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Implement new "load_data_for_updating" method based on dataframes

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This commit is contained in:
Matthias 2019-12-27 06:58:50 +01:00
parent ec8fb5f308
commit c648d973c1
1 changed files with 46 additions and 12 deletions
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58
freqtrade/data/history.py
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@ -8,7 +8,7 @@ Includes:
import logging
import operator
from datetime import datetime
from datetime import datetime, timezone
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple
@ -17,7 +17,8 @@ from pandas import DataFrame
from freqtrade import OperationalException, misc
from freqtrade.configuration import TimeRange
from freqtrade.data.converter import trades_to_ohlcv
from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS
from freqtrade.data.converter import parse_ticker_dataframe, trades_to_ohlcv
from freqtrade.data.datahandlers import get_datahandler
from freqtrade.data.datahandlers.idatahandler import IDataHandler
from freqtrade.exchange import Exchange, timeframe_to_minutes
@ -184,9 +185,9 @@ def pair_data_filename(datadir: Path, pair: str, timeframe: str) -> Path:
return filename
def _load_cached_data_for_updating(datadir: Path, pair: str, timeframe: str,
timerange: Optional[TimeRange]) -> Tuple[List[Any],
Optional[int]]:
def _load_cached_data_for_updating_old(datadir: Path, pair: str, timeframe: str,
timerange: Optional[TimeRange]) -> Tuple[List[Any],
Optional[int]]:
"""
Load cached data to download more data.
If timerange is passed in, checks whether data from an before the stored data will be
@ -225,6 +226,27 @@ def _load_cached_data_for_updating(datadir: Path, pair: str, timeframe: str,
return (data, since_ms)
def _load_cached_data_for_updating(pair: str, timeframe: str, timerange: Optional[TimeRange],
data_handler: IDataHandler) -> Tuple[DataFrame, Optional[int]]:
start = None
if timerange:
if timerange.starttype == 'date':
# TODO: convert to date for conversation
start = datetime.fromtimestamp(timerange.startts, tz=timezone.utc)
# Intentionally don't pass timerange in - since we need to load the full dataset.
data = data_handler.ohlcv_load(pair, timeframe=timeframe,
timerange=None, fill_missing=False,
drop_incomplete=True, warn_no_data=False)
if not data.empty:
if start < data.iloc[0]['date']:
# Earlier data than existing data requested, redownload all
return DataFrame(columns=DEFAULT_DATAFRAME_COLUMNS), None
start = data.iloc[-1]['date']
start_ms = int(start.timestamp() * 1000) if start else None
return data, start_ms
def _download_pair_history(datadir: Path,
exchange: Exchange,
pair: str, *,
@ -252,10 +274,14 @@ def _download_pair_history(datadir: Path,
f'and store in {datadir}.'
)
data, since_ms = _load_cached_data_for_updating(datadir, pair, timeframe, timerange)
# data, since_ms = _load_cached_data_for_updating_old(datadir, pair, timeframe, timerange)
data, since_ms = _load_cached_data_for_updating(pair, timeframe, timerange,
data_handler=data_handler)
logger.debug("Current Start: %s", misc.format_ms_time(data[1][0]) if data else 'None')
logger.debug("Current End: %s", misc.format_ms_time(data[-1][0]) if data else 'None')
logger.debug("Current Start: %s",
f"{data.iloc[0]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
logger.debug("Current End: %s",
f"{data.iloc[-1]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
# Default since_ms to 30 days if nothing is given
new_data = exchange.get_historic_ohlcv(pair=pair,
@ -264,12 +290,20 @@ def _download_pair_history(datadir: Path,
int(arrow.utcnow().shift(
days=-30).float_timestamp) * 1000
)
data.extend(new_data)
# TODO: Maybe move parsing to exchange class (?)
new_dataframe = parse_ticker_dataframe(new_data, timeframe, pair,
fill_missing=False, drop_incomplete=True)
if data.empty:
data = new_dataframe
else:
data = data.append(new_dataframe)
logger.debug("New Start: %s", misc.format_ms_time(data[0][0]))
logger.debug("New End: %s", misc.format_ms_time(data[-1][0]))
logger.debug("New Start: %s",
f"{data.iloc[0]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
logger.debug("New End: %s",
f"{data.iloc[-1]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
store_tickerdata_file(datadir, pair, timeframe, data=data)
data_handler.ohlcv_store(pair, timeframe, data=data)
return True
except Exception as e: