Merge pull request #2494 from freqtrade/fix/timezone_timestamp
Fix UTC handling of timestamp() conversation in fetch_my_trades
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commit
60acbc97ab
@ -7,7 +7,7 @@ from typing import Dict
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import numpy as np
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import numpy as np
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import pandas as pd
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import pandas as pd
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import pytz
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from datetime import timezone
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from freqtrade import persistence
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from freqtrade import persistence
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from freqtrade.misc import json_load
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from freqtrade.misc import json_load
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@ -106,8 +106,8 @@ def load_trades_from_db(db_url: str) -> pd.DataFrame:
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"stop_loss", "initial_stop_loss", "strategy", "ticker_interval"]
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"stop_loss", "initial_stop_loss", "strategy", "ticker_interval"]
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trades = pd.DataFrame([(t.pair,
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trades = pd.DataFrame([(t.pair,
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t.open_date.replace(tzinfo=pytz.UTC),
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t.open_date.replace(tzinfo=timezone.utc),
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t.close_date.replace(tzinfo=pytz.UTC) if t.close_date else None,
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t.close_date.replace(tzinfo=timezone.utc) if t.close_date else None,
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t.calc_profit(), t.calc_profit_percent(),
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t.calc_profit(), t.calc_profit_percent(),
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t.open_rate, t.close_rate, t.amount,
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t.open_rate, t.close_rate, t.amount,
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(round((t.close_date.timestamp() - t.open_date.timestamp()) / 60, 2)
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(round((t.close_date.timestamp() - t.open_date.timestamp()) / 60, 2)
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@ -9,12 +9,11 @@ Includes:
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import logging
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import logging
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import operator
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import operator
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from copy import deepcopy
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from copy import deepcopy
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from datetime import datetime
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from datetime import datetime, timezone
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from pathlib import Path
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from pathlib import Path
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from typing import Any, Dict, List, Optional, Tuple
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from typing import Any, Dict, List, Optional, Tuple
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import arrow
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import arrow
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import pytz
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from pandas import DataFrame
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from pandas import DataFrame
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from freqtrade import OperationalException, misc
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from freqtrade import OperationalException, misc
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@ -56,10 +55,10 @@ def trim_dataframe(df: DataFrame, timerange: TimeRange) -> DataFrame:
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Trim dataframe based on given timerange
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Trim dataframe based on given timerange
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"""
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"""
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if timerange.starttype == 'date':
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if timerange.starttype == 'date':
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start = datetime.fromtimestamp(timerange.startts, tz=pytz.utc)
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start = datetime.fromtimestamp(timerange.startts, tz=timezone.utc)
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df = df.loc[df['date'] >= start, :]
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df = df.loc[df['date'] >= start, :]
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if timerange.stoptype == 'date':
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if timerange.stoptype == 'date':
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stop = datetime.fromtimestamp(timerange.stopts, tz=pytz.utc)
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stop = datetime.fromtimestamp(timerange.stopts, tz=timezone.utc)
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df = df.loc[df['date'] <= stop, :]
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df = df.loc[df['date'] <= stop, :]
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return df
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return df
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@ -875,6 +875,22 @@ class Exchange:
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@retrier
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@retrier
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def get_trades_for_order(self, order_id: str, pair: str, since: datetime) -> List:
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def get_trades_for_order(self, order_id: str, pair: str, since: datetime) -> List:
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"""
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Fetch Orders using the "fetch_my_trades" endpoint and filter them by order-id.
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The "since" argument passed in is coming from the database and is in UTC,
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as timezone-native datetime object.
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From the python documentation:
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> Naive datetime instances are assumed to represent local time
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Therefore, calling "since.timestamp()" will get the UTC timestamp, after applying the
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transformation from local timezone to UTC.
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This works for timezones UTC+ since then the result will contain trades from a few hours
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instead of from the last 5 seconds, however fails for UTC- timezones,
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since we're then asking for trades with a "since" argument in the future.
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:param order_id order_id: Order-id as given when creating the order
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:param pair: Pair the order is for
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:param since: datetime object of the order creation time. Assumes object is in UTC.
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"""
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if self._config['dry_run']:
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if self._config['dry_run']:
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return []
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return []
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if not self.exchange_has('fetchMyTrades'):
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if not self.exchange_has('fetchMyTrades'):
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@ -882,7 +898,8 @@ class Exchange:
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try:
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try:
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# Allow 5s offset to catch slight time offsets (discovered in #1185)
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# Allow 5s offset to catch slight time offsets (discovered in #1185)
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# since needs to be int in milliseconds
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# since needs to be int in milliseconds
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my_trades = self._api.fetch_my_trades(pair, int((since.timestamp() - 5) * 1000))
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my_trades = self._api.fetch_my_trades(
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pair, int((since.replace(tzinfo=timezone.utc).timestamp() - 5) * 1000))
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matched_trades = [trade for trade in my_trades if trade['order'] == order_id]
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matched_trades = [trade for trade in my_trades if trade['order'] == order_id]
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return matched_trades
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return matched_trades
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@ -1586,8 +1586,9 @@ def test_name(default_conf, mocker, exchange_name):
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@pytest.mark.parametrize("exchange_name", EXCHANGES)
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@pytest.mark.parametrize("exchange_name", EXCHANGES)
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def test_get_trades_for_order(default_conf, mocker, exchange_name):
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def test_get_trades_for_order(default_conf, mocker, exchange_name):
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order_id = 'ABCD-ABCD'
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order_id = 'ABCD-ABCD'
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since = datetime(2018, 5, 5, tzinfo=timezone.utc)
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since = datetime(2018, 5, 5, 0, 0, 0)
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default_conf["dry_run"] = False
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default_conf["dry_run"] = False
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mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
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mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
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api_mock = MagicMock()
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api_mock = MagicMock()
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@ -1623,7 +1624,8 @@ def test_get_trades_for_order(default_conf, mocker, exchange_name):
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assert api_mock.fetch_my_trades.call_args[0][0] == 'LTC/BTC'
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assert api_mock.fetch_my_trades.call_args[0][0] == 'LTC/BTC'
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# Same test twice, hardcoded number and doing the same calculation
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# Same test twice, hardcoded number and doing the same calculation
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assert api_mock.fetch_my_trades.call_args[0][1] == 1525478395000
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assert api_mock.fetch_my_trades.call_args[0][1] == 1525478395000
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assert api_mock.fetch_my_trades.call_args[0][1] == int(since.timestamp() - 5) * 1000
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assert api_mock.fetch_my_trades.call_args[0][1] == int(since.replace(
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tzinfo=timezone.utc).timestamp() - 5) * 1000
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ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
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ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
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'get_trades_for_order', 'fetch_my_trades',
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'get_trades_for_order', 'fetch_my_trades',
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