mirror of
https://github.com/OpenBB-finance/OpenBB.git
synced 2026-10-29 05:21:48 +00:00
649dd1d64b
* Fix linter issue * Didnt import optimization menu * Fix some things for deployment * openbbterminal -> openbb * openbb
77 lines
2.3 KiB
Python
77 lines
2.3 KiB
Python
"""Chartexchange model"""
|
|
|
|
import logging
|
|
from typing import Union
|
|
|
|
import pandas as pd
|
|
import requests
|
|
from bs4 import BeautifulSoup
|
|
|
|
from openbb_terminal.decorators import log_start_end
|
|
from openbb_terminal.helper_funcs import get_user_agent
|
|
from openbb_terminal.rich_config import console
|
|
from openbb_terminal.stocks.options.op_helpers import convert
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
@log_start_end(log=logger)
|
|
def get_option_history(
|
|
symbol: str = "GME",
|
|
date: str = "2021-02-05",
|
|
call: bool = True,
|
|
price: Union[str, Union[int, float]] = "90",
|
|
) -> pd.DataFrame:
|
|
"""Historic prices for a specific option [chartexchange]
|
|
|
|
Parameters
|
|
----------
|
|
symbol : str
|
|
Ticker symbol to get historical data from
|
|
date : str
|
|
Date as a string YYYYMMDD
|
|
call : bool
|
|
Whether to show a call or a put
|
|
price : Union[str, Union[int, float]]
|
|
Strike price for a specific option
|
|
|
|
Returns
|
|
-------
|
|
historical : pd.Dataframe
|
|
Historic information for an option
|
|
"""
|
|
url = (
|
|
f"https://chartexchange.com/symbol/opra-{symbol.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; "})
|
|
if table:
|
|
rows = table.find_all("div", attrs={"style": "display: table-row;"})
|
|
else:
|
|
return pd.DataFrame()
|
|
clean_rows = []
|
|
|
|
if rows:
|
|
for row in rows[1:]:
|
|
item = row.find_all("div")
|
|
clean_rows.append([x.text for x in item])
|
|
else:
|
|
console.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[2], ",") for x in clean_rows]
|
|
df["High"] = [convert(x[3], ",") for x in clean_rows]
|
|
df["Low"] = [convert(x[4], ",") for x in clean_rows]
|
|
df["Close"] = [convert(x[5], ",") for x in clean_rows]
|
|
df["Change"] = [convert(x[6], "%") for x in clean_rows]
|
|
df["Volume"] = [convert(x[7], ",") for x in clean_rows]
|
|
df["Open Interest"] = [convert(x[8], ",") for x in clean_rows]
|
|
df["Change Since"] = [convert(x[9], "%") for x in clean_rows]
|
|
|
|
return df
|