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add more tests for datakitchen functionalities, add regression tests for freqai_interface train/backtest

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This commit is contained in:
robcaulk
2022-07-20 12:56:46 +02:00
parent 9c051958a6
commit d43c146676
7 changed files with 415 additions and 119 deletions
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61
tests/freqai/conftest.py
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@@ -2,9 +2,12 @@ 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")
@@ -21,16 +24,17 @@ def freqai_conf(default_conf):
"freqai": {
"startup_candles": 10000,
"purge_old_models": True,
"train_period_days": 15,
"backtest_period_days": 7,
"train_period_days": 5,
"backtest_period_days": 2,
"live_retrain_hours": 0,
"identifier": "uniqe-id7",
"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": 2,
"include_shifted_candles": 1,
"DI_threshold": 0.9,
"weight_factor": 0.9,
"principal_component_analysis": False,
@@ -40,7 +44,7 @@ def freqai_conf(default_conf):
"indicator_periods_candles": [10],
},
"data_split_parameters": {"test_size": 0.33, "random_state": 1},
"model_training_parameters": {"n_estimators": 1000, "task_type": "CPU"},
"model_training_parameters": {"n_estimators": 100},
},
"config_files": [Path('config_examples', 'config_freqai_futures.example.json')]
}
@@ -55,7 +59,7 @@ def get_patched_data_kitchen(mocker, freqaiconf):
return dk
def get_patched_strategy(mocker, freqaiconf):
def get_patched_freqai_strategy(mocker, freqaiconf):
strategy = StrategyResolver.load_strategy(freqaiconf)
strategy.bot_start()
@@ -66,3 +70,48 @@ 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

95
tests/freqai/test_freqai.py
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@@ -1,95 +0,0 @@
# from unittest.mock import MagicMock
# from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_edge
import copy
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_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
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)
def test_split_timerange(mocker, default_conf):
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("20220101-20220201", 30, 7)
assert len(tr_list) == len(bt_list) == 9
tr_list, bt_list = dk.split_timerange("20220101-20220201", 30, 0.5)
assert len(tr_list) == len(bt_list) == 120
tr_list, bt_list = dk.split_timerange("20220101-20220201", 10, 1)
assert len(tr_list) == len(bt_list) == 80
with pytest.raises(
OperationalException, match=r"train_period_days must be an integer greater than 0."
):
dk.split_timerange("20220101-20220201", -1, 0.5)
def test_update_historic_data(mocker, default_conf):
freqaiconf = freqai_conf(copy.deepcopy(default_conf))
strategy = get_patched_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
# def generate_test_data(timeframe: str, size: int, start: str = '2020-07-05'):
# np.random.seed(42)
# tf_mins = timeframe_to_minutes(timeframe)
# base = np.random.normal(20, 2, size=size)
# date = pd.date_range(start, periods=size, freq=f'{tf_mins}min', tz='UTC')
# df = pd.DataFrame({
# 'date': date,
# 'open': base,
# 'high': base + np.random.normal(2, 1, size=size),
# 'low': base - np.random.normal(2, 1, size=size),
# 'close': base + np.random.normal(0, 1, size=size),
# 'volume': np.random.normal(200, size=size)
# }
# )
# df = df.dropna()
# return df

167
tests/freqai/test_freqai_datakitchen.py Normal file
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@@ -0,0 +1,167 @@
# 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) == 90
shutil.rmtree(Path(freqai.dk.full_path))

183
tests/freqai/test_freqai_interface.py Normal file
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@@ -0,0 +1,183 @@
# 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_drawer import FreqaiDataDrawer
from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
from tests.conftest import get_patched_exchange, log_has
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))
# Catboost not available for ARM architecture. using platform lib to check processor type
if "arm" not in platform.uname()[-1]:
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(
"Found model at user_data/models/uniqe-id100/sub-train-ADA1517097600/cb_ada_1517097600",
caplog,
)
shutil.rmtree(Path(freqai.dk.full_path))