mirror of
https://gitlab.com/simple-stock-bots/simple-stock-bot.git
synced 2025-06-16 07:16:40 +00:00
228 lines
6.7 KiB
Python
228 lines
6.7 KiB
Python
"""Function that routes symbols to the correct API provider.
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"""
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import re
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import pandas as pd
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from typing import List, Dict
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from IEX_Symbol import IEX_Symbol
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from cg_Crypto import cg_Crypto
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class Router:
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STOCK_REGEX = "(?:^|[^\\$])\\$([a-zA-Z]{1,4})"
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CRYPTO_REGEX = "[$]{2}([a-zA-Z]{1,9})"
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def __init__(self, IEX_TOKEN):
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self.symbol = IEX_Symbol(IEX_TOKEN)
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self.crypto = cg_Crypto()
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def find_symbols(self, text: str) -> Dict[str, str]:
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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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Only returns each match once. Example: Whats the price of $tsla?
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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[str]
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List of stock symbols as strings without dollar sign.
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"""
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symbols = {}
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symbols["stocks"] = list(set(re.findall(self.STOCK_REGEX, text)))
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symbols["crypto"] = [
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self.crypto.symbol_id(c) for c in set(re.findall(self.CRYPTO_REGEX, text))
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]
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return symbols
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def status(self) -> 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 IEX API
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"""
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def search_symbols(self, search: str) -> List[str]:
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"""Performs a fuzzy search to find stock symbols closest to a search term.
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Parameters
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----------
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search : str
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String used to search, could be a company name or something close to the companies stock ticker.
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Returns
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-------
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List[tuple[str, str]]
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A list tuples of every stock sorted in order of how well they match. Each tuple contains: (Symbol, Issue Name).
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"""
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# TODO add support for crypto
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return self.symbol.find_symbols(str)
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def price_reply(self, symbols: dict) -> 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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if symbols["stocks"]:
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for s in symbols["stocks"]:
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replies.append(self.symbol.price_reply(s))
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if symbols["crypto"]:
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for s in symbols["crypto"]:
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replies.append(self.crypto.price_reply(s))
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return replies
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def dividend_reply(self, symbols: dict) -> Dict[str, str]:
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"""Returns the most recent, or next dividend date for a 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 formatted string of the symbols div dates.
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"""
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replies = []
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if symbols["stocks"]:
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for s in symbols["stocks"]:
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replies.append(self.symbol.price_reply(s))
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if symbols["crypto"]:
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replies.append("Cryptocurrencies do no have Dividends.")
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def news_reply(self, symbols: dict) -> List[str]:
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"""Gets recent english news on stock symbols.
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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 markdown formatted string of the symbols news.
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"""
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replies = []
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if symbols["stocks"]:
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for s in symbols["stocks"]:
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replies.append(self.symbol.price_reply(s))
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if symbols["crypto"]:
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for s in symbols["crypto"]:
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replies.append(self.crypto.price_reply(s))
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return replies
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def info_reply(self, symbols: dict) -> 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 string of the symbols information.
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"""
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replies = []
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if symbols["stocks"]:
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for s in symbols["stocks"]:
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replies.append(self.symbol.price_reply(s))
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if symbols["crypto"]:
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for s in symbols["crypto"]:
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replies.append(self.crypto.price_reply(s))
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return replies
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def intra_reply(self, symbol: str, type: str) -> 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. Otherwise returns empty pd.DataFrame.
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"""
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if type == "stocks":
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return self.symbol.intra_reply(symbol)
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elif type == "crypto":
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return self.crypto.intra_reply(symbol)
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else:
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raise f"Unknown type: {type}"
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def chart_reply(self, symbols: str) -> 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. Otherwise returns empty pd.DataFrame.
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"""
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if symbols["stocks"]:
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return self.symbol.intra_reply(symbol := symbols["stocks"][0]), symbol
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if symbols["crypto"]:
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return self.symbol.intra_reply(symbol := symbols["crypto"][0]), symbol
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def stat_reply(self, symbols: List[str]) -> Dict[str, 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 formatted string of the symbols statistics.
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"""
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replies = []
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if symbols["stocks"]:
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for s in symbols["stocks"]:
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replies.append(self.symbol.price_reply(s))
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if symbols["crypto"]:
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for s in symbols["crypto"]:
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replies.append(self.crypto.price_reply(s))
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