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https://github.com/OpenBB-finance/OpenBB.git
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13283fbfce
* BIGGGG LINTING * fixing lints * fixing lints * black * very ruff * no export * fix hedge_view again * lints * platform lints * lints * black * black it @hjoaquim * fix some more linting --------- Co-authored-by: hjoaquim <h.joaquim@campus.fct.unl.pt>
87 lines
2.4 KiB
Python
87 lines
2.4 KiB
Python
"""Polygon.io model"""
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__docformat__ = "numpy"
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from datetime import datetime
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from typing import Optional
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import pandas as pd
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from openbb_terminal.core.session.current_user import get_current_user
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from openbb_terminal.decorators import check_api_key
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from openbb_terminal.helper_funcs import get_user_agent, get_user_timezone, request
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from openbb_terminal.rich_config import console
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# pylint: disable=unsupported-assignment-operation
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@check_api_key(["API_POLYGON_KEY"])
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def get_historical(
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fx_pair: str,
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multiplier: int = 1,
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timespan: str = "day",
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start_date: str = "2000-01-01",
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end_date: Optional[str] = None,
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) -> pd.DataFrame:
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"""Load historical fx data from polygon
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Parameters
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----------
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fx_pair: str
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Forex pair to download
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multiplier: int
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Multiplier for timespan. 5 with minute timespan indicated 5min windows
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timespan: str
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Window to aggregate data.
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start_date : str
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Initial date, format YYYY-MM-DD
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end_date : Optional[str]
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Final date, format YYYY-MM-DD
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Returns
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-------
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pd.DataFrame
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Dataframe of historical forex prices
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"""
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if end_date is None:
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end_date = datetime.now().date().strftime("%Y-%m-%d")
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request_url = (
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f"https://api.polygon.io/v2/aggs/ticker/C:{fx_pair}/range"
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f"/{multiplier}/{timespan}/{start_date}/{end_date}?adjusted=true&sort=desc&"
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f"limit=50000&apiKey={get_current_user().credentials.API_POLYGON_KEY}"
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)
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json_response = request(
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request_url, headers={"User-Agent": get_user_agent()}
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).json()
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if json_response["status"] == "ERROR":
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console.print(f"[red]{json_response['error']}[/red]\n")
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return pd.DataFrame()
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if "results" not in json_response:
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console.print("[red]Error in polygon request[/red]\n")
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return pd.DataFrame()
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historical = pd.DataFrame(json_response["results"]).rename(
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columns={
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"o": "Open",
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"c": "Close",
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"h": "High",
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"l": "Low",
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"t": "date",
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"v": "Volume",
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"n": "Transactions",
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}
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)
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historical["date"] = pd.to_datetime(historical.date, unit="ms")
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historical = historical.sort_values(by="date", ascending=True)
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historical = historical.set_index("date")
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historical.index = (
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historical.index.tz_localize(tz="UTC")
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.tz_convert(get_user_timezone())
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.tz_localize(None)
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)
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return historical
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