mirror of
https://gitlab.com/simple-stock-bots/simple-stock-bot.git
synced 2025-07-22 06:01:40 +00:00
revert changes to master
This commit is contained in:
@@ -1,263 +0,0 @@
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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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@@ -1,50 +0,0 @@
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import pandas as pd
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import logging
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class Symbol:
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"""
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symbol: What the user calls it. ie tsla or btc
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id: What the api expects. ie tsla or bitcoin
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name: Human readable. ie Tesla or Bitcoin
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tag: Uppercase tag to call the symbol. ie $TSLA or $$BTC
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"""
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currency = "usd"
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pass
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def __init__(self, symbol) -> None:
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self.symbol = symbol
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self.id = symbol
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self.name = symbol
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self.tag = "$" + symbol
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def __repr__(self) -> str:
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return f"<{self.__class__.__name__} instance of {self.id} at {id(self)}>"
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def __str__(self) -> str:
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return self.id
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class Stock(Symbol):
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"""Stock Market Object. Gets data from MarketData"""
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def __init__(self, symbol: str) -> None:
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self.symbol = symbol
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self.id = symbol
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self.name = "$" + symbol.upper()
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self.tag = "$" + symbol.lower()
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class Coin(Symbol):
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"""Cryptocurrency Object. Gets data from CoinGecko."""
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def __init__(self, symbol: pd.DataFrame) -> None:
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if len(symbol) > 1:
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logging.info(f"Crypto with shared id:\n\t{symbol.id}")
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symbol = symbol.head(1)
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self.symbol = symbol.symbol.values[0]
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self.id = symbol.id.values[0]
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self.name = symbol.name.values[0]
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self.tag = symbol.type_id.values[0].upper()
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@@ -1,367 +0,0 @@
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import logging
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from typing import List
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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 markdownify import markdownify
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from common.Symbol import Coin
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log = logging.getLogger(__name__)
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class cg_Crypto:
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"""
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Functions for finding crypto info
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"""
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vs_currency = "usd" # simple/supported_vs_currencies for list of options
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trending_cache: List[str] = []
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||||
def __init__(self) -> None:
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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: dict = {}, timeout=10) -> dict:
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url = "https://api.coingecko.com/api/v3" + endpoint
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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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||||
log.error(e)
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||||
return {}
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|
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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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log.error(e)
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return {}
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|
||||
def symbol_id(self, symbol) -> str:
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try:
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||||
return self.symbol_list[self.symbol_list["symbol"] == symbol]["id"].values[0]
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except KeyError:
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||||
return ""
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||||
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||||
def get_symbol_list(self):
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||||
raw_symbols = self.get("/coins/list")
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symbols = pd.DataFrame(data=raw_symbols)
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||||
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||||
# Removes all binance-peg symbols
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||||
symbols = symbols[~symbols["id"].str.contains("binance-peg")]
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||||
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||||
symbols["description"] = "$$" + symbols["symbol"].str.upper() + ": " + symbols["name"]
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||||
symbols = symbols[["id", "symbol", "name", "description"]]
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||||
symbols["type_id"] = "$$" + symbols["symbol"]
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||||
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||||
self.symbol_list = symbols
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||||
|
||||
def status(self) -> str:
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||||
"""Checks CoinGecko /ping endpoint for API issues.
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||||
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||||
Returns
|
||||
-------
|
||||
str
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||||
Human readable text on status of CoinGecko API
|
||||
"""
|
||||
status = r.get(
|
||||
"https://api.coingecko.com/api/v3/ping",
|
||||
timeout=5,
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||||
)
|
||||
|
||||
try:
|
||||
status.raise_for_status()
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||||
return (
|
||||
f"CoinGecko API responded that it was OK with a {status.status_code} in {status.elapsed.total_seconds()} Seconds."
|
||||
)
|
||||
except r.HTTPError:
|
||||
return f"CoinGecko API returned an error code {status.status_code} in {status.elapsed.total_seconds()} Seconds."
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||||
|
||||
def price_reply(self, coin: Coin) -> str:
|
||||
"""Returns current market price or after hours if its available for a given coin symbol.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
symbols : list
|
||||
List of coin symbols.
|
||||
|
||||
Returns
|
||||
-------
|
||||
Dict[str, str]
|
||||
Each symbol passed in is a key with its value being a human readable
|
||||
markdown formatted string of the symbols price and movement.
|
||||
"""
|
||||
|
||||
if resp := self.get(
|
||||
"/simple/price",
|
||||
params={
|
||||
"ids": coin.id,
|
||||
"vs_currencies": self.vs_currency,
|
||||
"include_24hr_change": "true",
|
||||
},
|
||||
):
|
||||
try:
|
||||
data = resp[coin.id]
|
||||
|
||||
price = data[self.vs_currency]
|
||||
change = data[self.vs_currency + "_24h_change"]
|
||||
if change is None:
|
||||
change = 0
|
||||
except KeyError:
|
||||
return f"{coin.id} returned an error."
|
||||
|
||||
message = f"The current price of {coin.name} is $**{price:,}**"
|
||||
|
||||
# Determine wording of change text
|
||||
if change > 0:
|
||||
message += f", the coin is currently **up {change:.3f}%** for today"
|
||||
elif change < 0:
|
||||
message += f", the coin is currently **down {change:.3f}%** for today"
|
||||
else:
|
||||
message += ", the coin hasn't shown any movement today."
|
||||
|
||||
else:
|
||||
message = f"The price for {coin.name} is not available. If you suspect this is an error run `/status`"
|
||||
|
||||
return message
|
||||
|
||||
def intra_reply(self, symbol: Coin) -> 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 resp := self.get(
|
||||
f"/coins/{symbol.id}/ohlc",
|
||||
params={"vs_currency": self.vs_currency, "days": 1},
|
||||
):
|
||||
df = pd.DataFrame(resp, columns=["Date", "Open", "High", "Low", "Close"]).dropna()
|
||||
df["Date"] = pd.to_datetime(df["Date"], unit="ms")
|
||||
df = df.set_index("Date")
|
||||
return df
|
||||
|
||||
return pd.DataFrame()
|
||||
|
||||
def chart_reply(self, symbol: Coin) -> 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.
|
||||
"""
|
||||
|
||||
if resp := self.get(
|
||||
f"/coins/{symbol.id}/ohlc",
|
||||
params={"vs_currency": self.vs_currency, "days": 30},
|
||||
):
|
||||
df = pd.DataFrame(resp, columns=["Date", "Open", "High", "Low", "Close"]).dropna()
|
||||
df["Date"] = pd.to_datetime(df["Date"], unit="ms")
|
||||
df = df.set_index("Date")
|
||||
return df
|
||||
|
||||
return pd.DataFrame()
|
||||
|
||||
def stat_reply(self, symbol: Coin) -> str:
|
||||
"""Gathers key statistics on coin. Mostly just CoinGecko scores.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
symbol : Coin
|
||||
|
||||
Returns
|
||||
-------
|
||||
str
|
||||
Preformatted markdown.
|
||||
"""
|
||||
|
||||
if data := self.get(
|
||||
f"/coins/{symbol.id}",
|
||||
params={
|
||||
"localization": "false",
|
||||
},
|
||||
):
|
||||
return f"""
|
||||
[{data['name']}]({data['links']['homepage'][0]}) Statistics:
|
||||
Market Cap: ${data['market_data']['market_cap'][self.vs_currency]:,}
|
||||
Market Cap Ranking: {data.get('market_cap_rank',"Not Available")}
|
||||
CoinGecko Scores:
|
||||
Overall: {data.get('coingecko_score','Not Available')}
|
||||
Development: {data.get('developer_score','Not Available')}
|
||||
Community: {data.get('community_score','Not Available')}
|
||||
Public Interest: {data.get('public_interest_score','Not Available')}
|
||||
"""
|
||||
else:
|
||||
return f"{symbol.symbol} returned an error."
|
||||
|
||||
def cap_reply(self, coin: Coin) -> str:
|
||||
"""Gets market cap for Coin
|
||||
|
||||
Parameters
|
||||
----------
|
||||
coin : Coin
|
||||
|
||||
Returns
|
||||
-------
|
||||
str
|
||||
Preformatted markdown.
|
||||
"""
|
||||
|
||||
if resp := self.get(
|
||||
"/simple/price",
|
||||
params={
|
||||
"ids": coin.id,
|
||||
"vs_currencies": self.vs_currency,
|
||||
"include_market_cap": "true",
|
||||
},
|
||||
):
|
||||
log.debug(resp)
|
||||
try:
|
||||
data = resp[coin.id]
|
||||
|
||||
price = data[self.vs_currency]
|
||||
cap = data[self.vs_currency + "_market_cap"]
|
||||
except KeyError:
|
||||
return f"{coin.id} returned an error."
|
||||
|
||||
if cap == 0:
|
||||
return f"The market cap for {coin.name} is not available for unknown reasons."
|
||||
|
||||
message = (
|
||||
f"The current price of {coin.name} is $**{price:,}** and"
|
||||
+ " its market cap is $**{cap:,.2f}** {self.vs_currency.upper()}"
|
||||
)
|
||||
|
||||
else:
|
||||
message = f"The Coin: {coin.name} was not found or returned and error."
|
||||
|
||||
return message
|
||||
|
||||
def info_reply(self, symbol: Coin) -> str:
|
||||
"""Gets coin description
|
||||
|
||||
Parameters
|
||||
----------
|
||||
symbol : Coin
|
||||
|
||||
Returns
|
||||
-------
|
||||
str
|
||||
Preformatted markdown.
|
||||
"""
|
||||
|
||||
if data := self.get(
|
||||
f"/coins/{symbol.id}",
|
||||
params={"localization": "false"},
|
||||
):
|
||||
try:
|
||||
return markdownify(data["description"]["en"])
|
||||
except KeyError:
|
||||
return f"{symbol} does not have a description available."
|
||||
|
||||
return f"No information found for: {symbol}\nEither today is boring or the symbol does not exist."
|
||||
|
||||
def spark_reply(self, symbol: Coin) -> str:
|
||||
change = self.get(
|
||||
"/simple/price",
|
||||
params={
|
||||
"ids": symbol.id,
|
||||
"vs_currencies": self.vs_currency,
|
||||
"include_24hr_change": "true",
|
||||
},
|
||||
)[symbol.id]["usd_24h_change"]
|
||||
|
||||
return f"`{symbol.tag}`: {symbol.name}, {change:.2f}%"
|
||||
|
||||
def trending(self) -> list[str]:
|
||||
"""Gets current coins trending on coingecko
|
||||
|
||||
Returns
|
||||
-------
|
||||
list[str]
|
||||
list of $$ID: NAME, CHANGE%
|
||||
"""
|
||||
|
||||
coins = self.get("/search/trending")
|
||||
try:
|
||||
trending = []
|
||||
for coin in coins["coins"]:
|
||||
c = coin["item"]
|
||||
|
||||
sym = c["symbol"].upper()
|
||||
name = c["name"]
|
||||
change = self.get(
|
||||
"/simple/price",
|
||||
params={
|
||||
"ids": c["id"],
|
||||
"vs_currencies": self.vs_currency,
|
||||
"include_24hr_change": "true",
|
||||
},
|
||||
)[c["id"]]["usd_24h_change"]
|
||||
|
||||
msg = f"`$${sym}`: {name}, {change:.2f}%"
|
||||
|
||||
trending.append(msg)
|
||||
|
||||
except Exception as e:
|
||||
log.warning(e)
|
||||
return self.trending_cache
|
||||
|
||||
self.trending_cache = trending
|
||||
return trending
|
||||
|
||||
def batch_price(self, coins: list[Coin]) -> list[str]:
|
||||
"""Gets price of a list of coins all in one API call
|
||||
|
||||
Parameters
|
||||
----------
|
||||
coins : list[Coin]
|
||||
|
||||
Returns
|
||||
-------
|
||||
list[str]
|
||||
returns preformatted list of strings detailing price movement of each coin passed in.
|
||||
"""
|
||||
query = ",".join([c.id for c in coins])
|
||||
|
||||
prices = self.get(
|
||||
"/simple/price",
|
||||
params={
|
||||
"ids": query,
|
||||
"vs_currencies": self.vs_currency,
|
||||
"include_24hr_change": "true",
|
||||
},
|
||||
)
|
||||
|
||||
replies = []
|
||||
for coin in coins:
|
||||
if coin.id in prices:
|
||||
p = prices[coin.id]
|
||||
|
||||
if p.get("usd_24h_change") is None:
|
||||
p["usd_24h_change"] = 0
|
||||
|
||||
replies.append(
|
||||
f"{coin.name}: ${p.get('usd',0):,} and has moved {p.get('usd_24h_change',0.0):.2f}% in the past 24 hours."
|
||||
)
|
||||
|
||||
return replies
|
||||
@@ -1,393 +0,0 @@
|
||||
"""Function that routes symbols to the correct API provider.
|
||||
"""
|
||||
|
||||
import datetime
|
||||
import logging
|
||||
import random
|
||||
import re
|
||||
|
||||
import pandas as pd
|
||||
import schedule
|
||||
from cachetools import TTLCache, cached
|
||||
|
||||
from common.cg_Crypto import cg_Crypto
|
||||
from common.MarketData import MarketData
|
||||
from common.Symbol import Coin, Stock, Symbol
|
||||
|
||||
from typing import Dict
|
||||
|
||||
log = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class Router:
|
||||
STOCK_REGEX = "(?:^|[^\\$])\\$([a-zA-Z.]{1,6})"
|
||||
CRYPTO_REGEX = "[$]{2}([a-zA-Z]{1,20})"
|
||||
trending_count: Dict[str, float] = {}
|
||||
|
||||
def __init__(self):
|
||||
self.stock = MarketData()
|
||||
self.crypto = cg_Crypto()
|
||||
|
||||
schedule.every().hour.do(self.trending_decay)
|
||||
|
||||
def trending_decay(self, decay=0.5):
|
||||
"""Decays the value of each trending stock by a multiplier"""
|
||||
t_copy = {}
|
||||
dead_keys = []
|
||||
if self.trending_count:
|
||||
t_copy = self.trending_count.copy()
|
||||
for key in t_copy.keys():
|
||||
if t_copy[key] < 0.01:
|
||||
# This just makes sure were not keeping around keys that havent been called in a very long time.
|
||||
dead_keys.append(key)
|
||||
else:
|
||||
t_copy[key] = t_copy[key] * decay
|
||||
for dead in dead_keys:
|
||||
t_copy.pop(dead)
|
||||
|
||||
self.trending_count = t_copy.copy()
|
||||
log.info("Decayed trending symbols.")
|
||||
|
||||
def find_symbols(self, text: str, *, trending_weight: int = 1) -> list[Stock | Symbol]:
|
||||
"""Finds stock tickers starting with a dollar sign, and cryptocurrencies with two dollar signs
|
||||
in a blob of text and returns them in a list.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
text : str
|
||||
Blob of text.
|
||||
|
||||
Returns
|
||||
-------
|
||||
list[Symbol]
|
||||
List of stock symbols as Symbol objects
|
||||
"""
|
||||
schedule.run_pending()
|
||||
|
||||
symbols: list[Symbol] = []
|
||||
stocks = set(re.findall(self.STOCK_REGEX, text))
|
||||
for stock in stocks:
|
||||
# Market data lacks tools to check if a symbol is valid.
|
||||
symbols.append(Stock(stock))
|
||||
|
||||
coins = set(re.findall(self.CRYPTO_REGEX, text))
|
||||
for coin in coins:
|
||||
sym = self.crypto.symbol_list[self.crypto.symbol_list["symbol"].str.fullmatch(coin.lower(), case=False)]
|
||||
if sym.empty:
|
||||
log.info(f"{coin} is not in list of coins")
|
||||
else:
|
||||
symbols.append(Coin(sym))
|
||||
if symbols:
|
||||
for symbol in symbols:
|
||||
self.trending_count[symbol.tag] = self.trending_count.get(symbol.tag, 0) + trending_weight
|
||||
log.debug(self.trending_count)
|
||||
|
||||
return symbols
|
||||
|
||||
def status(self, bot_resp) -> str:
|
||||
"""Checks for any issues with APIs.
|
||||
|
||||
Returns
|
||||
-------
|
||||
str
|
||||
Human readable text on status of the bot and relevant APIs
|
||||
"""
|
||||
|
||||
stats = f"""
|
||||
Bot Status:
|
||||
{bot_resp}
|
||||
|
||||
Stock Market Data:
|
||||
{self.stock.status()}
|
||||
|
||||
Cryptocurrency Data:
|
||||
{self.crypto.status()}
|
||||
"""
|
||||
|
||||
log.warning(stats)
|
||||
|
||||
return stats
|
||||
|
||||
def inline_search(self, search: str, matches: int = 5) -> pd.DataFrame:
|
||||
"""Searches based on the shortest symbol that contains the same string as the search.
|
||||
Should be very fast compared to a fuzzy search.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
search : str
|
||||
String used to match against symbols.
|
||||
|
||||
Returns
|
||||
-------
|
||||
list[tuple[str, str]]
|
||||
Each tuple contains: (Symbol, Issue Name).
|
||||
"""
|
||||
|
||||
df = pd.concat([self.stock.symbol_list, self.crypto.symbol_list])
|
||||
|
||||
df = df[df["description"].str.contains(search, regex=False, case=False)].sort_values(
|
||||
by="type_id", key=lambda x: x.str.len()
|
||||
)
|
||||
|
||||
symbols = df.head(matches)
|
||||
symbols["price_reply"] = symbols["type_id"].apply(
|
||||
lambda sym: self.price_reply(self.find_symbols(sym, trending_weight=0))[0]
|
||||
)
|
||||
|
||||
return symbols
|
||||
|
||||
def price_reply(self, symbols: list[Symbol]) -> list[str]:
|
||||
"""Returns current market price or after hours if its available for a given stock symbol.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
symbols : list
|
||||
List of stock symbols.
|
||||
|
||||
Returns
|
||||
-------
|
||||
Dict[str, str]
|
||||
Each symbol passed in is a key with its value being a human readable
|
||||
markdown formatted string of the symbols price and movement.
|
||||
"""
|
||||
replies = []
|
||||
|
||||
for symbol in symbols:
|
||||
log.info(symbol)
|
||||
if isinstance(symbol, Stock):
|
||||
replies.append(self.stock.price_reply(symbol))
|
||||
elif isinstance(symbol, Coin):
|
||||
replies.append(self.crypto.price_reply(symbol))
|
||||
else:
|
||||
log.info(f"{symbol} is not a Stock or Coin")
|
||||
|
||||
return replies
|
||||
|
||||
def info_reply(self, symbols: list) -> list[str]:
|
||||
"""Gets information on stock symbols.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
symbols : list[str]
|
||||
List of stock symbols.
|
||||
|
||||
Returns
|
||||
-------
|
||||
Dict[str, str]
|
||||
Each symbol passed in is a key with its value being a human readable formatted
|
||||
string of the symbols information.
|
||||
"""
|
||||
replies = []
|
||||
|
||||
for symbol in symbols:
|
||||
if isinstance(symbol, Stock):
|
||||
replies.append(self.stock.info_reply(symbol))
|
||||
elif isinstance(symbol, Coin):
|
||||
replies.append(self.crypto.info_reply(symbol))
|
||||
else:
|
||||
log.debug(f"{symbol} is not a Stock or Coin")
|
||||
|
||||
return replies
|
||||
|
||||
def intra_reply(self, symbol: Symbol) -> 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 isinstance(symbol, Stock):
|
||||
return self.stock.intra_reply(symbol)
|
||||
elif isinstance(symbol, Coin):
|
||||
return self.crypto.intra_reply(symbol)
|
||||
else:
|
||||
log.debug(f"{symbol} is not a Stock or Coin")
|
||||
return pd.DataFrame()
|
||||
|
||||
def chart_reply(self, symbol: Symbol) -> 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.
|
||||
"""
|
||||
if isinstance(symbol, Stock):
|
||||
return self.stock.chart_reply(symbol)
|
||||
elif isinstance(symbol, Coin):
|
||||
return self.crypto.chart_reply(symbol)
|
||||
else:
|
||||
log.debug(f"{symbol} is not a Stock or Coin")
|
||||
return pd.DataFrame()
|
||||
|
||||
def stat_reply(self, symbols: list[Symbol]) -> list[str]:
|
||||
"""Gets key statistics for each symbol in the list
|
||||
|
||||
Parameters
|
||||
----------
|
||||
symbols : list[str]
|
||||
List of stock symbols
|
||||
|
||||
Returns
|
||||
-------
|
||||
Dict[str, str]
|
||||
Each symbol passed in is a key with its value being a human readable
|
||||
formatted string of the symbols statistics.
|
||||
"""
|
||||
replies = []
|
||||
|
||||
for symbol in symbols:
|
||||
if isinstance(symbol, Stock):
|
||||
replies.append(self.stock.stat_reply(symbol))
|
||||
elif isinstance(symbol, Coin):
|
||||
replies.append(self.crypto.stat_reply(symbol))
|
||||
else:
|
||||
log.debug(f"{symbol} is not a Stock or Coin")
|
||||
|
||||
return replies
|
||||
|
||||
def cap_reply(self, symbols: list[Symbol]) -> list[str]:
|
||||
"""Gets market cap for each symbol in the list
|
||||
|
||||
Parameters
|
||||
----------
|
||||
symbols : list[str]
|
||||
List of stock symbols
|
||||
|
||||
Returns
|
||||
-------
|
||||
Dict[str, str]
|
||||
Each symbol passed in is a key with its value being a human readable
|
||||
formatted string of the symbols market cap.
|
||||
"""
|
||||
replies = []
|
||||
|
||||
for symbol in symbols:
|
||||
if isinstance(symbol, Stock):
|
||||
replies.append(self.stock.cap_reply(symbol))
|
||||
elif isinstance(symbol, Coin):
|
||||
replies.append(self.crypto.cap_reply(symbol))
|
||||
else:
|
||||
log.debug(f"{symbol} is not a Stock or Coin")
|
||||
|
||||
return replies
|
||||
|
||||
def spark_reply(self, symbols: list[Symbol]) -> list[str]:
|
||||
"""Gets change for each symbol and returns it in a compact format
|
||||
|
||||
Parameters
|
||||
----------
|
||||
symbols : list[str]
|
||||
List of stock symbols
|
||||
|
||||
Returns
|
||||
-------
|
||||
list[str]
|
||||
List of human readable strings.
|
||||
"""
|
||||
replies = []
|
||||
|
||||
for symbol in symbols:
|
||||
if isinstance(symbol, Stock):
|
||||
replies.append(self.stock.spark_reply(symbol))
|
||||
elif isinstance(symbol, Coin):
|
||||
replies.append(self.crypto.spark_reply(symbol))
|
||||
else:
|
||||
log.debug(f"{symbol} is not a Stock or Coin")
|
||||
|
||||
return replies
|
||||
|
||||
@cached(cache=TTLCache(maxsize=1024, ttl=600))
|
||||
def trending(self) -> str:
|
||||
"""Checks APIs for trending symbols.
|
||||
|
||||
Returns
|
||||
-------
|
||||
list[str]
|
||||
List of preformatted strings to be sent to user.
|
||||
"""
|
||||
|
||||
# stocks = self.stock.trending()
|
||||
coins = self.crypto.trending()
|
||||
|
||||
reply = ""
|
||||
|
||||
log.warning(self.trending_count)
|
||||
if self.trending_count:
|
||||
reply += "🔥Trending on the Stock Bot:\n`"
|
||||
reply += "━" * len("Trending on the Stock Bot:") + "`\n"
|
||||
|
||||
sorted_trending = [s[0] for s in sorted(self.trending_count.items(), key=lambda item: item[1])][::-1][0:5]
|
||||
log.warning(sorted_trending)
|
||||
for t in sorted_trending:
|
||||
reply += self.spark_reply(self.find_symbols(t))[0] + "\n"
|
||||
|
||||
if coins:
|
||||
reply += "\n\n🦎Trending Crypto:\n`"
|
||||
reply += "━" * len("Trending Crypto:") + "`\n"
|
||||
for coin in coins:
|
||||
reply += coin + "\n"
|
||||
|
||||
if "`$GME" in reply:
|
||||
reply = reply.replace("🔥", "🦍")
|
||||
|
||||
if reply:
|
||||
return reply
|
||||
else:
|
||||
log.warning("Failed to collect trending data.")
|
||||
return "Trending data is not currently available."
|
||||
|
||||
def random_pick(self) -> str:
|
||||
choice = random.choice(list(self.stock.symbol_list["description"]) + list(self.crypto.symbol_list["description"]))
|
||||
hold = (datetime.date.today() + datetime.timedelta(random.randint(1, 365))).strftime("%b %d, %Y")
|
||||
|
||||
return f"{choice}\nBuy and hold until: {hold}"
|
||||
|
||||
def batch_price_reply(self, symbols: list[Symbol]) -> list[str]:
|
||||
"""Returns current market price or after hours if its available for a given stock symbol.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
symbols : list
|
||||
List of stock symbols.
|
||||
|
||||
Returns
|
||||
-------
|
||||
Dict[str, str]
|
||||
Each symbol passed in is a key with its value being a human readable
|
||||
markdown formatted string of the symbols price and movement.
|
||||
"""
|
||||
replies = []
|
||||
stocks = []
|
||||
coins = []
|
||||
|
||||
for symbol in symbols:
|
||||
if isinstance(symbol, Stock):
|
||||
stocks.append(symbol)
|
||||
elif isinstance(symbol, Coin):
|
||||
coins.append(symbol)
|
||||
else:
|
||||
log.debug(f"{symbol} is not a Stock or Coin")
|
||||
|
||||
if stocks:
|
||||
for stock in stocks:
|
||||
replies.append(self.stock.price_reply(stock))
|
||||
if coins:
|
||||
replies = replies + self.crypto.batch_price(coins)
|
||||
|
||||
return replies
|
||||
Reference in New Issue
Block a user