mirror of
https://gitlab.com/simple-stock-bots/simple-telegram-stock-bot.git
synced 2025-07-25 23:51:32 +00:00
Resolve "Combine Discord and Telegram bots into one repo and deploy with docker compose"
This commit is contained in:
263
common/MarketData.py
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263
common/MarketData.py
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import datetime as dt
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import logging
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import os
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from typing import Dict
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import pandas as pd
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import pytz
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import requests as r
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import schedule
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from common.Symbol import Stock
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log = logging.getLogger(__name__)
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class MarketData:
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"""
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Functions for finding stock market information about symbols from MarkData.app
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"""
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SYMBOL_REGEX = "[$]([a-zA-Z]{1,4})"
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charts: Dict[Stock, pd.DataFrame] = {}
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openTime = dt.time(hour=9, minute=30, second=0)
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marketTimeZone = pytz.timezone("US/Eastern")
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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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MARKETDATA_TOKEN : str
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MarketData.app API Token
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"""
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try:
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self.MARKETDATA_TOKEN = os.environ["MARKETDATA"]
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if self.MARKETDATA_TOKEN == "TOKEN":
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self.MARKETDATA_TOKEN = ""
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except KeyError:
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self.MARKETDATA_TOKEN = ""
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log.warning("Starting without an MarketData.app Token will not allow you to get market data!")
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log.warning("Use this affiliate link so that the bot can stay free:")
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log.warning("https://dashboard.marketdata.app/marketdata/aff/go/misterbiggs?keyword=repo")
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if self.MARKETDATA_TOKEN != "":
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schedule.every().day.do(self.clear_charts)
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def get(self, endpoint, params: dict = {}, timeout=10) -> dict:
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url = "https://api.marketdata.app/v1/" + endpoint
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# set token param if it wasn't passed.
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params["token"] = self.MARKETDATA_TOKEN
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# Undocumented query variable that ensures bot usage can be
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# monitored even if someone doesn't make it through an affiliate link.
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params["application"] = "simplestockbot"
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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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match resp_json["s"]:
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case "ok":
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return resp_json
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case "no_data":
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return resp_json
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case "error":
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logging.error("MarketData Error:\n" + resp_json["errmsg"])
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return {}
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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 status(self) -> str:
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# TODO: At the moment this API is poorly documented, this function likely needs to be revisited later.
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try:
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status = r.get(
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"https://stats.uptimerobot.com/api/getMonitorList/6Kv3zIow0A",
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timeout=5,
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)
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status.raise_for_status()
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except r.HTTPError:
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return f"API returned an HTTP error code {status.status_code} in {status.elapsed.total_seconds()} Seconds."
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except r.Timeout:
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return "API timed out before it was able to give status. This is likely due to a surge in usage or a complete outage."
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statusJSON = status.json()
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if statusJSON["status"] == "ok":
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return (
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f"CoinGecko API responded that it was OK with a {status.status_code} in {status.elapsed.total_seconds()} Seconds."
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)
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else:
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return f"MarketData.app is currently reporting the following status: {statusJSON['status']}"
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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 quoteResp := self.get(f"stocks/quotes/{symbol}/"):
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price = round(quoteResp["last"][0], 2)
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changePercent = round(quoteResp["changepct"][0], 2)
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message = f"The current price of {symbol.name} is ${price} and "
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if changePercent > 0.0:
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message += f"is currently up {changePercent}% for the day."
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elif changePercent < 0.0:
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message += f"is currently down {changePercent}% for the day."
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else:
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message += "hasn't shown any movement for the day."
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return message
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else:
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return f"Getting a quote for {symbol} encountered an error."
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def spark_reply(self, symbol: Stock) -> str:
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if quoteResp := self.get(f"stocks/quotes/{symbol}/"):
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changePercent = round(quoteResp["changepct"][0], 2)
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return f"`{symbol.tag}`: {changePercent}%"
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else:
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logging.warning(f"{symbol} did not have 'changepct' field.")
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return f"`{symbol.tag}`"
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def intra_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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try:
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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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resolution = "15" # minutes
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now = dt.datetime.now(self.marketTimeZone)
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if self.openTime < now.time():
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startTime = now.replace(hour=9, minute=30)
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else:
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startTime = now - dt.timedelta(days=1)
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if data := self.get(
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f"stocks/candles/{resolution}/{symbol}",
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params={"from": startTime.timestamp(), "to": now.timestamp(), "extended": True},
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):
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data.pop("s")
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df = pd.DataFrame(data)
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df["t"] = pd.to_datetime(df["t"], unit="s", utc=True)
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df.set_index("t", inplace=True)
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df.rename(
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columns={
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"o": "Open",
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"h": "High",
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"l": "Low",
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"c": "Close",
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"v": "Volume",
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},
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inplace=True,
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)
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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 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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try:
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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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to_date = dt.datetime.today().strftime("%Y-%m-%d")
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from_date = (dt.datetime.today() - dt.timedelta(days=30)).strftime("%Y-%m-%d")
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resultion = "daily"
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if data := self.get(
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f"stocks/candles/{resultion}/{symbol}",
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params={
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"from": from_date,
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"to": to_date,
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},
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):
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data.pop("s")
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df = pd.DataFrame(data)
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df["t"] = pd.to_datetime(df["t"], unit="s")
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df.set_index("t", inplace=True)
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df.rename(
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columns={
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"o": "Open",
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"h": "High",
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"l": "Low",
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"c": "Close",
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"v": "Volume",
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},
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inplace=True,
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)
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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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