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Merge pull request #4284 from freqtrade/windows_ci_error
Version bump numpy 1.20.0
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commit
f288ed1f36
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@ -2,7 +2,7 @@
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# Downloaded from https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib
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# Invoke-WebRequest -Uri "https://download.lfd.uci.edu/pythonlibs/xxxxxxx/TA_Lib-0.4.17-cp37-cp37m-win_amd64.whl" -OutFile "TA_Lib-0.4.17-cp37-cp37m-win_amd64.whl"
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python -m pip install --upgrade pip==21.0.0
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python -m pip install --upgrade pip
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$pyv = python -c "import sys; print(f'{sys.version_info.major}.{sys.version_info.minor}')"
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@ -312,7 +312,7 @@ def calculate_market_change(data: Dict[str, pd.DataFrame], column: str = "close"
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end = df[column].dropna().iloc[-1]
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tmp_means.append((end - start) / start)
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return np.mean(tmp_means)
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return float(np.mean(tmp_means))
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def combine_dataframes_with_mean(data: Dict[str, pd.DataFrame],
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@ -9,7 +9,6 @@ from pathlib import Path
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from typing import Any
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from typing.io import IO
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import numpy as np
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import rapidjson
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@ -28,20 +27,6 @@ def shorten_date(_date: str) -> str:
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return new_date
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############################################
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# Used by scripts #
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# Matplotlib doesn't support ::datetime64, #
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# so we need to convert it into ::datetime #
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############################################
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def datesarray_to_datetimearray(dates: np.ndarray) -> np.ndarray:
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"""
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Convert an pandas-array of timestamps into
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An numpy-array of datetimes
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:return: numpy-array of datetime
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"""
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return dates.dt.to_pydatetime()
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def file_dump_json(filename: Path, data: Any, is_zip: bool = False, log: bool = True) -> None:
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"""
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Dump JSON data into a file
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@ -378,7 +378,7 @@ class RPC:
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# Prepare data to display
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profit_closed_coin_sum = round(sum(profit_closed_coin), 8)
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profit_closed_ratio_mean = mean(profit_closed_ratio) if profit_closed_ratio else 0.0
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profit_closed_ratio_mean = float(mean(profit_closed_ratio) if profit_closed_ratio else 0.0)
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profit_closed_ratio_sum = sum(profit_closed_ratio) if profit_closed_ratio else 0.0
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profit_closed_fiat = self._fiat_converter.convert_amount(
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@ -388,7 +388,7 @@ class RPC:
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) if self._fiat_converter else 0
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profit_all_coin_sum = round(sum(profit_all_coin), 8)
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profit_all_ratio_mean = mean(profit_all_ratio) if profit_all_ratio else 0.0
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profit_all_ratio_mean = float(mean(profit_all_ratio) if profit_all_ratio else 0.0)
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profit_all_ratio_sum = sum(profit_all_ratio) if profit_all_ratio else 0.0
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profit_all_fiat = self._fiat_converter.convert_amount(
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profit_all_coin_sum,
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@ -1,4 +1,4 @@
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numpy==1.19.5
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numpy==1.20.0
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pandas==1.2.1
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ccxt==1.40.99
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@ -6,11 +6,9 @@ from unittest.mock import MagicMock
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import pytest
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from freqtrade.data.converter import ohlcv_to_dataframe
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from freqtrade.misc import (datesarray_to_datetimearray, file_dump_json, file_load_json,
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format_ms_time, pair_to_filename, plural, render_template,
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render_template_with_fallback, safe_value_fallback,
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safe_value_fallback2, shorten_date)
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from freqtrade.misc import (file_dump_json, file_load_json, format_ms_time, pair_to_filename,
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plural, render_template, render_template_with_fallback,
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safe_value_fallback, safe_value_fallback2, shorten_date)
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def test_shorten_date() -> None:
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@ -19,22 +17,6 @@ def test_shorten_date() -> None:
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assert shorten_date(str_data) == str_shorten_data
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def test_datesarray_to_datetimearray(ohlcv_history_list):
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dataframes = ohlcv_to_dataframe(ohlcv_history_list, "5m", pair="UNITTEST/BTC",
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fill_missing=True)
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dates = datesarray_to_datetimearray(dataframes['date'])
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assert isinstance(dates[0], datetime.datetime)
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assert dates[0].year == 2017
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assert dates[0].month == 11
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assert dates[0].day == 26
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assert dates[0].hour == 8
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assert dates[0].minute == 50
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date_len = len(dates)
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assert date_len == 2
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def test_file_dump_json(mocker) -> None:
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file_open = mocker.patch('freqtrade.misc.open', MagicMock())
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json_dump = mocker.patch('rapidjson.dump', MagicMock())
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