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Remove formatting changes

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This commit is contained in:
Joe Schr
2024-02-12 13:13:50 +01:00
parent d7b88194e0
commit 64e9784d1f
1 changed files with 9 additions and 18 deletions
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27
freqtrade/data/converter/converter.py
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@@ -9,8 +9,7 @@ import numpy as np
import pandas as pd import pandas as pd
from pandas import DataFrame, to_datetime from pandas import DataFrame, to_datetime
from freqtrade.constants import (DEFAULT_DATAFRAME_COLUMNS, DEFAULT_ORDERFLOW_COLUMNS, from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, DEFAULT_ORDERFLOW_COLUMNS, Config
Config)
from freqtrade.enums import CandleType, TradingMode from freqtrade.enums import CandleType, TradingMode
from freqtrade.exchange.exchange_utils import timeframe_to_resample_freq from freqtrade.exchange.exchange_utils import timeframe_to_resample_freq
@@ -31,8 +30,7 @@ def ohlcv_to_dataframe(ohlcv: list, timeframe: str, pair: str, *,
:param drop_incomplete: Drop the last candle of the dataframe, assuming it's incomplete :param drop_incomplete: Drop the last candle of the dataframe, assuming it's incomplete
:return: DataFrame :return: DataFrame
""" """
logger.debug( logger.debug(f"Converting candle (OHLCV) data to dataframe for pair {pair}.")
f"Converting candle (OHLCV) data to dataframe for pair {pair}.")
cols = DEFAULT_DATAFRAME_COLUMNS cols = DEFAULT_DATAFRAME_COLUMNS
df = DataFrame(ohlcv, columns=cols) df = DataFrame(ohlcv, columns=cols)
@@ -375,8 +373,7 @@ def ohlcv_fill_up_missing_data(dataframe: DataFrame, timeframe: str, pair: str)
df.reset_index(inplace=True) df.reset_index(inplace=True)
len_before = len(dataframe) len_before = len(dataframe)
len_after = len(df) len_after = len(df)
pct_missing = (len_after - len_before) / \ pct_missing = (len_after - len_before) / len_before if len_before > 0 else 0
len_before if len_before > 0 else 0
if len_before != len_after: if len_before != len_after:
message = (f"Missing data fillup for {pair}, {timeframe}: " message = (f"Missing data fillup for {pair}, {timeframe}: "
f"before: {len_before} - after: {len_after} - {pct_missing:.2%}") f"before: {len_before} - after: {len_after} - {pct_missing:.2%}")
@@ -421,8 +418,7 @@ def trim_dataframes(preprocessed: Dict[str, DataFrame], timerange,
processed: Dict[str, DataFrame] = {} processed: Dict[str, DataFrame] = {}
for pair, df in preprocessed.items(): for pair, df in preprocessed.items():
trimed_df = trim_dataframe( trimed_df = trim_dataframe(df, timerange, startup_candles=startup_candles)
df, timerange, startup_candles=startup_candles)
if not trimed_df.empty: if not trimed_df.empty:
processed[pair] = trimed_df processed[pair] = trimed_df
else: else:
@@ -478,18 +474,15 @@ def convert_ohlcv_format(
candle_types = [CandleType.from_string(ct) for ct in config.get('candle_types', [ candle_types = [CandleType.from_string(ct) for ct in config.get('candle_types', [
c.value for c in CandleType])] c.value for c in CandleType])]
logger.info(candle_types) logger.info(candle_types)
paircombs = src.ohlcv_get_available_data( paircombs = src.ohlcv_get_available_data(config['datadir'], TradingMode.SPOT)
config['datadir'], TradingMode.SPOT) paircombs.extend(src.ohlcv_get_available_data(config['datadir'], TradingMode.FUTURES))
paircombs.extend(src.ohlcv_get_available_data(
config['datadir'], TradingMode.FUTURES))
if 'pairs' in config: if 'pairs' in config:
# Filter pairs # Filter pairs
paircombs = [comb for comb in paircombs if comb[0] in config['pairs']] paircombs = [comb for comb in paircombs if comb[0] in config['pairs']]
if 'timeframes' in config: if 'timeframes' in config:
paircombs = [comb for comb in paircombs if comb[1] paircombs = [comb for comb in paircombs if comb[1] in config['timeframes']]
in config['timeframes']]
paircombs = [comb for comb in paircombs if comb[2] in candle_types] 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)) paircombs = sorted(paircombs, key=lambda x: (x[0], x[1], x[2].value))
@@ -506,8 +499,7 @@ def convert_ohlcv_format(
drop_incomplete=False, drop_incomplete=False,
startup_candles=0, startup_candles=0,
candle_type=candle_type) candle_type=candle_type)
logger.info( logger.info(f"Converting {len(data)} {timeframe} {candle_type} candles for {pair}")
f"Converting {len(data)} {timeframe} {candle_type} candles for {pair}")
if len(data) > 0: if len(data) > 0:
trg.ohlcv_store( trg.ohlcv_store(
pair=pair, pair=pair,
@@ -517,8 +509,7 @@ def convert_ohlcv_format(
) )
if erase and convert_from != convert_to: if erase and convert_from != convert_to:
logger.info(f"Deleting source data for {pair} / {timeframe}") logger.info(f"Deleting source data for {pair} / {timeframe}")
src.ohlcv_purge(pair=pair, timeframe=timeframe, src.ohlcv_purge(pair=pair, timeframe=timeframe, candle_type=candle_type)
candle_type=candle_type)
def reduce_dataframe_footprint(df: DataFrame) -> DataFrame: def reduce_dataframe_footprint(df: DataFrame) -> DataFrame: