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https://github.com/OpenBB-finance/OpenBB.git
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581fd94276
* fix options hist to display date column when raw is True * make raw table title same as other sources * if export
85 lines
2.8 KiB
Python
85 lines
2.8 KiB
Python
"""Chartexchange model"""
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import logging
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from typing import Optional, Union
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import pandas as pd
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from bs4 import BeautifulSoup
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from openbb_terminal.decorators import log_start_end
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from openbb_terminal.helper_funcs import get_user_agent, request
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from openbb_terminal.rich_config import console
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from openbb_terminal.stocks.options.op_helpers import convert
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logger = logging.getLogger(__name__)
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@log_start_end(log=logger)
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def get_option_history(
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symbol: str = "GME",
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date: str = "2021-02-05",
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call: bool = True,
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price: Union[str, Union[int, float]] = "90",
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chain_id: Optional[str] = None,
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) -> pd.DataFrame:
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"""Historic prices for a specific option [chartexchange]
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Parameters
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----------
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symbol : str
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Ticker symbol to get historical data from
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date : str
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Date as a string YYYYMMDD
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call : bool
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Whether to show a call or a put
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price : Union[str, Union[int, float]]
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Strike price for a specific option
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chain_id: str
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Option symbol. Overwrites other inputs. ChartExchange uses the format:
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`{TICKER}{YYYYMMDD}{C/P}{PRICE}`, where the price has no leading and trailing zeros.
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Returns
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-------
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historical : pd.Dataframe
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Historic information for an option
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"""
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if chain_id is None:
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url = f"https://chartexchange.com/symbol/opra-{symbol.lower()}{date.replace('-', '')}"
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url += f"{'c' if call else 'p'}{float(price):g}/historical/"
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else:
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url = f"https://chartexchange.com/symbol/opra-{chain_id}/historical/"
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data = request(url, headers={"User-Agent": get_user_agent()}).content
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soup = BeautifulSoup(data, "html.parser")
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table = soup.find("div", attrs={"style": "display: table; font-size: 0.9em; "})
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if table:
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rows = table.find_all("div", attrs={"style": "display: table-row;"})
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else:
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return pd.DataFrame()
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clean_rows = []
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if rows:
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for row in rows[1:]:
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item = row.find_all("div")
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clean_rows.append([x.text for x in item])
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else:
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if chain_id is not None:
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console.print(
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f"No data for {chain_id}. Check that you are using OPRA notation.\n"
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)
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return pd.DataFrame()
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console.print("No data for this option\n")
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return pd.DataFrame()
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df = pd.DataFrame()
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df["Date"] = [x[0] for x in clean_rows]
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df["Open"] = [convert(x[2], ",") for x in clean_rows]
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df["High"] = [convert(x[3], ",") for x in clean_rows]
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df["Low"] = [convert(x[4], ",") for x in clean_rows]
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df["Close"] = [convert(x[5], ",") for x in clean_rows]
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df["Change"] = [convert(x[6], "%") for x in clean_rows]
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df["Volume"] = [convert(x[7], ",") for x in clean_rows]
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df["Open Interest"] = [convert(x[8], ",") for x in clean_rows]
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df["Change Since"] = [convert(x[9], "%") for x in clean_rows]
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return df
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