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fix conflicts

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longyu
2022-07-22 17:17:57 +02:00
parent 5ad8d08b84
commit 38841e30b8
16 changed files with 838 additions and 180 deletions
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117
tests/freqai/conftest.py Normal file
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from copy import deepcopy
from pathlib import Path
from unittest.mock import MagicMock
from freqtrade.configuration import TimeRange
from freqtrade.data.dataprovider import DataProvider
from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
from freqtrade.resolvers import StrategyResolver
from freqtrade.resolvers.freqaimodel_resolver import FreqaiModelResolver
from tests.conftest import get_patched_exchange
# @pytest.fixture(scope="function")
def freqai_conf(default_conf):
freqaiconf = deepcopy(default_conf)
freqaiconf.update(
{
"datadir": Path(default_conf["datadir"]),
"strategy": "freqai_test_strat",
"strategy-path": "freqtrade/tests/strategy/strats",
"freqaimodel": "LightGBMPredictionModel",
"freqaimodel_path": "freqai/prediction_models",
"timerange": "20180110-20180115",
"freqai": {
"startup_candles": 10000,
"purge_old_models": True,
"train_period_days": 5,
"backtest_period_days": 2,
"live_retrain_hours": 0,
"expiration_hours": 1,
"identifier": "uniqe-id100",
"live_trained_timestamp": 0,
"feature_parameters": {
"include_timeframes": ["5m"],
"include_corr_pairlist": ["ADA/BTC", "DASH/BTC"],
"label_period_candles": 20,
"include_shifted_candles": 1,
"DI_threshold": 0.9,
"weight_factor": 0.9,
"principal_component_analysis": False,
"use_SVM_to_remove_outliers": True,
"stratify_training_data": 0,
"indicator_max_period_candles": 10,
"indicator_periods_candles": [10],
},
"data_split_parameters": {"test_size": 0.33, "random_state": 1},
"model_training_parameters": {"n_estimators": 100, "verbosity": 0},
},
"config_files": [Path('config_examples', 'config_freqai_futures.example.json')]
}
)
freqaiconf['exchange'].update({'pair_whitelist': ['ADA/BTC', 'DASH/BTC', 'ETH/BTC', 'LTC/BTC']})
return freqaiconf
def get_patched_data_kitchen(mocker, freqaiconf):
dd = mocker.patch('freqtrade.freqai.data_drawer', MagicMock())
dk = FreqaiDataKitchen(freqaiconf, dd)
return dk
def get_patched_freqai_strategy(mocker, freqaiconf):
strategy = StrategyResolver.load_strategy(freqaiconf)
strategy.bot_start()
return strategy
def get_patched_freqaimodel(mocker, freqaiconf):
freqaimodel = FreqaiModelResolver.load_freqaimodel(freqaiconf)
return freqaimodel
def get_freqai_live_analyzed_dataframe(mocker, freqaiconf):
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)
strategy.analyze_pair('ADA/BTC', '5m')
return strategy.dp.get_analyzed_dataframe('ADA/BTC', '5m')
def get_freqai_analyzed_dataframe(mocker, freqaiconf):
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")
return freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, 'LTC/BTC')
def get_ready_to_train(mocker, freqaiconf):
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")
return corr_df, base_df, freqai, strategy

167
tests/freqai/test_freqai_datakitchen.py Normal file
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# 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))

181
tests/freqai/test_freqai_interface.py Normal file
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# from unittest.mock import MagicMock
# from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_edge
import copy
# import platform
import shutil
from pathlib import Path
from unittest.mock import MagicMock
from freqtrade.configuration import TimeRange
from freqtrade.data.dataprovider import DataProvider
from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
from tests.conftest import get_patched_exchange, log_has_re
from tests.freqai.conftest import freqai_conf, get_patched_freqai_strategy
def test_train_model_in_series_LightGBM(mocker, default_conf):
freqaiconf = freqai_conf(copy.deepcopy(default_conf))
freqaiconf.update({"timerange": "20180110-20180130"})
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("20180110-20180130")
freqai.dk.load_all_pair_histories(timerange)
freqai.dd.pair_dict = MagicMock()
data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
new_timerange = TimeRange.parse_timerange("20180120-20180130")
freqai.train_model_in_series(new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange)
assert (
Path(freqai.dk.data_path / str(freqai.dk.model_filename + "_model.joblib"))
.resolve()
.exists()
)
assert (
Path(freqai.dk.data_path / str(freqai.dk.model_filename + "_metadata.json"))
.resolve()
.exists()
)
assert (
Path(freqai.dk.data_path / str(freqai.dk.model_filename + "_trained_df.pkl"))
.resolve()
.exists()
)
assert (
Path(freqai.dk.data_path / str(freqai.dk.model_filename + "_svm_model.joblib"))
.resolve()
.exists()
)
shutil.rmtree(Path(freqai.dk.full_path))
# FIXME: hits segfault
# @pytest.mark.skipif("arm" in platform.uname()[-1], reason="no ARM..")
# def test_train_model_in_series_Catboost(mocker, default_conf):
# freqaiconf = freqai_conf(copy.deepcopy(default_conf))
# freqaiconf.update({"timerange": "20180110-20180130"})
# freqaiconf.update({"freqaimodel": "CatboostPredictionModel"})
# 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("20180110-20180130")
# freqai.dk.load_all_pair_histories(timerange)
# freqai.dd.pair_dict = MagicMock()
# data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
# new_timerange = TimeRange.parse_timerange("20180120-20180130")
# freqai.train_model_in_series(new_timerange, "ADA/BTC",
# strategy, freqai.dk, data_load_timerange)
# assert (
# Path(freqai.dk.data_path / str(freqai.dk.model_filename + "_model.joblib"))
# .resolve()
# .exists()
# )
# assert (
# Path(freqai.dk.data_path / str(freqai.dk.model_filename + "_metadata.json"))
# .resolve()
# .exists()
# )
# assert (
# Path(freqai.dk.data_path / str(freqai.dk.model_filename + "_trained_df.pkl"))
# .resolve()
# .exists()
# )
# assert (
# Path(freqai.dk.data_path / str(freqai.dk.model_filename + "_svm_model.joblib"))
# .resolve()
# .exists()
# )
# shutil.rmtree(Path(freqai.dk.full_path))
def test_start_backtesting(mocker, default_conf):
freqaiconf = freqai_conf(copy.deepcopy(default_conf))
freqaiconf.update({"timerange": "20180120-20180130"})
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 = False
freqai.dk = FreqaiDataKitchen(freqaiconf, freqai.dd)
timerange = TimeRange.parse_timerange("20180110-20180130")
freqai.dk.load_all_pair_histories(timerange)
sub_timerange = TimeRange.parse_timerange("20180110-20180130")
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")
metadata = {"pair": "ADA/BTC"}
freqai.start_backtesting(df, metadata, freqai.dk)
model_folders = [x for x in freqai.dd.full_path.iterdir() if x.is_dir()]
assert len(model_folders) == 5
shutil.rmtree(Path(freqai.dk.full_path))
def test_start_backtesting_from_existing_folder(mocker, default_conf, caplog):
freqaiconf = freqai_conf(copy.deepcopy(default_conf))
freqaiconf.update({"timerange": "20180120-20180130"})
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 = False
freqai.dk = FreqaiDataKitchen(freqaiconf, freqai.dd)
timerange = TimeRange.parse_timerange("20180110-20180130")
freqai.dk.load_all_pair_histories(timerange)
sub_timerange = TimeRange.parse_timerange("20180110-20180130")
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")
metadata = {"pair": "ADA/BTC"}
freqai.start_backtesting(df, metadata, freqai.dk)
model_folders = [x for x in freqai.dd.full_path.iterdir() if x.is_dir()]
assert len(model_folders) == 5
# without deleting the exiting folder structure, re-run
freqaiconf.update({"timerange": "20180120-20180130"})
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 = False
freqai.dk = FreqaiDataKitchen(freqaiconf, freqai.dd)
timerange = TimeRange.parse_timerange("20180110-20180130")
freqai.dk.load_all_pair_histories(timerange)
sub_timerange = TimeRange.parse_timerange("20180110-20180130")
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")
freqai.start_backtesting(df, metadata, freqai.dk)
assert log_has_re(
"Found model at ",
caplog,
)
shutil.rmtree(Path(freqai.dk.full_path))