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Fix "needed_candle_for*" logic

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we can't compare this to "required_candle_call_count" - that'd yield 1 ...
This commit is contained in:
Matthias
2024-07-10 19:40:19 +02:00
parent aa86e95650
commit e5f6ce9724
2 changed files with 14 additions and 15 deletions
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27
freqtrade/exchange/exchange.py
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@@ -2617,25 +2617,22 @@ class Exchange:
# fetch Trade data stuff
def needed_candle_ms(self, timeframe: str, candle_type: CandleType):
one_call = timeframe_to_msecs(timeframe) * self.ohlcv_candle_limit(timeframe, candle_type)
move_to = one_call * self.required_candle_call_count
now = timeframe_to_next_date(timeframe)
return int((now - timedelta(seconds=move_to // 1000)).timestamp() * 1000)
def needed_candle_for_trades_ms(self, timeframe: str, candle_type: CandleType) -> int:
candle_limit = self.ohlcv_candle_limit(timeframe, candle_type)
tf_s = timeframe_to_seconds(timeframe)
candles_fetched = candle_limit * self.required_candle_call_count
def needed_candle_for_trades_ms(self, timeframe: str, candle_type: CandleType):
one_call = timeframe_to_msecs(timeframe) * self.ohlcv_candle_limit(timeframe, candle_type)
config_orderflow = self._config["orderflow"]
required_candles = config_orderflow["max_candles"]
required_candles = (
required_candles
if required_candles < self.required_candle_call_count
else self.required_candle_call_count
max_candles = self._config["orderflow"]["max_candles"]
required_candles = min(max_candles, candles_fetched)
move_to = (
tf_s * candle_limit * required_candles
if required_candles > candle_limit
else (max_candles + 1) * tf_s
)
move_to = one_call * required_candles
now = timeframe_to_next_date(timeframe)
return int((now - timedelta(seconds=move_to // 1000)).timestamp() * 1000)
return int((now - timedelta(seconds=move_to)).timestamp() * 1000)
def _process_trades_df(
self,

2
freqtrade/rpc/rpc.py
View File

@@ -1317,6 +1317,8 @@ class RPC:
# replace NaT with `None`
dataframe[date_column] = dataframe[date_column].astype(object).replace({NaT: None})
# TODO: Temporary workaround for orderflow: drop orderflow columns
dataframe = dataframe.drop(["orderflow", "trades", "imbalances"], axis=1, errors="ignore")
dataframe = dataframe.replace({inf: None, -inf: None, NAN: None})
res = {