Merge commit '1134c81aad049d4357c8f299ffc801218f3d9574' into feature/objectify
This commit is contained in:
Gerald Lonlas
@@ -1,12 +1,14 @@
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# pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, unused-argument
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import json
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import random
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import math
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from typing import List
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from copy import deepcopy
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from unittest.mock import MagicMock
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from arrow import Arrow
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import pandas as pd
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import numpy as np
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from freqtrade import optimize
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from freqtrade.optimize.backtesting import Backtesting, start, setup_configuration
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from freqtrade.arguments import Arguments
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@@ -96,6 +98,70 @@ def mocked_load_data(datadir, pairs=[], ticker_interval=0, refresh_pairs=False,
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return pairdata
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# use for mock freqtrade.exchange.get_ticker_history'
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def _load_pair_as_ticks(pair, tickfreq):
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ticks = optimize.load_data(None, ticker_interval=tickfreq, pairs=[pair])
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ticks = trim_dictlist(ticks, -200)
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return ticks[pair]
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# FIX: fixturize this?
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def _make_backtest_conf(conf=None, pair='BTC_UNITEST', record=None):
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data = optimize.load_data(None, ticker_interval=8, pairs=[pair])
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data = trim_dictlist(data, -200)
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return {
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'stake_amount': conf['stake_amount'],
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'processed': _BACKTESTING.tickerdata_to_dataframe(data),
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'max_open_trades': 10,
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'realistic': True,
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'record': record
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}
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def _trend(signals, buy_value, sell_value):
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n = len(signals['low'])
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buy = np.zeros(n)
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sell = np.zeros(n)
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for i in range(0, len(signals['buy'])):
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if random.random() > 0.5: # Both buy and sell signals at same timeframe
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buy[i] = buy_value
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sell[i] = sell_value
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signals['buy'] = buy
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signals['sell'] = sell
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return signals
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def _trend_alternate(dataframe=None):
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signals = dataframe
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low = signals['low']
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n = len(low)
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buy = np.zeros(n)
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sell = np.zeros(n)
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for i in range(0, len(buy)):
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if i % 2 == 0:
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buy[i] = 1
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else:
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sell[i] = 1
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signals['buy'] = buy
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signals['sell'] = sell
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return dataframe
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def _run_backtest_1(fun, backtest_conf):
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# strategy is a global (hidden as a singleton), so we
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# emulate strategy being pure, by override/restore here
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# if we dont do this, the override in strategy will carry over
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# to other tests
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old_buy = _BACKTESTING.populate_buy_trend
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old_sell = _BACKTESTING.populate_sell_trend
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_BACKTESTING.populate_buy_trend = fun # Override
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_BACKTESTING.populate_sell_trend = fun # Override
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results = _BACKTESTING.backtest(backtest_conf)
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_BACKTESTING.populate_buy_trend = old_buy # restore override
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_BACKTESTING.populate_sell_trend = old_sell # restore override
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return results
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# Unit tests
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def test_setup_configuration_without_arguments(mocker, default_conf, caplog) -> None:
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"""
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@@ -418,3 +484,125 @@ def test_backtest_pricecontours(default_conf) -> None:
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tests = [['raise', 17], ['lower', 0], ['sine', 17]]
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for [contour, numres] in tests:
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simple_backtest(default_conf, contour, numres)
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# Test backtest using offline data (testdata directory)
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def test_backtest_ticks(default_conf):
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ticks = [1, 5]
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fun = _BACKTESTING.populate_buy_trend
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for tick in ticks:
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backtest_conf = _make_backtest_conf(conf=default_conf)
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results = _run_backtest_1(fun, backtest_conf)
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assert not results.empty
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def test_backtest_clash_buy_sell(default_conf):
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# Override the default buy trend function in our default_strategy
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def fun(dataframe=None):
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buy_value = 1
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sell_value = 1
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return _trend(dataframe, buy_value, sell_value)
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backtest_conf = _make_backtest_conf(conf=default_conf)
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results = _run_backtest_1(fun, backtest_conf)
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assert results.empty
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def test_backtest_only_sell(default_conf):
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# Override the default buy trend function in our default_strategy
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def fun(dataframe=None):
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buy_value = 0
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sell_value = 1
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return _trend(dataframe, buy_value, sell_value)
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backtest_conf = _make_backtest_conf(conf=default_conf)
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results = _run_backtest_1(fun, backtest_conf)
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assert results.empty
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def test_backtest_alternate_buy_sell(default_conf):
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backtest_conf = _make_backtest_conf(conf=default_conf, pair='BTC_UNITEST')
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results = _run_backtest_1(_trend_alternate, backtest_conf)
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assert len(results) == 3
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def test_backtest_record(default_conf, mocker):
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names = []
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records = []
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mocker.patch(
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'freqtrade.optimize.backtesting.file_dump_json',
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new=lambda n, r: (names.append(n), records.append(r))
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)
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backtest_conf = _make_backtest_conf(
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conf=default_conf,
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pair='BTC_UNITEST',
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record="trades"
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)
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results = _run_backtest_1(_trend_alternate, backtest_conf)
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assert len(results) == 3
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# Assert file_dump_json was only called once
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assert names == ['backtest-result.json']
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records = records[0]
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# Ensure records are of correct type
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assert len(records) == 3
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# ('BTC_UNITEST', 0.00331158, '1510684320', '1510691700', 0, 117)
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# Below follows just a typecheck of the schema/type of trade-records
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oix = None
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for (pair, profit, date_buy, date_sell, buy_index, dur) in records:
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assert pair == 'BTC_UNITEST'
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isinstance(profit, float)
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# FIX: buy/sell should be converted to ints
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isinstance(date_buy, str)
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isinstance(date_sell, str)
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isinstance(buy_index, pd._libs.tslib.Timestamp)
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if oix:
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assert buy_index > oix
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oix = buy_index
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assert dur > 0
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def test_backtest_start_live(default_conf, mocker, caplog):
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default_conf['exchange']['pair_whitelist'] = ['BTC_UNITEST']
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mocker.patch('freqtrade.exchange.get_ticker_history',
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new=lambda n, i: _load_pair_as_ticks(n, i))
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mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', MagicMock())
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mocker.patch('freqtrade.optimize.backtesting.Backtesting._generate_text_table', MagicMock())
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mocker.patch('freqtrade.configuration.open', mocker.mock_open(
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read_data=json.dumps(default_conf)
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))
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args = MagicMock()
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args.ticker_interval = 1
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args.level = 10
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args.live = True
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args.datadir = None
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args.export = None
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args.strategy = 'default_strategy'
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args.timerange = '-100' # needed due to MagicMock malleability
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args = [
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'--config', 'config.json',
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'--strategy', 'default_strategy',
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'backtesting',
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'--ticker-interval', '1',
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'--live',
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'--timerange', '-100'
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]
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args = get_args(args)
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start(args)
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# check the logs, that will contain the backtest result
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exists = [
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'Parameter -i/--ticker-interval detected ...',
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'Using ticker_interval: 1 ...',
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'Parameter -l/--live detected ...',
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'Using max_open_trades: 1 ...',
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'Parameter --timerange detected: -100 ..',
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'Parameter --datadir detected: freqtrade/tests/testdata ...',
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'Using stake_currency: BTC ...',
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'Using stake_amount: 0.001 ...',
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'Downloading data for all pairs in whitelist ...',
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'Measuring data from 2017-11-14T19:32:00+00:00 up to 2017-11-14T22:59:00+00:00 (0 days)..'
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]
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for line in exists:
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tt.log_has(line, caplog.record_tuples)
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@@ -2,6 +2,7 @@
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import os
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from copy import deepcopy
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from unittest.mock import MagicMock
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import pandas as pd
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from freqtrade.optimize.hyperopt import Hyperopt
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import freqtrade.tests.conftest as tt # test tools
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@@ -157,7 +158,7 @@ def test_fmin_best_results(mocker, default_conf, caplog) -> None:
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'"uptrend_long_ema": {\n "enabled": true\n },',
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'"uptrend_short_ema": {\n "enabled": false\n },',
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'"uptrend_sma": {\n "enabled": false\n }',
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'ROI table:\n{\'0\': 6.0, \'3.0\': 3.0, \'5.0\': 1.0, \'6.0\': 0}',
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'ROI table:\n{0: 6.0, 3.0: 3.0, 5.0: 1.0, 6.0: 0}',
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'Best Result:\nfoo'
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]
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for line in exists:
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@@ -275,7 +276,7 @@ def test_roi_table_generation() -> None:
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}
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hyperopt = _HYPEROPT
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assert hyperopt.generate_roi_table(params) == {'0': 6, '15': 3, '25': 1, '30': 0}
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assert hyperopt.generate_roi_table(params) == {0: 6, 15: 3, 25: 1, 30: 0}
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def test_start_calls_fmin(mocker, default_conf) -> None:
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@@ -319,3 +320,36 @@ def test_start_uses_mongotrials(mocker, default_conf) -> None:
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hyperopt.start()
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mock_mongotrials.assert_called_once()
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mock_fmin.assert_called_once()
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# test log_trials_result
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# test buy_strategy_generator def populate_buy_trend
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# test optimizer if 'ro_t1' in params
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def test_format_results():
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"""
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Test Hyperopt.format_results()
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"""
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trades = [
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('BTC_ETH', 2, 2, 123),
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('BTC_LTC', 1, 1, 123),
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('BTC_XRP', -1, -2, -246)
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]
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labels = ['currency', 'profit_percent', 'profit_BTC', 'duration']
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df = pd.DataFrame.from_records(trades, columns=labels)
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x = Hyperopt.format_results(df)
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assert x.find(' 66.67%')
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def test_signal_handler(mocker):
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"""
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Test Hyperopt.signal_handler()
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"""
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m = MagicMock()
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mocker.patch('sys.exit', m)
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mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.save_trials', m)
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mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.log_trials_result', m)
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hyperopt = _HYPEROPT
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hyperopt.signal_handler(9, None)
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assert m.call_count == 3
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