stable/freqtrade/tests/data/test_btanalysis.py

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from unittest.mock import MagicMock
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import pytest
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from arrow import Arrow
from pandas import DataFrame, to_datetime
from freqtrade.configuration import TimeRange
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from freqtrade.data.btanalysis import (BT_DATA_COLUMNS,
combine_tickers_with_mean,
create_cum_profit,
extract_trades_of_period,
load_backtest_data, load_trades,
load_trades_from_db)
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from freqtrade.data.history import load_data, load_pair_history
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from freqtrade.tests.test_persistence import create_mock_trades
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def test_load_backtest_data(testdatadir):
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filename = testdatadir / "backtest-result_test.json"
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bt_data = load_backtest_data(filename)
assert isinstance(bt_data, DataFrame)
assert list(bt_data.columns) == BT_DATA_COLUMNS + ["profitabs"]
assert len(bt_data) == 179
# Test loading from string (must yield same result)
bt_data2 = load_backtest_data(str(filename))
assert bt_data.equals(bt_data2)
with pytest.raises(ValueError, match=r"File .* does not exist\."):
load_backtest_data(str("filename") + "nofile")
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@pytest.mark.usefixtures("init_persistence")
def test_load_trades_db(default_conf, fee, mocker):
create_mock_trades(fee)
# remove init so it does not init again
init_mock = mocker.patch('freqtrade.persistence.init', MagicMock())
trades = load_trades_from_db(db_url=default_conf['db_url'])
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assert init_mock.call_count == 1
assert len(trades) == 3
assert isinstance(trades, DataFrame)
assert "pair" in trades.columns
assert "open_time" in trades.columns
assert "profitperc" in trades.columns
for col in BT_DATA_COLUMNS:
if col not in ['index', 'open_at_end']:
assert col in trades.columns
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def test_extract_trades_of_period(testdatadir):
pair = "UNITTEST/BTC"
timerange = TimeRange(None, 'line', 0, -1000)
data = load_pair_history(pair=pair, ticker_interval='1m',
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datadir=testdatadir, timerange=timerange)
# timerange = 2017-11-14 06:07 - 2017-11-14 22:58:00
trades = DataFrame(
{'pair': [pair, pair, pair, pair],
'profit_percent': [0.0, 0.1, -0.2, -0.5],
'profit_abs': [0.0, 1, -2, -5],
'open_time': to_datetime([Arrow(2017, 11, 13, 15, 40, 0).datetime,
Arrow(2017, 11, 14, 9, 41, 0).datetime,
Arrow(2017, 11, 14, 14, 20, 0).datetime,
Arrow(2017, 11, 15, 3, 40, 0).datetime,
], utc=True
),
'close_time': to_datetime([Arrow(2017, 11, 13, 16, 40, 0).datetime,
Arrow(2017, 11, 14, 10, 41, 0).datetime,
Arrow(2017, 11, 14, 15, 25, 0).datetime,
Arrow(2017, 11, 15, 3, 55, 0).datetime,
], utc=True)
})
trades1 = extract_trades_of_period(data, trades)
# First and last trade are dropped as they are out of range
assert len(trades1) == 2
assert trades1.iloc[0].open_time == Arrow(2017, 11, 14, 9, 41, 0).datetime
assert trades1.iloc[0].close_time == Arrow(2017, 11, 14, 10, 41, 0).datetime
assert trades1.iloc[-1].open_time == Arrow(2017, 11, 14, 14, 20, 0).datetime
assert trades1.iloc[-1].close_time == Arrow(2017, 11, 14, 15, 25, 0).datetime
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def test_load_trades(default_conf, mocker):
db_mock = mocker.patch("freqtrade.data.btanalysis.load_trades_from_db", MagicMock())
bt_mock = mocker.patch("freqtrade.data.btanalysis.load_backtest_data", MagicMock())
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load_trades("DB",
db_url=default_conf.get('db_url'),
exportfilename=default_conf.get('exportfilename'),
)
assert db_mock.call_count == 1
assert bt_mock.call_count == 0
db_mock.reset_mock()
bt_mock.reset_mock()
default_conf['exportfilename'] = "testfile.json"
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load_trades("file",
db_url=default_conf.get('db_url'),
exportfilename=default_conf.get('exportfilename'),)
assert db_mock.call_count == 0
assert bt_mock.call_count == 1
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def test_combine_tickers_with_mean(testdatadir):
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pairs = ["ETH/BTC", "XLM/BTC"]
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tickers = load_data(datadir=testdatadir,
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pairs=pairs,
ticker_interval='5m'
)
df = combine_tickers_with_mean(tickers)
assert isinstance(df, DataFrame)
assert "ETH/BTC" in df.columns
assert "XLM/BTC" in df.columns
assert "mean" in df.columns
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def test_create_cum_profit(testdatadir):
filename = testdatadir / "backtest-result_test.json"
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bt_data = load_backtest_data(filename)
timerange = TimeRange.parse_timerange("20180110-20180112")
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df = load_pair_history(pair="POWR/BTC", ticker_interval='5m',
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datadir=testdatadir, timerange=timerange)
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cum_profits = create_cum_profit(df.set_index('date'),
bt_data[bt_data["pair"] == 'POWR/BTC'],
"cum_profits")
assert "cum_profits" in cum_profits.columns
assert cum_profits.iloc[0]['cum_profits'] == 0
assert cum_profits.iloc[-1]['cum_profits'] == 0.0798005