def start(self, in_background: bool = False, **kwargs) -> None:
"""Start the bot.
`**kwargs` are passed to `telegram.ext.updater.Updater.start_polling`
and override settings under `messaging.telegram` in `vectorbt._settings.settings`."""
from vectorbt._settings import settings
telegram_cfg = settings['messaging']['telegram']
# Resolve kwargs
default_kwargs = dict()
passed_kwargs = dict()
for k in get_func_kwargs(self.updater.start_polling):
if k in telegram_cfg:
default_kwargs[k] = telegram_cfg[k]
if k in kwargs:
passed_kwargs[k] = kwargs.pop(k)
polling_kwargs = merge_dicts(default_kwargs, passed_kwargs)
# Start the Bot
logger.info("Running bot %s", str(self.updater.bot.get_me().username))
self.updater.start_polling(**polling_kwargs)
self.started_callback()
if not in_background:
# Run the bot until you press Ctrl-C or the process receives SIGINT,
# SIGTERM or SIGABRT. This should be used most of the time, since
# start_polling() is non-blocking and will stop the bot gracefully.
self.updater.idle()
def __init__(self, giphy_kwargs: tp.KwargsLike = None, **kwargs) -> None:
from vectorbt._settings import settings
telegram_cfg = settings['messaging']['telegram']
giphy_cfg = settings['messaging']['giphy']
Configured.__init__(self, giphy_kwargs=giphy_kwargs, **kwargs)
# Resolve kwargs
giphy_kwargs = merge_dicts(giphy_cfg, giphy_kwargs)
self.giphy_kwargs = giphy_kwargs
default_kwargs = dict()
passed_kwargs = dict()
for k in get_func_kwargs(Updater):
if k in telegram_cfg:
default_kwargs[k] = telegram_cfg[k]
if k in kwargs:
passed_kwargs[k] = kwargs.pop(k)
updater_kwargs = merge_dicts(default_kwargs, passed_kwargs)
persistence = updater_kwargs.pop('persistence', None)
if isinstance(persistence, str):
persistence = PicklePersistence(persistence)
defaults = updater_kwargs.pop('defaults', None)
if isinstance(defaults, dict):
defaults = Defaults(**defaults)
# Create the (persistent) Updater and pass it your bot's token.
logger.info("Initializing bot")
self._updater = Updater(persistence=persistence,
defaults=defaults,
**updater_kwargs)
# Get the dispatcher to register handlers
self._dispatcher = self.updater.dispatcher
# Register handlers
self.dispatcher.add_handler(self.log_handler)
self.dispatcher.add_handler(
CommandHandler('start', self.start_callback))
self.dispatcher.add_handler(CommandHandler("help", self.help_callback))
for handler in self.custom_handlers:
self.dispatcher.add_handler(handler)
self.dispatcher.add_handler(
MessageHandler(Filters.status_update.migrate,
self.chat_migration_callback))
self.dispatcher.add_handler(
MessageHandler(Filters.command, self.unknown_callback))
self.dispatcher.add_error_handler(
self_decorator(self, self.__class__.error_callback))
# Set up data
if 'chat_ids' not in self.dispatcher.bot_data:
self.dispatcher.bot_data['chat_ids'] = []
else:
logger.info("Loaded chat ids %s",
str(self.dispatcher.bot_data['chat_ids']))
def download(cls, symbols, client=None, **kwargs):
"""Override `vectorbt.data.base.Data.download` to instantiate a Binance client."""
from binance.client import Client
from vectorbt import settings
client_kwargs = dict()
for k in get_func_kwargs(Client):
if k in kwargs:
client_kwargs[k] = kwargs.pop(k)
client_kwargs = merge_dicts(settings.data['binance'], client_kwargs)
if client is None:
client = Client(**client_kwargs)
return super(BinanceData, cls).download(symbols,
client=client,
**kwargs)
def download(cls: tp.Type[BinanceDataT],
symbols: tp.Labels,
client: tp.Optional["ClientT"] = None,
**kwargs) -> BinanceDataT:
"""Override `vectorbt.data.base.Data.download` to instantiate a Binance client."""
from binance.client import Client
from vectorbt._settings import settings
binance_cfg = settings['data']['binance']
client_kwargs = dict()
for k in get_func_kwargs(Client):
if k in kwargs:
client_kwargs[k] = kwargs.pop(k)
client_kwargs = merge_dicts(binance_cfg, client_kwargs)
if client is None:
client = Client(**client_kwargs)
return super(BinanceData, cls).download(symbols, client=client, **kwargs)
def download_symbol(cls,
symbol: str,
timeframe: str = '1d',
start: tp.DatetimeLike = 0,
end: tp.DatetimeLike = 'now UTC',
adjustment: tp.Optional[str] = 'all',
limit: int = 500,
exchange: tp.Optional[str] = 'CBSE',
**kwargs) -> tp.Frame:
"""Download the symbol.
Args:
symbol (str): Symbol.
timeframe (str): Timeframe of data.
Must be integer multiple of 'm' (minute), 'h' (hour) or 'd' (day). i.e. '15m'.
See https://alpaca.markets/data.
!!! note
Data from the latest 15 minutes is not available with a free data plan.
start (any): Start datetime.
See `vectorbt.utils.datetime_.to_tzaware_datetime`.
end (any): End datetime.
See `vectorbt.utils.datetime_.to_tzaware_datetime`.
adjustment (str): Specifies the corporate action adjustment for the stocks.
Allowed are `raw`, `split`, `dividend` or `all`.
limit (int): The maximum number of returned items.
exchange (str): For crypto symbols. Which exchange you wish to retrieve data from.
Allowed are `FTX`, `ERSX`, `CBSE`
For defaults, see `data.alpaca` in `vectorbt._settings.settings`.
"""
from vectorbt._settings import settings
from alpaca_trade_api.rest import TimeFrameUnit, TimeFrame, REST
alpaca_cfg = settings['data']['alpaca']
client_kwargs = dict()
for k in get_func_kwargs(REST):
if k in kwargs:
client_kwargs[k] = kwargs.pop(k)
client_kwargs = merge_dicts(alpaca_cfg, client_kwargs)
client = REST(**client_kwargs)
_timeframe_units = {'d': TimeFrameUnit.Day, 'h': TimeFrameUnit.Hour, 'm': TimeFrameUnit.Minute}
if len(timeframe) < 2:
raise ValueError("invalid timeframe")
amount_str = timeframe[:-1]
unit_str = timeframe[-1]
if not amount_str.isnumeric() or unit_str not in _timeframe_units:
raise ValueError("invalid timeframe")
amount = int(amount_str)
unit = _timeframe_units[unit_str]
_timeframe = TimeFrame(amount, unit)
start_ts = to_tzaware_datetime(start, tz=get_utc_tz()).isoformat()
end_ts = to_tzaware_datetime(end, tz=get_utc_tz()).isoformat()
def _is_crypto_symbol(symbol):
return len(symbol) == 6 and "USD" in symbol
if _is_crypto_symbol(symbol):
df = client.get_crypto_bars(
symbol=symbol,
timeframe=_timeframe,
start=start_ts,
end=end_ts,
limit=limit,
exchanges=exchange
).df
else:
df = client.get_bars(
symbol=symbol,
timeframe=_timeframe,
start=start_ts,
end=end_ts,
adjustment=adjustment,
limit=limit
).df
# filter for OHLCV
# remove extra columns
df.drop(['trade_count', 'vwap'], axis=1, errors='ignore', inplace=True)
# capitalize
df.rename(columns={
'open': 'Open',
'high': 'High',
'low': 'Low',
'close': 'Close',
'volume': 'Volume',
'exchange': 'Exchange'
}, inplace=True)
df['Open'] = df['Open'].astype(float)
df['High'] = df['High'].astype(float)
df['Low'] = df['Low'].astype(float)
df['Close'] = df['Close'].astype(float)
df['Volume'] = df['Volume'].astype(float)
return df
