mirror of
https://gitlab.com/simple-stock-bots/simple-stock-bot.git
synced 2025-09-12 16:54:59 +00:00
Archive the Bot
This commit is contained in:
@@ -1,362 +1,367 @@
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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 collections import OrderedDict
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from typing import Dict
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import humanize
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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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symbol_list: Dict[str, Dict] = {}
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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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self.get_symbol_list()
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schedule.every().day.do(self.get_symbol_list)
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def get(self, endpoint, params=None, timeout=10, headers=None) -> dict:
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url = "https://api.marketdata.app/v1/" + endpoint
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if params is None:
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params = {}
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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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if headers is None:
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headers = {}
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headers = {"User-Agent": "Simple Stock Bot anson@ansonbiggs.com"} | headers
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resp = r.get(url, params=params, timeout=timeout, headers=headers)
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logging.error(resp.headers.items())
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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 symbol_id(self, symbol: str) -> Dict[str, Dict]:
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return self.symbol_list.get(symbol.upper(), None)
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def get_symbol_list(self):
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# Doesn't use `self.get`` since needs are much different
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sec_resp = r.get(
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"https://www.sec.gov/files/company_tickers.json",
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headers={
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"User-Agent": "Simple Stock Bot anson@ansonbiggs.com",
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"Accept-Encoding": "gzip, deflate",
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"Host": "www.sec.gov",
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},
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)
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sec_resp.raise_for_status()
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sec_data = sec_resp.json()
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for rank, ticker_info in sec_data.items():
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self.symbol_list[ticker_info["ticker"]] = {
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"ticker": ticker_info["ticker"],
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"title": ticker_info["title"],
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"mkt_cap_rank": rank,
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}
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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.symbol}/"):
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price = round(quoteResp["last"][0], 2)
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try:
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changePercent = round(quoteResp["changepct"][0], 2)
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except TypeError:
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return f"The price of {symbol.name} is ${price}"
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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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try:
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changePercent = round(quoteResp["changepct"][0], 2)
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return f"`{symbol.tag}`: {changePercent}%"
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except TypeError:
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pass
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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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def options_reply(self, request: str) -> str:
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"""Undocumented API Usage!"""
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options_data = self.get(f"options/quotes/{request}")
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for key in options_data.keys():
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options_data[key] = options_data[key][0]
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options_data["underlying"] = "$" + options_data["underlying"]
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options_data["updated"] = humanize.naturaltime(dt.datetime.now() - dt.datetime.fromtimestamp(options_data["updated"]))
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options_data["expiration"] = humanize.naturaltime(
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dt.datetime.now() - dt.datetime.fromtimestamp(options_data["expiration"])
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)
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options_data["firstTraded"] = humanize.naturaltime(
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dt.datetime.now() - dt.datetime.fromtimestamp(options_data["firstTraded"])
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)
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rename = {
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"optionSymbol": "Option Symbol",
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"underlying": "Underlying",
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"expiration": "Expiration",
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"side": "side",
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"strike": "strike",
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"firstTraded": "First Traded",
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"updated": "Last Updated",
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"bid": "bid",
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"bidSize": "bidSize",
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"mid": "mid",
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"ask": "ask",
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"askSize": "askSize",
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"last": "last",
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"openInterest": "Open Interest",
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"volume": "Volume",
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"inTheMoney": "inTheMoney",
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"intrinsicValue": "Intrinsic Value",
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"extrinsicValue": "Extrinsic Value",
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||||
"underlyingPrice": "Underlying Price",
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"iv": "Implied Volatility",
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"delta": "delta",
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||||
"gamma": "gamma",
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||||
"theta": "theta",
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||||
"vega": "vega",
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"rho": "rho",
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||||
}
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||||
options_cleaned = OrderedDict()
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||||
for old, new in rename.items():
|
||||
if old in options_data:
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||||
options_cleaned[new] = options_data[old]
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||||
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||||
return options_cleaned
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||||
import datetime as dt
|
||||
import logging
|
||||
import os
|
||||
from collections import OrderedDict
|
||||
from typing import Dict
|
||||
|
||||
import humanize
|
||||
import pandas as pd
|
||||
import pytz
|
||||
import requests as r
|
||||
import schedule
|
||||
|
||||
|
||||
from common.Symbol import Stock
|
||||
|
||||
log = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class MarketData:
|
||||
"""
|
||||
Functions for finding stock market information about symbols from MarkData.app
|
||||
"""
|
||||
|
||||
SYMBOL_REGEX = "[$]([a-zA-Z]{1,4})"
|
||||
|
||||
symbol_list: Dict[str, Dict] = {}
|
||||
charts: Dict[Stock, pd.DataFrame] = {}
|
||||
|
||||
openTime = dt.time(hour=9, minute=30, second=0)
|
||||
marketTimeZone = pytz.timezone("US/Eastern")
|
||||
|
||||
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 = ""
|
||||
log.warning("Starting without an MarketData.app Token will not allow you to get market data!")
|
||||
log.warning("Use this affiliate link so that the bot can stay free:")
|
||||
log.warning("https://dashboard.marketdata.app/marketdata/aff/go/misterbiggs?keyword=repo")
|
||||
|
||||
if self.MARKETDATA_TOKEN != "":
|
||||
schedule.every().day.do(self.clear_charts)
|
||||
|
||||
self.get_symbol_list()
|
||||
schedule.every().day.do(self.get_symbol_list)
|
||||
|
||||
def get(self, endpoint, params=None, timeout=10, headers=None) -> dict:
|
||||
url = "https://api.marketdata.app/v1/" + endpoint
|
||||
|
||||
if params is None:
|
||||
params = {}
|
||||
|
||||
# set token param if it wasn't passed.
|
||||
params["token"] = self.MARKETDATA_TOKEN
|
||||
|
||||
# Undocumented query variable that ensures bot usage can be
|
||||
# monitored even if someone doesn't make it through an affiliate link.
|
||||
params["application"] = "simplestockbot"
|
||||
|
||||
if headers is None:
|
||||
headers = {}
|
||||
headers = {"User-Agent": "Simple Stock Bot anson@ansonbiggs.com"} | headers
|
||||
|
||||
resp = r.get(url, params=params, timeout=timeout, headers=headers)
|
||||
|
||||
logging.error(resp.headers.items())
|
||||
|
||||
# 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 symbol_id(self, symbol: str) -> Dict[str, Dict]:
|
||||
return self.symbol_list.get(symbol.upper(), None)
|
||||
|
||||
def get_symbol_list(self):
|
||||
# Doesn't use `self.get()` since needs are much different
|
||||
sec_resp = r.get(
|
||||
"https://www.sec.gov/files/company_tickers.json",
|
||||
headers={
|
||||
"User-Agent": "Simple Stock Bot anson@ansonbiggs.com",
|
||||
"Accept-Encoding": "gzip, deflate",
|
||||
"Host": "www.sec.gov",
|
||||
},
|
||||
)
|
||||
sec_resp.raise_for_status()
|
||||
sec_data = sec_resp.json()
|
||||
|
||||
for rank, ticker_info in sec_data.items():
|
||||
self.symbol_list[ticker_info["ticker"]] = {
|
||||
"ticker": ticker_info["ticker"],
|
||||
"title": ticker_info["title"],
|
||||
"mkt_cap_rank": rank,
|
||||
}
|
||||
|
||||
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:
|
||||
# TODO: At the moment this API is poorly documented, this function likely needs to be revisited later.
|
||||
|
||||
try:
|
||||
status = r.get(
|
||||
"https://stats.uptimerobot.com/api/getMonitorList/6Kv3zIow0A",
|
||||
timeout=5,
|
||||
)
|
||||
status.raise_for_status()
|
||||
except r.HTTPError:
|
||||
return f"API returned an HTTP error code {status.status_code} in {status.elapsed.total_seconds()} seconds."
|
||||
except r.Timeout:
|
||||
return "API timed out before it was able to give status. This is likely due to a surge in usage or a complete outage."
|
||||
|
||||
statusJSON = status.json()
|
||||
|
||||
if statusJSON["status"] == "ok":
|
||||
return (
|
||||
f"CoinGecko API responded that it was OK with a {status.status_code} in {status.elapsed.total_seconds()} seconds."
|
||||
)
|
||||
else:
|
||||
return f"MarketData.app is currently reporting the following status: {statusJSON['status']}"
|
||||
|
||||
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.symbol}/"):
|
||||
price = round(quoteResp["last"][0], 2)
|
||||
|
||||
try:
|
||||
changePercent = round(quoteResp["changepct"][0], 2)
|
||||
except TypeError:
|
||||
return f"The price of {symbol.name} is ${price}"
|
||||
|
||||
message = f"The current price of {symbol.name} is ${price} and "
|
||||
|
||||
if changePercent > 0.0:
|
||||
message += f"is currently up {changePercent}% for the day."
|
||||
elif changePercent < 0.0:
|
||||
message += f"is currently down {changePercent}% for the day."
|
||||
else:
|
||||
message += "hasn't shown any movement for the day."
|
||||
|
||||
return message
|
||||
else:
|
||||
return f"Getting a quote for {symbol} encountered an error."
|
||||
|
||||
def spark_reply(self, symbol: Stock) -> str:
|
||||
if quoteResp := self.get(f"stocks/quotes/{symbol}/"):
|
||||
try:
|
||||
changePercent = round(quoteResp["changepct"][0], 2)
|
||||
return f"`{symbol.tag}`: {changePercent}%"
|
||||
except TypeError:
|
||||
pass
|
||||
|
||||
return f"`{symbol.tag}`"
|
||||
|
||||
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 = "15" # minutes
|
||||
now = dt.datetime.now(self.marketTimeZone)
|
||||
|
||||
if self.openTime < now.time():
|
||||
startTime = now.replace(hour=9, minute=30)
|
||||
else:
|
||||
startTime = now - dt.timedelta(days=1)
|
||||
|
||||
if data := self.get(
|
||||
f"stocks/candles/{resolution}/{symbol}",
|
||||
params={
|
||||
"from": startTime.timestamp(),
|
||||
"to": now.timestamp(),
|
||||
"extended": True,
|
||||
},
|
||||
):
|
||||
data.pop("s")
|
||||
df = pd.DataFrame(data)
|
||||
df["t"] = pd.to_datetime(df["t"], unit="s", utc=True)
|
||||
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()
|
||||
|
||||
def options_reply(self, request: str) -> str:
|
||||
"""Undocumented API Usage!"""
|
||||
|
||||
options_data = self.get(f"options/quotes/{request}")
|
||||
|
||||
for key in options_data.keys():
|
||||
options_data[key] = options_data[key][0]
|
||||
|
||||
options_data["underlying"] = "$" + options_data["underlying"]
|
||||
|
||||
options_data["updated"] = humanize.naturaltime(dt.datetime.now() - dt.datetime.fromtimestamp(options_data["updated"]))
|
||||
|
||||
options_data["expiration"] = humanize.naturaltime(
|
||||
dt.datetime.now() - dt.datetime.fromtimestamp(options_data["expiration"])
|
||||
)
|
||||
|
||||
options_data["firstTraded"] = humanize.naturaltime(
|
||||
dt.datetime.now() - dt.datetime.fromtimestamp(options_data["firstTraded"])
|
||||
)
|
||||
|
||||
rename = {
|
||||
"optionSymbol": "Option Symbol",
|
||||
"underlying": "Underlying",
|
||||
"expiration": "Expiration",
|
||||
"side": "side",
|
||||
"strike": "strike",
|
||||
"firstTraded": "First Traded",
|
||||
"updated": "Last Updated",
|
||||
"bid": "bid",
|
||||
"bidSize": "bidSize",
|
||||
"mid": "mid",
|
||||
"ask": "ask",
|
||||
"askSize": "askSize",
|
||||
"last": "last",
|
||||
"openInterest": "Open Interest",
|
||||
"volume": "Volume",
|
||||
"inTheMoney": "inTheMoney",
|
||||
"intrinsicValue": "Intrinsic Value",
|
||||
"extrinsicValue": "Extrinsic Value",
|
||||
"underlyingPrice": "Underlying Price",
|
||||
"iv": "Implied Volatility",
|
||||
"delta": "delta",
|
||||
"gamma": "gamma",
|
||||
"theta": "theta",
|
||||
"vega": "vega",
|
||||
"rho": "rho",
|
||||
}
|
||||
|
||||
options_cleaned = OrderedDict()
|
||||
for old, new in rename.items():
|
||||
if old in options_data:
|
||||
options_cleaned[new] = options_data[old]
|
||||
|
||||
return options_cleaned
|
||||
|
||||
Reference in New Issue
Block a user