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Anson 2023-11-30 21:50:25 -07:00
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733
common/MarketData.py
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@ -1,362 +1,371 @@
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
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

107
common/Symbol.py
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@ -1,52 +1,55 @@
import logging
import pandas as pd
class Symbol:
"""
symbol: What the user calls it. ie tsla or btc
id: What the api expects. ie tsla or bitcoin
name: Human readable. ie Tesla or Bitcoin
tag: Uppercase tag to call the symbol. ie $TSLA or $$BTC
"""
currency = "usd"
pass
def __init__(self, symbol) -> None:
self.symbol = symbol
self.id = symbol
self.name = symbol
self.tag = "$" + symbol
def __repr__(self) -> str:
return f"<{self.__class__.__name__} instance of {self.id} at {id(self)}>"
def __str__(self) -> str:
return self.id
class Stock(Symbol):
"""Stock Market Object. Gets data from MarketData"""
def __init__(self, symbol_info: dict) -> None:
self.symbol = symbol_info["ticker"]
self.id = symbol_info["ticker"]
self.name = symbol_info["title"]
self.tag = "$" + symbol_info["ticker"]
self.market_cap_rank = symbol_info["mkt_cap_rank"]
class Coin(Symbol):
"""Cryptocurrency Object. Gets data from CoinGecko."""
def __init__(self, symbol: pd.DataFrame) -> None:
if len(symbol) > 1:
logging.info(f"Crypto with shared id:\n\t{symbol.id}")
symbol = symbol.head(1)
self.symbol = symbol.symbol.values[0]
self.id = symbol.id.values[0]
self.name = symbol.name.values[0]
self.tag = symbol.type_id.values[0].upper()
import logging
import pandas as pd
class Symbol:
"""
symbol: What the user calls it. ie tsla or btc
id: What the api expects. ie tsla or bitcoin
name: Human readable. ie Tesla or Bitcoin
tag: Uppercase tag to call the symbol. ie $TSLA or $$BTC
"""
currency = "usd"
pass
def __init__(self, symbol) -> None:
self.symbol = symbol
self.id = symbol
self.name = symbol
self.tag = "$" + symbol
def __repr__(self) -> str:
return f"<{self.__class__.__name__} instance of {self.id} at {id(self)}>"
def __str__(self) -> str:
return self.id
def __hash__(self):
return hash(self.id)
class Stock(Symbol):
"""Stock Market Object. Gets data from MarketData"""
def __init__(self, symbol_info: dict) -> None:
self.symbol = symbol_info["ticker"]
self.id = symbol_info["ticker"]
self.name = symbol_info["title"]
self.tag = "$" + symbol_info["ticker"]
self.market_cap_rank = symbol_info["mkt_cap_rank"]
class Coin(Symbol):
"""Cryptocurrency Object. Gets data from CoinGecko."""
def __init__(self, symbol: pd.DataFrame) -> None:
if len(symbol) > 1:
logging.info(f"Crypto with shared id:\n\t{symbol.id}")
symbol = symbol.head(1)
self.symbol = symbol.symbol.values[0]
self.id = symbol.id.values[0]
self.name = symbol.name.values[0]
self.tag = symbol.type_id.values[0].upper()

769
common/cg_Crypto.py
View File

@ -1,381 +1,388 @@
import logging
from typing import List
import pandas as pd
import requests as r
import schedule
from markdownify import markdownify
from common.Symbol import Coin
from common.utilities import rate_limited
import time
log = logging.getLogger(__name__)
class cg_Crypto:
"""
Functions for finding crypto info
"""
vs_currency = "usd" # simple/supported_vs_currencies for list of options
trending_cache: List[str] = []
def __init__(self) -> None:
self.get_symbol_list()
schedule.every().day.do(self.get_symbol_list)
# Coingecko's rate limit is 30 requests per minute.
# Since there are two bots sharing the same IP, we allocate half of that limit to each bot.
# This results in a rate limit of 15 requests per minute for each bot.
# Given this, the rate limit effectively becomes 1 request every 4 seconds for each bot.
@rate_limited(0.25)
def get(self, endpoint, params: dict = {}, timeout=10) -> dict:
url = "https://api.coingecko.com/api/v3" + endpoint
resp = r.get(url, params=params, timeout=timeout)
# Make sure API returned a proper status code
if resp.status_code == 429:
log.warning(f"CoinGecko returned 429 - Too Many Requests for endpoint: {endpoint}. Sleeping and trying again.")
time.sleep(10)
return self.get(endpoint=endpoint, params=params, timeout=timeout)
try:
resp.raise_for_status()
except r.exceptions.HTTPError as e:
log.error(e)
return {}
# Make sure API returned valid JSON
try:
resp_json = resp.json()
return resp_json
except r.exceptions.JSONDecodeError as e:
log.error(e)
return {}
def symbol_id(self, symbol) -> str:
try:
return self.symbol_list[self.symbol_list["symbol"] == symbol]["id"].values[0]
except KeyError:
return ""
def get_symbol_list(self):
raw_symbols = self.get("/coins/list")
symbols = pd.DataFrame(data=raw_symbols)
# Removes all binance-peg symbols
symbols = symbols[~symbols["id"].str.contains("binance-peg")]
symbols["description"] = "$$" + symbols["symbol"].str.upper() + ": " + symbols["name"]
symbols = symbols[["id", "symbol", "name", "description"]]
symbols["type_id"] = "$$" + symbols["symbol"]
self.symbol_list = symbols
def status(self) -> str:
"""Checks CoinGecko /ping endpoint for API issues.
Returns
-------
str
Human readable text on status of CoinGecko API
"""
status = r.get(
"https://api.coingecko.com/api/v3/ping",
timeout=5,
)
try:
status.raise_for_status()
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."
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
import logging
from typing import List
import pandas as pd
import requests as r
import schedule
from markdownify import markdownify
from common.Symbol import Coin
from common.utilities import rate_limited
import time
log = logging.getLogger(__name__)
class cg_Crypto:
"""
Functions for finding crypto info
"""
vs_currency = "usd" # simple/supported_vs_currencies for list of options
trending_cache: List[str] = []
def __init__(self) -> None:
self.get_symbol_list()
schedule.every().day.do(self.get_symbol_list)
# Coingecko's rate limit is 30 requests per minute.
# Since there are two bots sharing the same IP, we allocate half of that limit to each bot.
# This results in a rate limit of 15 requests per minute for each bot.
# Given this, the rate limit effectively becomes 1 request every 4 seconds for each bot.
@rate_limited(0.25)
def get(self, endpoint, params: dict = {}, timeout=10) -> dict:
url = "https://api.coingecko.com/api/v3" + endpoint
resp = r.get(url, params=params, timeout=timeout)
# Make sure API returned a proper status code
if resp.status_code == 429:
log.warning(
f"CoinGecko returned 429 - Too Many Requests for endpoint: {endpoint}. Sleeping and trying again."
)
time.sleep(10)
return self.get(endpoint=endpoint, params=params, timeout=timeout)
try:
resp.raise_for_status()
except r.exceptions.HTTPError as e:
log.error(e)
return {}
# Make sure API returned valid JSON
try:
resp_json = resp.json()
return resp_json
except r.exceptions.JSONDecodeError as e:
log.error(e)
return {}
def symbol_id(self, symbol) -> str:
try:
return self.symbol_list[self.symbol_list["symbol"] == symbol]["id"].values[
0
]
except KeyError:
return ""
def get_symbol_list(self):
raw_symbols = self.get("/coins/list")
symbols = pd.DataFrame(data=raw_symbols)
# Removes all binance-peg symbols
symbols = symbols[~symbols["id"].str.contains("binance-peg")]
symbols["description"] = (
"$$" + symbols["symbol"].str.upper() + ": " + symbols["name"]
)
symbols = symbols[["id", "symbol", "name", "description"]]
symbols["type_id"] = "$$" + symbols["symbol"]
self.symbol_list = symbols
def status(self) -> str:
"""Checks CoinGecko /ping endpoint for API issues.
Returns
-------
str
Human readable text on status of CoinGecko API
"""
status = r.get(
"https://api.coingecko.com/api/v3/ping",
timeout=5,
)
try:
status.raise_for_status()
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."
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

814
common/symbol_router.py
View File

@ -1,407 +1,407 @@
"""Function that routes symbols to the correct API provider.
"""
import datetime
import logging
import random
import re
from typing import Dict
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
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:
# Prune Keys
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 | Coin]:
"""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] = []
stock_matches = set(re.findall(self.STOCK_REGEX, text))
coin_matches = set(re.findall(self.CRYPTO_REGEX, text))
for stock_match in stock_matches:
# Market data lacks tools to check if a symbol is valid.
if stock_info := self.stock.symbol_id(stock_match):
symbols.append(Stock(stock_info))
else:
log.info(f"{stock_match} is not in list of stocks")
for coin_match in coin_matches:
sym = self.crypto.symbol_list[self.crypto.symbol_list["symbol"].str.fullmatch(coin_match.lower(), case=False)]
if sym.empty:
log.info(f"{coin_match} 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 = 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 on CoinGecko:\n`"
reply += "━" * len("Trending on CoinGecko:") + "`\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"]))
choice = random.choice(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
def options(self, request: str, symbols: list[Symbol]) -> Dict:
request = request.lower()
if len(symbols) == 1:
symbol = symbols[0]
request = request.replace(symbol.tag.lower(), symbol.symbol.lower())
return self.stock.options_reply(request)
else:
return self.stock.options_reply(request)
"""Function that routes symbols to the correct API provider.
"""
import datetime
import logging
import random
import re
from typing import Dict
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
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:
# Prune Keys
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 | Coin]:
"""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] = []
stock_matches = set(re.findall(self.STOCK_REGEX, text))
coin_matches = set(re.findall(self.CRYPTO_REGEX, text))
for stock_match in stock_matches:
# Market data lacks tools to check if a symbol is valid.
if stock_info := self.stock.symbol_id(stock_match):
symbols.append(Stock(stock_info))
else:
log.info(f"{stock_match} is not in list of stocks")
for coin_match in coin_matches:
sym = self.crypto.symbol_list[self.crypto.symbol_list["symbol"].str.fullmatch(coin_match.lower(), case=False)]
if sym.empty:
log.info(f"{coin_match} 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 = 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 on CoinGecko:\n`"
reply += "━" * len("Trending on CoinGecko:") + "`\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"]))
choice = random.choice(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
def options(self, request: str, symbols: list[Symbol]) -> Dict:
request = request.lower()
if len(symbols) == 1:
symbol = symbols[0]
request = request.replace(symbol.tag.lower(), symbol.symbol.lower())
return self.stock.options_reply(request)
else:
return self.stock.options_reply(request)

62
common/utilities.py
View File

@ -1,31 +1,31 @@
import time
import logging
log = logging.getLogger(__name__)
def rate_limited(max_per_second):
"""
Decorator that ensures the wrapped function is called at most `max_per_second` times per second.
"""
min_interval = 1.0 / max_per_second
def decorate(func):
last_called = [0.0]
def rate_limited_function(*args, **kwargs):
elapsed = time.time() - last_called[0]
left_to_wait = min_interval - elapsed
if left_to_wait > 0:
log.info(f"Rate limit exceeded. Waiting for {left_to_wait:.2f} seconds.")
time.sleep(left_to_wait)
ret = func(*args, **kwargs)
last_called[0] = time.time()
return ret
return rate_limited_function
return decorate
import time
import logging
log = logging.getLogger(__name__)
def rate_limited(max_per_second):
"""
Decorator that ensures the wrapped function is called at most `max_per_second` times per second.
"""
min_interval = 1.0 / max_per_second
def decorate(func):
last_called = [0.0]
def rate_limited_function(*args, **kwargs):
elapsed = time.time() - last_called[0]
left_to_wait = min_interval - elapsed
if left_to_wait > 0:
log.info(f"Rate limit exceeded. Waiting for {left_to_wait:.2f} seconds.")
time.sleep(left_to_wait)
ret = func(*args, **kwargs)
last_called[0] = time.time()
return ret
return rate_limited_function
return decorate

118
discord/D_info.py
View File

@ -1,59 +1,59 @@
"""Functions and Info specific to the discord Bot
"""
import re
import requests as r
class D_info:
license = re.sub(
r"\b\n",
" ",
r.get("https://gitlab.com/simple-stock-bots/simple-stock-bot/-/raw/master/LICENSE").text,
)
help_text = """
Thanks for using this bot. If you like it, [support me with a beer](https://www.buymeacoffee.com/Anson). 🍻
For stock data or hosting your own bot, use my link. This helps keep the bot free:
[marketdata.app](https://dashboard.marketdata.app/marketdata/aff/go/misterbiggs?keyword=discord).
**Updates**: Join the bot's discord: https://t.me/simplestockbotnews.
**Documentation**: All details about the bot are at [docs](https://simplestockbot.com).
The bot reads _"Symbols"_. Use `$` for stock tickers and `$$` for cryptocurrencies. For example:
- `/chart $$eth` gives Ethereum's monthly chart.
- `/dividend $psec` shows Prospect Capital's dividend.
Type any symbol, and the bot shows its price. Like: `Is $$btc rising since $tsla accepts it?` will give Bitcoin and Tesla prices.
**Commands**
- `/donate [USD amount]`: Support the bot. 🎗️
- `/intra $[symbol]`: See stock's latest movement. 📈
- `/chart $[symbol]`: View a month's stock activity. 📊
- `/trending`: Check trending stocks and cryptos. 💬
- `/help`: Need help? Ask here. 🆘
**Inline Features**
Type @SimpleStockBot `[search]` anywhere to find and get stock/crypto prices. Note: Prices might be delayed up to an hour.
Data from: [marketdata.app](https://dashboard.marketdata.app/marketdata/aff/go/misterbiggs?keyword=discord).
Issues with the bot? Use `/status` or [contact us](https://simplestockbot.com/contact).
"""
donate_text = """
Simple Stock Bot runs purely on [donations.](https://www.buymeacoffee.com/Anson)
Every donation supports server costs and
[marketdata.app](https://dashboard.marketdata.app/marketdata/aff/go/misterbiggs?keyword=discord) provides our data.
**How to Donate?**
1. Use `/donate [amount in USD]` command.
- E.g., `/donate 2` donates 2 USD.
2. Or, donate at [buymeacoffee](https://www.buymeacoffee.com/Anson).
- It's quick, doesn't need an account, and accepts Paypal or Credit card.
Questions? Visit our [website](https://simplestockbot.com).
"""
"""Functions and Info specific to the discord Bot
"""
import re
import requests as r
class D_info:
license = re.sub(
r"\b\n",
" ",
r.get("https://gitlab.com/simple-stock-bots/simple-stock-bot/-/raw/master/LICENSE").text,
)
help_text = """
Thanks for using this bot. If you like it, [support me with a beer](https://www.buymeacoffee.com/Anson). 🍻
For stock data or hosting your own bot, use my link. This helps keep the bot free:
[marketdata.app](https://dashboard.marketdata.app/marketdata/aff/go/misterbiggs?keyword=discord).
**Updates**: Join the bot's discord: https://t.me/simplestockbotnews.
**Documentation**: All details about the bot are at [docs](https://simplestockbot.com).
The bot reads _"Symbols"_. Use `$` for stock tickers and `$$` for cryptocurrencies. For example:
- `/chart $$eth` gives Ethereum's monthly chart.
- `/dividend $psec` shows Prospect Capital's dividend.
Type any symbol, and the bot shows its price. Like: `Is $$btc rising since $tsla accepts it?` will give Bitcoin and Tesla prices.
**Commands**
- `/donate [USD amount]`: Support the bot. 🎗️
- `/intra $[symbol]`: See stock's latest movement. 📈
- `/chart $[symbol]`: View a month's stock activity. 📊
- `/trending`: Check trending stocks and cryptos. 💬
- `/help`: Need help? Ask here. 🆘
**Inline Features**
Type @SimpleStockBot `[search]` anywhere to find and get stock/crypto prices. Note: Prices might be delayed up to an hour.
Data from: [marketdata.app](https://dashboard.marketdata.app/marketdata/aff/go/misterbiggs?keyword=discord).
Issues with the bot? Use `/status` or [contact us](https://simplestockbot.com/contact).
"""
donate_text = """
Simple Stock Bot runs purely on [donations.](https://www.buymeacoffee.com/Anson)
Every donation supports server costs and
[marketdata.app](https://dashboard.marketdata.app/marketdata/aff/go/misterbiggs?keyword=discord) provides our data.
**How to Donate?**
1. Use `/donate [amount in USD]` command.
- E.g., `/donate 2` donates 2 USD.
2. Or, donate at [buymeacoffee](https://www.buymeacoffee.com/Anson).
- It's quick, doesn't need an account, and accepts Paypal or Credit card.
Questions? Visit our [website](https://simplestockbot.com).
"""

512
discord/bot.py
View File

@ -1,256 +1,256 @@
import datetime
import io
import logging
import os
import mplfinance as mpf
import nextcord
from D_info import D_info
from nextcord.ext import commands
from common.symbol_router import Router
DISCORD_TOKEN = os.environ["DISCORD"]
s = Router()
d = D_info()
intents = nextcord.Intents.default()
client = nextcord.Client(intents=intents)
bot = commands.Bot(command_prefix="/", description=d.help_text, intents=intents)
logger = logging.getLogger("nextcord")
logger.setLevel(logging.INFO)
handler = logging.FileHandler(filename="nextcord.log", encoding="utf-8", mode="w")
handler.setFormatter(logging.Formatter("%(asctime)s:%(levelname)s:%(name)s: %(message)s"))
logger.addHandler(handler)
@bot.event
async def on_ready():
logging.info("Starting Simple Stock Bot")
logging.info(f"Logged in as {bot.user.name} {bot.user.id}")
@bot.command()
async def status(ctx: commands):
"""Debug command for diagnosing if the bot is experiencing any issues."""
logging.info(f"Status command ran by {ctx.message.author}")
message = ""
try:
message = "Contact MisterBiggs#0465 if you need help.\n"
message += s.status(f"Bot recieved your message in: {bot.latency*10:.4f} seconds") + "\n"
except Exception as ex:
logging.critical(ex)
message += (
f"*\n\nERROR ENCOUNTERED:*\n{ex}\n\n"
+ "*The bot encountered an error while attempting to find errors. Please contact the bot admin.*"
)
await ctx.send(message)
@bot.command()
async def license(ctx: commands):
"""Returns the bots license agreement."""
await ctx.send(d.license)
@bot.command()
async def donate(ctx: commands):
"""Details on how to support the development and hosting of the bot."""
await ctx.send(d.donate_text)
@bot.command()
async def search(ctx: commands, *, query: str):
"""Search for a stock symbol using either symbol of company name."""
results = s.search_symbols(query)
if results:
reply = "*Search Results:*\n`$ticker: Company Name`\n"
for query in results:
reply += "`" + query[1] + "`\n"
await ctx.send(reply)
@bot.command()
async def crypto(ctx: commands, _: str):
"""Get the price of a cryptocurrency using in USD."""
await ctx.send("Crypto now has native support. Any crypto can be called using two dollar signs: `$$eth` `$$btc` `$$doge`")
@bot.command()
async def intra(ctx: commands, sym: str):
"""Get a chart for the stocks movement since market open."""
symbols = s.find_symbols(sym)
if len(symbols):
symbol = symbols[0]
else:
await ctx.send("No symbols or coins found.")
return
df = s.intra_reply(symbol)
if df.empty:
await ctx.send("Invalid symbol please see `/help` for usage details.")
return
with ctx.channel.typing():
buf = io.BytesIO()
mpf.plot(
df,
type="renko",
title=f"\n{symbol.name}",
volume="volume" in df.keys(),
style="yahoo",
savefig=dict(fname=buf, dpi=400, bbox_inches="tight"),
)
buf.seek(0)
# Get price so theres no request lag after the image is sent
price_reply = s.price_reply([symbol])[0]
await ctx.send(
file=nextcord.File(
buf,
filename=f"{symbol.name}:intra{datetime.date.today().strftime('%S%M%d%b%Y')}.png",
),
content=f"\nIntraday chart for {symbol.name} from {df.first_valid_index().strftime('%d %b at %H:%M')} to"
+ f" {df.last_valid_index().strftime('%d %b at %H:%M')}",
)
await ctx.send(price_reply)
@bot.command()
async def chart(ctx: commands, sym: str):
"""returns a chart of the past month of data for a symbol"""
symbols = s.find_symbols(sym)
if len(symbols):
symbol = symbols[0]
else:
await ctx.send("No symbols or coins found.")
return
df = s.chart_reply(symbol)
if df.empty:
await ctx.send("Invalid symbol please see `/help` for usage details.")
return
with ctx.channel.typing():
buf = io.BytesIO()
mpf.plot(
df,
type="candle",
title=f"\n{symbol.name}",
volume="volume" in df.keys(),
style="yahoo",
savefig=dict(fname=buf, dpi=400, bbox_inches="tight"),
)
buf.seek(0)
# Get price so theres no request lag after the image is sent
price_reply = s.price_reply([symbol])[0]
await ctx.send(
file=nextcord.File(
buf,
filename=f"{symbol.name}:1M{datetime.date.today().strftime('%d%b%Y')}.png",
),
content=f"\n1 Month chart for {symbol.name} from {df.first_valid_index().strftime('%d, %b %Y')}"
+ f" to {df.last_valid_index().strftime('%d, %b %Y')}",
)
await ctx.send(price_reply)
@bot.command()
async def cap(ctx: commands, sym: str):
"""Get the market cap of a symbol"""
symbols = s.find_symbols(sym)
if symbols:
with ctx.channel.typing():
for reply in s.cap_reply(symbols):
await ctx.send(reply)
@bot.command()
async def trending(ctx: commands):
"""Get a list of Trending Stocks and Coins"""
with ctx.channel.typing():
await ctx.send(s.trending())
@bot.event
async def on_message(message):
# Ignore messages from the bot itself
if message.author.id == bot.user.id:
return
content_lower = message.content.lower()
# Process commands starting with "/"
if message.content.startswith("/"):
await bot.process_commands(message)
return
symbols = None
if "$" in message.content:
symbols = s.find_symbols(message.content)
if "call" in content_lower or "put" in content_lower:
await handle_options(message, symbols)
return
if symbols:
for reply in s.price_reply(symbols):
await message.channel.send(reply)
return
async def handle_options(message, symbols):
logging.info("Options detected")
try:
options_data = s.options(message.content.lower(), symbols)
# Create the embed directly within the function
embed = nextcord.Embed(title=options_data["Option Symbol"], description=options_data["Underlying"], color=0x3498DB)
# Key details
details = (
f"Expiration: {options_data['Expiration']}\n" f"Side: {options_data['side']}\n" f"Strike: {options_data['strike']}"
)
embed.add_field(name="Details", value=details, inline=False)
# Pricing info
pricing_info = (
f"Bid: {options_data['bid']} (Size: {options_data['bidSize']})\n"
f"Mid: {options_data['mid']}\n"
f"Ask: {options_data['ask']} (Size: {options_data['askSize']})\n"
f"Last: {options_data['last']}"
)
embed.add_field(name="Pricing", value=pricing_info, inline=False)
# Volume and open interest
volume_info = f"Open Interest: {options_data['Open Interest']}\n" f"Volume: {options_data['Volume']}"
embed.add_field(name="Activity", value=volume_info, inline=False)
# Greeks
greeks_info = (
f"IV: {options_data['Implied Volatility']}\n"
f"Delta: {options_data['delta']}\n"
f"Gamma: {options_data['gamma']}\n"
f"Theta: {options_data['theta']}\n"
f"Vega: {options_data['vega']}\n"
f"Rho: {options_data['rho']}"
)
embed.add_field(name="Greeks", value=greeks_info, inline=False)
# Send the created embed
await message.channel.send(embed=embed)
except KeyError as ex:
logging.warning(f"KeyError processing options for message {message.content}: {ex}")
bot.run(DISCORD_TOKEN)
import datetime
import io
import logging
import os
import mplfinance as mpf
import nextcord
from D_info import D_info
from nextcord.ext import commands
from common.symbol_router import Router
DISCORD_TOKEN = os.environ["DISCORD"]
s = Router()
d = D_info()
intents = nextcord.Intents.default()
client = nextcord.Client(intents=intents)
bot = commands.Bot(command_prefix="/", description=d.help_text, intents=intents)
logger = logging.getLogger("nextcord")
logger.setLevel(logging.INFO)
handler = logging.FileHandler(filename="nextcord.log", encoding="utf-8", mode="w")
handler.setFormatter(logging.Formatter("%(asctime)s:%(levelname)s:%(name)s: %(message)s"))
logger.addHandler(handler)
@bot.event
async def on_ready():
logging.info("Starting Simple Stock Bot")
logging.info(f"Logged in as {bot.user.name} {bot.user.id}")
@bot.command()
async def status(ctx: commands):
"""Debug command for diagnosing if the bot is experiencing any issues."""
logging.info(f"Status command ran by {ctx.message.author}")
message = ""
try:
message = "Contact MisterBiggs#0465 if you need help.\n"
message += s.status(f"Bot recieved your message in: {bot.latency*10:.4f} seconds") + "\n"
except Exception as ex:
logging.critical(ex)
message += (
f"*\n\nERROR ENCOUNTERED:*\n{ex}\n\n"
+ "*The bot encountered an error while attempting to find errors. Please contact the bot admin.*"
)
await ctx.send(message)
@bot.command()
async def license(ctx: commands):
"""Returns the bots license agreement."""
await ctx.send(d.license)
@bot.command()
async def donate(ctx: commands):
"""Details on how to support the development and hosting of the bot."""
await ctx.send(d.donate_text)
@bot.command()
async def search(ctx: commands, *, query: str):
"""Search for a stock symbol using either symbol of company name."""
results = s.search_symbols(query)
if results:
reply = "*Search Results:*\n`$ticker: Company Name`\n"
for query in results:
reply += "`" + query[1] + "`\n"
await ctx.send(reply)
@bot.command()
async def crypto(ctx: commands, _: str):
"""Get the price of a cryptocurrency using in USD."""
await ctx.send("Crypto now has native support. Any crypto can be called using two dollar signs: `$$eth` `$$btc` `$$doge`")
@bot.command()
async def intra(ctx: commands, sym: str):
"""Get a chart for the stocks movement since market open."""
symbols = s.find_symbols(sym)
if len(symbols):
symbol = symbols[0]
else:
await ctx.send("No symbols or coins found.")
return
df = s.intra_reply(symbol)
if df.empty:
await ctx.send("Invalid symbol please see `/help` for usage details.")
return
with ctx.channel.typing():
buf = io.BytesIO()
mpf.plot(
df,
type="renko",
title=f"\n{symbol.name}",
volume="volume" in df.keys(),
style="yahoo",
savefig=dict(fname=buf, dpi=400, bbox_inches="tight"),
)
buf.seek(0)
# Get price so theres no request lag after the image is sent
price_reply = s.price_reply([symbol])[0]
await ctx.send(
file=nextcord.File(
buf,
filename=f"{symbol.name}:intra{datetime.date.today().strftime('%S%M%d%b%Y')}.png",
),
content=f"\nIntraday chart for {symbol.name} from {df.first_valid_index().strftime('%d %b at %H:%M')} to"
+ f" {df.last_valid_index().strftime('%d %b at %H:%M')}",
)
await ctx.send(price_reply)
@bot.command()
async def chart(ctx: commands, sym: str):
"""returns a chart of the past month of data for a symbol"""
symbols = s.find_symbols(sym)
if len(symbols):
symbol = symbols[0]
else:
await ctx.send("No symbols or coins found.")
return
df = s.chart_reply(symbol)
if df.empty:
await ctx.send("Invalid symbol please see `/help` for usage details.")
return
with ctx.channel.typing():
buf = io.BytesIO()
mpf.plot(
df,
type="candle",
title=f"\n{symbol.name}",
volume="volume" in df.keys(),
style="yahoo",
savefig=dict(fname=buf, dpi=400, bbox_inches="tight"),
)
buf.seek(0)
# Get price so theres no request lag after the image is sent
price_reply = s.price_reply([symbol])[0]
await ctx.send(
file=nextcord.File(
buf,
filename=f"{symbol.name}:1M{datetime.date.today().strftime('%d%b%Y')}.png",
),
content=f"\n1 Month chart for {symbol.name} from {df.first_valid_index().strftime('%d, %b %Y')}"
+ f" to {df.last_valid_index().strftime('%d, %b %Y')}",
)
await ctx.send(price_reply)
@bot.command()
async def cap(ctx: commands, sym: str):
"""Get the market cap of a symbol"""
symbols = s.find_symbols(sym)
if symbols:
with ctx.channel.typing():
for reply in s.cap_reply(symbols):
await ctx.send(reply)
@bot.command()
async def trending(ctx: commands):
"""Get a list of Trending Stocks and Coins"""
with ctx.channel.typing():
await ctx.send(s.trending())
@bot.event
async def on_message(message):
# Ignore messages from the bot itself
if message.author.id == bot.user.id:
return
content_lower = message.content.lower()
# Process commands starting with "/"
if message.content.startswith("/"):
await bot.process_commands(message)
return
symbols = None
if "$" in message.content:
symbols = s.find_symbols(message.content)
if "call" in content_lower or "put" in content_lower:
await handle_options(message, symbols)
return
if symbols:
for reply in s.price_reply(symbols):
await message.channel.send(reply)
return
async def handle_options(message, symbols):
logging.info("Options detected")
try:
options_data = s.options(message.content.lower(), symbols)
# Create the embed directly within the function
embed = nextcord.Embed(title=options_data["Option Symbol"], description=options_data["Underlying"], color=0x3498DB)
# Key details
details = (
f"Expiration: {options_data['Expiration']}\n" f"Side: {options_data['side']}\n" f"Strike: {options_data['strike']}"
)
embed.add_field(name="Details", value=details, inline=False)
# Pricing info
pricing_info = (
f"Bid: {options_data['bid']} (Size: {options_data['bidSize']})\n"
f"Mid: {options_data['mid']}\n"
f"Ask: {options_data['ask']} (Size: {options_data['askSize']})\n"
f"Last: {options_data['last']}"
)
embed.add_field(name="Pricing", value=pricing_info, inline=False)
# Volume and open interest
volume_info = f"Open Interest: {options_data['Open Interest']}\n" f"Volume: {options_data['Volume']}"
embed.add_field(name="Activity", value=volume_info, inline=False)
# Greeks
greeks_info = (
f"IV: {options_data['Implied Volatility']}\n"
f"Delta: {options_data['delta']}\n"
f"Gamma: {options_data['gamma']}\n"
f"Theta: {options_data['theta']}\n"
f"Vega: {options_data['vega']}\n"
f"Rho: {options_data['rho']}"
)
embed.add_field(name="Greeks", value=greeks_info, inline=False)
# Send the created embed
await message.channel.send(embed=embed)
except KeyError as ex:
logging.warning(f"KeyError processing options for message {message.content}: {ex}")
bot.run(DISCORD_TOKEN)

9
pyproject.toml
View File

@ -1,11 +1,2 @@
[tool.black]
line-length = 130
[tool.flake8]
max-line-length = 130
[tool.pycodestyle]
max_line_length = 130
[tool.ruff]
line-length = 130

140
telegram/T_info.py
View File

@ -1,70 +1,70 @@
"""Functions and Info specific to the Telegram Bot
"""
import re
import requests as r
class T_info:
license = re.sub(
r"\b\n",
" ",
r.get("https://gitlab.com/simple-stock-bots/simple-stock-bot/-/raw/master/LICENSE").text,
)
help_text = """
Appreciate this bot? Show support by [buying me a beer](https://www.buymeacoffee.com/Anson) 🍻.
Want stock data or to host your own bot? Help keep this bot free by using my
[affiliate link](https://dashboard.marketdata.app/marketdata/aff/go/misterbiggs?keyword=telegram).
📢 Stay updated on the bot's Telegram: https://t.me/simplestockbotnews.
**Guide**: All about using and setting up the bot is in the [docs](https://simplestockbot.com).
The bot recognizes _"Symbols"_. `$` for stocks and `$$` for cryptos. Example:
- `/chart $$eth` gets a month's Ethereum chart.
- `/dividend $psec` shows Prospect Capital's dividend info.
Mention a symbol, and the bot reveals its price.
E.g., `What's $$btc's price since $tsla accepts it?` gives Bitcoin and Tesla prices.
**Commands**
- `/donate [USD]`: Support the bot. 🎗️
- `/intra $[symbol]`: Today's stock activity. 📈
- `/chart $[symbol]`: Past month's stock chart. 📊
- `/trending`: What's hot in stocks and cryptos. 💬
- `/help`: Bot assistance. 🆘
**Inline Features**
Search with @SimpleStockBot `[query]` anywhere.
Pick a ticker, and the bot shares the current price in chat. Note: Prices can lag by an hour.
Data thanks to [marketdata.app](https://dashboard.marketdata.app/marketdata/aff/go/misterbiggs?keyword=telegram).
Bot issues? Use `/status` or [contact us](https://simplestockbot.com/contact).
"""
donate_text = """
Support Simple Stock Bot through [donations](https://www.buymeacoffee.com/Anson).
All funds help maintain servers, with data from
[marketdata.app](https://dashboard.marketdata.app/marketdata/aff/go/misterbiggs?keyword=telegram).
**How to Donate?**
1. Use `/donate [amount in USD]`. E.g., `/donate 2` donates 2 USD.
2. Or, quickly donate at [buymeacoffee](https://www.buymeacoffee.com/Anson). No account needed, accepts Paypal & Credit card.
For questions, visit our [website](https://simplestockbot.com).
"""
# Not used by the bot but for updating commands with BotFather
commands = """
donate - Donate to the bot 🎗️
help - Get some help using the bot. 🆘
trending - Trending Stocks and Cryptos. 💬
intra - $[symbol] Plot since the last market open. 📈
chart - $[chart] Plot of the past month. 📊
"""
"""Functions and Info specific to the Telegram Bot
"""
import re
import requests as r
class T_info:
license = re.sub(
r"\b\n",
" ",
r.get("https://gitlab.com/simple-stock-bots/simple-stock-bot/-/raw/master/LICENSE").text,
)
help_text = """
Appreciate this bot? Show support by [buying me a beer](https://www.buymeacoffee.com/Anson) 🍻.
Want stock data or to host your own bot? Help keep this bot free by using my
[affiliate link](https://dashboard.marketdata.app/marketdata/aff/go/misterbiggs?keyword=telegram).
📢 Stay updated on the bot's Telegram: https://t.me/simplestockbotnews.
**Guide**: All about using and setting up the bot is in the [docs](https://simplestockbot.com).
The bot recognizes _"Symbols"_. `$` for stocks and `$$` for cryptos. Example:
- `/chart $$eth` gets a month's Ethereum chart.
- `/dividend $psec` shows Prospect Capital's dividend info.
Mention a symbol, and the bot reveals its price.
E.g., `What's $$btc's price since $tsla accepts it?` gives Bitcoin and Tesla prices.
**Commands**
- `/donate [USD]`: Support the bot. 🎗️
- `/intra $[symbol]`: Today's stock activity. 📈
- `/chart $[symbol]`: Past month's stock chart. 📊
- `/trending`: What's hot in stocks and cryptos. 💬
- `/help`: Bot assistance. 🆘
**Inline Features**
Search with @SimpleStockBot `[query]` anywhere.
Pick a ticker, and the bot shares the current price in chat. Note: Prices can lag by an hour.
Data thanks to [marketdata.app](https://dashboard.marketdata.app/marketdata/aff/go/misterbiggs?keyword=telegram).
Bot issues? Use `/status` or [contact us](https://simplestockbot.com/contact).
"""
donate_text = """
Support Simple Stock Bot through [donations](https://www.buymeacoffee.com/Anson).
All funds help maintain servers, with data from
[marketdata.app](https://dashboard.marketdata.app/marketdata/aff/go/misterbiggs?keyword=telegram).
**How to Donate?**
1. Use `/donate [amount in USD]`. E.g., `/donate 2` donates 2 USD.
2. Or, quickly donate at [buymeacoffee](https://www.buymeacoffee.com/Anson). No account needed, accepts Paypal & Credit card.
For questions, visit our [website](https://simplestockbot.com).
"""
# Not used by the bot but for updating commands with BotFather
commands = """
donate - Donate to the bot 🎗️
help - Get some help using the bot. 🆘
trending - Trending Stocks and Cryptos. 💬
intra - $[symbol] Plot since the last market open. 📈
chart - $[chart] Plot of the past month. 📊
"""

1016
telegram/bot.py
View File

File diff suppressed because it is too large Load Diff

44
tests.py
View File

@ -1,23 +1,21 @@
import time
import keyboard
tests = """$$xno
$tsla
/intra $tsla
/intra $$btc
/chart $tsla
/chart $$btc
/help
/trending""".split(
"\n"
)
print("press enter to start")
keyboard.wait("enter")
for test in tests:
print(test)
keyboard.write(test)
time.sleep(1)
keyboard.press_and_release("enter")
import time
import keyboard
tests = """$$xno
$tsla
/intra $tsla
/intra $$btc
/chart $tsla
/chart $$btc
/help
/trending""".split("\n")
print("press enter to start")
keyboard.wait("enter")
for test in tests:
print(test)
keyboard.write(test)
time.sleep(1)
keyboard.press_and_release("enter")