2018-11-30 19:42:16 +00:00
|
|
|
"""
|
|
|
|
Dataprovider
|
|
|
|
Responsible to provide data to the bot
|
2020-03-08 10:35:31 +00:00
|
|
|
including ticker and orderbook data, live and historical candle (OHLCV) data
|
2018-11-30 19:42:16 +00:00
|
|
|
Common Interface for bot and strategy to access data.
|
|
|
|
"""
|
|
|
|
import logging
|
2022-07-26 18:15:49 +00:00
|
|
|
from collections import deque
|
2020-06-14 09:51:20 +00:00
|
|
|
from datetime import datetime, timezone
|
2020-06-12 12:02:21 +00:00
|
|
|
from typing import Any, Dict, List, Optional, Tuple
|
2018-11-30 19:42:16 +00:00
|
|
|
|
2018-12-02 08:16:35 +00:00
|
|
|
from pandas import DataFrame
|
|
|
|
|
2021-07-18 21:47:51 +00:00
|
|
|
from freqtrade.configuration import TimeRange
|
2022-09-18 11:20:36 +00:00
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|
|
from freqtrade.constants import Config, ListPairsWithTimeframes, PairWithTimeframe
|
2018-12-17 05:52:13 +00:00
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|
|
from freqtrade.data.history import load_pair_history
|
2022-08-31 16:40:26 +00:00
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|
|
from freqtrade.enums import CandleType, RPCMessageType, RunMode
|
2020-06-28 14:01:40 +00:00
|
|
|
from freqtrade.exceptions import ExchangeError, OperationalException
|
2021-07-18 21:25:24 +00:00
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|
|
from freqtrade.exchange import Exchange, timeframe_to_seconds
|
2022-08-31 16:40:26 +00:00
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|
|
from freqtrade.rpc import RPCManager
|
2022-08-10 08:57:19 +00:00
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|
|
from freqtrade.util import PeriodicCache
|
2020-05-16 08:09:50 +00:00
|
|
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|
2020-09-28 17:39:41 +00:00
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|
2018-11-30 19:42:16 +00:00
|
|
|
logger = logging.getLogger(__name__)
|
|
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|
|
2021-05-05 18:08:31 +00:00
|
|
|
NO_EXCHANGE_EXCEPTION = 'Exchange is not available to DataProvider.'
|
2021-05-08 13:06:19 +00:00
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|
|
MAX_DATAFRAME_CANDLES = 1000
|
2021-05-05 18:08:31 +00:00
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|
2018-11-30 19:42:16 +00:00
|
|
|
|
2019-09-12 09:13:20 +00:00
|
|
|
class DataProvider:
|
2018-11-30 19:42:16 +00:00
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|
2022-08-27 05:40:13 +00:00
|
|
|
def __init__(
|
|
|
|
self,
|
2022-09-20 04:56:15 +00:00
|
|
|
config: Config,
|
2022-08-27 05:40:13 +00:00
|
|
|
exchange: Optional[Exchange],
|
2022-08-31 17:43:02 +00:00
|
|
|
pairlists=None,
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|
|
|
rpc: Optional[RPCManager] = None
|
2022-08-27 05:40:13 +00:00
|
|
|
) -> None:
|
2018-12-02 08:16:35 +00:00
|
|
|
self._config = config
|
|
|
|
self._exchange = exchange
|
2020-05-11 15:32:28 +00:00
|
|
|
self._pairlists = pairlists
|
2022-08-31 16:40:26 +00:00
|
|
|
self.__rpc = rpc
|
2020-06-15 12:08:57 +00:00
|
|
|
self.__cached_pairs: Dict[PairWithTimeframe, Tuple[DataFrame, datetime]] = {}
|
2021-05-09 07:56:36 +00:00
|
|
|
self.__slice_index: Optional[int] = None
|
2021-07-18 21:25:24 +00:00
|
|
|
self.__cached_pairs_backtesting: Dict[PairWithTimeframe, DataFrame] = {}
|
2022-08-31 17:43:02 +00:00
|
|
|
self.__producer_pairs_df: Dict[str,
|
|
|
|
Dict[PairWithTimeframe, Tuple[DataFrame, datetime]]] = {}
|
|
|
|
self.__producer_pairs: Dict[str, List[str]] = {}
|
2022-07-26 18:15:49 +00:00
|
|
|
self._msg_queue: deque = deque()
|
2022-07-26 18:24:52 +00:00
|
|
|
|
2022-09-04 16:22:10 +00:00
|
|
|
self._default_candle_type = self._config.get('candle_type_def', CandleType.SPOT)
|
|
|
|
self._default_timeframe = self._config.get('timeframe', '1h')
|
|
|
|
|
2022-07-26 18:15:49 +00:00
|
|
|
self.__msg_cache = PeriodicCache(
|
2022-09-04 16:22:10 +00:00
|
|
|
maxsize=1000, ttl=timeframe_to_seconds(self._default_timeframe))
|
2021-05-08 13:06:19 +00:00
|
|
|
|
2022-09-07 23:14:26 +00:00
|
|
|
self.producers = self._config.get('external_message_consumer', {}).get('producers', [])
|
|
|
|
self.external_data_enabled = len(self.producers) > 0
|
2022-08-27 05:40:13 +00:00
|
|
|
|
2021-05-08 13:06:19 +00:00
|
|
|
def _set_dataframe_max_index(self, limit_index: int):
|
|
|
|
"""
|
|
|
|
Limit analyzed dataframe to max specified index.
|
|
|
|
:param limit_index: dataframe index.
|
|
|
|
"""
|
|
|
|
self.__slice_index = limit_index
|
2020-06-12 12:02:21 +00:00
|
|
|
|
2021-11-21 07:43:05 +00:00
|
|
|
def _set_cached_df(
|
|
|
|
self,
|
|
|
|
pair: str,
|
|
|
|
timeframe: str,
|
|
|
|
dataframe: DataFrame,
|
2021-12-03 12:04:31 +00:00
|
|
|
candle_type: CandleType
|
2021-11-21 07:43:05 +00:00
|
|
|
) -> None:
|
2020-06-12 12:02:21 +00:00
|
|
|
"""
|
|
|
|
Store cached Dataframe.
|
|
|
|
Using private method as this should never be used by a user
|
|
|
|
(but the class is exposed via `self.dp` to the strategy)
|
|
|
|
:param pair: pair to get the data for
|
|
|
|
:param timeframe: Timeframe to get data for
|
|
|
|
:param dataframe: analyzed dataframe
|
2021-12-03 12:04:31 +00:00
|
|
|
:param candle_type: Any of the enum CandleType (must match trading mode!)
|
2020-06-12 12:02:21 +00:00
|
|
|
"""
|
2022-08-22 04:45:36 +00:00
|
|
|
pair_key = (pair, timeframe, candle_type)
|
|
|
|
self.__cached_pairs[pair_key] = (
|
2021-11-21 07:43:05 +00:00
|
|
|
dataframe, datetime.now(timezone.utc))
|
2018-11-30 19:42:16 +00:00
|
|
|
|
2022-08-31 16:40:26 +00:00
|
|
|
# For multiple producers we will want to merge the pairlists instead of overwriting
|
2022-09-04 16:22:10 +00:00
|
|
|
def _set_producer_pairs(self, pairlist: List[str], producer_name: str = "default"):
|
2022-08-31 16:40:26 +00:00
|
|
|
"""
|
|
|
|
Set the pairs received to later be used.
|
|
|
|
|
|
|
|
:param pairlist: List of pairs
|
|
|
|
"""
|
2022-09-12 05:28:31 +00:00
|
|
|
self.__producer_pairs[producer_name] = pairlist
|
2022-08-31 16:40:26 +00:00
|
|
|
|
2022-08-31 17:43:02 +00:00
|
|
|
def get_producer_pairs(self, producer_name: str = "default") -> List[str]:
|
2022-08-31 16:40:26 +00:00
|
|
|
"""
|
|
|
|
Get the pairs cached from the producer
|
|
|
|
|
|
|
|
:returns: List of pairs
|
|
|
|
"""
|
2022-09-12 05:28:31 +00:00
|
|
|
return self.__producer_pairs.get(producer_name, []).copy()
|
2022-08-31 16:40:26 +00:00
|
|
|
|
2022-09-04 16:22:10 +00:00
|
|
|
def _emit_df(
|
2022-08-31 16:40:26 +00:00
|
|
|
self,
|
|
|
|
pair_key: PairWithTimeframe,
|
|
|
|
dataframe: DataFrame
|
|
|
|
) -> None:
|
|
|
|
"""
|
|
|
|
Send this dataframe as an ANALYZED_DF message to RPC
|
|
|
|
|
|
|
|
:param pair_key: PairWithTimeframe tuple
|
|
|
|
:param data: Tuple containing the DataFrame and the datetime it was cached
|
|
|
|
"""
|
|
|
|
if self.__rpc:
|
|
|
|
self.__rpc.send_msg(
|
|
|
|
{
|
|
|
|
'type': RPCMessageType.ANALYZED_DF,
|
|
|
|
'data': {
|
|
|
|
'key': pair_key,
|
2022-09-07 21:08:01 +00:00
|
|
|
'df': dataframe,
|
|
|
|
'la': datetime.now(timezone.utc)
|
2022-08-31 16:40:26 +00:00
|
|
|
}
|
|
|
|
}
|
|
|
|
)
|
|
|
|
|
2022-09-04 16:22:10 +00:00
|
|
|
def _add_external_df(
|
2022-08-22 04:45:36 +00:00
|
|
|
self,
|
|
|
|
pair: str,
|
|
|
|
dataframe: DataFrame,
|
2022-09-12 20:21:39 +00:00
|
|
|
last_analyzed: datetime,
|
|
|
|
timeframe: str,
|
|
|
|
candle_type: CandleType,
|
2022-08-31 17:43:02 +00:00
|
|
|
producer_name: str = "default"
|
2022-08-22 04:45:36 +00:00
|
|
|
) -> None:
|
|
|
|
"""
|
2022-08-27 05:40:13 +00:00
|
|
|
Add the pair data to this class from an external source.
|
|
|
|
|
|
|
|
:param pair: pair to get the data for
|
|
|
|
:param timeframe: Timeframe to get data for
|
|
|
|
:param candle_type: Any of the enum CandleType (must match trading mode!)
|
2022-08-22 04:45:36 +00:00
|
|
|
"""
|
2022-09-12 20:21:39 +00:00
|
|
|
pair_key = (pair, timeframe, candle_type)
|
2022-08-22 04:45:36 +00:00
|
|
|
|
2022-08-31 17:43:02 +00:00
|
|
|
if producer_name not in self.__producer_pairs_df:
|
|
|
|
self.__producer_pairs_df[producer_name] = {}
|
|
|
|
|
2022-09-07 21:08:01 +00:00
|
|
|
_last_analyzed = datetime.now(timezone.utc) if not last_analyzed else last_analyzed
|
2022-09-06 18:12:05 +00:00
|
|
|
|
|
|
|
self.__producer_pairs_df[producer_name][pair_key] = (dataframe, _last_analyzed)
|
2022-09-04 16:22:10 +00:00
|
|
|
logger.debug(f"External DataFrame for {pair_key} from {producer_name} added.")
|
2022-08-22 04:45:36 +00:00
|
|
|
|
|
|
|
def get_external_df(
|
|
|
|
self,
|
|
|
|
pair: str,
|
2022-09-04 16:22:10 +00:00
|
|
|
timeframe: Optional[str] = None,
|
|
|
|
candle_type: Optional[CandleType] = None,
|
2022-08-31 17:43:02 +00:00
|
|
|
producer_name: str = "default"
|
|
|
|
) -> Tuple[DataFrame, datetime]:
|
2022-08-22 04:45:36 +00:00
|
|
|
"""
|
2022-09-12 20:21:39 +00:00
|
|
|
Get the pair data from the external sources.
|
2022-08-27 05:40:13 +00:00
|
|
|
|
|
|
|
:param pair: pair to get the data for
|
|
|
|
:param timeframe: Timeframe to get data for
|
|
|
|
:param candle_type: Any of the enum CandleType (must match trading mode!)
|
2022-09-21 21:50:11 +00:00
|
|
|
:returns: Tuple of the DataFrame and last analyzed timestamp
|
2022-08-22 04:45:36 +00:00
|
|
|
"""
|
2022-09-04 16:22:10 +00:00
|
|
|
_timeframe = self._default_timeframe if not timeframe else timeframe
|
|
|
|
_candle_type = self._default_candle_type if not candle_type else candle_type
|
|
|
|
|
|
|
|
pair_key = (pair, _timeframe, _candle_type)
|
2022-08-25 04:42:29 +00:00
|
|
|
|
2022-09-04 16:22:10 +00:00
|
|
|
# If we have no data from this Producer yet
|
2022-08-31 17:43:02 +00:00
|
|
|
if producer_name not in self.__producer_pairs_df:
|
|
|
|
# We don't have this data yet, return empty DataFrame and datetime (01-01-1970)
|
|
|
|
return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc))
|
|
|
|
|
2022-09-04 16:22:10 +00:00
|
|
|
# If we do have data from that Producer, but no data on this pair_key
|
2022-09-04 15:42:43 +00:00
|
|
|
if pair_key not in self.__producer_pairs_df[producer_name]:
|
2022-08-31 16:40:26 +00:00
|
|
|
# We don't have this data yet, return empty DataFrame and datetime (01-01-1970)
|
|
|
|
return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc))
|
2022-08-22 04:45:36 +00:00
|
|
|
|
2022-09-04 16:22:10 +00:00
|
|
|
# We have it, return this data
|
2022-09-12 19:57:29 +00:00
|
|
|
df, la = self.__producer_pairs_df[producer_name][pair_key]
|
|
|
|
return (df.copy(), la)
|
2022-08-22 04:45:36 +00:00
|
|
|
|
2020-08-30 08:07:28 +00:00
|
|
|
def add_pairlisthandler(self, pairlists) -> None:
|
|
|
|
"""
|
|
|
|
Allow adding pairlisthandler after initialization
|
|
|
|
"""
|
|
|
|
self._pairlists = pairlists
|
|
|
|
|
2021-11-21 07:43:05 +00:00
|
|
|
def historic_ohlcv(
|
|
|
|
self,
|
|
|
|
pair: str,
|
|
|
|
timeframe: str = None,
|
|
|
|
candle_type: str = ''
|
|
|
|
) -> DataFrame:
|
2018-11-30 19:42:16 +00:00
|
|
|
"""
|
2020-03-08 10:35:31 +00:00
|
|
|
Get stored historical candle (OHLCV) data
|
2018-12-30 06:15:21 +00:00
|
|
|
:param pair: pair to get the data for
|
2019-11-13 10:28:26 +00:00
|
|
|
:param timeframe: timeframe to get data for
|
2021-11-27 08:55:42 +00:00
|
|
|
:param candle_type: '', mark, index, premiumIndex, or funding_rate
|
2018-11-30 19:42:16 +00:00
|
|
|
"""
|
2022-01-28 18:18:03 +00:00
|
|
|
_candle_type = CandleType.from_string(
|
|
|
|
candle_type) if candle_type != '' else self._config['candle_type_def']
|
2022-09-11 09:24:01 +00:00
|
|
|
saved_pair: PairWithTimeframe = (pair, str(timeframe), _candle_type)
|
2021-07-18 21:25:24 +00:00
|
|
|
if saved_pair not in self.__cached_pairs_backtesting:
|
|
|
|
timerange = TimeRange.parse_timerange(None if self._config.get(
|
|
|
|
'timerange') is None else str(self._config.get('timerange')))
|
|
|
|
# Move informative start time respecting startup_candle_count
|
2022-08-26 11:56:44 +00:00
|
|
|
startup_candles = self.get_required_startup(str(timeframe))
|
|
|
|
tf_seconds = timeframe_to_seconds(str(timeframe))
|
|
|
|
timerange.subtract_start(tf_seconds * startup_candles)
|
2021-07-18 21:25:24 +00:00
|
|
|
self.__cached_pairs_backtesting[saved_pair] = load_pair_history(
|
|
|
|
pair=pair,
|
|
|
|
timeframe=timeframe or self._config['timeframe'],
|
|
|
|
datadir=self._config['datadir'],
|
|
|
|
timerange=timerange,
|
2021-11-21 07:43:05 +00:00
|
|
|
data_format=self._config.get('dataformat_ohlcv', 'json'),
|
2022-01-28 18:18:03 +00:00
|
|
|
candle_type=_candle_type,
|
2021-12-03 12:04:31 +00:00
|
|
|
|
2021-07-18 21:25:24 +00:00
|
|
|
)
|
|
|
|
return self.__cached_pairs_backtesting[saved_pair].copy()
|
2018-11-30 19:42:16 +00:00
|
|
|
|
2022-08-26 11:56:44 +00:00
|
|
|
def get_required_startup(self, timeframe: str) -> int:
|
2022-08-26 13:30:01 +00:00
|
|
|
freqai_config = self._config.get('freqai', {})
|
|
|
|
if not freqai_config.get('enabled', False):
|
2022-08-26 11:56:44 +00:00
|
|
|
return self._config.get('startup_candle_count', 0)
|
2022-08-22 16:19:07 +00:00
|
|
|
else:
|
2022-08-26 13:30:01 +00:00
|
|
|
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))
|
2022-08-26 11:56:44 +00:00
|
|
|
tf_seconds = timeframe_to_seconds(timeframe)
|
2022-08-26 13:30:01 +00:00
|
|
|
train_candles = freqai_config['train_period_days'] * 86400 / tf_seconds
|
|
|
|
total_candles = int(self._config['startup_candle_count'] + train_candles)
|
2022-08-26 11:56:44 +00:00
|
|
|
logger.info(f'Increasing startup_candle_count for freqai to {total_candles}')
|
|
|
|
return total_candles
|
2022-08-22 16:19:07 +00:00
|
|
|
|
2021-11-21 07:43:05 +00:00
|
|
|
def get_pair_dataframe(
|
|
|
|
self,
|
|
|
|
pair: str,
|
|
|
|
timeframe: str = None,
|
|
|
|
candle_type: str = ''
|
|
|
|
) -> DataFrame:
|
2019-08-17 08:43:36 +00:00
|
|
|
"""
|
2020-03-08 10:35:31 +00:00
|
|
|
Return pair candle (OHLCV) data, either live or cached historical -- depending
|
2019-08-17 08:43:36 +00:00
|
|
|
on the runmode.
|
2021-11-28 14:53:13 +00:00
|
|
|
Only combinations in the pairlist or which have been specified as informative pairs
|
|
|
|
will be available.
|
2019-08-17 08:43:36 +00:00
|
|
|
:param pair: pair to get the data for
|
2019-11-13 10:28:26 +00:00
|
|
|
:param timeframe: timeframe to get data for
|
2019-11-02 19:25:18 +00:00
|
|
|
:return: Dataframe for this pair
|
2021-11-27 08:55:42 +00:00
|
|
|
:param candle_type: '', mark, index, premiumIndex, or funding_rate
|
2019-08-17 08:43:36 +00:00
|
|
|
"""
|
|
|
|
if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
|
2020-03-08 10:35:31 +00:00
|
|
|
# Get live OHLCV data.
|
2021-11-21 07:43:05 +00:00
|
|
|
data = self.ohlcv(pair=pair, timeframe=timeframe, candle_type=candle_type)
|
2019-08-17 08:43:36 +00:00
|
|
|
else:
|
2020-03-08 10:35:31 +00:00
|
|
|
# Get historical OHLCV data (cached on disk).
|
2021-11-21 07:43:05 +00:00
|
|
|
data = self.historic_ohlcv(pair=pair, timeframe=timeframe, candle_type=candle_type)
|
2019-08-17 08:43:36 +00:00
|
|
|
if len(data) == 0:
|
2021-11-21 07:43:05 +00:00
|
|
|
logger.warning(f"No data found for ({pair}, {timeframe}, {candle_type}).")
|
2019-08-17 08:43:36 +00:00
|
|
|
return data
|
|
|
|
|
2021-11-28 14:53:13 +00:00
|
|
|
def get_analyzed_dataframe(self, pair: str, timeframe: str) -> Tuple[DataFrame, datetime]:
|
2020-06-12 12:02:21 +00:00
|
|
|
"""
|
2021-05-09 07:56:36 +00:00
|
|
|
Retrieve the analyzed dataframe. Returns the full dataframe in trade mode (live / dry),
|
|
|
|
and the last 1000 candles (up to the time evaluated at this moment) in all other modes.
|
2020-06-12 12:02:21 +00:00
|
|
|
:param pair: pair to get the data for
|
|
|
|
:param timeframe: timeframe to get data for
|
2020-06-12 12:12:33 +00:00
|
|
|
:return: Tuple of (Analyzed Dataframe, lastrefreshed) for the requested pair / timeframe
|
2020-06-14 09:51:20 +00:00
|
|
|
combination.
|
|
|
|
Returns empty dataframe and Epoch 0 (1970-01-01) if no dataframe was cached.
|
2020-06-12 12:02:21 +00:00
|
|
|
"""
|
2021-12-27 20:29:25 +00:00
|
|
|
pair_key = (pair, timeframe, self._config.get('candle_type_def', CandleType.SPOT))
|
2021-05-08 13:06:19 +00:00
|
|
|
if pair_key in self.__cached_pairs:
|
|
|
|
if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
|
|
|
|
df, date = self.__cached_pairs[pair_key]
|
|
|
|
else:
|
|
|
|
df, date = self.__cached_pairs[pair_key]
|
2021-05-09 07:56:36 +00:00
|
|
|
if self.__slice_index is not None:
|
|
|
|
max_index = self.__slice_index
|
|
|
|
df = df.iloc[max(0, max_index - MAX_DATAFRAME_CANDLES):max_index]
|
2021-05-08 13:06:19 +00:00
|
|
|
return df, date
|
2020-06-12 12:02:21 +00:00
|
|
|
else:
|
2020-06-14 09:51:20 +00:00
|
|
|
return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc))
|
2020-06-12 12:02:21 +00:00
|
|
|
|
2021-05-03 06:47:58 +00:00
|
|
|
@property
|
|
|
|
def runmode(self) -> RunMode:
|
|
|
|
"""
|
|
|
|
Get runmode of the bot
|
|
|
|
can be "live", "dry-run", "backtest", "edgecli", "hyperopt" or "other".
|
|
|
|
"""
|
|
|
|
return RunMode(self._config.get('runmode', RunMode.OTHER))
|
|
|
|
|
|
|
|
def current_whitelist(self) -> List[str]:
|
|
|
|
"""
|
|
|
|
fetch latest available whitelist.
|
|
|
|
|
|
|
|
Useful when you have a large whitelist and need to call each pair as an informative pair.
|
|
|
|
As available pairs does not show whitelist until after informative pairs have been cached.
|
|
|
|
:return: list of pairs in whitelist
|
|
|
|
"""
|
|
|
|
|
|
|
|
if self._pairlists:
|
|
|
|
return self._pairlists.whitelist.copy()
|
|
|
|
else:
|
|
|
|
raise OperationalException("Dataprovider was not initialized with a pairlist provider.")
|
|
|
|
|
|
|
|
def clear_cache(self):
|
|
|
|
"""
|
|
|
|
Clear pair dataframe cache.
|
|
|
|
"""
|
|
|
|
self.__cached_pairs = {}
|
2022-09-11 13:42:27 +00:00
|
|
|
# Don't reset backtesting pairs -
|
|
|
|
# otherwise they're reloaded each time during hyperopt due to with analyze_per_epoch
|
|
|
|
# self.__cached_pairs_backtesting = {}
|
2021-09-26 13:07:48 +00:00
|
|
|
self.__slice_index = 0
|
2021-05-03 06:47:58 +00:00
|
|
|
|
|
|
|
# Exchange functions
|
|
|
|
|
|
|
|
def refresh(self,
|
|
|
|
pairlist: ListPairsWithTimeframes,
|
|
|
|
helping_pairs: ListPairsWithTimeframes = None) -> None:
|
|
|
|
"""
|
|
|
|
Refresh data, called with each cycle
|
|
|
|
"""
|
|
|
|
if self._exchange is None:
|
2021-05-05 18:08:31 +00:00
|
|
|
raise OperationalException(NO_EXCHANGE_EXCEPTION)
|
2021-05-03 06:47:58 +00:00
|
|
|
if helping_pairs:
|
|
|
|
self._exchange.refresh_latest_ohlcv(pairlist + helping_pairs)
|
|
|
|
else:
|
|
|
|
self._exchange.refresh_latest_ohlcv(pairlist)
|
|
|
|
|
|
|
|
@property
|
|
|
|
def available_pairs(self) -> ListPairsWithTimeframes:
|
|
|
|
"""
|
|
|
|
Return a list of tuples containing (pair, timeframe) for which data is currently cached.
|
|
|
|
Should be whitelist + open trades.
|
|
|
|
"""
|
|
|
|
if self._exchange is None:
|
2021-05-05 18:08:31 +00:00
|
|
|
raise OperationalException(NO_EXCHANGE_EXCEPTION)
|
2021-05-03 06:47:58 +00:00
|
|
|
return list(self._exchange._klines.keys())
|
|
|
|
|
2021-11-21 06:21:10 +00:00
|
|
|
def ohlcv(
|
|
|
|
self,
|
|
|
|
pair: str,
|
|
|
|
timeframe: str = None,
|
|
|
|
copy: bool = True,
|
|
|
|
candle_type: str = ''
|
|
|
|
) -> DataFrame:
|
2021-05-03 06:47:58 +00:00
|
|
|
"""
|
|
|
|
Get candle (OHLCV) data for the given pair as DataFrame
|
|
|
|
Please use the `available_pairs` method to verify which pairs are currently cached.
|
|
|
|
:param pair: pair to get the data for
|
|
|
|
:param timeframe: Timeframe to get data for
|
2021-11-27 08:55:42 +00:00
|
|
|
:param candle_type: '', mark, index, premiumIndex, or funding_rate
|
2021-05-03 06:47:58 +00:00
|
|
|
:param copy: copy dataframe before returning if True.
|
|
|
|
Use False only for read-only operations (where the dataframe is not modified)
|
|
|
|
"""
|
2021-05-05 18:08:31 +00:00
|
|
|
if self._exchange is None:
|
|
|
|
raise OperationalException(NO_EXCHANGE_EXCEPTION)
|
2021-05-03 06:47:58 +00:00
|
|
|
if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
|
2022-01-28 18:18:03 +00:00
|
|
|
_candle_type = CandleType.from_string(
|
|
|
|
candle_type) if candle_type != '' else self._config['candle_type_def']
|
2021-11-21 07:43:05 +00:00
|
|
|
return self._exchange.klines(
|
2022-01-28 18:18:03 +00:00
|
|
|
(pair, timeframe or self._config['timeframe'], _candle_type),
|
2021-11-21 07:43:05 +00:00
|
|
|
copy=copy
|
|
|
|
)
|
2021-05-03 06:47:58 +00:00
|
|
|
else:
|
|
|
|
return DataFrame()
|
|
|
|
|
2019-10-10 15:03:52 +00:00
|
|
|
def market(self, pair: str) -> Optional[Dict[str, Any]]:
|
2019-10-02 23:58:45 +00:00
|
|
|
"""
|
|
|
|
Return market data for the pair
|
|
|
|
:param pair: Pair to get the data for
|
|
|
|
:return: Market data dict from ccxt or None if market info is not available for the pair
|
|
|
|
"""
|
2021-05-03 06:47:58 +00:00
|
|
|
if self._exchange is None:
|
2021-05-05 18:08:31 +00:00
|
|
|
raise OperationalException(NO_EXCHANGE_EXCEPTION)
|
2019-10-02 23:58:45 +00:00
|
|
|
return self._exchange.markets.get(pair)
|
|
|
|
|
2018-12-02 08:16:35 +00:00
|
|
|
def ticker(self, pair: str):
|
|
|
|
"""
|
2020-05-14 10:36:48 +00:00
|
|
|
Return last ticker data from exchange
|
|
|
|
:param pair: Pair to get the data for
|
|
|
|
:return: Ticker dict from exchange or empty dict if ticker is not available for the pair
|
2018-12-02 08:16:35 +00:00
|
|
|
"""
|
2021-05-03 06:47:58 +00:00
|
|
|
if self._exchange is None:
|
2021-05-05 18:08:31 +00:00
|
|
|
raise OperationalException(NO_EXCHANGE_EXCEPTION)
|
2020-05-14 10:36:48 +00:00
|
|
|
try:
|
|
|
|
return self._exchange.fetch_ticker(pair)
|
2020-06-28 14:01:40 +00:00
|
|
|
except ExchangeError:
|
2020-05-14 10:36:48 +00:00
|
|
|
return {}
|
2018-11-30 19:42:16 +00:00
|
|
|
|
2019-10-10 15:03:52 +00:00
|
|
|
def orderbook(self, pair: str, maximum: int) -> Dict[str, List]:
|
2018-12-02 08:16:35 +00:00
|
|
|
"""
|
2020-05-26 18:27:35 +00:00
|
|
|
Fetch latest l2 orderbook data
|
|
|
|
Warning: Does a network request - so use with common sense.
|
2019-07-14 18:05:28 +00:00
|
|
|
:param pair: pair to get the data for
|
|
|
|
:param maximum: Maximum number of orderbook entries to query
|
|
|
|
:return: dict including bids/asks with a total of `maximum` entries.
|
2018-12-02 08:16:35 +00:00
|
|
|
"""
|
2021-05-03 06:47:58 +00:00
|
|
|
if self._exchange is None:
|
2021-05-05 18:08:31 +00:00
|
|
|
raise OperationalException(NO_EXCHANGE_EXCEPTION)
|
2020-05-26 18:27:35 +00:00
|
|
|
return self._exchange.fetch_l2_order_book(pair, maximum)
|
2022-07-26 18:15:49 +00:00
|
|
|
|
2022-07-26 18:24:52 +00:00
|
|
|
def send_msg(self, message: str, *, always_send: bool = False) -> None:
|
2022-07-26 18:15:49 +00:00
|
|
|
"""
|
2022-07-26 18:24:52 +00:00
|
|
|
Send custom RPC Notifications from your bot.
|
|
|
|
Will not send any bot in modes other than Dry-run or Live.
|
2022-07-26 18:15:49 +00:00
|
|
|
:param message: Message to be sent. Must be below 4096.
|
|
|
|
:param always_send: If False, will send the message only once per candle, and surpress
|
|
|
|
identical messages.
|
|
|
|
Careful as this can end up spaming your chat.
|
|
|
|
Defaults to False
|
|
|
|
"""
|
|
|
|
if self.runmode not in (RunMode.DRY_RUN, RunMode.LIVE):
|
|
|
|
return
|
|
|
|
|
|
|
|
if always_send or message not in self.__msg_cache:
|
|
|
|
self._msg_queue.append(message)
|
|
|
|
self.__msg_cache[message] = True
|