0 or self.timerange.stopdt > datetime.now(tz=timezone.utc):
self.timerange.stopts, tz=timezone.utc) > datetime.now(tz=timezone.utc):
logger.warning('Backtest result caching disabled due to use of open-ended timerange.') logger.warning('Backtest result caching disabled due to use of open-ended timerange.')
elif backtest_cache_age == 'day': elif backtest_cache_age == 'day':
min_backtest_date = datetime.now(tz=timezone.utc) - timedelta(days=1) min_backtest_date = datetime.now(tz=timezone.utc) - timedelta(days=1)

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@ -1062,7 +1062,7 @@ class Telegram(RPCHandler):
self._rpc._rpc_force_entry(pair, price, order_side=order_side) self._rpc._rpc_force_entry(pair, price, order_side=order_side)
except RPCException as e: except RPCException as e:
logger.exception("Forcebuy error!") logger.exception("Forcebuy error!")
self._send_msg(str(e)) self._send_msg(str(e), ParseMode.HTML)
def _force_enter_inline(self, update: Update, _: CallbackContext) -> None: def _force_enter_inline(self, update: Update, _: CallbackContext) -> None:
if update.callback_query: if update.callback_query:

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@ -1,4 +1,6 @@
# pragma pylint: disable=missing-docstring, C0103 # pragma pylint: disable=missing-docstring, C0103
from datetime import datetime, timezone
import arrow import arrow
import pytest import pytest
@ -8,16 +10,28 @@ from freqtrade.exceptions import OperationalException
def test_parse_timerange_incorrect(): def test_parse_timerange_incorrect():
assert TimeRange('date', None, 1274486400, 0) == TimeRange.parse_timerange('20100522-') timerange = TimeRange.parse_timerange('20100522-')
assert TimeRange(None, 'date', 0, 1274486400) == TimeRange.parse_timerange('-20100522') assert TimeRange('date', None, 1274486400, 0) == timerange
assert timerange.timerange_str == '20100522-'
timerange = TimeRange.parse_timerange('-20100522')
assert TimeRange(None, 'date', 0, 1274486400) == timerange
assert timerange.timerange_str == '-20100522'
timerange = TimeRange.parse_timerange('20100522-20150730') timerange = TimeRange.parse_timerange('20100522-20150730')
assert timerange == TimeRange('date', 'date', 1274486400, 1438214400) assert timerange == TimeRange('date', 'date', 1274486400, 1438214400)
assert timerange.timerange_str == '20100522-20150730'
assert timerange.start_fmt == '2010-05-22 00:00:00'
assert timerange.stop_fmt == '2015-07-30 00:00:00'
# Added test for unix timestamp - BTC genesis date # Added test for unix timestamp - BTC genesis date
assert TimeRange('date', None, 1231006505, 0) == TimeRange.parse_timerange('1231006505-') assert TimeRange('date', None, 1231006505, 0) == TimeRange.parse_timerange('1231006505-')
assert TimeRange(None, 'date', 0, 1233360000) == TimeRange.parse_timerange('-1233360000') assert TimeRange(None, 'date', 0, 1233360000) == TimeRange.parse_timerange('-1233360000')
timerange = TimeRange.parse_timerange('1231006505-1233360000') timerange = TimeRange.parse_timerange('1231006505-1233360000')
assert TimeRange('date', 'date', 1231006505, 1233360000) == timerange assert TimeRange('date', 'date', 1231006505, 1233360000) == timerange
assert isinstance(timerange.startdt, datetime)
assert isinstance(timerange.stopdt, datetime)
assert timerange.startdt == datetime.fromtimestamp(1231006505, tz=timezone.utc)
assert timerange.stopdt == datetime.fromtimestamp(1233360000, tz=timezone.utc)
assert timerange.timerange_str == '20090103-20090131'
timerange = TimeRange.parse_timerange('1231006505000-1233360000000') timerange = TimeRange.parse_timerange('1231006505000-1233360000000')
assert TimeRange('date', 'date', 1231006505, 1233360000) == timerange assert TimeRange('date', 'date', 1231006505, 1233360000) == timerange
@ -45,6 +59,7 @@ def test_subtract_start():
x = TimeRange(None, 'date', 0, 1438214400) x = TimeRange(None, 'date', 0, 1438214400)
x.subtract_start(300) x.subtract_start(300)
assert not x.startts assert not x.startts
assert not x.startdt
x = TimeRange('date', None, 1274486400, 0) x = TimeRange('date', None, 1274486400, 0)
x.subtract_start(300) x.subtract_start(300)