mirror of
https://gitlab.com/simple-stock-bots/simple-telegram-stock-bot.git
synced 2025-06-16 06:56:46 +00:00
fixed stock market cap bug
This commit is contained in:
parent
d533c2c4a2
commit
9d510fc104
958
IEX_Symbol.py
958
IEX_Symbol.py
@ -1,479 +1,479 @@
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"""Class with functions for running the bot with IEX Cloud.
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"""
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import logging
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import os
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from datetime import datetime
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from logging import warning
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from typing import List, Optional, Tuple
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import pandas as pd
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import requests as r
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import schedule
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from Symbol import Stock
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class IEX_Symbol:
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"""
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Functions for finding stock market information about symbols.
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"""
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SYMBOL_REGEX = "[$]([a-zA-Z]{1,4})"
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searched_symbols = {}
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otc_list = []
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charts = {}
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trending_cache = None
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def __init__(self) -> None:
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"""Creates a Symbol Object
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Parameters
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----------
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IEX_TOKEN : str
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IEX API Token
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"""
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try:
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self.IEX_TOKEN = os.environ["IEX"]
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except KeyError:
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self.IEX_TOKEN = ""
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warning(
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"Starting without an IEX Token will not allow you to get market data!"
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)
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if self.IEX_TOKEN != "":
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self.get_symbol_list()
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schedule.every().day.do(self.get_symbol_list)
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schedule.every().day.do(self.clear_charts)
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def get(self, endpoint, params: dict = {}, timeout=5) -> dict:
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url = "https://cloud.iexapis.com/stable" + endpoint
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# set token param if it wasn't passed.
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params["token"] = params.get("token", self.IEX_TOKEN)
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resp = r.get(url, params=params, timeout=timeout)
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# Make sure API returned a proper status code
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try:
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resp.raise_for_status()
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except r.exceptions.HTTPError as e:
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logging.error(e)
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return {}
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# Make sure API returned valid JSON
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try:
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resp_json = resp.json()
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return resp_json
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except r.exceptions.JSONDecodeError as e:
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logging.error(e)
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return {}
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def clear_charts(self) -> None:
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"""
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Clears cache of chart data.
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Charts are cached so that only 1 API call per 24 hours is needed since the
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chart data is expensive and a large download.
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"""
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self.charts = {}
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def get_symbol_list(
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self, return_df=False
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) -> Optional[Tuple[pd.DataFrame, datetime]]:
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"""Gets list of all symbols supported by IEX
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Parameters
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----------
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return_df : bool, optional
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return the dataframe of all stock symbols, by default False
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Returns
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-------
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Optional[Tuple[pd.DataFrame, datetime]]
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If `return_df` is set to `True` returns a dataframe, otherwise returns `None`.
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"""
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reg_symbols = self.get("/ref-data/symbols")
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otc_symbols = self.get("/ref-data/otc/symbols")
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reg = pd.DataFrame(data=reg_symbols)
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otc = pd.DataFrame(data=otc_symbols)
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self.otc_list = set(otc["symbol"].to_list())
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symbols = pd.concat([reg, otc])
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symbols["description"] = "$" + symbols["symbol"] + ": " + symbols["name"]
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symbols["id"] = symbols["symbol"]
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symbols["type_id"] = "$" + symbols["symbol"].str.lower()
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symbols = symbols[["id", "symbol", "name", "description", "type_id"]]
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self.symbol_list = symbols
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if return_df:
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return symbols, datetime.now()
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def status(self) -> str:
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"""Checks IEX Status dashboard for any current API issues.
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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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resp = r.get(
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"https://pjmps0c34hp7.statuspage.io/api/v2/status.json",
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timeout=15,
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)
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if resp.status_code == 200:
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status = resp.json()["status"]
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else:
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return "IEX Cloud did not respond. Please check their status page for more information. https://status.iexapis.com"
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if status["indicator"] == "none":
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return "IEX Cloud is currently not reporting any issues with its API."
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else:
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return (
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f"{status['indicator']}: {status['description']}."
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+ " Please check the status page for more information. https://status.iexapis.com"
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)
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def price_reply(self, symbol: Stock) -> str:
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"""Returns price movement of Stock for the last market day, or after hours.
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Parameters
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----------
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symbol : Stock
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Returns
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-------
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str
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Formatted markdown
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"""
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if IEXData := self.get(f"/stock/{symbol.id}/quote"):
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if symbol.symbol.upper() in self.otc_list:
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return f"OTC - {symbol.symbol.upper()}, {IEXData['companyName']} most recent price is: $**{IEXData['latestPrice']}**"
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keys = (
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"extendedChangePercent",
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"extendedPrice",
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"companyName",
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"latestPrice",
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"changePercent",
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)
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if set(keys).issubset(IEXData):
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if change := IEXData.get("changePercent", 0):
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change = round(change * 100, 2)
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else:
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change = 0
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if (
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IEXData.get("isUSMarketOpen", True)
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or (IEXData["extendedChangePercent"] is None)
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or (IEXData["extendedPrice"] is None)
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): # Check if market is open.
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message = f"The current stock price of {IEXData['companyName']} is $**{IEXData['latestPrice']}**"
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else:
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message = (
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f"{IEXData['companyName']} closed at $**{IEXData['latestPrice']}** with a change of {change}%,"
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+ f" after hours _(15 minutes delayed)_ the stock price is $**{IEXData['extendedPrice']}**"
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)
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if change := IEXData.get("extendedChangePercent", 0):
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change = round(change * 100, 2)
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else:
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change = 0
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# Determine wording of change text
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if change > 0:
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message += f", the stock is currently **up {change}%**"
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elif change < 0:
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message += f", the stock is currently **down {change}%**"
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else:
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message += ", the stock hasn't shown any movement today."
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else:
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message = (
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f"The symbol: {symbol} encountered and error. This could be due to "
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)
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else:
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message = f"The symbol: {symbol} was not found."
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return message
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def dividend_reply(self, symbol: Stock) -> 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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symbol : Stock
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Returns
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-------
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str
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Formatted markdown
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"""
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if symbol.symbol.upper() in self.otc_list:
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return "OTC stocks do not currently support any commands."
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if resp := self.get(f"/stock/{symbol.id}/dividends/next"):
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try:
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IEXData = resp[0]
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except IndexError as e:
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return f"${symbol.id.upper()} either doesn't exist or pays no dividend."
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keys = (
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"amount",
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"currency",
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"declaredDate",
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"exDate",
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"frequency",
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"paymentDate",
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"flag",
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)
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if set(keys).issubset(IEXData):
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if IEXData["currency"] == "USD":
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price = f"${IEXData['amount']}"
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else:
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price = f"{IEXData['amount']} {IEXData['currency']}"
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# Pattern IEX uses for dividend date.
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pattern = "%Y-%m-%d"
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declared = datetime.strptime(IEXData["declaredDate"], pattern).strftime(
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"%A, %B %w"
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)
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ex = datetime.strptime(IEXData["exDate"], pattern).strftime("%A, %B %w")
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payment = datetime.strptime(IEXData["paymentDate"], pattern).strftime(
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"%A, %B %w"
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)
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daysDelta = (
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datetime.strptime(IEXData["paymentDate"], pattern) - datetime.now()
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).days
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return (
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"The next dividend for "
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+ f"{self.symbol_list[self.symbol_list['symbol']==symbol.id.upper()]['description'].item()}" # Get full name without api call
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+ f" is on {payment} which is in {daysDelta} days."
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+ f" The dividend is for {price} per share."
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+ f"\n\nThe dividend was declared on {declared} and the ex-dividend date is {ex}"
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)
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return f"${symbol.id.upper()} either doesn't exist or pays no dividend."
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def news_reply(self, symbol: Stock) -> str:
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"""Gets most recent, english, non-paywalled news
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Parameters
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----------
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symbol : Stock
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Returns
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-------
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str
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Formatted markdown
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"""
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if symbol.symbol.upper() in self.otc_list:
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return "OTC stocks do not currently support any commands."
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if data := self.get(f"/stock/{symbol.id}/news/last/15"):
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line = []
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for news in data:
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if news["lang"] == "en" and not news["hasPaywall"]:
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line.append(
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f"*{news['source']}*: [{news['headline']}]({news['url']})"
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)
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return f"News for **{symbol.id.upper()}**:\n" + "\n".join(line[:5])
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else:
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return f"No news found for: {symbol.id}\nEither today is boring or the symbol does not exist."
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def info_reply(self, symbol: Stock) -> str:
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"""Gets description for Stock
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Parameters
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----------
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symbol : Stock
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Returns
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-------
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str
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Formatted text
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"""
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if symbol.symbol.upper() in self.otc_list:
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return "OTC stocks do not currently support any commands."
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if data := self.get(f"/stock/{symbol.id}/company"):
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[data.pop(k) for k in list(data) if data[k] == ""]
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if "description" in data:
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return data["description"]
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return f"No information found for: {symbol}\nEither today is boring or the symbol does not exist."
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def stat_reply(self, symbol: Stock) -> str:
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"""Key statistics on a Stock
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Parameters
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----------
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symbol : Stock
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Returns
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-------
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str
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Formatted markdown
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"""
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if symbol.symbol.upper() in self.otc_list:
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return "OTC stocks do not currently support any commands."
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if data := self.get(f"/stock/{symbol.id}/stats"):
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[data.pop(k) for k in list(data) if data[k] == ""]
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m = ""
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if "companyName" in data:
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m += f"Company Name: {data['companyName']}\n"
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if "marketcap" in data:
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m += f"Market Cap: ${data['marketcap']:,}\n"
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if "week52high" in data:
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m += f"52 Week (high-low): {data['week52high']:,} "
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if "week52low" in data:
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m += f"- {data['week52low']:,}\n"
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if "employees" in data:
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m += f"Number of Employees: {data['employees']:,}\n"
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if "nextEarningsDate" in data:
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m += f"Next Earnings Date: {data['nextEarningsDate']}\n"
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if "peRatio" in data:
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m += f"Price to Earnings: {data['peRatio']:.3f}\n"
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if "beta" in data:
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m += f"Beta: {data['beta']:.3f}\n"
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return m
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else:
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return f"No information found for: {symbol}\nEither today is boring or the symbol does not exist."
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def cap_reply(self, symbol: Stock) -> str:
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"""Get the Market Cap of a stock"""
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if data := self.get(f"/stable/stock/{symbol.id}/stats"):
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try:
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cap = data["marketcap"]
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except KeyError:
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return f"{symbol.id} returned an error."
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message = f"The current market cap of {symbol.name} is $**{cap:,.2f}**"
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else:
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message = f"The Stock: {symbol.name} was not found or returned and error."
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return message
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def intra_reply(self, symbol: Stock) -> 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 symbol.symbol.upper() in self.otc_list:
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return pd.DataFrame()
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if symbol.id.upper() not in list(self.symbol_list["symbol"]):
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return pd.DataFrame()
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if data := self.get(f"/stock/{symbol.id}/intraday-prices"):
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df = pd.DataFrame(data)
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df.dropna(inplace=True, subset=["date", "minute", "high", "low", "volume"])
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df["DT"] = pd.to_datetime(df["date"] + "T" + df["minute"])
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df = df.set_index("DT")
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return df
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return pd.DataFrame()
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def chart_reply(self, symbol: Stock) -> 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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schedule.run_pending()
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if symbol.symbol.upper() in self.otc_list:
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return pd.DataFrame()
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if symbol.id.upper() not in list(self.symbol_list["symbol"]):
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return pd.DataFrame()
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try: # https://stackoverflow.com/a/3845776/8774114
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return self.charts[symbol.id.upper()]
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except KeyError:
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pass
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if data := self.get(
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f"/stock/{symbol.id}/chart/1mm",
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params={"chartInterval": 3, "includeToday": "false"},
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):
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df = pd.DataFrame(data)
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df.dropna(inplace=True, subset=["date", "minute", "high", "low", "volume"])
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df["DT"] = pd.to_datetime(df["date"] + "T" + df["minute"])
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df = df.set_index("DT")
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self.charts[symbol.id.upper()] = df
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return df
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return pd.DataFrame()
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def spark_reply(self, symbol: Stock) -> str:
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quote = self.get(f"/stock/{symbol.id}/quote")
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open_change = quote.get("changePercent", 0)
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after_change = quote.get("extendedChangePercent", 0)
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change = 0
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if open_change:
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change = change + open_change
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if after_change:
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change = change + after_change
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change = change * 100
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return f"`{symbol.tag}`: {quote['companyName']}, {change:.2f}%"
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def trending(self) -> list[str]:
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"""Gets current coins trending on IEX. Only returns when market is open.
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Returns
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-------
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list[str]
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list of $ID: NAME, CHANGE%
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"""
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if data := self.get(f"/stock/market/list/mostactive"):
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self.trending_cache = [
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f"`${s['symbol']}`: {s['companyName']}, {100*s['changePercent']:.2f}%"
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for s in data
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]
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return self.trending_cache
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"""Class with functions for running the bot with IEX Cloud.
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"""
|
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import logging
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import os
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from datetime import datetime
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from logging import warning
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from typing import List, Optional, Tuple
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|
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import pandas as pd
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import requests as r
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import schedule
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from Symbol import Stock
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|
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|
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class IEX_Symbol:
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"""
|
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Functions for finding stock market information about symbols.
|
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"""
|
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|
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SYMBOL_REGEX = "[$]([a-zA-Z]{1,4})"
|
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|
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searched_symbols = {}
|
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otc_list = []
|
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charts = {}
|
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trending_cache = None
|
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|
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def __init__(self) -> None:
|
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"""Creates a Symbol Object
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|
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Parameters
|
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----------
|
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IEX_TOKEN : str
|
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IEX API Token
|
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"""
|
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try:
|
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self.IEX_TOKEN = os.environ["IEX"]
|
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except KeyError:
|
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self.IEX_TOKEN = ""
|
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warning(
|
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"Starting without an IEX Token will not allow you to get market data!"
|
||||
)
|
||||
|
||||
if self.IEX_TOKEN != "":
|
||||
self.get_symbol_list()
|
||||
|
||||
schedule.every().day.do(self.get_symbol_list)
|
||||
schedule.every().day.do(self.clear_charts)
|
||||
|
||||
def get(self, endpoint, params: dict = {}, timeout=5) -> dict:
|
||||
|
||||
url = "https://cloud.iexapis.com/stable" + endpoint
|
||||
|
||||
# set token param if it wasn't passed.
|
||||
params["token"] = params.get("token", self.IEX_TOKEN)
|
||||
|
||||
resp = r.get(url, params=params, timeout=timeout)
|
||||
|
||||
# Make sure API returned a proper status code
|
||||
try:
|
||||
resp.raise_for_status()
|
||||
except r.exceptions.HTTPError as e:
|
||||
logging.error(e)
|
||||
return {}
|
||||
|
||||
# Make sure API returned valid JSON
|
||||
try:
|
||||
resp_json = resp.json()
|
||||
return resp_json
|
||||
except r.exceptions.JSONDecodeError as e:
|
||||
logging.error(e)
|
||||
return {}
|
||||
|
||||
def clear_charts(self) -> None:
|
||||
"""
|
||||
Clears cache of chart data.
|
||||
Charts are cached so that only 1 API call per 24 hours is needed since the
|
||||
chart data is expensive and a large download.
|
||||
"""
|
||||
self.charts = {}
|
||||
|
||||
def get_symbol_list(
|
||||
self, return_df=False
|
||||
) -> Optional[Tuple[pd.DataFrame, datetime]]:
|
||||
"""Gets list of all symbols supported by IEX
|
||||
|
||||
Parameters
|
||||
----------
|
||||
return_df : bool, optional
|
||||
return the dataframe of all stock symbols, by default False
|
||||
|
||||
Returns
|
||||
-------
|
||||
Optional[Tuple[pd.DataFrame, datetime]]
|
||||
If `return_df` is set to `True` returns a dataframe, otherwise returns `None`.
|
||||
"""
|
||||
|
||||
reg_symbols = self.get("/ref-data/symbols")
|
||||
otc_symbols = self.get("/ref-data/otc/symbols")
|
||||
|
||||
reg = pd.DataFrame(data=reg_symbols)
|
||||
otc = pd.DataFrame(data=otc_symbols)
|
||||
self.otc_list = set(otc["symbol"].to_list())
|
||||
|
||||
symbols = pd.concat([reg, otc])
|
||||
|
||||
symbols["description"] = "$" + symbols["symbol"] + ": " + symbols["name"]
|
||||
symbols["id"] = symbols["symbol"]
|
||||
symbols["type_id"] = "$" + symbols["symbol"].str.lower()
|
||||
|
||||
symbols = symbols[["id", "symbol", "name", "description", "type_id"]]
|
||||
self.symbol_list = symbols
|
||||
if return_df:
|
||||
return symbols, datetime.now()
|
||||
|
||||
def status(self) -> str:
|
||||
"""Checks IEX Status dashboard for any current API issues.
|
||||
|
||||
Returns
|
||||
-------
|
||||
str
|
||||
Human readable text on status of IEX API
|
||||
"""
|
||||
resp = r.get(
|
||||
"https://pjmps0c34hp7.statuspage.io/api/v2/status.json",
|
||||
timeout=15,
|
||||
)
|
||||
|
||||
if resp.status_code == 200:
|
||||
status = resp.json()["status"]
|
||||
else:
|
||||
return "IEX Cloud did not respond. Please check their status page for more information. https://status.iexapis.com"
|
||||
|
||||
if status["indicator"] == "none":
|
||||
return "IEX Cloud is currently not reporting any issues with its API."
|
||||
else:
|
||||
return (
|
||||
f"{status['indicator']}: {status['description']}."
|
||||
+ " Please check the status page for more information. https://status.iexapis.com"
|
||||
)
|
||||
|
||||
def price_reply(self, symbol: Stock) -> str:
|
||||
"""Returns price movement of Stock for the last market day, or after hours.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
symbol : Stock
|
||||
|
||||
Returns
|
||||
-------
|
||||
str
|
||||
Formatted markdown
|
||||
"""
|
||||
|
||||
if IEXData := self.get(f"/stock/{symbol.id}/quote"):
|
||||
|
||||
if symbol.symbol.upper() in self.otc_list:
|
||||
return f"OTC - {symbol.symbol.upper()}, {IEXData['companyName']} most recent price is: $**{IEXData['latestPrice']}**"
|
||||
|
||||
keys = (
|
||||
"extendedChangePercent",
|
||||
"extendedPrice",
|
||||
"companyName",
|
||||
"latestPrice",
|
||||
"changePercent",
|
||||
)
|
||||
|
||||
if set(keys).issubset(IEXData):
|
||||
|
||||
if change := IEXData.get("changePercent", 0):
|
||||
change = round(change * 100, 2)
|
||||
else:
|
||||
change = 0
|
||||
|
||||
if (
|
||||
IEXData.get("isUSMarketOpen", True)
|
||||
or (IEXData["extendedChangePercent"] is None)
|
||||
or (IEXData["extendedPrice"] is None)
|
||||
): # Check if market is open.
|
||||
message = f"The current stock price of {IEXData['companyName']} is $**{IEXData['latestPrice']}**"
|
||||
else:
|
||||
message = (
|
||||
f"{IEXData['companyName']} closed at $**{IEXData['latestPrice']}** with a change of {change}%,"
|
||||
+ f" after hours _(15 minutes delayed)_ the stock price is $**{IEXData['extendedPrice']}**"
|
||||
)
|
||||
if change := IEXData.get("extendedChangePercent", 0):
|
||||
change = round(change * 100, 2)
|
||||
else:
|
||||
change = 0
|
||||
|
||||
# Determine wording of change text
|
||||
if change > 0:
|
||||
message += f", the stock is currently **up {change}%**"
|
||||
elif change < 0:
|
||||
message += f", the stock is currently **down {change}%**"
|
||||
else:
|
||||
message += ", the stock hasn't shown any movement today."
|
||||
else:
|
||||
message = (
|
||||
f"The symbol: {symbol} encountered and error. This could be due to "
|
||||
)
|
||||
|
||||
else:
|
||||
message = f"The symbol: {symbol} was not found."
|
||||
|
||||
return message
|
||||
|
||||
def dividend_reply(self, symbol: Stock) -> str:
|
||||
"""Returns the most recent, or next dividend date for a stock symbol.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
symbol : Stock
|
||||
|
||||
Returns
|
||||
-------
|
||||
str
|
||||
Formatted markdown
|
||||
"""
|
||||
if symbol.symbol.upper() in self.otc_list:
|
||||
return "OTC stocks do not currently support any commands."
|
||||
|
||||
if resp := self.get(f"/stock/{symbol.id}/dividends/next"):
|
||||
try:
|
||||
IEXData = resp[0]
|
||||
except IndexError as e:
|
||||
return f"${symbol.id.upper()} either doesn't exist or pays no dividend."
|
||||
keys = (
|
||||
"amount",
|
||||
"currency",
|
||||
"declaredDate",
|
||||
"exDate",
|
||||
"frequency",
|
||||
"paymentDate",
|
||||
"flag",
|
||||
)
|
||||
|
||||
if set(keys).issubset(IEXData):
|
||||
|
||||
if IEXData["currency"] == "USD":
|
||||
price = f"${IEXData['amount']}"
|
||||
else:
|
||||
price = f"{IEXData['amount']} {IEXData['currency']}"
|
||||
|
||||
# Pattern IEX uses for dividend date.
|
||||
pattern = "%Y-%m-%d"
|
||||
|
||||
declared = datetime.strptime(IEXData["declaredDate"], pattern).strftime(
|
||||
"%A, %B %w"
|
||||
)
|
||||
ex = datetime.strptime(IEXData["exDate"], pattern).strftime("%A, %B %w")
|
||||
payment = datetime.strptime(IEXData["paymentDate"], pattern).strftime(
|
||||
"%A, %B %w"
|
||||
)
|
||||
|
||||
daysDelta = (
|
||||
datetime.strptime(IEXData["paymentDate"], pattern) - datetime.now()
|
||||
).days
|
||||
|
||||
return (
|
||||
"The next dividend for "
|
||||
+ f"{self.symbol_list[self.symbol_list['symbol']==symbol.id.upper()]['description'].item()}" # Get full name without api call
|
||||
+ f" is on {payment} which is in {daysDelta} days."
|
||||
+ f" The dividend is for {price} per share."
|
||||
+ f"\n\nThe dividend was declared on {declared} and the ex-dividend date is {ex}"
|
||||
)
|
||||
|
||||
return f"${symbol.id.upper()} either doesn't exist or pays no dividend."
|
||||
|
||||
def news_reply(self, symbol: Stock) -> str:
|
||||
"""Gets most recent, english, non-paywalled news
|
||||
|
||||
Parameters
|
||||
----------
|
||||
symbol : Stock
|
||||
|
||||
Returns
|
||||
-------
|
||||
str
|
||||
Formatted markdown
|
||||
"""
|
||||
if symbol.symbol.upper() in self.otc_list:
|
||||
return "OTC stocks do not currently support any commands."
|
||||
|
||||
if data := self.get(f"/stock/{symbol.id}/news/last/15"):
|
||||
line = []
|
||||
|
||||
for news in data:
|
||||
if news["lang"] == "en" and not news["hasPaywall"]:
|
||||
line.append(
|
||||
f"*{news['source']}*: [{news['headline']}]({news['url']})"
|
||||
)
|
||||
|
||||
return f"News for **{symbol.id.upper()}**:\n" + "\n".join(line[:5])
|
||||
|
||||
else:
|
||||
return f"No news found for: {symbol.id}\nEither today is boring or the symbol does not exist."
|
||||
|
||||
def info_reply(self, symbol: Stock) -> str:
|
||||
"""Gets description for Stock
|
||||
|
||||
Parameters
|
||||
----------
|
||||
symbol : Stock
|
||||
|
||||
Returns
|
||||
-------
|
||||
str
|
||||
Formatted text
|
||||
"""
|
||||
if symbol.symbol.upper() in self.otc_list:
|
||||
return "OTC stocks do not currently support any commands."
|
||||
|
||||
if data := self.get(f"/stock/{symbol.id}/company"):
|
||||
[data.pop(k) for k in list(data) if data[k] == ""]
|
||||
|
||||
if "description" in data:
|
||||
return data["description"]
|
||||
|
||||
return f"No information found for: {symbol}\nEither today is boring or the symbol does not exist."
|
||||
|
||||
def stat_reply(self, symbol: Stock) -> str:
|
||||
"""Key statistics on a Stock
|
||||
|
||||
Parameters
|
||||
----------
|
||||
symbol : Stock
|
||||
|
||||
Returns
|
||||
-------
|
||||
str
|
||||
Formatted markdown
|
||||
"""
|
||||
if symbol.symbol.upper() in self.otc_list:
|
||||
return "OTC stocks do not currently support any commands."
|
||||
|
||||
if data := self.get(f"/stock/{symbol.id}/stats"):
|
||||
[data.pop(k) for k in list(data) if data[k] == ""]
|
||||
|
||||
m = ""
|
||||
if "companyName" in data:
|
||||
m += f"Company Name: {data['companyName']}\n"
|
||||
if "marketcap" in data:
|
||||
m += f"Market Cap: ${data['marketcap']:,}\n"
|
||||
if "week52high" in data:
|
||||
m += f"52 Week (high-low): {data['week52high']:,} "
|
||||
if "week52low" in data:
|
||||
m += f"- {data['week52low']:,}\n"
|
||||
if "employees" in data:
|
||||
m += f"Number of Employees: {data['employees']:,}\n"
|
||||
if "nextEarningsDate" in data:
|
||||
m += f"Next Earnings Date: {data['nextEarningsDate']}\n"
|
||||
if "peRatio" in data:
|
||||
m += f"Price to Earnings: {data['peRatio']:.3f}\n"
|
||||
if "beta" in data:
|
||||
m += f"Beta: {data['beta']:.3f}\n"
|
||||
return m
|
||||
else:
|
||||
return f"No information found for: {symbol}\nEither today is boring or the symbol does not exist."
|
||||
|
||||
def cap_reply(self, symbol: Stock) -> str:
|
||||
"""Get the Market Cap of a stock"""
|
||||
|
||||
if data := self.get(f"/stock/{symbol.id}/stats"):
|
||||
|
||||
try:
|
||||
cap = data["marketcap"]
|
||||
except KeyError:
|
||||
return f"{symbol.id} returned an error."
|
||||
|
||||
message = f"The current market cap of {symbol.name} is $**{cap:,.2f}**"
|
||||
|
||||
else:
|
||||
message = f"The Stock: {symbol.name} was not found or returned and error."
|
||||
|
||||
return message
|
||||
|
||||
def intra_reply(self, symbol: Stock) -> pd.DataFrame:
|
||||
"""Returns price data for a symbol since the last market open.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
symbol : str
|
||||
Stock symbol.
|
||||
|
||||
Returns
|
||||
-------
|
||||
pd.DataFrame
|
||||
Returns a timeseries dataframe with high, low, and volume data if its available. Otherwise returns empty pd.DataFrame.
|
||||
"""
|
||||
if symbol.symbol.upper() in self.otc_list:
|
||||
return pd.DataFrame()
|
||||
|
||||
if symbol.id.upper() not in list(self.symbol_list["symbol"]):
|
||||
return pd.DataFrame()
|
||||
|
||||
if data := self.get(f"/stock/{symbol.id}/intraday-prices"):
|
||||
df = pd.DataFrame(data)
|
||||
df.dropna(inplace=True, subset=["date", "minute", "high", "low", "volume"])
|
||||
df["DT"] = pd.to_datetime(df["date"] + "T" + df["minute"])
|
||||
df = df.set_index("DT")
|
||||
return df
|
||||
|
||||
return pd.DataFrame()
|
||||
|
||||
def chart_reply(self, symbol: Stock) -> pd.DataFrame:
|
||||
"""Returns price data for a symbol of the past month up until the previous trading days close.
|
||||
Also caches multiple requests made in the same day.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
symbol : str
|
||||
Stock symbol.
|
||||
|
||||
Returns
|
||||
-------
|
||||
pd.DataFrame
|
||||
Returns a timeseries dataframe with high, low, and volume data if its available. Otherwise returns empty pd.DataFrame.
|
||||
"""
|
||||
schedule.run_pending()
|
||||
|
||||
if symbol.symbol.upper() in self.otc_list:
|
||||
return pd.DataFrame()
|
||||
|
||||
if symbol.id.upper() not in list(self.symbol_list["symbol"]):
|
||||
return pd.DataFrame()
|
||||
|
||||
try: # https://stackoverflow.com/a/3845776/8774114
|
||||
return self.charts[symbol.id.upper()]
|
||||
except KeyError:
|
||||
pass
|
||||
|
||||
if data := self.get(
|
||||
f"/stock/{symbol.id}/chart/1mm",
|
||||
params={"chartInterval": 3, "includeToday": "false"},
|
||||
):
|
||||
df = pd.DataFrame(data)
|
||||
df.dropna(inplace=True, subset=["date", "minute", "high", "low", "volume"])
|
||||
df["DT"] = pd.to_datetime(df["date"] + "T" + df["minute"])
|
||||
df = df.set_index("DT")
|
||||
self.charts[symbol.id.upper()] = df
|
||||
return df
|
||||
|
||||
return pd.DataFrame()
|
||||
|
||||
def spark_reply(self, symbol: Stock) -> str:
|
||||
quote = self.get(f"/stock/{symbol.id}/quote")
|
||||
|
||||
open_change = quote.get("changePercent", 0)
|
||||
after_change = quote.get("extendedChangePercent", 0)
|
||||
|
||||
change = 0
|
||||
|
||||
if open_change:
|
||||
change = change + open_change
|
||||
if after_change:
|
||||
change = change + after_change
|
||||
|
||||
change = change * 100
|
||||
|
||||
return f"`{symbol.tag}`: {quote['companyName']}, {change:.2f}%"
|
||||
|
||||
def trending(self) -> list[str]:
|
||||
"""Gets current coins trending on IEX. Only returns when market is open.
|
||||
|
||||
Returns
|
||||
-------
|
||||
list[str]
|
||||
list of $ID: NAME, CHANGE%
|
||||
"""
|
||||
|
||||
if data := self.get(f"/stock/market/list/mostactive"):
|
||||
self.trending_cache = [
|
||||
f"`${s['symbol']}`: {s['companyName']}, {100*s['changePercent']:.2f}%"
|
||||
for s in data
|
||||
]
|
||||
|
||||
return self.trending_cache
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user