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https://gitlab.com/simple-stock-bots/simple-telegram-stock-bot.git
synced 2025-07-23 14:41:26 +00:00
refactor telegram bot to use docker compose
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393
common/symbol_router.py
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393
common/symbol_router.py
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"""Function that routes symbols to the correct API provider.
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"""
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import datetime
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import logging
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import random
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import re
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import pandas as pd
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import schedule
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from cachetools import TTLCache, cached
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from common.cg_Crypto import cg_Crypto
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from common.MarketData import MarketData
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from common.Symbol import Coin, Stock, Symbol
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from typing import Dict
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log = logging.getLogger(__name__)
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class Router:
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STOCK_REGEX = "(?:^|[^\\$])\\$([a-zA-Z.]{1,6})"
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CRYPTO_REGEX = "[$]{2}([a-zA-Z]{1,20})"
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trending_count: Dict[str, float] = {}
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def __init__(self):
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self.stock = MarketData()
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self.crypto = cg_Crypto()
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schedule.every().hour.do(self.trending_decay)
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def trending_decay(self, decay=0.5):
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"""Decays the value of each trending stock by a multiplier"""
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t_copy = {}
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dead_keys = []
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if self.trending_count:
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t_copy = self.trending_count.copy()
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for key in t_copy.keys():
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if t_copy[key] < 0.01:
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# This just makes sure were not keeping around keys that havent been called in a very long time.
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dead_keys.append(key)
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else:
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t_copy[key] = t_copy[key] * decay
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for dead in dead_keys:
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t_copy.pop(dead)
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self.trending_count = t_copy.copy()
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log.info("Decayed trending symbols.")
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def find_symbols(self, text: str, *, trending_weight: int = 1) -> list[Stock | Symbol]:
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"""Finds stock tickers starting with a dollar sign, and cryptocurrencies with two dollar signs
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in a blob of text and returns them in a list.
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Parameters
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----------
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text : str
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Blob of text.
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Returns
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-------
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list[Symbol]
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List of stock symbols as Symbol objects
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"""
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schedule.run_pending()
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symbols: list[Symbol] = []
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stocks = set(re.findall(self.STOCK_REGEX, text))
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for stock in stocks:
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# Market data lacks tools to check if a symbol is valid.
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symbols.append(Stock(stock))
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coins = set(re.findall(self.CRYPTO_REGEX, text))
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for coin in coins:
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sym = self.crypto.symbol_list[self.crypto.symbol_list["symbol"].str.fullmatch(coin.lower(), case=False)]
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if sym.empty:
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log.info(f"{coin} is not in list of coins")
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else:
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symbols.append(Coin(sym))
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if symbols:
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for symbol in symbols:
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self.trending_count[symbol.tag] = self.trending_count.get(symbol.tag, 0) + trending_weight
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log.debug(self.trending_count)
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return symbols
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def status(self, bot_resp) -> str:
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"""Checks for any issues with APIs.
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Returns
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-------
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str
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Human readable text on status of the bot and relevant APIs
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"""
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stats = f"""
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Bot Status:
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{bot_resp}
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Stock Market Data:
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{self.stock.status()}
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Cryptocurrency Data:
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{self.crypto.status()}
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"""
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log.warning(stats)
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return stats
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def inline_search(self, search: str, matches: int = 5) -> pd.DataFrame:
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"""Searches based on the shortest symbol that contains the same string as the search.
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Should be very fast compared to a fuzzy search.
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Parameters
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----------
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search : str
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String used to match against symbols.
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Returns
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-------
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list[tuple[str, str]]
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Each tuple contains: (Symbol, Issue Name).
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"""
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df = pd.concat([self.stock.symbol_list, self.crypto.symbol_list])
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df = df[df["description"].str.contains(search, regex=False, case=False)].sort_values(
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by="type_id", key=lambda x: x.str.len()
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)
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symbols = df.head(matches)
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symbols["price_reply"] = symbols["type_id"].apply(
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lambda sym: self.price_reply(self.find_symbols(sym, trending_weight=0))[0]
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)
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return symbols
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def price_reply(self, symbols: list[Symbol]) -> list[str]:
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"""Returns current market price or after hours if its available for a given stock symbol.
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Parameters
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----------
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symbols : list
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List of stock symbols.
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Returns
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-------
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Dict[str, str]
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Each symbol passed in is a key with its value being a human readable
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markdown formatted string of the symbols price and movement.
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"""
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replies = []
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for symbol in symbols:
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log.info(symbol)
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if isinstance(symbol, Stock):
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replies.append(self.stock.price_reply(symbol))
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elif isinstance(symbol, Coin):
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replies.append(self.crypto.price_reply(symbol))
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else:
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log.info(f"{symbol} is not a Stock or Coin")
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return replies
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def info_reply(self, symbols: list) -> list[str]:
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"""Gets information on stock symbols.
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Parameters
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----------
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symbols : list[str]
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List of stock symbols.
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Returns
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-------
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Dict[str, str]
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Each symbol passed in is a key with its value being a human readable formatted
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string of the symbols information.
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"""
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replies = []
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for symbol in symbols:
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if isinstance(symbol, Stock):
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replies.append(self.stock.info_reply(symbol))
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elif isinstance(symbol, Coin):
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replies.append(self.crypto.info_reply(symbol))
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else:
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log.debug(f"{symbol} is not a Stock or Coin")
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return replies
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def intra_reply(self, symbol: Symbol) -> pd.DataFrame:
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"""Returns price data for a symbol since the last market open.
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Parameters
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----------
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symbol : str
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Stock symbol.
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Returns
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-------
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pd.DataFrame
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Returns a timeseries dataframe with high, low, and volume data if its available.
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Otherwise returns empty pd.DataFrame.
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"""
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if isinstance(symbol, Stock):
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return self.stock.intra_reply(symbol)
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elif isinstance(symbol, Coin):
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return self.crypto.intra_reply(symbol)
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else:
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log.debug(f"{symbol} is not a Stock or Coin")
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return pd.DataFrame()
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def chart_reply(self, symbol: Symbol) -> pd.DataFrame:
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"""Returns price data for a symbol of the past month up until the previous trading days close.
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Also caches multiple requests made in the same day.
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Parameters
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----------
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symbol : str
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Stock symbol.
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Returns
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-------
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pd.DataFrame
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Returns a timeseries dataframe with high, low, and volume data if its available.
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Otherwise returns empty pd.DataFrame.
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"""
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if isinstance(symbol, Stock):
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return self.stock.chart_reply(symbol)
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elif isinstance(symbol, Coin):
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return self.crypto.chart_reply(symbol)
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else:
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log.debug(f"{symbol} is not a Stock or Coin")
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return pd.DataFrame()
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def stat_reply(self, symbols: list[Symbol]) -> list[str]:
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"""Gets key statistics for each symbol in the list
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Parameters
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----------
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symbols : list[str]
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List of stock symbols
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Returns
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-------
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Dict[str, str]
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Each symbol passed in is a key with its value being a human readable
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formatted string of the symbols statistics.
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"""
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replies = []
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for symbol in symbols:
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if isinstance(symbol, Stock):
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replies.append(self.stock.stat_reply(symbol))
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elif isinstance(symbol, Coin):
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replies.append(self.crypto.stat_reply(symbol))
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else:
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log.debug(f"{symbol} is not a Stock or Coin")
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return replies
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def cap_reply(self, symbols: list[Symbol]) -> list[str]:
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"""Gets market cap for each symbol in the list
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Parameters
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----------
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symbols : list[str]
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List of stock symbols
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Returns
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-------
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Dict[str, str]
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Each symbol passed in is a key with its value being a human readable
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formatted string of the symbols market cap.
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"""
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replies = []
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for symbol in symbols:
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if isinstance(symbol, Stock):
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replies.append(self.stock.cap_reply(symbol))
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elif isinstance(symbol, Coin):
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replies.append(self.crypto.cap_reply(symbol))
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else:
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log.debug(f"{symbol} is not a Stock or Coin")
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return replies
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def spark_reply(self, symbols: list[Symbol]) -> list[str]:
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"""Gets change for each symbol and returns it in a compact format
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Parameters
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----------
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symbols : list[str]
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List of stock symbols
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Returns
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-------
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list[str]
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List of human readable strings.
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"""
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replies = []
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for symbol in symbols:
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if isinstance(symbol, Stock):
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replies.append(self.stock.spark_reply(symbol))
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elif isinstance(symbol, Coin):
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replies.append(self.crypto.spark_reply(symbol))
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else:
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log.debug(f"{symbol} is not a Stock or Coin")
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return replies
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@cached(cache=TTLCache(maxsize=1024, ttl=600))
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def trending(self) -> str:
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"""Checks APIs for trending symbols.
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Returns
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-------
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list[str]
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List of preformatted strings to be sent to user.
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"""
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# stocks = self.stock.trending()
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coins = self.crypto.trending()
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reply = ""
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log.warning(self.trending_count)
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if self.trending_count:
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reply += "🔥Trending on the Stock Bot:\n`"
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reply += "━" * len("Trending on the Stock Bot:") + "`\n"
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sorted_trending = [s[0] for s in sorted(self.trending_count.items(), key=lambda item: item[1])][::-1][0:5]
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log.warning(sorted_trending)
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for t in sorted_trending:
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reply += self.spark_reply(self.find_symbols(t))[0] + "\n"
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if coins:
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reply += "\n\n🦎Trending Crypto:\n`"
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reply += "━" * len("Trending Crypto:") + "`\n"
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for coin in coins:
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reply += coin + "\n"
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if "`$GME" in reply:
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reply = reply.replace("🔥", "🦍")
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if reply:
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return reply
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else:
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log.warning("Failed to collect trending data.")
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return "Trending data is not currently available."
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def random_pick(self) -> str:
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choice = random.choice(list(self.stock.symbol_list["description"]) + list(self.crypto.symbol_list["description"]))
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hold = (datetime.date.today() + datetime.timedelta(random.randint(1, 365))).strftime("%b %d, %Y")
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return f"{choice}\nBuy and hold until: {hold}"
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def batch_price_reply(self, symbols: list[Symbol]) -> list[str]:
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"""Returns current market price or after hours if its available for a given stock symbol.
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Parameters
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----------
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symbols : list
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List of stock symbols.
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Returns
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-------
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Dict[str, str]
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Each symbol passed in is a key with its value being a human readable
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markdown formatted string of the symbols price and movement.
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"""
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replies = []
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stocks = []
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coins = []
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for symbol in symbols:
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if isinstance(symbol, Stock):
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stocks.append(symbol)
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elif isinstance(symbol, Coin):
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coins.append(symbol)
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else:
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log.debug(f"{symbol} is not a Stock or Coin")
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if stocks:
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for stock in stocks:
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replies.append(self.stock.price_reply(stock))
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if coins:
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replies = replies + self.crypto.batch_price(coins)
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return replies
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