Merge pull request #4284 from freqtrade/windows_ci_error

Version bump numpy 1.20.0
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Matthias 2021-01-31 13:59:36 +01:00 committed by GitHub
commit f288ed1f36
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6 changed files with 8 additions and 41 deletions

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@ -2,7 +2,7 @@
# Downloaded from https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib
# 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"
python -m pip install --upgrade pip==21.0.0
python -m pip install --upgrade pip
$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"
end = df[column].dropna().iloc[-1]
tmp_means.append((end - start) / start)
return np.mean(tmp_means)
return float(np.mean(tmp_means))
def combine_dataframes_with_mean(data: Dict[str, pd.DataFrame],

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@ -9,7 +9,6 @@ from pathlib import Path
from typing import Any
from typing.io import IO
import numpy as np
import rapidjson
@ -28,20 +27,6 @@ def shorten_date(_date: str) -> str:
return new_date
############################################
# Used by scripts #
# Matplotlib doesn't support ::datetime64, #
# so we need to convert it into ::datetime #
############################################
def datesarray_to_datetimearray(dates: np.ndarray) -> np.ndarray:
"""
Convert an pandas-array of timestamps into
An numpy-array of datetimes
:return: numpy-array of datetime
"""
return dates.dt.to_pydatetime()
def file_dump_json(filename: Path, data: Any, is_zip: bool = False, log: bool = True) -> None:
"""
Dump JSON data into a file

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@ -378,7 +378,7 @@ class RPC:
# Prepare data to display
profit_closed_coin_sum = round(sum(profit_closed_coin), 8)
profit_closed_ratio_mean = mean(profit_closed_ratio) if profit_closed_ratio else 0.0
profit_closed_ratio_mean = float(mean(profit_closed_ratio) if profit_closed_ratio else 0.0)
profit_closed_ratio_sum = sum(profit_closed_ratio) if profit_closed_ratio else 0.0
profit_closed_fiat = self._fiat_converter.convert_amount(
@ -388,7 +388,7 @@ class RPC:
) if self._fiat_converter else 0
profit_all_coin_sum = round(sum(profit_all_coin), 8)
profit_all_ratio_mean = mean(profit_all_ratio) if profit_all_ratio else 0.0
profit_all_ratio_mean = float(mean(profit_all_ratio) if profit_all_ratio else 0.0)
profit_all_ratio_sum = sum(profit_all_ratio) if profit_all_ratio else 0.0
profit_all_fiat = self._fiat_converter.convert_amount(
profit_all_coin_sum,

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@ -1,4 +1,4 @@
numpy==1.19.5
numpy==1.20.0
pandas==1.2.1
ccxt==1.40.99

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@ -6,11 +6,9 @@ from unittest.mock import MagicMock
import pytest
from freqtrade.data.converter import ohlcv_to_dataframe
from freqtrade.misc import (datesarray_to_datetimearray, file_dump_json, file_load_json,
format_ms_time, pair_to_filename, plural, render_template,
render_template_with_fallback, safe_value_fallback,
safe_value_fallback2, shorten_date)
from freqtrade.misc import (file_dump_json, file_load_json, format_ms_time, pair_to_filename,
plural, render_template, render_template_with_fallback,
safe_value_fallback, safe_value_fallback2, shorten_date)
def test_shorten_date() -> None:
@ -19,22 +17,6 @@ def test_shorten_date() -> None:
assert shorten_date(str_data) == str_shorten_data
def test_datesarray_to_datetimearray(ohlcv_history_list):
dataframes = ohlcv_to_dataframe(ohlcv_history_list, "5m", pair="UNITTEST/BTC",
fill_missing=True)
dates = datesarray_to_datetimearray(dataframes['date'])
assert isinstance(dates[0], datetime.datetime)
assert dates[0].year == 2017
assert dates[0].month == 11
assert dates[0].day == 26
assert dates[0].hour == 8
assert dates[0].minute == 50
date_len = len(dates)
assert date_len == 2
def test_file_dump_json(mocker) -> None:
file_open = mocker.patch('freqtrade.misc.open', MagicMock())
json_dump = mocker.patch('rapidjson.dump', MagicMock())