96 lines
2.6 KiB
Python
96 lines
2.6 KiB
Python
import logging
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import re
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import arrow
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from pandas import DataFrame
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from freqtrade.persistence import Trade
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from freqtrade.misc import State, get_state
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from freqtrade import exchange
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from . import telegram
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logger = logging.getLogger(__name__)
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REGISTERED_MODULES = []
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def init(config: dict) -> None:
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"""
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Initializes all enabled rpc modules
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:param config: config to use
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:return: None
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"""
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if config['telegram'].get('enabled', False):
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logger.info('Enabling rpc.telegram ...')
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REGISTERED_MODULES.append('telegram')
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telegram.init(config)
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def cleanup() -> None:
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"""
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Stops all enabled rpc modules
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:return: None
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"""
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if 'telegram' in REGISTERED_MODULES:
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logger.debug('Cleaning up rpc.telegram ...')
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telegram.cleanup()
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def send_msg(msg: str) -> None:
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"""
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Send given markdown message to all registered rpc modules
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:param msg: message
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:return: None
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"""
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logger.info(msg)
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if 'telegram' in REGISTERED_MODULES:
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telegram.send_msg(msg)
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def shorten_date(_date):
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"""
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Trim the date so it fits on small screens
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"""
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new_date = re.sub('seconds?', 'sec', _date)
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new_date = re.sub('minutes?', 'min', new_date)
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new_date = re.sub('hours?', 'h', new_date)
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new_date = re.sub('days?', 'd', new_date)
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new_date = re.sub('^an?', '1', new_date)
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return new_date
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#
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# Below follows the RPC backend
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# it is prefixed with rpc_
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# to raise awareness that it is
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# a remotely exposed function
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def rpc_status_table():
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trades = Trade.query.filter(Trade.is_open.is_(True)).all()
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if get_state() != State.RUNNING:
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return (True, '*Status:* `trader is not running`')
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elif not trades:
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return (True, '*Status:* `no active order`')
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else:
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trades_list = []
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for trade in trades:
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# calculate profit and send message to user
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current_rate = exchange.get_ticker(trade.pair, False)['bid']
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trades_list.append([
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trade.id,
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trade.pair,
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shorten_date(arrow.get(trade.open_date).humanize(only_distance=True)),
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'{:.2f}%'.format(100 * trade.calc_profit_percent(current_rate))
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])
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columns = ['ID', 'Pair', 'Since', 'Profit']
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df_statuses = DataFrame.from_records(trades_list, columns=columns)
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df_statuses = df_statuses.set_index(columns[0])
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# The style used throughout is to return a tuple
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# consisting of (error_occured?, result)
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# Another approach would be to just return the
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# result, or raise error
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return (False, df_statuses)
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