mirror of
https://github.com/freqtrade/freqtrade.git
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577 lines
21 KiB
Python
577 lines
21 KiB
Python
from datetime import datetime, timezone
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from unittest.mock import MagicMock
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import pytest
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from pandas import DataFrame, Timestamp
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from freqtrade.data.dataprovider import DataProvider
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from freqtrade.enums import CandleType, RunMode
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from freqtrade.exceptions import ExchangeError, OperationalException
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from freqtrade.plugins.pairlistmanager import PairListManager
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from tests.conftest import EXMS, generate_test_data, get_patched_exchange
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@pytest.mark.parametrize(
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"candle_type",
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[
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"mark",
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"",
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],
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)
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def test_dp_ohlcv(mocker, default_conf, ohlcv_history, candle_type):
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default_conf["runmode"] = RunMode.DRY_RUN
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timeframe = default_conf["timeframe"]
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exchange = get_patched_exchange(mocker, default_conf)
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candletype = CandleType.from_string(candle_type)
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exchange._klines[("XRP/BTC", timeframe, candletype)] = ohlcv_history
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exchange._klines[("UNITTEST/BTC", timeframe, candletype)] = ohlcv_history
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dp = DataProvider(default_conf, exchange)
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assert dp.runmode == RunMode.DRY_RUN
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assert ohlcv_history.equals(dp.ohlcv("UNITTEST/BTC", timeframe, candle_type=candletype))
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assert isinstance(dp.ohlcv("UNITTEST/BTC", timeframe, candle_type=candletype), DataFrame)
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assert dp.ohlcv("UNITTEST/BTC", timeframe, candle_type=candletype) is not ohlcv_history
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assert dp.ohlcv("UNITTEST/BTC", timeframe, copy=False, candle_type=candletype) is ohlcv_history
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assert not dp.ohlcv("UNITTEST/BTC", timeframe, candle_type=candletype).empty
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assert dp.ohlcv("NONSENSE/AAA", timeframe, candle_type=candletype).empty
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# Test with and without parameter
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assert dp.ohlcv("UNITTEST/BTC", timeframe, candle_type=candletype).equals(
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dp.ohlcv("UNITTEST/BTC", candle_type=candle_type)
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)
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default_conf["runmode"] = RunMode.LIVE
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dp = DataProvider(default_conf, exchange)
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assert dp.runmode == RunMode.LIVE
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assert isinstance(dp.ohlcv("UNITTEST/BTC", timeframe, candle_type=candle_type), DataFrame)
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default_conf["runmode"] = RunMode.BACKTEST
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dp = DataProvider(default_conf, exchange)
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assert dp.runmode == RunMode.BACKTEST
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assert dp.ohlcv("UNITTEST/BTC", timeframe, candle_type=candle_type).empty
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def test_historic_ohlcv(mocker, default_conf, ohlcv_history):
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historymock = MagicMock(return_value=ohlcv_history)
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mocker.patch("freqtrade.data.dataprovider.load_pair_history", historymock)
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dp = DataProvider(default_conf, None)
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data = dp.historic_ohlcv("UNITTEST/BTC", "5m")
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assert isinstance(data, DataFrame)
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assert historymock.call_count == 1
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assert historymock.call_args_list[0][1]["timeframe"] == "5m"
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def test_historic_ohlcv_dataformat(mocker, default_conf, ohlcv_history):
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hdf5loadmock = MagicMock(return_value=ohlcv_history)
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featherloadmock = MagicMock(return_value=ohlcv_history)
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mocker.patch(
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"freqtrade.data.history.datahandlers.hdf5datahandler.HDF5DataHandler._ohlcv_load",
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hdf5loadmock,
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)
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mocker.patch(
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"freqtrade.data.history.datahandlers.featherdatahandler.FeatherDataHandler._ohlcv_load",
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featherloadmock,
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)
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default_conf["runmode"] = RunMode.BACKTEST
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exchange = get_patched_exchange(mocker, default_conf)
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dp = DataProvider(default_conf, exchange)
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data = dp.historic_ohlcv("UNITTEST/BTC", "5m")
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assert isinstance(data, DataFrame)
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hdf5loadmock.assert_not_called()
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featherloadmock.assert_called_once()
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# Switching to dataformat hdf5
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hdf5loadmock.reset_mock()
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featherloadmock.reset_mock()
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default_conf["dataformat_ohlcv"] = "hdf5"
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dp = DataProvider(default_conf, exchange)
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data = dp.historic_ohlcv("UNITTEST/BTC", "5m")
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assert isinstance(data, DataFrame)
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hdf5loadmock.assert_called_once()
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featherloadmock.assert_not_called()
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@pytest.mark.parametrize(
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"candle_type",
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[
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"mark",
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"futures",
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"",
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],
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)
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def test_get_pair_dataframe(mocker, default_conf, ohlcv_history, candle_type):
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default_conf["runmode"] = RunMode.DRY_RUN
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timeframe = default_conf["timeframe"]
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exchange = get_patched_exchange(mocker, default_conf)
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candletype = CandleType.from_string(candle_type)
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exchange._klines[("XRP/BTC", timeframe, candletype)] = ohlcv_history
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exchange._klines[("UNITTEST/BTC", timeframe, candletype)] = ohlcv_history
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dp = DataProvider(default_conf, exchange)
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assert dp.runmode == RunMode.DRY_RUN
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assert ohlcv_history.equals(
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dp.get_pair_dataframe("UNITTEST/BTC", timeframe, candle_type=candle_type)
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)
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assert ohlcv_history.equals(
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dp.get_pair_dataframe("UNITTEST/BTC", timeframe, candle_type=candletype)
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)
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assert isinstance(
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dp.get_pair_dataframe("UNITTEST/BTC", timeframe, candle_type=candle_type), DataFrame
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)
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assert (
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dp.get_pair_dataframe("UNITTEST/BTC", timeframe, candle_type=candle_type)
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is not ohlcv_history
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)
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assert not dp.get_pair_dataframe("UNITTEST/BTC", timeframe, candle_type=candle_type).empty
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assert dp.get_pair_dataframe("NONSENSE/AAA", timeframe, candle_type=candle_type).empty
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# Test with and without parameter
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assert dp.get_pair_dataframe("UNITTEST/BTC", timeframe, candle_type=candle_type).equals(
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dp.get_pair_dataframe("UNITTEST/BTC", candle_type=candle_type)
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)
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default_conf["runmode"] = RunMode.LIVE
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dp = DataProvider(default_conf, exchange)
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assert dp.runmode == RunMode.LIVE
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assert isinstance(
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dp.get_pair_dataframe("UNITTEST/BTC", timeframe, candle_type=candle_type), DataFrame
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)
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assert dp.get_pair_dataframe("NONSENSE/AAA", timeframe, candle_type=candle_type).empty
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historymock = MagicMock(return_value=ohlcv_history)
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mocker.patch("freqtrade.data.dataprovider.load_pair_history", historymock)
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default_conf["runmode"] = RunMode.BACKTEST
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dp = DataProvider(default_conf, exchange)
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assert dp.runmode == RunMode.BACKTEST
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df = dp.get_pair_dataframe("UNITTEST/BTC", timeframe, candle_type=candle_type)
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assert isinstance(df, DataFrame)
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assert len(df) == 3 # ohlcv_history mock has just 3 rows
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dp._set_dataframe_max_date(ohlcv_history.iloc[-1]["date"])
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df = dp.get_pair_dataframe("UNITTEST/BTC", timeframe, candle_type=candle_type)
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assert isinstance(df, DataFrame)
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assert len(df) == 2 # ohlcv_history is limited to 2 rows now
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def test_available_pairs(mocker, default_conf, ohlcv_history):
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exchange = get_patched_exchange(mocker, default_conf)
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timeframe = default_conf["timeframe"]
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exchange._klines[("XRP/BTC", timeframe)] = ohlcv_history
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exchange._klines[("UNITTEST/BTC", timeframe)] = ohlcv_history
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dp = DataProvider(default_conf, exchange)
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assert len(dp.available_pairs) == 2
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assert dp.available_pairs == [
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("XRP/BTC", timeframe),
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("UNITTEST/BTC", timeframe),
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]
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def test_producer_pairs(default_conf):
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dataprovider = DataProvider(default_conf, None)
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producer = "default"
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whitelist = ["XRP/BTC", "ETH/BTC"]
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assert len(dataprovider.get_producer_pairs(producer)) == 0
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dataprovider._set_producer_pairs(whitelist, producer)
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assert len(dataprovider.get_producer_pairs(producer)) == 2
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new_whitelist = ["BTC/USDT"]
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dataprovider._set_producer_pairs(new_whitelist, producer)
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assert dataprovider.get_producer_pairs(producer) == new_whitelist
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assert dataprovider.get_producer_pairs("bad") == []
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def test_get_producer_df(default_conf):
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dataprovider = DataProvider(default_conf, None)
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ohlcv_history = generate_test_data("5m", 150)
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pair = "BTC/USDT"
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timeframe = default_conf["timeframe"]
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candle_type = CandleType.SPOT
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empty_la = datetime.fromtimestamp(0, tz=timezone.utc)
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now = datetime.now(timezone.utc)
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# no data has been added, any request should return an empty dataframe
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dataframe, la = dataprovider.get_producer_df(pair, timeframe, candle_type)
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assert dataframe.empty
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assert la == empty_la
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# the data is added, should return that added dataframe
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dataprovider._add_external_df(pair, ohlcv_history, now, timeframe, candle_type)
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dataframe, la = dataprovider.get_producer_df(pair, timeframe, candle_type)
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assert len(dataframe) > 0
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assert la > empty_la
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# no data on this producer, should return empty dataframe
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dataframe, la = dataprovider.get_producer_df(pair, producer_name="bad")
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assert dataframe.empty
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assert la == empty_la
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# non existent timeframe, empty dataframe
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_dataframe, la = dataprovider.get_producer_df(pair, timeframe="1h")
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assert dataframe.empty
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assert la == empty_la
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def test_emit_df(mocker, default_conf, ohlcv_history):
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mocker.patch("freqtrade.rpc.rpc_manager.RPCManager.__init__", MagicMock())
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rpc_mock = mocker.patch("freqtrade.rpc.rpc_manager.RPCManager", MagicMock())
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send_mock = mocker.patch("freqtrade.rpc.rpc_manager.RPCManager.send_msg", MagicMock())
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dataprovider = DataProvider(default_conf, exchange=None, rpc=rpc_mock)
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dataprovider_no_rpc = DataProvider(default_conf, exchange=None)
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pair = "BTC/USDT"
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# No emit yet
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assert send_mock.call_count == 0
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# Rpc is added, we call emit, should call send_msg
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dataprovider._emit_df(pair, ohlcv_history, False)
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assert send_mock.call_count == 1
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send_mock.reset_mock()
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dataprovider._emit_df(pair, ohlcv_history, True)
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assert send_mock.call_count == 2
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send_mock.reset_mock()
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# No rpc added, emit called, should not call send_msg
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dataprovider_no_rpc._emit_df(pair, ohlcv_history, False)
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assert send_mock.call_count == 0
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def test_refresh(mocker, default_conf):
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refresh_mock = MagicMock()
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mocker.patch(f"{EXMS}.refresh_latest_ohlcv", refresh_mock)
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exchange = get_patched_exchange(mocker, default_conf, id="binance")
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timeframe = default_conf["timeframe"]
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pairs = [("XRP/BTC", timeframe), ("UNITTEST/BTC", timeframe)]
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pairs_non_trad = [("ETH/USDT", timeframe), ("BTC/TUSD", "1h")]
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dp = DataProvider(default_conf, exchange)
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dp.refresh(pairs)
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assert refresh_mock.call_count == 1
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assert len(refresh_mock.call_args[0]) == 1
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assert len(refresh_mock.call_args[0][0]) == len(pairs)
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assert refresh_mock.call_args[0][0] == pairs
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refresh_mock.reset_mock()
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dp.refresh(pairs, pairs_non_trad)
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assert refresh_mock.call_count == 1
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assert len(refresh_mock.call_args[0]) == 1
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assert len(refresh_mock.call_args[0][0]) == len(pairs) + len(pairs_non_trad)
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assert refresh_mock.call_args[0][0] == pairs + pairs_non_trad
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def test_orderbook(mocker, default_conf, order_book_l2):
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api_mock = MagicMock()
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api_mock.fetch_l2_order_book = order_book_l2
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exchange = get_patched_exchange(mocker, default_conf, api_mock=api_mock)
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dp = DataProvider(default_conf, exchange)
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res = dp.orderbook("ETH/BTC", 5)
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assert order_book_l2.call_count == 1
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assert order_book_l2.call_args_list[0][0][0] == "ETH/BTC"
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assert order_book_l2.call_args_list[0][0][1] >= 5
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assert isinstance(res, dict)
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assert "bids" in res
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assert "asks" in res
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def test_market(mocker, default_conf, markets):
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api_mock = MagicMock()
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api_mock.markets = markets
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exchange = get_patched_exchange(mocker, default_conf, api_mock=api_mock)
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dp = DataProvider(default_conf, exchange)
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res = dp.market("ETH/BTC")
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assert isinstance(res, dict)
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assert "symbol" in res
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assert res["symbol"] == "ETH/BTC"
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res = dp.market("UNITTEST/BTC")
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assert res is None
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def test_ticker(mocker, default_conf, tickers):
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ticker_mock = MagicMock(return_value=tickers()["ETH/BTC"])
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mocker.patch(f"{EXMS}.fetch_ticker", ticker_mock)
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exchange = get_patched_exchange(mocker, default_conf)
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dp = DataProvider(default_conf, exchange)
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res = dp.ticker("ETH/BTC")
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assert isinstance(res, dict)
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assert "symbol" in res
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assert res["symbol"] == "ETH/BTC"
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ticker_mock = MagicMock(side_effect=ExchangeError("Pair not found"))
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mocker.patch(f"{EXMS}.fetch_ticker", ticker_mock)
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exchange = get_patched_exchange(mocker, default_conf)
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dp = DataProvider(default_conf, exchange)
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res = dp.ticker("UNITTEST/BTC")
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assert res == {}
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def test_current_whitelist(mocker, default_conf, tickers):
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# patch default conf to volumepairlist
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default_conf["pairlists"][0] = {"method": "VolumePairList", "number_assets": 5}
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mocker.patch.multiple(EXMS, exchange_has=MagicMock(return_value=True), get_tickers=tickers)
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exchange = get_patched_exchange(mocker, default_conf)
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pairlist = PairListManager(exchange, default_conf)
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dp = DataProvider(default_conf, exchange, pairlist)
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# Simulate volumepairs from exchange.
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pairlist.refresh_pairlist()
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assert dp.current_whitelist() == pairlist._whitelist
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# The identity of the 2 lists should not be identical, but a copy
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assert dp.current_whitelist() is not pairlist._whitelist
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with pytest.raises(OperationalException):
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dp = DataProvider(default_conf, exchange)
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dp.current_whitelist()
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def test_get_analyzed_dataframe(mocker, default_conf, ohlcv_history):
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default_conf["runmode"] = RunMode.DRY_RUN
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timeframe = default_conf["timeframe"]
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exchange = get_patched_exchange(mocker, default_conf)
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dp = DataProvider(default_conf, exchange)
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dp._set_cached_df("XRP/BTC", timeframe, ohlcv_history, CandleType.SPOT)
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dp._set_cached_df("UNITTEST/BTC", timeframe, ohlcv_history, CandleType.SPOT)
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assert dp.runmode == RunMode.DRY_RUN
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dataframe, time = dp.get_analyzed_dataframe("UNITTEST/BTC", timeframe)
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assert ohlcv_history.equals(dataframe)
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assert isinstance(time, datetime)
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dataframe, time = dp.get_analyzed_dataframe("XRP/BTC", timeframe)
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assert ohlcv_history.equals(dataframe)
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assert isinstance(time, datetime)
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dataframe, time = dp.get_analyzed_dataframe("NOTHING/BTC", timeframe)
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assert dataframe.empty
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assert isinstance(time, datetime)
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assert time == datetime(1970, 1, 1, tzinfo=timezone.utc)
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# Test backtest mode
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default_conf["runmode"] = RunMode.BACKTEST
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dp._set_dataframe_max_index(1)
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dataframe, time = dp.get_analyzed_dataframe("XRP/BTC", timeframe)
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assert len(dataframe) == 1
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dp._set_dataframe_max_index(2)
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dataframe, time = dp.get_analyzed_dataframe("XRP/BTC", timeframe)
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assert len(dataframe) == 2
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dp._set_dataframe_max_index(3)
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dataframe, time = dp.get_analyzed_dataframe("XRP/BTC", timeframe)
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assert len(dataframe) == 3
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dp._set_dataframe_max_index(500)
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dataframe, time = dp.get_analyzed_dataframe("XRP/BTC", timeframe)
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assert len(dataframe) == len(ohlcv_history)
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def test_no_exchange_mode(default_conf):
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dp = DataProvider(default_conf, None)
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message = "Exchange is not available to DataProvider."
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with pytest.raises(OperationalException, match=message):
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dp.refresh([()])
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with pytest.raises(OperationalException, match=message):
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dp.ohlcv("XRP/USDT", "5m", "")
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with pytest.raises(OperationalException, match=message):
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dp.market("XRP/USDT")
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with pytest.raises(OperationalException, match=message):
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dp.ticker("XRP/USDT")
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with pytest.raises(OperationalException, match=message):
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dp.orderbook("XRP/USDT", 20)
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with pytest.raises(OperationalException, match=message):
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dp.available_pairs()
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def test_dp_send_msg(default_conf):
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default_conf["runmode"] = RunMode.DRY_RUN
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default_conf["timeframe"] = "1h"
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dp = DataProvider(default_conf, None)
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msg = "Test message"
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dp.send_msg(msg)
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assert msg in dp._msg_queue
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dp._msg_queue.pop()
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assert msg not in dp._msg_queue
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# Message is not resent due to caching
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dp.send_msg(msg)
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assert msg not in dp._msg_queue
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dp.send_msg(msg, always_send=True)
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assert msg in dp._msg_queue
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default_conf["runmode"] = RunMode.BACKTEST
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dp = DataProvider(default_conf, None)
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dp.send_msg(msg, always_send=True)
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assert msg not in dp._msg_queue
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def test_dp__add_external_df(default_conf_usdt):
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timeframe = "1h"
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default_conf_usdt["timeframe"] = timeframe
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dp = DataProvider(default_conf_usdt, None)
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df = generate_test_data(timeframe, 24, "2022-01-01 00:00:00+00:00")
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last_analyzed = datetime.now(timezone.utc)
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|
|
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res = dp._add_external_df("ETH/USDT", df, last_analyzed, timeframe, CandleType.SPOT)
|
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assert res[0] is False
|
|
# Why 1000 ??
|
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assert res[1] == 1000
|
|
|
|
# Hard add dataframe
|
|
dp._replace_external_df("ETH/USDT", df, last_analyzed, timeframe, CandleType.SPOT)
|
|
# BTC is not stored yet
|
|
res = dp._add_external_df("BTC/USDT", df, last_analyzed, timeframe, CandleType.SPOT)
|
|
assert res[0] is False
|
|
df_res, _ = dp.get_producer_df("ETH/USDT", timeframe, CandleType.SPOT)
|
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assert len(df_res) == 24
|
|
|
|
# Add the same dataframe again - dataframe size shall not change.
|
|
res = dp._add_external_df("ETH/USDT", df, last_analyzed, timeframe, CandleType.SPOT)
|
|
assert res[0] is True
|
|
assert isinstance(res[1], int)
|
|
assert res[1] == 0
|
|
df, _ = dp.get_producer_df("ETH/USDT", timeframe, CandleType.SPOT)
|
|
assert len(df) == 24
|
|
|
|
# Add a new day.
|
|
df2 = generate_test_data(timeframe, 24, "2022-01-02 00:00:00+00:00")
|
|
|
|
res = dp._add_external_df("ETH/USDT", df2, last_analyzed, timeframe, CandleType.SPOT)
|
|
assert res[0] is True
|
|
assert isinstance(res[1], int)
|
|
assert res[1] == 0
|
|
df, _ = dp.get_producer_df("ETH/USDT", timeframe, CandleType.SPOT)
|
|
assert len(df) == 48
|
|
|
|
# Add a dataframe with a 12 hour offset - so 12 candles are overlapping, and 12 valid.
|
|
df3 = generate_test_data(timeframe, 24, "2022-01-02 12:00:00+00:00")
|
|
|
|
res = dp._add_external_df("ETH/USDT", df3, last_analyzed, timeframe, CandleType.SPOT)
|
|
assert res[0] is True
|
|
assert isinstance(res[1], int)
|
|
assert res[1] == 0
|
|
df, _ = dp.get_producer_df("ETH/USDT", timeframe, CandleType.SPOT)
|
|
# New length = 48 + 12 (since we have a 12 hour offset).
|
|
assert len(df) == 60
|
|
assert df.iloc[-1]["date"] == df3.iloc[-1]["date"]
|
|
assert df.iloc[-1]["date"] == Timestamp("2022-01-03 11:00:00+00:00")
|
|
|
|
# Generate 1 new candle
|
|
df4 = generate_test_data(timeframe, 1, "2022-01-03 12:00:00+00:00")
|
|
res = dp._add_external_df("ETH/USDT", df4, last_analyzed, timeframe, CandleType.SPOT)
|
|
# assert res[0] is True
|
|
# assert res[1] == 0
|
|
df, _ = dp.get_producer_df("ETH/USDT", timeframe, CandleType.SPOT)
|
|
# New length = 61 + 1
|
|
assert len(df) == 61
|
|
assert df.iloc[-2]["date"] == Timestamp("2022-01-03 11:00:00+00:00")
|
|
assert df.iloc[-1]["date"] == Timestamp("2022-01-03 12:00:00+00:00")
|
|
|
|
# Gap in the data ...
|
|
df4 = generate_test_data(timeframe, 1, "2022-01-05 00:00:00+00:00")
|
|
res = dp._add_external_df("ETH/USDT", df4, last_analyzed, timeframe, CandleType.SPOT)
|
|
assert res[0] is False
|
|
# 36 hours - from 2022-01-03 12:00:00+00:00 to 2022-01-05 00:00:00+00:00
|
|
assert isinstance(res[1], int)
|
|
assert res[1] == 36
|
|
df, _ = dp.get_producer_df("ETH/USDT", timeframe, CandleType.SPOT)
|
|
# New length = 61 + 1
|
|
assert len(df) == 61
|
|
|
|
# Empty dataframe
|
|
df4 = generate_test_data(timeframe, 0, "2022-01-05 00:00:00+00:00")
|
|
res = dp._add_external_df("ETH/USDT", df4, last_analyzed, timeframe, CandleType.SPOT)
|
|
assert res[0] is False
|
|
# 36 hours - from 2022-01-03 12:00:00+00:00 to 2022-01-05 00:00:00+00:00
|
|
assert isinstance(res[1], int)
|
|
assert res[1] == 0
|
|
|
|
|
|
def test_dp_get_required_startup(default_conf_usdt):
|
|
timeframe = "1h"
|
|
default_conf_usdt["timeframe"] = timeframe
|
|
dp = DataProvider(default_conf_usdt, None)
|
|
|
|
# No FreqAI config
|
|
assert dp.get_required_startup("5m") == 0
|
|
assert dp.get_required_startup("1h") == 0
|
|
assert dp.get_required_startup("1d") == 0
|
|
|
|
dp._config["startup_candle_count"] = 20
|
|
assert dp.get_required_startup("5m") == 20
|
|
assert dp.get_required_startup("1h") == 20
|
|
assert dp.get_required_startup("1h") == 20
|
|
|
|
# With freqAI config
|
|
|
|
dp._config["freqai"] = {
|
|
"enabled": True,
|
|
"train_period_days": 20,
|
|
"feature_parameters": {
|
|
"indicator_periods_candles": [
|
|
5,
|
|
20,
|
|
]
|
|
},
|
|
}
|
|
assert dp.get_required_startup("5m") == 5780
|
|
assert dp.get_required_startup("1h") == 500
|
|
assert dp.get_required_startup("1d") == 40
|
|
|
|
# FreqAI kindof ignores startup_candle_count if it's below indicator_periods_candles
|
|
dp._config["startup_candle_count"] = 0
|
|
assert dp.get_required_startup("5m") == 5780
|
|
assert dp.get_required_startup("1h") == 500
|
|
assert dp.get_required_startup("1d") == 40
|
|
|
|
dp._config["freqai"]["feature_parameters"]["indicator_periods_candles"][1] = 50
|
|
assert dp.get_required_startup("5m") == 5810
|
|
assert dp.get_required_startup("1h") == 530
|
|
assert dp.get_required_startup("1d") == 70
|
|
|
|
# scenario from issue https://github.com/freqtrade/freqtrade/issues/9432
|
|
dp._config["freqai"] = {
|
|
"enabled": True,
|
|
"train_period_days": 180,
|
|
"feature_parameters": {
|
|
"indicator_periods_candles": [
|
|
10,
|
|
20,
|
|
]
|
|
},
|
|
}
|
|
dp._config["startup_candle_count"] = 40
|
|
assert dp.get_required_startup("5m") == 51880
|
|
assert dp.get_required_startup("1h") == 4360
|
|
assert dp.get_required_startup("1d") == 220
|