mirror of
https://gitlab.com/simple-stock-bots/simple-discord-stock-bot.git
synced 2025-06-15 23:06:40 +00:00
498 lines
16 KiB
Python
498 lines
16 KiB
Python
"""Class with functions for running the bot with IEX Cloud.
|
|
"""
|
|
|
|
import logging
|
|
import os
|
|
from datetime import datetime
|
|
from logging import warning
|
|
from typing import List, Optional, Tuple
|
|
|
|
import pandas as pd
|
|
import requests as r
|
|
import schedule
|
|
|
|
from Symbol import Stock
|
|
|
|
|
|
class IEX_Symbol:
|
|
"""
|
|
Functions for finding stock market information about symbols.
|
|
"""
|
|
|
|
SYMBOL_REGEX = "[$]([a-zA-Z]{1,4})"
|
|
|
|
searched_symbols = {}
|
|
otc_list = []
|
|
charts = {}
|
|
trending_cache = None
|
|
|
|
def __init__(self) -> None:
|
|
"""Creates a Symbol Object
|
|
|
|
Parameters
|
|
----------
|
|
IEX_TOKEN : str
|
|
IEX API Token
|
|
"""
|
|
try:
|
|
self.IEX_TOKEN = os.environ["IEX"]
|
|
|
|
if self.IEX_TOKEN == "TOKEN":
|
|
self.IEX_TOKEN = ""
|
|
except KeyError:
|
|
self.IEX_TOKEN = ""
|
|
warning(
|
|
"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()
|
|
|
|
# IEX uses backtick ` as apostrophe which breaks telegram markdown parsing
|
|
if type(resp_json) is dict:
|
|
resp_json["companyName"] = resp_json.get("companyName", "").replace(
|
|
"`", "'"
|
|
)
|
|
|
|
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])
|
|
|
|
# IEX uses backtick ` as apostrophe which breaks telegram markdown parsing
|
|
symbols["name"] = symbols["name"].str.replace("`", "'")
|
|
|
|
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
|
|
"""
|
|
|
|
if self.IEX_TOKEN == "":
|
|
return "The `IEX_TOKEN` is not set so Stock Market data is not available."
|
|
|
|
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:
|
|
logging.info(e)
|
|
return f"Getting dividend information for ${symbol.id.upper()} encountered an error. The provider for upcoming dividend information has been having issues recently which has likely caused this error. It is also possible that the stock has no dividend or does not exist."
|
|
keys = (
|
|
"amount",
|
|
"currency",
|
|
"declaredDate",
|
|
"exDate",
|
|
"frequency",
|
|
"paymentDate",
|
|
"flag",
|
|
)
|
|
|
|
if set(keys).issubset(IEXData):
|
|
|
|
if IEXData["currency"] == "USD":
|
|
price = f"${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"Getting dividend information for ${symbol.id.upper()} encountered an error. The provider for upcoming dividend information has been having issues recently which has likely caused this error. It is also possible that the stock has no dividend or does not exist."
|
|
|
|
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
|