World News
Implementation details
Class names
| Model name | Parameters class | Data class |
|---|---|---|
WorldNews | WorldNewsQueryParams | WorldNewsData |
Import Statement
from openbb_core.provider.standard_models.world_news import (
WorldNewsData,
WorldNewsQueryParams,
)
Parameters
- standard
- benzinga
- biztoc
- fmp
- intrinio
- tiingo
start_date: Union[date, str]
Start date of the data, in YYYY-MM-DD format. The default is 2 weeks ago.
• Optional: True
end_date: Union[date, str]
End date of the data, in YYYY-MM-DD format. The default is today.
• Optional: True
limit: Annotated[int, Ge(ge=0)]
The number of data entries to return. The number of articles to return.
• Optional: True
start_date: Union[date, str]
Start date of the data, in YYYY-MM-DD format. The default is 2 weeks ago.
• Optional: True
end_date: Union[date, str]
End date of the data, in YYYY-MM-DD format. The default is today.
• Optional: True
limit: Annotated[int, Ge(ge=0)]
The number of data entries to return. The number of articles to return.
• Optional: True
date: Union[date, str]
A specific date to get data for.
• Optional: True
display: Literal['headline', 'abstract', 'full']
Specify headline only (headline), headline + teaser (abstract), or headline + full body (full).
• Default: full
• Optional: True
updated_since: int
Number of seconds since the news was updated.
• Optional: True
published_since: int
Number of seconds since the news was published.
• Optional: True
sort: Literal['id', 'created', 'updated']
Key to sort the news by.
• Default: created
• Optional: True
order: Literal['asc', 'desc']
Order to sort the news by.
• Default: desc
• Optional: True
isin: str
The ISIN of the news to retrieve.
• Optional: True
cusip: str
The CUSIP of the news to retrieve.
• Optional: True
channels: str
Channels of the news to retrieve.
• Optional: True
topics: str
Topics of the news to retrieve.
• Optional: True
authors: str
Authors of the news to retrieve.
• Optional: True
content_types: str
Content types of the news to retrieve.
• Optional: True
start_date: Union[date, str]
Start date of the data, in YYYY-MM-DD format. The default is 2 weeks ago.
• Optional: True
end_date: Union[date, str]
End date of the data, in YYYY-MM-DD format. The default is today.
• Optional: True
limit: Annotated[int, Ge(ge=0)]
The number of data entries to return. The number of articles to return.
• Optional: True
term: str
Search term to filter articles by. This overrides all other filters.
• Optional: True
source: str
Filter by a specific publisher. Only valid when filter is set to source.
• Optional: True
start_date: Union[date, str]
Start date of the data, in YYYY-MM-DD format. The default is 2 weeks ago.
• Optional: True
end_date: Union[date, str]
End date of the data, in YYYY-MM-DD format. The default is today.
• Optional: True
limit: Annotated[int, Ge(ge=0)]
The number of data entries to return. The number of articles to return.
• Optional: True
topic: Literal['fmp_articles', 'general', 'press_releases', 'stocks', 'forex', 'crypto']
The topic of the news to be fetched.
• Default: general
• Optional: True
page: int
Page number of the results. Use in combination with limit.
• Optional: True
start_date: Union[date, str]
Start date of the data, in YYYY-MM-DD format. The default is 2 weeks ago.
• Optional: True
end_date: Union[date, str]
End date of the data, in YYYY-MM-DD format. The default is today.
• Optional: True
limit: Annotated[int, Ge(ge=0)]
The number of data entries to return. The number of articles to return.
• Optional: True
source: Literal['yahoo', 'moody', 'moody_us_news', 'moody_us_press_releases']
The source of the news article.
• Optional: True
sentiment: Literal['positive', 'neutral', 'negative']
Return news only from this source.
• Optional: True
language: str
Filter by language. Unsupported for yahoo source.
• Optional: True
topic: str
Filter by topic. Unsupported for yahoo source.
• Optional: True
word_count_greater_than: int
News stories will have a word count greater than this value. Unsupported for yahoo source.
• Optional: True
word_count_less_than: int
News stories will have a word count less than this value. Unsupported for yahoo source.
• Optional: True
is_spam: bool
Filter whether it is marked as spam or not. Unsupported for yahoo source.
• Optional: True
business_relevance_greater_than: float
News stories will have a business relevance score more than this value. Unsupported for yahoo source. Value is a decimal between 0 and 1.
• Optional: True
business_relevance_less_than: float
News stories will have a business relevance score less than this value. Unsupported for yahoo source. Value is a decimal between 0 and 1.
• Optional: True
start_date: Union[date, str]
Start date of the data, in YYYY-MM-DD format. The default is 2 weeks ago.
• Optional: True
end_date: Union[date, str]
End date of the data, in YYYY-MM-DD format. The default is today.
• Optional: True
limit: Annotated[int, Ge(ge=0)]
The number of data entries to return. The number of articles to return.
• Optional: True
offset: int
Page offset, used in conjunction with limit.
• Default: 0
• Optional: True
source: Union[str, list[str]]
A comma-separated list of the domains requested. Multiple items allowed for provider(s): tiingo.
• Optional: True
Data
- standard
- benzinga
- biztoc
- fmp
- intrinio
- tiingo
date: Union[datetime, str]
The date of the data. The date of publication.
title: str
Title of the article.
author: str
Author of the article.
excerpt: str
Excerpt of the article text.
body: str
Body of the article text.
images: Any
Images associated with the article.
url: str
URL to the article.
date: Union[datetime, str]
The date of the data. The date of publication.
title: str
Title of the article.
author: str
Author of the article.
excerpt: str
Excerpt of the article text.
body: str
Body of the article text.
images: Any
Images associated with the article.
url: str
URL to the article.
channels: str
Channels associated with the news.
stocks: str
Stocks associated with the news.
tags: str
Tags associated with the news.
updated: datetime
Updated date of the news.
id: str
Article ID.
updated_id: str
Updated article ID if the article was updated.
date: Union[datetime, str]
The date of the data. The date of publication.
title: str
Title of the article.
author: str
Author of the article.
excerpt: str
Excerpt of the article text.
body: str
Body of the article text.
images: list[dict[str, str]]
Images for the article.
url: str
URL to the article.
tags: list[str]
Tags for the article.
score: float
Search relevance score for the article.
date: Union[datetime, str]
The date of the data. The date of publication.
title: str
Title of the article.
author: str
Author of the article.
excerpt: str
Excerpt of the article text.
body: str
Body of the article text.
images: Any
Images associated with the article.
url: str
URL to the article.
source: str
News source.
date: Union[datetime, str]
The date of the data. The date of publication.
title: str
Title of the article.
author: str
Author of the article.
excerpt: str
Excerpt of the article text.
body: str
Body of the article text.
images: Any
Images associated with the article.
url: str
URL to the article.
source: str
The source of the news article.
summary: str
The summary of the news article.
topics: str
The topics related to the news article.
word_count: int
The word count of the news article.
business_relevance: float
How strongly correlated the news article is to the business
sentiment: str
The sentiment of the news article - i.e, negative, positive.
sentiment_confidence: float
The confidence score of the sentiment rating.
language: str
The language of the news article.
spam: bool
Whether the news article is spam.
copyright: str
The copyright notice of the news article.
id: str
Article ID.
company: IntrinioCompany
The Intrinio Company object. Contains details company reference data.
security: IntrinioSecurity
The Intrinio Security object. Contains the security details related to the news article.
date: Union[datetime, str]
The date of the data. The date of publication.
title: str
Title of the article.
author: str
Author of the article.
excerpt: str
Excerpt of the article text.
body: str
Body of the article text.
images: Any
Images associated with the article.
url: str
URL to the article.
symbols: str
Ticker tagged in the fetched news.
article_id: int
Unique ID of the news article.
site: str
News source.
tags: str
Tags associated with the news article.
crawl_date: datetime
Date the news article was crawled.