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Move trim_dataframe from history to converter

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This commit is contained in:
Matthias
2019-12-25 15:47:04 +01:00
parent 9d8ea2f13b
commit 416517b0c9
8 changed files with 73 additions and 77 deletions
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19
freqtrade/data/converter.py
View File

@@ -2,10 +2,12 @@
Functions to convert data from one format to another
"""
import logging
from datetime import datetime, timezone
import pandas as pd
from pandas import DataFrame, to_datetime
from freqtrade.configuration.timerange import TimeRange
logger = logging.getLogger(__name__)
@@ -112,6 +114,23 @@ def ohlcv_fill_up_missing_data(dataframe: DataFrame, timeframe: str, pair: str)
return df
def trim_dataframe(df: DataFrame, timerange: TimeRange, df_date_col: str = 'date') -> DataFrame:
"""
Trim dataframe based on given timerange
:param df: Dataframe to trim
:param timerange: timerange (use start and end date if available)
:param: df_date_col: Column in the dataframe to use as Date column
:return: trimmed dataframe
"""
if timerange.starttype == 'date':
start = datetime.fromtimestamp(timerange.startts, tz=timezone.utc)
df = df.loc[df[df_date_col] >= start, :]
if timerange.stoptype == 'date':
stop = datetime.fromtimestamp(timerange.stopts, tz=timezone.utc)
df = df.loc[df[df_date_col] <= stop, :]
return df
def order_book_to_dataframe(bids: list, asks: list) -> DataFrame:
"""
Gets order book list, returns dataframe with below format per suggested by creslin

3
freqtrade/data/datahandlers/jsondatahandler.py
View File

@@ -7,8 +7,7 @@ from pandas import DataFrame, read_json, to_datetime
from freqtrade import misc
from freqtrade.configuration import TimeRange
from freqtrade.data.converter import clean_ohlcv_dataframe
from freqtrade.data.history import trim_dataframe
from freqtrade.data.converter import clean_ohlcv_dataframe, trim_dataframe
from .idatahandler import IDataHandler

26
freqtrade/data/history.py
View File

@@ -50,23 +50,6 @@ def trim_tickerlist(tickerlist: List[Dict], timerange: TimeRange) -> List[Dict]:
return tickerlist[start_index:stop_index]
def trim_dataframe(df: DataFrame, timerange: TimeRange, df_date_col: str = 'date') -> DataFrame:
"""
Trim dataframe based on given timerange
:param df: Dataframe to trim
:param timerange: timerange (use start and end date if available)
:param: df_date_col: Column in the dataframe to use as Date column
:return: trimmed dataframe
"""
if timerange.starttype == 'date':
start = datetime.fromtimestamp(timerange.startts, tz=timezone.utc)
df = df.loc[df[df_date_col] >= start, :]
if timerange.stoptype == 'date':
stop = datetime.fromtimestamp(timerange.stopts, tz=timezone.utc)
df = df.loc[df[df_date_col] <= stop, :]
return df
def load_tickerdata_file(datadir: Path, pair: str, timeframe: str,
timerange: Optional[TimeRange] = None) -> List[Dict]:
"""
@@ -115,15 +98,6 @@ def store_trades_file(datadir: Path, pair: str,
misc.file_dump_json(filename, data, is_zip=is_zip)
def _validate_pairdata(pair, pairdata, timerange: TimeRange):
if timerange.starttype == 'date' and pairdata[0][0] > timerange.startts * 1000:
logger.warning('Missing data at start for pair %s, data starts at %s',
pair, arrow.get(pairdata[0][0] // 1000).strftime('%Y-%m-%d %H:%M:%S'))
if timerange.stoptype == 'date' and pairdata[-1][0] < timerange.stopts * 1000:
logger.warning('Missing data at end for pair %s, data ends at %s',
pair, arrow.get(pairdata[-1][0] // 1000).strftime('%Y-%m-%d %H:%M:%S'))
def load_pair_history(pair: str,
timeframe: str,
datadir: Path, *,