Refactor generic data generation to conftest
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@ -10,6 +10,7 @@ from unittest.mock import MagicMock, Mock, PropertyMock
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import arrow
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import numpy as np
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import pandas as pd
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import pytest
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from telegram import Chat, Message, Update
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@ -19,6 +20,7 @@ from freqtrade.data.converter import ohlcv_to_dataframe
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from freqtrade.edge import PairInfo
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from freqtrade.enums import CandleType, MarginMode, RunMode, SignalDirection, TradingMode
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from freqtrade.exchange import Exchange
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from freqtrade.exchange.exchange import timeframe_to_minutes
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from freqtrade.freqtradebot import FreqtradeBot
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from freqtrade.persistence import LocalTrade, Order, Trade, init_db
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from freqtrade.resolvers import ExchangeResolver
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@ -82,6 +84,26 @@ def get_args(args):
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return Arguments(args).get_parsed_arg()
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def generate_test_data(timeframe: str, size: int, start: str = '2020-07-05'):
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np.random.seed(42)
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tf_mins = timeframe_to_minutes(timeframe)
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base = np.random.normal(20, 2, size=size)
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date = pd.date_range(start, periods=size, freq=f'{tf_mins}min', tz='UTC')
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df = pd.DataFrame({
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'date': date,
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'open': base,
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'high': base + np.random.normal(2, 1, size=size),
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'low': base - np.random.normal(2, 1, size=size),
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'close': base + np.random.normal(0, 1, size=size),
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'volume': np.random.normal(200, size=size)
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}
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)
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df = df.dropna()
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return df
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# Source: https://stackoverflow.com/questions/29881236/how-to-mock-asyncio-coroutines
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# TODO: This should be replaced with AsyncMock once support for python 3.7 is dropped.
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def get_mock_coro(return_value=None, side_effect=None):
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@ -5,29 +5,8 @@ import pytest
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from freqtrade.data.dataprovider import DataProvider
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from freqtrade.enums import CandleType
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from freqtrade.resolvers.strategy_resolver import StrategyResolver
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from freqtrade.strategy import (merge_informative_pair, stoploss_from_absolute, stoploss_from_open,
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timeframe_to_minutes)
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from tests.conftest import get_patched_exchange
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def generate_test_data(timeframe: str, size: int, start: str = '2020-07-05'):
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np.random.seed(42)
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tf_mins = timeframe_to_minutes(timeframe)
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base = np.random.normal(20, 2, size=size)
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date = pd.date_range(start, periods=size, freq=f'{tf_mins}min', tz='UTC')
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df = pd.DataFrame({
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'date': date,
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'open': base,
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'high': base + np.random.normal(2, 1, size=size),
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'low': base - np.random.normal(2, 1, size=size),
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'close': base + np.random.normal(0, 1, size=size),
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'volume': np.random.normal(200, size=size)
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}
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)
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df = df.dropna()
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return df
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from freqtrade.strategy import merge_informative_pair, stoploss_from_absolute, stoploss_from_open
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from tests.conftest import generate_test_data, get_patched_exchange
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def test_merge_informative_pair():
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