Simplify functional tests
This commit is contained in:
Matthias
parent
98050ff594
commit
6096f3ca47
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@ -1,11 +1,11 @@
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# pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, unused-argument
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import logging
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from unittest.mock import MagicMock
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from typing import NamedTuple
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from typing import NamedTuple, List
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from pandas import DataFrame
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import pytest
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from arrow import get as getdate
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import arrow
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from freqtrade.optimize.backtesting import Backtesting
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@ -13,11 +13,15 @@ from freqtrade.strategy.interface import SellType
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from freqtrade.tests.conftest import patch_exchange, log_has
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ticker_start_time = arrow.get(2018, 10, 3)
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ticker_interval_in_minute = 60
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class BTContainer(NamedTuple):
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"""
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NamedTuple Defining BacktestResults inputs.
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"""
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data: DataFrame
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data: List[float]
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stop_loss: float
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roi: float
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trades: int
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@ -25,19 +29,24 @@ class BTContainer(NamedTuple):
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sell_r: SellType
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columns = ['date', 'open', 'high', 'low', 'close', 'volume', 'buy', 'sell']
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data_profit = DataFrame([
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[getdate('2018-07-08 18:00:00').datetime, 0.0009910,
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0.001011, 0.00098618, 0.001000, 12345, 1, 0],
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[getdate('2018-07-08 19:00:00').datetime, 0.001000,
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0.001010, 0.0009900, 0.0009900, 12345, 0, 0],
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[getdate('2018-07-08 20:00:00').datetime, 0.0009900,
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0.001011, 0.00091618, 0.0009900, 12345, 0, 0],
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[getdate('2018-07-08 21:00:00').datetime, 0.001000,
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0.001011, 0.00098618, 0.001100, 12345, 0, 1],
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[getdate('2018-07-08 22:00:00').datetime, 0.001000,
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0.001011, 0.00098618, 0.0009900, 12345, 0, 0]
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], columns=columns)
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def _build_dataframe(ticker_with_signals):
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columns = ['date', 'open', 'high', 'low', 'close', 'volume', 'buy', 'sell']
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frame = DataFrame.from_records(ticker_with_signals, columns=columns)
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frame['date'] = frame['date'].apply(lambda x: ticker_start_time.shift(
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minutes=(x * ticker_interval_in_minute)).datetime)
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# Ensure floats are in place
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for column in ['open', 'high', 'low', 'close', 'volume']:
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frame[column] = frame[column].astype('float64')
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return frame
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data_profit = [
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[0, 0.0009910, 0.001011, 0.00098618, 0.001000, 12345, 1, 0],
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[1, 0.001000, 0.001010, 0.0009900, 0.0009900, 12345, 0, 0],
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[2, 0.0009900, 0.001011, 0.00091618, 0.0009900, 12345, 0, 0],
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[3, 0.001000, 0.001011, 0.00098618, 0.001100, 12345, 0, 1],
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[4, 0.001000, 0.001011, 0.00098618, 0.0009900, 12345, 0, 0]]
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tc_profit1 = BTContainer(data=data_profit, stop_loss=-0.01, roi=1, trades=1,
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profit_perc=0.10557, sell_r=SellType.STOP_LOSS) # should be stoploss - drops 8%
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@ -45,18 +54,12 @@ tc_profit2 = BTContainer(data=data_profit, stop_loss=-0.10, roi=1,
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trades=1, profit_perc=0.10557, sell_r=SellType.STOP_LOSS)
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tc_loss0 = BTContainer(data=DataFrame([
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[getdate('2018-07-08 18:00:00').datetime, 0.0009910,
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0.001011, 0.00098618, 0.001000, 12345, 1, 0],
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[getdate('2018-07-08 19:00:00').datetime, 0.001000,
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0.001010, 0.0009900, 0.001000, 12345, 0, 0],
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[getdate('2018-07-08 20:00:00').datetime, 0.001000,
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0.001011, 0.0010618, 0.00091618, 12345, 0, 0],
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[getdate('2018-07-08 21:00:00').datetime, 0.001000,
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0.001011, 0.00098618, 0.00091618, 12345, 0, 0],
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[getdate('2018-07-08 22:00:00').datetime, 0.001000,
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0.001011, 0.00098618, 0.00091618, 12345, 0, 0]
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], columns=columns),
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tc_loss0 = BTContainer(data=[
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[0, 0.0009910, 0.001011, 0.00098618, 0.001000, 12345, 1, 0],
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[1, 0.001000, 0.001010, 0.0009900, 0.001000, 12345, 0, 0],
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[2, 0.001000, 0.001011, 0.0010618, 0.00091618, 12345, 0, 0],
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[3, 0.001000, 0.001011, 0.00098618, 0.00091618, 12345, 0, 0],
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[4, 0.001000, 0.001011, 0.00098618, 0.00091618, 12345, 0, 0]],
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stop_loss=-0.05, roi=1, trades=1, profit_perc=-0.08839, sell_r=SellType.STOP_LOSS)
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@ -64,30 +67,27 @@ tc_loss0 = BTContainer(data=DataFrame([
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# Candle Data for test 1 – close at -8% (9200)
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# Test with Stop-loss at 1%
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# TC1: Stop-Loss Triggered 1% loss
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tc1 = BTContainer(data=DataFrame([
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[getdate('2018-06-10 07:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 1, 0],
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[getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 0, 0],
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[getdate('2018-06-10 09:00:00').datetime, 9975, 10025, 9200, 9200, 12345, 0, 0],
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[getdate('2018-06-10 10:00:00').datetime, 9950, 10000, 9960, 9955, 12345, 0, 0],
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[getdate('2018-06-10 11:00:00').datetime, 9955, 9975, 9955, 9990, 12345, 0, 0],
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[getdate('2018-06-10 12:00:00').datetime, 9990, 9990, 9990, 9900, 12345, 0, 0]
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], columns=columns),
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stop_loss=-0.01, roi=1, trades=1, profit_perc=-0.01, sell_r=SellType.STOP_LOSS) # should be
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# stop_loss=-0.01, roi=1, trades=1, profit_perc=-0.003, sell_r=SellType.FORCE_SELL) #
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tc1 = BTContainer(data=[
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[0, 10000.0, 10050, 9950, 9975, 12345, 1, 0],
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[1, 10000, 10050, 9950, 9975, 12345, 0, 0],
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[2, 9975, 10025, 9200, 9200, 12345, 0, 0],
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[3, 9950, 10000, 9960, 9955, 12345, 0, 0],
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[4, 9955, 9975, 9955, 9990, 12345, 0, 0],
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[5, 9990, 9990, 9990, 9900, 12345, 0, 0]],
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stop_loss=-0.01, roi=1, trades=1, profit_perc=-0.01, sell_r=SellType.STOP_LOSS)
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# Test 2 Minus 4% Low, minus 1% close
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# Candle Data for test 2
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# Test with Stop-Loss at 3%
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# TC2: Stop-Loss Triggered 3% Loss
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tc2 = BTContainer(data=DataFrame([
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[getdate('2018-06-10 07:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 1, 0],
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[getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 0, 0],
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[getdate('2018-06-10 09:00:00').datetime, 9975, 10025, 9925, 9950, 12345, 0, 0],
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[getdate('2018-06-10 10:00:00').datetime, 9950, 10000, 9600, 9925, 12345, 0, 0],
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[getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9875, 9900, 12345, 0, 0],
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[getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0]
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], columns=columns),
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tc2 = BTContainer(data=[
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[0, 10000, 10050, 9950, 9975, 12345, 1, 0],
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[1, 10000, 10050, 9950, 9975, 12345, 0, 0],
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[2, 9975, 10025, 9925, 9950, 12345, 0, 0],
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[3, 9950, 10000, 9600, 9925, 12345, 0, 0],
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[4, 9925, 9975, 9875, 9900, 12345, 0, 0],
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[5, 9900, 9950, 9850, 9900, 12345, 0, 0]],
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stop_loss=-0.03, roi=1, trades=1, profit_perc=-0.03, sell_r=SellType.STOP_LOSS) #should be
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# stop_loss=-0.03, roi=1, trades=1, profit_perc=-0.007, sell_r=SellType.FORCE_SELL) #
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@ -99,15 +99,14 @@ tc2 = BTContainer(data=DataFrame([
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# Test with Stop-Loss at 2%
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# TC3: Trade-A: Stop-Loss Triggered 2% Loss
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# Trade-B: Stop-Loss Triggered 2% Loss
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tc3 = BTContainer(data=DataFrame([
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[getdate('2018-06-10 07:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 1, 0],
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[getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 0, 0],
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[getdate('2018-06-10 09:00:00').datetime, 9975, 10025, 9600, 9950, 12345, 0, 0],
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[getdate('2018-06-10 10:00:00').datetime, 9950, 10000, 9900, 9925, 12345, 1, 0],
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[getdate('2018-06-10 11:00:00').datetime, 9950, 10000, 9900, 9925, 12345, 0, 0],
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[getdate('2018-06-10 12:00:00').datetime, 9925, 9975, 8000, 8000, 12345, 0, 0],
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[getdate('2018-06-10 13:00:00').datetime, 9900, 9950, 9950, 9900, 12345, 0, 0]
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], columns=columns),
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tc3 = BTContainer(data=[
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[0, 10000, 10050, 9950, 9975, 12345, 1, 0],
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[1, 10000, 10050, 9950, 9975, 12345, 0, 0],
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[2, 9975, 10025, 9600, 9950, 12345, 0, 0],
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[3, 9950, 10000, 9900, 9925, 12345, 1, 0],
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[4, 9950, 10000, 9900, 9925, 12345, 0, 0],
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[5, 9925, 9975, 8000, 8000, 12345, 0, 0],
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[6, 9900, 9950, 9950, 9900, 12345, 0, 0]],
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stop_loss=-0.02, roi=1, trades=2, profit_perc=-0.04, sell_r=SellType.STOP_LOSS) #should be
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# stop_loss=-0.02, roi=1, trades=1, profit_perc=-0.02, sell_r=SellType.STOP_LOSS) #should be
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# stop_loss=-0.02, roi=1, trades=1, profit_perc=-0.012, sell_r=SellType.FORCE_SELL) #
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@ -117,14 +116,13 @@ tc3 = BTContainer(data=DataFrame([
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# Candle Data for test 4 – Candle drops 3% Closed 15% up
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# Test with Stop-loss at 2% ROI 6%
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# TC4: Stop-Loss Triggered 2% Loss
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tc4 = BTContainer(data=DataFrame([
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[getdate('2018-06-10 07:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 1, 0],
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[getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 0, 0],
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[getdate('2018-06-10 09:00:00').datetime, 9975, 11500, 9700, 11500, 12345, 0, 0],
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[getdate('2018-06-10 10:00:00').datetime, 9950, 10000, 9900, 9925, 12345, 0, 0],
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[getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9875, 9900, 12345, 0, 0],
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[getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0]
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], columns=columns),
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tc4 = BTContainer(data=[
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[0, 10000, 10050, 9950, 9975, 12345, 1, 0],
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[1, 10000, 10050, 9950, 9975, 12345, 0, 0],
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[2, 9975, 11500, 9700, 11500, 12345, 0, 0],
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[3, 9950, 10000, 9900, 9925, 12345, 0, 0],
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[4, 9925, 9975, 9875, 9900, 12345, 0, 0],
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[5, 9900, 9950, 9850, 9900, 12345, 0, 0]],
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stop_loss=-0.02, roi=0.06, trades=1, profit_perc=-0.02, sell_r=SellType.STOP_LOSS) #should be
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# stop_loss=-0.02, roi=0.06, trades=1, profit_perc=-0.012, sell_r=SellType.FORCE_SELL)
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@ -132,14 +130,13 @@ tc4 = BTContainer(data=DataFrame([
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# Candle Data for test 5
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# Set stop-loss at 1% ROI 3%
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# TC5: ROI triggers 3% Gain
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tc5 = BTContainer(data=DataFrame([
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[getdate('2018-06-10 07:00:00').datetime, 10000, 10050, 9960, 9975, 12345, 1, 0],
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[getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9960, 9975, 12345, 0, 0],
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[getdate('2018-06-10 09:00:00').datetime, 9975, 10050, 9950, 9975, 12345, 0, 0],
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[getdate('2018-06-10 10:00:00').datetime, 9950, 12000, 9950, 12000, 12345, 0, 0],
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[getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9945, 9900, 12345, 0, 0],
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[getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0]
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], columns=columns),
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tc5 = BTContainer(data=[
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[0, 10000, 10050, 9960, 9975, 12345, 1, 0],
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[1, 10000, 10050, 9960, 9975, 12345, 0, 0],
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[2, 9975, 10050, 9950, 9975, 12345, 0, 0],
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[3, 9950, 12000, 9950, 12000, 12345, 0, 0],
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[4, 9925, 9975, 9945, 9900, 12345, 0, 0],
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[5, 9900, 9950, 9850, 9900, 12345, 0, 0]],
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stop_loss=-0.01, roi=0.03, trades=1, profit_perc=0.03, sell_r=SellType.ROI) #should be
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# stop_loss=-0.01, roi=0.03, trades=1, profit_perc=-0.012, sell_r=SellType.FORCE_SELL)
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@ -147,14 +144,13 @@ tc5 = BTContainer(data=DataFrame([
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# Candle Data for test 6
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# Set stop-loss at 2% ROI at 5%
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# TC6: Stop-Loss triggers 2% Loss
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tc6 = BTContainer(data=DataFrame([
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[getdate('2018-06-10 07:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 1, 0],
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[getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 0, 0],
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[getdate('2018-06-10 09:00:00').datetime, 9975, 10600, 9700, 10100, 12345, 0, 0],
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[getdate('2018-06-10 10:00:00').datetime, 9950, 10000, 9900, 9925, 12345, 0, 0],
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[getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9945, 9900, 12345, 0, 0],
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[getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0]
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], columns=columns),
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tc6 = BTContainer(data=[
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[0, 10000, 10050, 9950, 9975, 12345, 1, 0],
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[1, 10000, 10050, 9950, 9975, 12345, 0, 0],
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[2, 9975, 10600, 9700, 10100, 12345, 0, 0],
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[3, 9950, 10000, 9900, 9925, 12345, 0, 0],
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[4, 9925, 9975, 9945, 9900, 12345, 0, 0],
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[5, 9900, 9950, 9850, 9900, 12345, 0, 0]],
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stop_loss=-0.02, roi=0.05, trades=1, profit_perc=-0.02, sell_r=SellType.STOP_LOSS) #should be
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# stop_loss=-0.02, roi=0.05, trades=1, profit_perc=-0.012, sell_r=SellType.FORCE_SELL) #
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@ -162,14 +158,13 @@ tc6 = BTContainer(data=DataFrame([
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# Candle Data for test 7
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# Set stop-loss at 2% ROI at 3%
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# TC7: ROI Triggers 3% Gain
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tc7 = BTContainer(data=DataFrame([
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[getdate('2018-06-10 07:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 1, 0],
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[getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 0, 0],
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[getdate('2018-06-10 09:00:00').datetime, 9975, 10600, 9900, 10100, 12345, 0, 0],
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[getdate('2018-06-10 10:00:00').datetime, 9950, 10000, 9900, 9925, 12345, 0, 0],
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[getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9945, 9900, 12345, 0, 0],
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[getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0]
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], columns=columns),
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tc7 = BTContainer(data=[
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[0, 10000, 10050, 9950, 9975, 12345, 1, 0],
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[1, 10000, 10050, 9950, 9975, 12345, 0, 0],
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[2, 9975, 10600, 9900, 10100, 12345, 0, 0],
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[3, 9950, 10000, 9900, 9925, 12345, 0, 0],
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[4, 9925, 9975, 9945, 9900, 12345, 0, 0],
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[5, 9900, 9950, 9850, 9900, 12345, 0, 0]],
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stop_loss=-0.02, roi=0.03, trades=1, profit_perc=0.03, sell_r=SellType.ROI) #should be
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# stop_loss=-0.02, roi=0.03, trades=1, profit_perc=-0.012, sell_r=SellType.FORCE_SELL) #
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@ -198,10 +193,10 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
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# TODO: don't Mock fee to for now
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mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.0))
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patch_exchange(mocker)
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frame = _build_dataframe(data.data)
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backtesting = Backtesting(default_conf)
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backtesting.advise_buy = lambda a, m: data.data
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backtesting.advise_sell = lambda a, m: data.data
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backtesting.advise_buy = lambda a, m: frame
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backtesting.advise_sell = lambda a, m: frame
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caplog.set_level(logging.DEBUG)
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pair = 'UNITTEST/BTC'
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