184 lines
7.1 KiB
Python
184 lines
7.1 KiB
Python
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# from unittest.mock import MagicMock
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# from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_edge
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import copy
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import platform
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import shutil
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from pathlib import Path
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from unittest.mock import MagicMock
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from freqtrade.configuration import TimeRange
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from freqtrade.data.dataprovider import DataProvider
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# from freqtrade.freqai.data_drawer import FreqaiDataDrawer
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from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
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from tests.conftest import get_patched_exchange, log_has
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from tests.freqai.conftest import freqai_conf, get_patched_freqai_strategy
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def test_train_model_in_series_LightGBM(mocker, default_conf):
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freqaiconf = freqai_conf(copy.deepcopy(default_conf))
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freqaiconf.update({"timerange": "20180110-20180130"})
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strategy = get_patched_freqai_strategy(mocker, freqaiconf)
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exchange = get_patched_exchange(mocker, freqaiconf)
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strategy.dp = DataProvider(freqaiconf, exchange)
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strategy.freqai_info = freqaiconf.get("freqai", {})
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freqai = strategy.model.bridge
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freqai.live = True
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freqai.dk = FreqaiDataKitchen(freqaiconf, freqai.dd)
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timerange = TimeRange.parse_timerange("20180110-20180130")
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freqai.dk.load_all_pair_histories(timerange)
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freqai.dd.pair_dict = MagicMock()
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data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
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new_timerange = TimeRange.parse_timerange("20180120-20180130")
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freqai.train_model_in_series(new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange)
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assert (
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Path(freqai.dk.data_path / str(freqai.dk.model_filename + "_model.joblib"))
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.resolve()
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.exists()
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)
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assert (
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Path(freqai.dk.data_path / str(freqai.dk.model_filename + "_metadata.json"))
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.resolve()
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.exists()
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)
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assert (
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Path(freqai.dk.data_path / str(freqai.dk.model_filename + "_trained_df.pkl"))
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.resolve()
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.exists()
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)
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assert (
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Path(freqai.dk.data_path / str(freqai.dk.model_filename + "_svm_model.joblib"))
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.resolve()
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.exists()
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)
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shutil.rmtree(Path(freqai.dk.full_path))
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# Catboost not available for ARM architecture. using platform lib to check processor type
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if "arm" not in platform.uname()[-1]:
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def test_train_model_in_series_Catboost(mocker, default_conf):
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freqaiconf = freqai_conf(copy.deepcopy(default_conf))
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freqaiconf.update({"timerange": "20180110-20180130"})
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freqaiconf.update({"freqaimodel": "CatboostPredictionModel"})
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strategy = get_patched_freqai_strategy(mocker, freqaiconf)
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exchange = get_patched_exchange(mocker, freqaiconf)
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strategy.dp = DataProvider(freqaiconf, exchange)
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strategy.freqai_info = freqaiconf.get("freqai", {})
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freqai = strategy.model.bridge
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freqai.live = True
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freqai.dk = FreqaiDataKitchen(freqaiconf, freqai.dd)
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timerange = TimeRange.parse_timerange("20180110-20180130")
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freqai.dk.load_all_pair_histories(timerange)
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freqai.dd.pair_dict = MagicMock()
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data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
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new_timerange = TimeRange.parse_timerange("20180120-20180130")
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freqai.train_model_in_series(
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new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange
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)
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assert (
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Path(freqai.dk.data_path / str(freqai.dk.model_filename + "_model.joblib"))
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.resolve()
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.exists()
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)
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assert (
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Path(freqai.dk.data_path / str(freqai.dk.model_filename + "_metadata.json"))
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.resolve()
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.exists()
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)
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assert (
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Path(freqai.dk.data_path / str(freqai.dk.model_filename + "_trained_df.pkl"))
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.resolve()
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.exists()
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)
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assert (
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Path(freqai.dk.data_path / str(freqai.dk.model_filename + "_svm_model.joblib"))
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.resolve()
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.exists()
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)
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shutil.rmtree(Path(freqai.dk.full_path))
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def test_start_backtesting(mocker, default_conf):
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freqaiconf = freqai_conf(copy.deepcopy(default_conf))
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freqaiconf.update({"timerange": "20180120-20180130"})
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strategy = get_patched_freqai_strategy(mocker, freqaiconf)
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exchange = get_patched_exchange(mocker, freqaiconf)
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strategy.dp = DataProvider(freqaiconf, exchange)
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strategy.freqai_info = freqaiconf.get("freqai", {})
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freqai = strategy.model.bridge
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freqai.live = False
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freqai.dk = FreqaiDataKitchen(freqaiconf, freqai.dd)
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timerange = TimeRange.parse_timerange("20180110-20180130")
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freqai.dk.load_all_pair_histories(timerange)
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sub_timerange = TimeRange.parse_timerange("20180110-20180130")
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corr_df, base_df = freqai.dk.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC")
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df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, "LTC/BTC")
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metadata = {"pair": "ADA/BTC"}
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freqai.start_backtesting(df, metadata, freqai.dk)
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model_folders = [x for x in freqai.dd.full_path.iterdir() if x.is_dir()]
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assert len(model_folders) == 5
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shutil.rmtree(Path(freqai.dk.full_path))
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def test_start_backtesting_from_existing_folder(mocker, default_conf, caplog):
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freqaiconf = freqai_conf(copy.deepcopy(default_conf))
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freqaiconf.update({"timerange": "20180120-20180130"})
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strategy = get_patched_freqai_strategy(mocker, freqaiconf)
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exchange = get_patched_exchange(mocker, freqaiconf)
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strategy.dp = DataProvider(freqaiconf, exchange)
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strategy.freqai_info = freqaiconf.get("freqai", {})
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freqai = strategy.model.bridge
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freqai.live = False
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freqai.dk = FreqaiDataKitchen(freqaiconf, freqai.dd)
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timerange = TimeRange.parse_timerange("20180110-20180130")
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freqai.dk.load_all_pair_histories(timerange)
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sub_timerange = TimeRange.parse_timerange("20180110-20180130")
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corr_df, base_df = freqai.dk.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC")
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df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, "LTC/BTC")
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metadata = {"pair": "ADA/BTC"}
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freqai.start_backtesting(df, metadata, freqai.dk)
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model_folders = [x for x in freqai.dd.full_path.iterdir() if x.is_dir()]
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assert len(model_folders) == 5
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# without deleting the exiting folder structure, re-run
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freqaiconf.update({"timerange": "20180120-20180130"})
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strategy = get_patched_freqai_strategy(mocker, freqaiconf)
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exchange = get_patched_exchange(mocker, freqaiconf)
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strategy.dp = DataProvider(freqaiconf, exchange)
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strategy.freqai_info = freqaiconf.get("freqai", {})
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freqai = strategy.model.bridge
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freqai.live = False
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freqai.dk = FreqaiDataKitchen(freqaiconf, freqai.dd)
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timerange = TimeRange.parse_timerange("20180110-20180130")
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freqai.dk.load_all_pair_histories(timerange)
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sub_timerange = TimeRange.parse_timerange("20180110-20180130")
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corr_df, base_df = freqai.dk.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC")
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df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, "LTC/BTC")
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freqai.start_backtesting(df, metadata, freqai.dk)
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assert log_has(
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"Found model at user_data/models/uniqe-id100/sub-train-ADA1517097600/cb_ada_1517097600",
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caplog,
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)
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shutil.rmtree(Path(freqai.dk.full_path))
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