stable/tests/freqai/test_freqai_datakitchen.py
2022-07-20 14:39:28 +02:00

168 lines
6.7 KiB
Python

# from unittest.mock import MagicMock
# from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_edge
import copy
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 freqai_conf, 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, default_conf, mocker, caplog
):
dk = get_patched_data_kitchen(mocker, freqai_conf(copy.deepcopy(default_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, default_conf):
dk = get_patched_data_kitchen(mocker, freqai_conf(copy.deepcopy(default_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, default_conf, timerange, train_period_days, backtest_period_days, expected_result
):
freqaiconf = freqai_conf(copy.deepcopy(default_conf))
freqaiconf.update({"timerange": "20220101-20220401"})
dk = get_patched_data_kitchen(mocker, freqaiconf)
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, default_conf):
freqaiconf = freqai_conf(copy.deepcopy(default_conf))
strategy = get_patched_freqai_strategy(mocker, freqaiconf)
exchange = get_patched_exchange(mocker, freqaiconf)
strategy.dp = DataProvider(freqaiconf, exchange)
freqai = strategy.model.bridge
freqai.live = True
freqai.dk = FreqaiDataKitchen(freqaiconf, 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, default_conf, timestamp, expected):
freqaiconf = freqai_conf(copy.deepcopy(default_conf))
dk = get_patched_data_kitchen(mocker, freqaiconf)
assert dk.check_if_model_expired(timestamp) == expected
shutil.rmtree(Path(dk.full_path))
def test_load_all_pairs_histories(mocker, default_conf):
freqaiconf = freqai_conf(copy.deepcopy(default_conf))
strategy = get_patched_freqai_strategy(mocker, freqaiconf)
exchange = get_patched_exchange(mocker, freqaiconf)
strategy.dp = DataProvider(freqaiconf, exchange)
freqai = strategy.model.bridge
freqai.live = True
freqai.dk = FreqaiDataKitchen(freqaiconf, freqai.dd)
timerange = TimeRange.parse_timerange("20180110-20180114")
freqai.dk.load_all_pair_histories(timerange)
assert len(freqai.dd.historic_data.keys()) == len(
freqaiconf.get("exchange", {}).get("pair_whitelist")
)
assert len(freqai.dd.historic_data["ADA/BTC"]) == len(
freqaiconf.get("freqai", {}).get("feature_parameters", {}).get("include_timeframes")
)
shutil.rmtree(Path(freqai.dk.full_path))
def test_get_base_and_corr_dataframes(mocker, default_conf):
freqaiconf = freqai_conf(copy.deepcopy(default_conf))
strategy = get_patched_freqai_strategy(mocker, freqaiconf)
exchange = get_patched_exchange(mocker, freqaiconf)
strategy.dp = DataProvider(freqaiconf, exchange)
freqai = strategy.model.bridge
freqai.live = True
freqai.dk = FreqaiDataKitchen(freqaiconf, 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(
freqaiconf.get("freqai", {}).get("feature_parameters", {}).get("include_timeframes")
)
assert len(base_df.keys()) == num_tfs
assert len(corr_df.keys()) == len(
freqaiconf.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, default_conf):
freqaiconf = freqai_conf(copy.deepcopy(default_conf))
strategy = get_patched_freqai_strategy(mocker, freqaiconf)
exchange = get_patched_exchange(mocker, freqaiconf)
strategy.dp = DataProvider(freqaiconf, exchange)
strategy.freqai_info = freqaiconf.get("freqai", {})
freqai = strategy.model.bridge
freqai.live = True
freqai.dk = FreqaiDataKitchen(freqaiconf, 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))