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update code to freqai_backtest_live_models only from historic predictions

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This commit is contained in:
Wagner Costa
2022-11-22 13:09:09 -03:00
parent fdc82af883
commit c01f25ddc9
9 changed files with 36 additions and 227 deletions
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2
tests/freqai/test_freqai_backtesting.py
View File

@@ -81,7 +81,7 @@ def test_freqai_backtest_live_models_model_not_found(freqai_conf, mocker, testda
bt_config = setup_optimize_configuration(args, RunMode.BACKTEST)
with pytest.raises(OperationalException,
match=r".* Saved models are required to run backtest .*"):
match=r".* Historic predictions data is required to run backtest .*"):
Backtesting(bt_config)
Backtesting.cleanup()

6
tests/freqai/test_freqai_datadrawer.py
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@@ -98,7 +98,7 @@ def test_use_strategy_to_populate_indicators(mocker, freqai_conf):
shutil.rmtree(Path(freqai.dk.full_path))
def test_get_timerange_from_backtesting_live_dataframe(mocker, freqai_conf):
def test_get_timerange_from_live_historic_predictions(mocker, freqai_conf):
strategy = get_patched_freqai_strategy(mocker, freqai_conf)
exchange = get_patched_exchange(mocker, freqai_conf)
strategy.dp = DataProvider(freqai_conf, exchange)
@@ -115,7 +115,7 @@ def test_get_timerange_from_backtesting_live_dataframe(mocker, freqai_conf):
freqai.dd.save_historic_predictions_to_disk()
freqai.dd.save_global_metadata_to_disk({"start_dry_live_date": 1516406400})
timerange = freqai.dd.get_timerange_from_backtesting_live_dataframe()
timerange = freqai.dd.get_timerange_from_live_historic_predictions()
assert timerange.startts == 1516406400
assert timerange.stopts == 1517356500
@@ -129,4 +129,4 @@ def test_get_timerange_from_backtesting_live_df_pred_not_found(mocker, freqai_co
OperationalException,
match=r'Historic predictions not found.*'
):
freqai.dd.get_timerange_from_backtesting_live_dataframe()
freqai.dd.get_timerange_from_live_historic_predictions()

67
tests/freqai/test_freqai_datakitchen.py
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@@ -9,7 +9,6 @@ from freqtrade.configuration import TimeRange
from freqtrade.data.dataprovider import DataProvider
from freqtrade.exceptions import OperationalException
from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
from freqtrade.freqai.utils import get_timerange_backtest_live_models
from tests.conftest import get_patched_exchange, log_has_re
from tests.freqai.conftest import (get_patched_data_kitchen, get_patched_freqai_strategy,
make_data_dictionary, make_unfiltered_dataframe)
@@ -166,72 +165,6 @@ def test_make_train_test_datasets(mocker, freqai_conf):
assert len(data_dictionary['train_features'].index) == 1916
def test_get_pairs_timestamp_validation(mocker, freqai_conf):
exchange = get_patched_exchange(mocker, freqai_conf)
strategy = get_patched_freqai_strategy(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_conf['freqai'].update({"identifier": "invalid_id"})
model_path = freqai.dk.get_full_models_path(freqai_conf)
with pytest.raises(
OperationalException,
match=r'.*required to run backtest with the freqai-backtest-live-models.*'
):
freqai.dk.get_assets_timestamps_training_from_ready_models(model_path)
@pytest.mark.parametrize('model', [
'LightGBMRegressor'
])
def test_get_timerange_from_ready_models(mocker, freqai_conf, model):
freqai_conf.update({"freqaimodel": model})
freqai_conf.update({"timerange": "20180110-20180130"})
freqai_conf.update({"strategy": "freqai_test_strat"})
freqai_conf.get("freqai", {}).update({"backtest_using_historic_predictions": False})
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)
timerange = TimeRange.parse_timerange("20180101-20180130")
freqai.dd.load_all_pair_histories(timerange, freqai.dk)
freqai.dd.pair_dict = MagicMock()
data_load_timerange = TimeRange.parse_timerange("20180101-20180130")
# 1516233600 (2018-01-18 00:00) - Start Training 1
# 1516406400 (2018-01-20 00:00) - End Training 1 (Backtest slice 1)
# 1516579200 (2018-01-22 00:00) - End Training 2 (Backtest slice 2)
# 1516838400 (2018-01-25 00:00) - End Timerange
new_timerange = TimeRange("date", "date", 1516233600, 1516406400)
freqai.extract_data_and_train_model(
new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange)
new_timerange = TimeRange("date", "date", 1516406400, 1516579200)
freqai.extract_data_and_train_model(
new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange)
model_path = freqai.dk.get_full_models_path(freqai_conf)
(backtesting_timerange,
pairs_end_dates) = freqai.dk.get_timerange_and_assets_end_dates_from_ready_models(
models_path=model_path)
assert len(pairs_end_dates["ADA"]) == 2
assert backtesting_timerange.startts == 1516406400
assert backtesting_timerange.stopts == 1516838400
backtesting_string_timerange = get_timerange_backtest_live_models(freqai_conf)
assert backtesting_string_timerange == '20180120-20180125'
@pytest.mark.parametrize('model', [
'LightGBMRegressor'
])