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Improve behavior for convert-data

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This commit is contained in:
Matthias 2023-07-09 15:28:05 +02:00
parent 5a43dd4766
commit 448f02960f
2 changed files with 43 additions and 39 deletions
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10
freqtrade/commands/data_commands.py
View File

@ -7,7 +7,7 @@ from freqtrade.configuration import TimeRange, setup_utils_configuration
from freqtrade.constants import DATETIME_PRINT_FORMAT, DL_DATA_TIMEFRAMES, Config
from freqtrade.data.converter import convert_ohlcv_format, convert_trades_format
from freqtrade.data.history import convert_trades_to_ohlcv, download_data_main
from freqtrade.enums import CandleType, RunMode, TradingMode
from freqtrade.enums import RunMode, TradingMode
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import timeframe_to_minutes
from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
@ -88,11 +88,9 @@ def start_convert_data(args: Dict[str, Any], ohlcv: bool = True) -> None:
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
if ohlcv:
migrate_binance_futures_data(config)
candle_types = [CandleType.from_string(ct) for ct in config.get('candle_types', ['spot'])]
for candle_type in candle_types:
convert_ohlcv_format(config,
convert_from=args['format_from'], convert_to=args['format_to'],
erase=args['erase'], candle_type=candle_type)
convert_ohlcv_format(config,
convert_from=args['format_from'], convert_to=args['format_to'],
erase=args['erase'])
else:
convert_trades_format(config,
convert_from=args['format_from'], convert_to=args['format_to'],

72
freqtrade/data/converter.py
View File

@ -11,7 +11,7 @@ import pandas as pd
from pandas import DataFrame, to_datetime
from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, DEFAULT_TRADES_COLUMNS, Config, TradeList
from freqtrade.enums import CandleType
from freqtrade.enums import CandleType, TradingMode
logger = logging.getLogger(__name__)
@ -264,7 +264,6 @@ def convert_ohlcv_format(
convert_from: str,
convert_to: str,
erase: bool,
candle_type: CandleType
):
"""
Convert OHLCV from one format to another
@ -272,7 +271,6 @@ def convert_ohlcv_format(
:param convert_from: Source format
:param convert_to: Target format
:param erase: Erase source data (does not apply if source and target format are identical)
:param candle_type: Any of the enum CandleType (must match trading mode!)
"""
from freqtrade.data.history.idatahandler import get_datahandler
src = get_datahandler(config['datadir'], convert_from)
@ -280,37 +278,45 @@ def convert_ohlcv_format(
timeframes = config.get('timeframes', [config.get('timeframe')])
logger.info(f"Converting candle (OHLCV) for timeframe {timeframes}")
if 'pairs' not in config:
config['pairs'] = []
# Check timeframes or fall back to timeframe.
for timeframe in timeframes:
config['pairs'].extend(src.ohlcv_get_pairs(
config['datadir'],
timeframe,
candle_type=candle_type
))
config['pairs'] = sorted(set(config['pairs']))
logger.info(f"Converting candle (OHLCV) data for {config['pairs']}")
candle_types = [CandleType.from_string(ct) for ct in config.get('candle_types', [
c.value for c in CandleType])]
logger.info(candle_types)
paircombs = src.ohlcv_get_available_data(config['datadir'], TradingMode.SPOT)
paircombs.extend(src.ohlcv_get_available_data(config['datadir'], TradingMode.FUTURES))
for timeframe in timeframes:
for pair in config['pairs']:
data = src.ohlcv_load(pair=pair, timeframe=timeframe,
timerange=None,
fill_missing=False,
drop_incomplete=False,
startup_candles=0,
candle_type=candle_type)
logger.info(f"Converting {len(data)} {timeframe} {candle_type} candles for {pair}")
if len(data) > 0:
trg.ohlcv_store(
pair=pair,
timeframe=timeframe,
data=data,
candle_type=candle_type
)
if erase and convert_from != convert_to:
logger.info(f"Deleting source data for {pair} / {timeframe}")
src.ohlcv_purge(pair=pair, timeframe=timeframe, candle_type=candle_type)
if 'pairs' in config:
# Filter pairs
paircombs = [comb for comb in paircombs if comb[0] in config['pairs']]
if 'timeframes' in config:
paircombs = [comb for comb in paircombs if comb[1] in config['timeframes']]
paircombs = [comb for comb in paircombs if comb[2] in candle_types]
paircombs = sorted(paircombs, key=lambda x: (x[0], x[1], x[2].value))
formatted_paircombs = '\n'.join([f"{pair}, {timeframe}, {candle_type}"
for pair, timeframe, candle_type in paircombs])
logger.info(f"Converting candle (OHLCV) data for the following pair combinations:\n"
f"{formatted_paircombs}")
for pair, timeframe, candle_type in paircombs:
data = src.ohlcv_load(pair=pair, timeframe=timeframe,
timerange=None,
fill_missing=False,
drop_incomplete=False,
startup_candles=0,
candle_type=candle_type)
logger.info(f"Converting {len(data)} {timeframe} {candle_type} candles for {pair}")
if len(data) > 0:
trg.ohlcv_store(
pair=pair,
timeframe=timeframe,
data=data,
candle_type=candle_type
)
if erase and convert_from != convert_to:
logger.info(f"Deleting source data for {pair} / {timeframe}")
src.ohlcv_purge(pair=pair, timeframe=timeframe, candle_type=candle_type)
def reduce_dataframe_footprint(df: DataFrame) -> DataFrame: