Files
OpenBB/gamestonk_terminal/stocks/options/chartexchange_model.py
DidierRLopes 432ccf386b Refactor options menu into stocks and others (#931)
* Improve candle and make interactive default

* change path of dcf file

* Remove RS lines when intraday plot

* refactor options menu

* remove candle start and end params
2021-11-08 17:22:08 +00:00

62 lines
2.0 KiB
Python

"""Chartexchange model"""
__docformat__ = "numpy"
import requests
import pandas as pd
from bs4 import BeautifulSoup
from gamestonk_terminal.stocks.options.op_helpers import convert
from gamestonk_terminal.helper_funcs import get_user_agent
def get_option_history(ticker: str, date: str, call: bool, price: str) -> pd.DataFrame:
"""Historic prices for a specific option [chartexchange]
Parameters
----------
ticker : str
Ticker to get historical data from
date : str
Date as a string YYYYMMDD
call : bool
Whether to show a call or a put
price : str
Strike price for a specific option
Returns
-------
historical : pd.Dataframe
Historic information for an option
"""
url = (
f"https://chartexchange.com/symbol/opra-{ticker.lower()}{date.replace('-', '')}"
)
url += f"{'c' if call else 'p'}{float(price):g}/historical/"
data = requests.get(url, headers={"User-Agent": get_user_agent()}).content
soup = BeautifulSoup(data, "html.parser")
table = soup.find("div", attrs={"style": "display: table; font-size: 0.9em; "})
rows = table.find_all("div", attrs={"style": "display: table-row;"})
clean_rows = []
if rows:
for row in rows[1:]:
item = row.find_all("div")
clean_rows.append([x.text for x in item])
else:
print("No data for this option\n")
return pd.DataFrame()
df = pd.DataFrame()
df["Date"] = [x[0] for x in clean_rows]
df["Open"] = [convert(x[1], ",") for x in clean_rows]
df["High"] = [convert(x[2], ",") for x in clean_rows]
df["Low"] = [convert(x[3], ",") for x in clean_rows]
df["Close"] = [convert(x[4], ",") for x in clean_rows]
df["Change"] = [convert(x[5], "%") for x in clean_rows]
df["Volume"] = [convert(x[6], ",") for x in clean_rows]
df["Open Interest"] = [convert(x[7], ",") for x in clean_rows]
df["Change Since"] = [convert(x[8], "%") for x in clean_rows]
return df