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add candle difference calculation to dataprovider

This commit is contained in:
Timothy Pogue 2022-11-28 11:02:03 -07:00
parent 89338fa677
commit c050eb8b8b
1 changed files with 23 additions and 17 deletions
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40
freqtrade/data/dataprovider.py
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@ -9,7 +9,7 @@ from collections import deque
from datetime import datetime, timezone from datetime import datetime, timezone
from typing import Any, Dict, List, Optional, Tuple from typing import Any, Dict, List, Optional, Tuple
from pandas import DataFrame, concat from pandas import DataFrame, concat, to_timedelta
from freqtrade.configuration import TimeRange from freqtrade.configuration import TimeRange
from freqtrade.constants import Config, ListPairsWithTimeframes, PairWithTimeframe from freqtrade.constants import Config, ListPairsWithTimeframes, PairWithTimeframe
@ -176,24 +176,30 @@ class DataProvider:
""" """
pair_key = (pair, timeframe, candle_type) pair_key = (pair, timeframe, candle_type)
if producer_name not in self.__producer_pairs_df: if (producer_name not in self.__producer_pairs_df) \
or (pair_key not in self.__producer_pairs_df[producer_name]):
# We don't have data from this producer yet, # We don't have data from this producer yet,
# so we can't append a candle # sor we don't have data for this pair_key
return (False, 999) # return False and 1000 for the full df
return (False, 1000)
if pair_key not in self.__producer_pairs_df[producer_name]:
# We don't have data for this pair_key,
# so we can't append a candle
return (False, 999)
# CHECK FOR MISSING CANDLES
# Calculate difference between last candle in local dataframe
# and first candle in incoming dataframe. Take difference and divide
# by timeframe to find out how many candles we still need. If 1
# then the incoming candle is the right candle. If more than 1,
# return (False, missing candles - 1)
existing_df, _ = self.__producer_pairs_df[producer_name][pair_key] existing_df, _ = self.__producer_pairs_df[producer_name][pair_key]
# CHECK FOR MISSING CANDLES
timeframe_delta = to_timedelta(timeframe) # Convert the timeframe to a timedelta for pandas
local_last = existing_df.iloc[-1]['date'] # We want the last date from our copy of data
incoming_first = dataframe.iloc[0]['date'] # We want the first date from the incoming data
candle_difference = (incoming_first - local_last) / timeframe_delta
# If the difference divided by the timeframe is 1, then this
# is the candle we want and the incoming data isn't missing any.
# If the candle_difference is more than 1, that means
# we missed some candles between our data and the incoming
# so return False and candle_difference.
if candle_difference > 1:
return (False, candle_difference)
appended_df = self._append_candle_to_dataframe(existing_df, dataframe) appended_df = self._append_candle_to_dataframe(existing_df, dataframe)
# Everything is good, we appended # Everything is good, we appended
@ -212,7 +218,7 @@ class DataProvider:
existing = concat([existing, new]) existing = concat([existing, new])
# Only keep the last 1500 candles in memory # Only keep the last 1500 candles in memory
existing = existing[-1500:] if len(existing) > 1000 else existing existing = existing[-1500:] if len(existing) > 1500 else existing
return existing return existing