# pragma pylint: disable=missing-docstring, C0103 import logging from pathlib import Path from shutil import copyfile import pytest from freqtrade.configuration.timerange import TimeRange from freqtrade.data.converter import (convert_ohlcv_format, convert_trades_format, ohlcv_fill_up_missing_data, ohlcv_to_dataframe, trades_dict_to_list, trades_remove_duplicates, trades_to_ohlcv, trim_dataframe) from freqtrade.data.history import (get_timerange, load_data, load_pair_history, validate_backtest_data) from freqtrade.data.history.idatahandler import IDataHandler from freqtrade.enums import CandleType from tests.conftest import log_has, log_has_re from tests.data.test_history import _clean_test_file def test_dataframe_correct_columns(result): assert result.columns.tolist() == ['date', 'open', 'high', 'low', 'close', 'volume'] def test_ohlcv_to_dataframe(ohlcv_history_list, caplog): columns = ['date', 'open', 'high', 'low', 'close', 'volume'] caplog.set_level(logging.DEBUG) # Test file with BV data dataframe = ohlcv_to_dataframe(ohlcv_history_list, '5m', pair="UNITTEST/BTC", fill_missing=True) assert dataframe.columns.tolist() == columns assert log_has('Converting candle (OHLCV) data to dataframe for pair UNITTEST/BTC.', caplog) def test_trades_to_ohlcv(ohlcv_history_list, caplog): caplog.set_level(logging.DEBUG) with pytest.raises(ValueError, match="Trade-list empty."): trades_to_ohlcv([], '1m') trades = [ [1570752011620, "13519807", None, "sell", 0.00141342, 23.0, 0.03250866], [1570752011620, "13519808", None, "sell", 0.00141266, 54.0, 0.07628364], [1570752017964, "13519809", None, "sell", 0.00141266, 8.0, 0.01130128]] df = trades_to_ohlcv(trades, '1m') assert not df.empty assert len(df) == 1 assert 'open' in df.columns assert 'high' in df.columns assert 'low' in df.columns assert 'close' in df.columns assert df.loc[:, 'high'][0] == 0.00141342 assert df.loc[:, 'low'][0] == 0.00141266 def test_ohlcv_fill_up_missing_data(testdatadir, caplog): data = load_pair_history(datadir=testdatadir, timeframe='1m', pair='UNITTEST/BTC', fill_up_missing=False) caplog.set_level(logging.DEBUG) data2 = ohlcv_fill_up_missing_data(data, '1m', 'UNITTEST/BTC') assert len(data2) > len(data) # Column names should not change assert (data.columns == data2.columns).all() assert log_has_re(f"Missing data fillup for UNITTEST/BTC: before: " f"{len(data)} - after: {len(data2)}.*", caplog) # Test fillup actually fixes invalid backtest data min_date, max_date = get_timerange({'UNITTEST/BTC': data}) assert validate_backtest_data(data, 'UNITTEST/BTC', min_date, max_date, 1) assert not validate_backtest_data(data2, 'UNITTEST/BTC', min_date, max_date, 1) def test_ohlcv_fill_up_missing_data2(caplog): timeframe = '5m' ticks = [ [ 1511686200000, # 8:50:00 8.794e-05, # open 8.948e-05, # high 8.794e-05, # low 8.88e-05, # close 2255, # volume (in quote currency) ], [ 1511686500000, # 8:55:00 8.88e-05, 8.942e-05, 8.88e-05, 8.893e-05, 9911, ], [ 1511687100000, # 9:05:00 8.891e-05, 8.893e-05, 8.875e-05, 8.877e-05, 2251 ], [ 1511687400000, # 9:10:00 8.877e-05, 8.883e-05, 8.895e-05, 8.817e-05, 123551 ] ] # Generate test-data without filling missing data = ohlcv_to_dataframe(ticks, timeframe, pair="UNITTEST/BTC", fill_missing=False) assert len(data) == 3 caplog.set_level(logging.DEBUG) data2 = ohlcv_fill_up_missing_data(data, timeframe, "UNITTEST/BTC") assert len(data2) == 4 # 3rd candle has been filled row = data2.loc[2, :] assert row['volume'] == 0 # close should match close of previous candle assert row['close'] == data.loc[1, 'close'] assert row['open'] == row['close'] assert row['high'] == row['close'] assert row['low'] == row['close'] # Column names should not change assert (data.columns == data2.columns).all() assert log_has_re(f"Missing data fillup for UNITTEST/BTC: before: " f"{len(data)} - after: {len(data2)}.*", caplog) def test_ohlcv_drop_incomplete(caplog): timeframe = '1d' ticks = [ [ 1559750400000, # 2019-06-04 8.794e-05, # open 8.948e-05, # high 8.794e-05, # low 8.88e-05, # close 2255, # volume (in quote currency) ], [ 1559836800000, # 2019-06-05 8.88e-05, 8.942e-05, 8.88e-05, 8.893e-05, 9911, ], [ 1559923200000, # 2019-06-06 8.891e-05, 8.893e-05, 8.875e-05, 8.877e-05, 2251 ], [ 1560009600000, # 2019-06-07 8.877e-05, 8.883e-05, 8.895e-05, 8.817e-05, 123551 ] ] caplog.set_level(logging.DEBUG) data = ohlcv_to_dataframe(ticks, timeframe, pair="UNITTEST/BTC", fill_missing=False, drop_incomplete=False) assert len(data) == 4 assert not log_has("Dropping last candle", caplog) # Drop last candle data = ohlcv_to_dataframe(ticks, timeframe, pair="UNITTEST/BTC", fill_missing=False, drop_incomplete=True) assert len(data) == 3 assert log_has("Dropping last candle", caplog) def test_trim_dataframe(testdatadir) -> None: data = load_data( datadir=testdatadir, timeframe='1m', pairs=['UNITTEST/BTC'] )['UNITTEST/BTC'] min_date = int(data.iloc[0]['date'].timestamp()) max_date = int(data.iloc[-1]['date'].timestamp()) data_modify = data.copy() # Remove first 30 minutes (1800 s) tr = TimeRange('date', None, min_date + 1800, 0) data_modify = trim_dataframe(data_modify, tr) assert not data_modify.equals(data) assert len(data_modify) < len(data) assert len(data_modify) == len(data) - 30 assert all(data_modify.iloc[-1] == data.iloc[-1]) assert all(data_modify.iloc[0] == data.iloc[30]) data_modify = data.copy() tr = TimeRange('date', None, min_date + 1800, 0) # Remove first 20 candles - ignores min date data_modify = trim_dataframe(data_modify, tr, startup_candles=20) assert not data_modify.equals(data) assert len(data_modify) < len(data) assert len(data_modify) == len(data) - 20 assert all(data_modify.iloc[-1] == data.iloc[-1]) assert all(data_modify.iloc[0] == data.iloc[20]) data_modify = data.copy() # Remove last 30 minutes (1800 s) tr = TimeRange(None, 'date', 0, max_date - 1800) data_modify = trim_dataframe(data_modify, tr) assert not data_modify.equals(data) assert len(data_modify) < len(data) assert len(data_modify) == len(data) - 30 assert all(data_modify.iloc[0] == data.iloc[0]) assert all(data_modify.iloc[-1] == data.iloc[-31]) data_modify = data.copy() # Remove first 25 and last 30 minutes (1800 s) tr = TimeRange('date', 'date', min_date + 1500, max_date - 1800) data_modify = trim_dataframe(data_modify, tr) assert not data_modify.equals(data) assert len(data_modify) < len(data) assert len(data_modify) == len(data) - 55 # first row matches 25th original row assert all(data_modify.iloc[0] == data.iloc[25]) def test_trades_remove_duplicates(trades_history): trades_history1 = trades_history * 3 assert len(trades_history1) == len(trades_history) * 3 res = trades_remove_duplicates(trades_history1) assert len(res) == len(trades_history) for i, t in enumerate(res): assert t == trades_history[i] def test_trades_dict_to_list(fetch_trades_result): res = trades_dict_to_list(fetch_trades_result) assert isinstance(res, list) assert isinstance(res[0], list) for i, t in enumerate(res): assert t[0] == fetch_trades_result[i]['timestamp'] assert t[1] == fetch_trades_result[i]['id'] assert t[2] == fetch_trades_result[i]['type'] assert t[3] == fetch_trades_result[i]['side'] assert t[4] == fetch_trades_result[i]['price'] assert t[5] == fetch_trades_result[i]['amount'] assert t[6] == fetch_trades_result[i]['cost'] def test_convert_trades_format(default_conf, testdatadir, tmpdir): tmpdir1 = Path(tmpdir) files = [{'old': tmpdir1 / "XRP_ETH-trades.json.gz", 'new': tmpdir1 / "XRP_ETH-trades.json"}, {'old': tmpdir1 / "XRP_OLD-trades.json.gz", 'new': tmpdir1 / "XRP_OLD-trades.json"}, ] for file in files: copyfile(testdatadir / file['old'].name, file['old']) assert not file['new'].exists() default_conf['datadir'] = tmpdir1 convert_trades_format(default_conf, convert_from='jsongz', convert_to='json', erase=False) for file in files: assert file['new'].exists() assert file['old'].exists() # Remove original file file['old'].unlink() # Convert back convert_trades_format(default_conf, convert_from='json', convert_to='jsongz', erase=True) for file in files: assert file['old'].exists() assert not file['new'].exists() _clean_test_file(file['old']) if file['new'].exists(): file['new'].unlink() @pytest.mark.parametrize('file_base,candletype', [ (['XRP_ETH-5m', 'XRP_ETH-1m'], CandleType.SPOT), (['UNITTEST_USDT-1h-mark', 'XRP_USDT-1h-mark'], CandleType.MARK), (['XRP_USDT-1h-futures'], CandleType.FUTURES), ]) def test_convert_ohlcv_format(default_conf, testdatadir, tmpdir, file_base, candletype): tmpdir1 = Path(tmpdir) prependix = '' if candletype == CandleType.SPOT else 'futures/' files_orig = [] files_temp = [] files_new = [] for file in file_base: file_orig = testdatadir / f"{prependix}{file}.json" file_temp = tmpdir1 / f"{prependix}{file}.json" file_new = tmpdir1 / f"{prependix}{file}.json.gz" IDataHandler.create_dir_if_needed(file_temp) copyfile(file_orig, file_temp) files_orig.append(file_orig) files_temp.append(file_temp) files_new.append(file_new) default_conf['datadir'] = tmpdir1 default_conf['pairs'] = ['XRP_ETH', 'XRP_USDT', 'UNITTEST_USDT'] default_conf['timeframes'] = ['1m', '5m', '1h'] assert not file_new.exists() convert_ohlcv_format( default_conf, convert_from='json', convert_to='jsongz', erase=False, candle_type=candletype ) for file in (files_temp + files_new): assert file.exists() # Remove original files for file in (files_temp): file.unlink() # Convert back convert_ohlcv_format( default_conf, convert_from='jsongz', convert_to='json', erase=True, candle_type=candletype ) for file in (files_temp): assert file.exists() for file in (files_new): assert not file.exists()