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mirror of https://gitlab.com/simple-stock-bots/simple-telegram-stock-bot.git synced 2025-06-16 15:06:53 +00:00

213 lines
5.8 KiB
Python

"""Class with functions for running the bot with IEX Cloud.
"""
import logging
import os
import datetime as dt
from logging import warning
from typing import Dict
import pandas as pd
import requests as r
import schedule
from Symbol import Stock
class MarketData:
"""
Functions for finding stock market information about symbols from MarkData.app
"""
SYMBOL_REGEX = "[$]([a-zA-Z]{1,4})"
charts: Dict[Stock, pd.DataFrame] = {}
def __init__(self) -> None:
"""Creates a Symbol Object
Parameters
----------
MARKETDATA_TOKEN : str
MarketData.app API Token
"""
try:
self.MARKETDATA_TOKEN = os.environ["MARKETDATA"]
if self.MARKETDATA_TOKEN == "TOKEN":
self.MARKETDATA_TOKEN = ""
except KeyError:
self.MARKETDATA_TOKEN = ""
warning("Starting without an MarketData.app Token will not allow you to get market data!")
if self.MARKETDATA_TOKEN != "":
schedule.every().day.do(self.clear_charts)
def get(self, endpoint, params: dict = {}, timeout=10) -> dict:
url = "https://api.marketdata.app/v1/" + endpoint
# set token param if it wasn't passed.
params["token"] = params.get("token", self.MARKETDATA_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()
match resp_json["s"]:
case "ok":
return resp_json
case "no_data":
return resp_json
case "error":
logging.error("MarketData Error:\n" + resp_json["errmsg"])
return {}
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 status(self) -> str:
return "status isnt implemented by marketdata.app"
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 quoteResp := self.get(f"stocks/quotes/{symbol}/"):
return f"The current price of {quoteResp['symbol']} is ${quoteResp['last']}"
else:
return f"Getting a quote for {symbol} encountered an error."
def intra_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()
try:
return self.charts[symbol.id.upper()]
except KeyError:
pass
resolution = "5" # minutes
if data := self.get(
f"stocks/candles/{resolution}/{symbol}",
params={
"from": dt.datetime.now().strftime("%Y-%m-%d"),
"to": dt.datetime.now().isoformat(),
},
):
data.pop("s")
df = pd.DataFrame(data)
df["t"] = pd.to_datetime(df["t"], unit="s")
df.set_index("t", inplace=True)
df.rename(
columns={
"o": "Open",
"h": "High",
"l": "Low",
"c": "Close",
"v": "Volume",
},
inplace=True,
)
self.charts[symbol.id.upper()] = df
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()
try:
return self.charts[symbol.id.upper()]
except KeyError:
pass
to_date = dt.datetime.today().strftime("%Y-%m-%d")
from_date = (dt.datetime.today() - dt.timedelta(days=30)).strftime("%Y-%m-%d")
resultion = "daily"
if data := self.get(
f"stocks/candles/{resultion}/{symbol}",
params={
"from": from_date,
"to": to_date,
},
):
data.pop("s")
df = pd.DataFrame(data)
df["t"] = pd.to_datetime(df["t"], unit="s")
df.set_index("t", inplace=True)
df.rename(
columns={
"o": "Open",
"h": "High",
"l": "Low",
"c": "Close",
"v": "Volume",
},
inplace=True,
)
self.charts[symbol.id.upper()] = df
return df
return pd.DataFrame()