def convert_trades_to_ohlcv(
pairs: List[str],
timeframes: List[str],
datadir: Path,
timerange: TimeRange,
erase: bool = False,
data_format_ohlcv: str = 'json',
data_format_trades: str = 'jsongz',
candle_type: CandleType = CandleType.SPOT
) -> None:
"""
Convert stored trades data to ohlcv data
"""
data_handler_trades = get_datahandler(datadir, data_format=data_format_trades)
data_handler_ohlcv = get_datahandler(datadir, data_format=data_format_ohlcv)
for pair in pairs:
trades = data_handler_trades.trades_load(pair)
for timeframe in timeframes:
if erase:
if data_handler_ohlcv.ohlcv_purge(pair, timeframe, candle_type=candle_type):
logger.info(f'Deleting existing data for pair {pair}, interval {timeframe}.')
try:
ohlcv = trades_to_ohlcv(trades, timeframe)
# Store ohlcv
data_handler_ohlcv.ohlcv_store(pair, timeframe, data=ohlcv, candle_type=candle_type)
except ValueError:
logger.exception(f'Could not convert {pair} to OHLCV.')
def convert_trades_to_ohlcv(pairs: List[str],
timeframes: List[str],
datadir: Path,
timerange: TimeRange,
erase: bool = False,
data_format_ohlcv: str = 'json',
data_format_trades: str = 'jsongz') -> None:
"""
Convert stored trades data to ohlcv data
"""
data_handler_trades = get_datahandler(datadir,
data_format=data_format_trades)
data_handler_ohlcv = get_datahandler(datadir,
data_format=data_format_ohlcv)
for pair in pairs:
trades = data_handler_trades.trades_load(pair)
for timeframe in timeframes:
if erase:
if data_handler_ohlcv.ohlcv_purge(pair, timeframe):
logger.info(
f'Deleting existing data for pair {pair}, interval {timeframe}.'
)
ohlcv = trades_to_ohlcv(trades, timeframe)
# Store ohlcv
data_handler_ohlcv.ohlcv_store(pair, timeframe, data=ohlcv)
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 convert_trades_to_ohlcv(pairs: List[str], timeframes: List[str],
datadir: Path, timerange: TimeRange, erase=False) -> None:
"""
Convert stored trades data to ohlcv data
"""
for pair in pairs:
trades = load_trades_file(datadir, pair)
for timeframe in timeframes:
ohlcv_file = pair_data_filename(datadir, pair, timeframe)
if erase and ohlcv_file.exists():
logger.info(f'Deleting existing data for pair {pair}, interval {timeframe}.')
ohlcv_file.unlink()
ohlcv = trades_to_ohlcv(trades, timeframe)
# Store ohlcv
store_tickerdata_file(datadir, pair, timeframe, data=ohlcv)