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Fix superfluous formatting

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This commit is contained in:
Joe Schr
2024-02-09 13:12:22 +01:00
parent 9ec45ce042
commit 4ae63d7ecb
3 changed files with 56 additions and 94 deletions
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86
freqtrade/data/dataprovider.py
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@@ -46,27 +46,23 @@ class DataProvider:
self._exchange = exchange
self._pairlists = pairlists
self.__rpc = rpc
self.__cached_pairs: Dict[PairWithTimeframe,
Tuple[DataFrame, datetime]] = {}
self.__cached_pairs: Dict[PairWithTimeframe, Tuple[DataFrame, datetime]] = {}
self.__slice_index: Optional[int] = None
self.__slice_date: Optional[datetime] = None
self.__cached_pairs_backtesting: Dict[PairWithTimeframe, DataFrame] = {
}
self.__cached_pairs_backtesting: Dict[PairWithTimeframe, DataFrame] = {}
self.__producer_pairs_df: Dict[str,
Dict[PairWithTimeframe, Tuple[DataFrame, datetime]]] = {}
self.__producer_pairs: Dict[str, List[str]] = {}
self._msg_queue: deque = deque()
self._default_candle_type = self._config.get(
'candle_type_def', CandleType.SPOT)
self._default_candle_type = self._config.get('candle_type_def', CandleType.SPOT)
self._default_timeframe = self._config.get('timeframe', '1h')
self.__msg_cache = PeriodicCache(
maxsize=1000, ttl=timeframe_to_seconds(self._default_timeframe))
self.producers = self._config.get(
'external_message_consumer', {}).get('producers', [])
self.producers = self._config.get('external_message_consumer', {}).get('producers', [])
self.external_data_enabled = len(self.producers) > 0
def _set_dataframe_max_index(self, limit_index: int):
@@ -137,19 +133,19 @@ class DataProvider:
"""
if self.__rpc:
msg: RPCAnalyzedDFMsg = {
'type': RPCMessageType.ANALYZED_DF,
'data': {
'key': pair_key,
'df': dataframe.tail(1),
'la': datetime.now(timezone.utc)
'type': RPCMessageType.ANALYZED_DF,
'data': {
'key': pair_key,
'df': dataframe.tail(1),
'la': datetime.now(timezone.utc)
}
}
}
self.__rpc.send_msg(msg)
if new_candle:
self.__rpc.send_msg({
'type': RPCMessageType.NEW_CANDLE,
'data': pair_key,
})
'type': RPCMessageType.NEW_CANDLE,
'data': pair_key,
})
def _replace_external_df(
self,
@@ -172,13 +168,10 @@ class DataProvider:
if producer_name not in self.__producer_pairs_df:
self.__producer_pairs_df[producer_name] = {}
_last_analyzed = datetime.now(
timezone.utc) if not last_analyzed else last_analyzed
_last_analyzed = datetime.now(timezone.utc) if not last_analyzed else last_analyzed
self.__producer_pairs_df[producer_name][pair_key] = (
dataframe, _last_analyzed)
logger.debug(
f"External DataFrame for {pair_key} from {producer_name} added.")
self.__producer_pairs_df[producer_name][pair_key] = (dataframe, _last_analyzed)
logger.debug(f"External DataFrame for {pair_key} from {producer_name} added.")
def _add_external_df(
self,
@@ -229,8 +222,7 @@ class DataProvider:
# CHECK FOR MISSING CANDLES
# Convert the timeframe to a timedelta for pandas
timeframe_delta: Timedelta = to_timedelta(timeframe)
# We want the last date from our copy
local_last: Timestamp = existing_df.iloc[-1]['date']
local_last: Timestamp = existing_df.iloc[-1]['date'] # We want the last date from our copy
# We want the first date from the incoming
incoming_first: Timestamp = dataframe.iloc[0]['date']
@@ -253,13 +245,13 @@ class DataProvider:
# Everything is good, we appended
self._replace_external_df(
pair,
appended_df,
last_analyzed=last_analyzed,
timeframe=timeframe,
candle_type=candle_type,
producer_name=producer_name
)
pair,
appended_df,
last_analyzed=last_analyzed,
timeframe=timeframe,
candle_type=candle_type,
producer_name=producer_name
)
return (True, 0)
def get_producer_df(
@@ -347,13 +339,10 @@ class DataProvider:
startup_candles = self._config.get('startup_candle_count', 0)
indicator_periods = freqai_config['feature_parameters']['indicator_periods_candles']
# make sure the startupcandles is at least the set maximum indicator periods
self._config['startup_candle_count'] = max(
startup_candles, max(indicator_periods))
self._config['startup_candle_count'] = max(startup_candles, max(indicator_periods))
tf_seconds = timeframe_to_seconds(timeframe)
train_candles = freqai_config['train_period_days'] * \
86400 / tf_seconds
total_candles = int(
self._config['startup_candle_count'] + train_candles)
train_candles = freqai_config['train_period_days'] * 86400 / tf_seconds
total_candles = int(self._config['startup_candle_count'] + train_candles)
logger.info(
f'Increasing startup_candle_count for freqai on {timeframe} to {total_candles}')
return total_candles
@@ -376,22 +365,18 @@ class DataProvider:
"""
if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
# Get live OHLCV data.
data = self.ohlcv(pair=pair, timeframe=timeframe,
candle_type=candle_type)
data = self.ohlcv(pair=pair, timeframe=timeframe, candle_type=candle_type)
else:
# Get historical OHLCV data (cached on disk).
timeframe = timeframe or self._config['timeframe']
data = self.historic_ohlcv(
pair=pair, timeframe=timeframe, candle_type=candle_type)
data = self.historic_ohlcv(pair=pair, timeframe=timeframe, candle_type=candle_type)
# Cut date to timeframe-specific date.
# This is necessary to prevent lookahead bias in callbacks through informative pairs.
if self.__slice_date:
cutoff_date = timeframe_to_prev_date(
timeframe, self.__slice_date)
cutoff_date = timeframe_to_prev_date(timeframe, self.__slice_date)
data = data.loc[data['date'] < cutoff_date]
if len(data) == 0:
logger.warning(
f"No data found for ({pair}, {timeframe}, {candle_type}).")
logger.warning(f"No data found for ({pair}, {timeframe}, {candle_type}).")
return data
def get_analyzed_dataframe(self, pair: str, timeframe: str) -> Tuple[DataFrame, datetime]:
@@ -404,8 +389,7 @@ class DataProvider:
combination.
Returns empty dataframe and Epoch 0 (1970-01-01) if no dataframe was cached.
"""
pair_key = (pair, timeframe, self._config.get(
'candle_type_def', CandleType.SPOT))
pair_key = (pair, timeframe, self._config.get('candle_type_def', CandleType.SPOT))
if pair_key in self.__cached_pairs:
if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
df, date = self.__cached_pairs[pair_key]
@@ -413,8 +397,7 @@ class DataProvider:
df, date = self.__cached_pairs[pair_key]
if self.__slice_index is not None:
max_index = self.__slice_index
df = df.iloc[max(
0, max_index - MAX_DATAFRAME_CANDLES):max_index]
df = df.iloc[max(0, max_index - MAX_DATAFRAME_CANDLES):max_index]
return df, date
else:
return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc))
@@ -439,8 +422,7 @@ class DataProvider:
if self._pairlists:
return self._pairlists.whitelist.copy()
else:
raise OperationalException(
"Dataprovider was not initialized with a pairlist provider.")
raise OperationalException("Dataprovider was not initialized with a pairlist provider.")
def clear_cache(self):
"""