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88 lines
2.6 KiB
Python
88 lines
2.6 KiB
Python
""" News Model """
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__docformat__ = "numpy"
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import logging
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from datetime import datetime, timedelta
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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, log_start_end
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from openbb_terminal.helper_funcs import request
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from openbb_terminal.rich_config import console
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logger = logging.getLogger(__name__)
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@log_start_end(log=logger)
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@check_api_key(["API_NEWS_TOKEN"])
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def get_news(
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query: str,
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limit: int = 10,
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start_date: Optional[str] = None,
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show_newest: bool = True,
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sources: str = "",
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) -> pd.DataFrame:
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"""Get news for a given term. [Source: NewsAPI]
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Parameters
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----------
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query : str
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term to search on the news articles
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start_date: Optional[str]
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date to start searching articles from formatted YYYY-MM-DD
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show_newest: bool
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flag to show newest articles first
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sources: str
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sources to exclusively show news from (comma separated)
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Returns
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-------
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pd.DataFrame
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DataFrame with columns Date, Description, URL
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"""
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if start_date is None:
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start_date = (datetime.now() - timedelta(days=7)).strftime("%Y-%m-%d")
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link = (
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f"https://newsapi.org/v2/everything?q={query}&from={start_date}&sortBy=publishedAt"
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"&language=en"
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)
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if sources:
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if "," in sources:
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sources = ".com,".join(sources.split(","))
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link += f"&domains={sources}.com"
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link += f"&apiKey={get_current_user().credentials.API_NEWS_TOKEN}"
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response = request(link)
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articles = {}
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if response.status_code == 200:
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response_json = response.json()
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articles = (
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response_json["articles"]
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if show_newest
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else response_json["articles"][::-1]
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)
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elif response.status_code == 426:
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console.print(f"Error in request: {response.json()['message']}", "\n")
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elif response.status_code == 401:
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console.print("[red]Invalid API Key[/red]\n")
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elif response.status_code == 429:
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console.print("[red]Exceeded number of calls per minute[/red]\n")
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else:
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console.print(f"Error in request: {response.json()['message']}", "\n")
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if articles:
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df = pd.DataFrame(articles)
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df["publishedAt"] = pd.to_datetime(df["publishedAt"])
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df["publishedAt"].apply(lambda x: x.strftime("%Y-%m-%d %H:%M:%S"))
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df = df[["publishedAt", "description", "url"]]
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df.columns = ["Date", "Description", "URL"]
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df = df[:limit]
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return df
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return pd.DataFrame()
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