159 lines
6.2 KiB
Python
159 lines
6.2 KiB
Python
import datetime
|
|
import shutil
|
|
from pathlib import Path
|
|
|
|
import pytest
|
|
|
|
from freqtrade.configuration import TimeRange
|
|
from freqtrade.data.dataprovider import DataProvider
|
|
# from freqtrade.freqai.data_drawer import FreqaiDataDrawer
|
|
from freqtrade.exceptions import OperationalException
|
|
from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
|
|
from tests.conftest import get_patched_exchange
|
|
from tests.freqai.conftest import get_patched_data_kitchen, get_patched_freqai_strategy
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"timerange, train_period_days, expected_result",
|
|
[
|
|
("20220101-20220201", 30, "20211202-20220201"),
|
|
("20220301-20220401", 15, "20220214-20220401"),
|
|
],
|
|
)
|
|
def test_create_fulltimerange(
|
|
timerange, train_period_days, expected_result, freqai_conf, mocker, caplog
|
|
):
|
|
dk = get_patched_data_kitchen(mocker, freqai_conf)
|
|
assert dk.create_fulltimerange(timerange, train_period_days) == expected_result
|
|
shutil.rmtree(Path(dk.full_path))
|
|
|
|
|
|
def test_create_fulltimerange_incorrect_backtest_period(mocker, freqai_conf):
|
|
dk = get_patched_data_kitchen(mocker, freqai_conf)
|
|
with pytest.raises(OperationalException, match=r"backtest_period_days must be an integer"):
|
|
dk.create_fulltimerange("20220101-20220201", 0.5)
|
|
with pytest.raises(OperationalException, match=r"backtest_period_days must be positive"):
|
|
dk.create_fulltimerange("20220101-20220201", -1)
|
|
shutil.rmtree(Path(dk.full_path))
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"timerange, train_period_days, backtest_period_days, expected_result",
|
|
[
|
|
("20220101-20220201", 30, 7, 9),
|
|
("20220101-20220201", 30, 0.5, 120),
|
|
("20220101-20220201", 10, 1, 80),
|
|
],
|
|
)
|
|
def test_split_timerange(
|
|
mocker, freqai_conf, timerange, train_period_days, backtest_period_days, expected_result
|
|
):
|
|
freqai_conf.update({"timerange": "20220101-20220401"})
|
|
dk = get_patched_data_kitchen(mocker, freqai_conf)
|
|
tr_list, bt_list = dk.split_timerange(timerange, train_period_days, backtest_period_days)
|
|
assert len(tr_list) == len(bt_list) == expected_result
|
|
|
|
with pytest.raises(
|
|
OperationalException, match=r"train_period_days must be an integer greater than 0."
|
|
):
|
|
dk.split_timerange("20220101-20220201", -1, 0.5)
|
|
shutil.rmtree(Path(dk.full_path))
|
|
|
|
|
|
def test_update_historic_data(mocker, freqai_conf):
|
|
strategy = get_patched_freqai_strategy(mocker, freqai_conf)
|
|
exchange = get_patched_exchange(mocker, freqai_conf)
|
|
strategy.dp = DataProvider(freqai_conf, exchange)
|
|
freqai = strategy.freqai
|
|
freqai.live = True
|
|
freqai.dk = FreqaiDataKitchen(freqai_conf, freqai.dd)
|
|
timerange = TimeRange.parse_timerange("20180110-20180114")
|
|
|
|
freqai.dk.load_all_pair_histories(timerange)
|
|
historic_candles = len(freqai.dd.historic_data["ADA/BTC"]["5m"])
|
|
dp_candles = len(strategy.dp.get_pair_dataframe("ADA/BTC", "5m"))
|
|
candle_difference = dp_candles - historic_candles
|
|
freqai.dk.update_historic_data(strategy)
|
|
|
|
updated_historic_candles = len(freqai.dd.historic_data["ADA/BTC"]["5m"])
|
|
|
|
assert updated_historic_candles - historic_candles == candle_difference
|
|
shutil.rmtree(Path(freqai.dk.full_path))
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"timestamp, expected",
|
|
[
|
|
(datetime.datetime.now(tz=datetime.timezone.utc).timestamp() - 7200, True),
|
|
(datetime.datetime.now(tz=datetime.timezone.utc).timestamp(), False),
|
|
],
|
|
)
|
|
def test_check_if_model_expired(mocker, freqai_conf, timestamp, expected):
|
|
dk = get_patched_data_kitchen(mocker, freqai_conf)
|
|
assert dk.check_if_model_expired(timestamp) == expected
|
|
shutil.rmtree(Path(dk.full_path))
|
|
|
|
|
|
def test_load_all_pairs_histories(mocker, freqai_conf):
|
|
strategy = get_patched_freqai_strategy(mocker, freqai_conf)
|
|
exchange = get_patched_exchange(mocker, freqai_conf)
|
|
strategy.dp = DataProvider(freqai_conf, exchange)
|
|
freqai = strategy.freqai
|
|
freqai.live = True
|
|
freqai.dk = FreqaiDataKitchen(freqai_conf, freqai.dd)
|
|
timerange = TimeRange.parse_timerange("20180110-20180114")
|
|
freqai.dk.load_all_pair_histories(timerange)
|
|
|
|
assert len(freqai.dd.historic_data.keys()) == len(
|
|
freqai_conf.get("exchange", {}).get("pair_whitelist")
|
|
)
|
|
assert len(freqai.dd.historic_data["ADA/BTC"]) == len(
|
|
freqai_conf.get("freqai", {}).get("feature_parameters", {}).get("include_timeframes")
|
|
)
|
|
shutil.rmtree(Path(freqai.dk.full_path))
|
|
|
|
|
|
def test_get_base_and_corr_dataframes(mocker, freqai_conf):
|
|
strategy = get_patched_freqai_strategy(mocker, freqai_conf)
|
|
exchange = get_patched_exchange(mocker, freqai_conf)
|
|
strategy.dp = DataProvider(freqai_conf, exchange)
|
|
freqai = strategy.freqai
|
|
freqai.live = True
|
|
freqai.dk = FreqaiDataKitchen(freqai_conf, freqai.dd)
|
|
timerange = TimeRange.parse_timerange("20180110-20180114")
|
|
freqai.dk.load_all_pair_histories(timerange)
|
|
sub_timerange = TimeRange.parse_timerange("20180111-20180114")
|
|
corr_df, base_df = freqai.dk.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC")
|
|
|
|
num_tfs = len(
|
|
freqai_conf.get("freqai", {}).get("feature_parameters", {}).get("include_timeframes")
|
|
)
|
|
|
|
assert len(base_df.keys()) == num_tfs
|
|
|
|
assert len(corr_df.keys()) == len(
|
|
freqai_conf.get("freqai", {}).get("feature_parameters", {}).get("include_corr_pairlist")
|
|
)
|
|
|
|
assert len(corr_df["ADA/BTC"].keys()) == num_tfs
|
|
shutil.rmtree(Path(freqai.dk.full_path))
|
|
|
|
|
|
def test_use_strategy_to_populate_indicators(mocker, freqai_conf):
|
|
strategy = get_patched_freqai_strategy(mocker, freqai_conf)
|
|
exchange = get_patched_exchange(mocker, freqai_conf)
|
|
strategy.dp = DataProvider(freqai_conf, exchange)
|
|
strategy.freqai_info = freqai_conf.get("freqai", {})
|
|
freqai = strategy.freqai
|
|
freqai.live = True
|
|
freqai.dk = FreqaiDataKitchen(freqai_conf, freqai.dd)
|
|
timerange = TimeRange.parse_timerange("20180110-20180114")
|
|
freqai.dk.load_all_pair_histories(timerange)
|
|
sub_timerange = TimeRange.parse_timerange("20180111-20180114")
|
|
corr_df, base_df = freqai.dk.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC")
|
|
|
|
df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, 'LTC/BTC')
|
|
|
|
assert len(df.columns) == 45
|
|
shutil.rmtree(Path(freqai.dk.full_path))
|