orange3-ilpost 0.2.1

Orange3 widget for fetching articles from Il Post

Orange3 Il Post Widget

An Orange3 add-on widget for fetching articles, podcasts, and newsletters from the Italian online newspaper Il Post. The widget queries the Il Post search API and outputs a Corpus ready for text mining workflows.

User Interface

Installation

pip install orange3-ilpost

The package requires Orange3 and orange3-text to be installed. The Il Post API wrapper (ilpost-api-wrapper) is installed automatically as a dependency.

Usage

After installation, the Il Post category will appear in the Orange Canvas widget toolbox.

1. Drag the Il Post widget onto the canvas.
2. Type a search query in the Query field and press Enter or click Search.
3. Adjust the filters as needed (see below).
4. Connect the widget output to any text mining widget (e.g. Corpus Viewer, Word Cloud, Topic Modelling).

Controls

Control	Description
Query	Search term. Keeps a history of recent queries.
Content type	Filter by All, Articles, Podcasts, or Newsletters.
Date range	Filter by All time, Past year, or Past 30 days.
Sort by	Sort results by Relevance, Newest, or Oldest.
Category	Optional editorial category filter (e.g. politica, cultura). Applies to articles only.
Max documents	Maximum number of results to retrieve (1–1000, capped at 100 when Content is selected).
Include paywalled content	When unchecked, subscriber-only results are excluded.
Text includes	Choose which fields are included in the output corpus and used as text features for analysis. Use Select All to check or uncheck all fields at once. Selecting Content (max 100 articles) also downloads the full article body (capped at 100 documents).

Output

The widget outputs a Corpus with the following metadata columns:

Field	Type	Description
Title	String	Article/episode title
Summary	String	Short description
Content	String	Full article body (only when Content is selected in Text includes)
Highlight	String	Search snippet with matched terms
Category	String	Editorial category
Tags	String	Comma-separated topic tags
Type	String	Content type (post, episodes, newsletter)
Publication Date	Time	Publication timestamp (Italian local time)
URL	String	Link to the full content
Relevance Score	Continuous	Search relevance score (0.0 when sorted by date)

Only the columns selected in Text includes appear in the output corpus (Publication Date and Relevance Score are always included).

Example workflow

[Il Post] → [Corpus Viewer]
[Il Post] → [Word Cloud]
[Il Post] → [Topic Modelling]
[Il Post] → [Sentiment Analysis]

Requirements

• Python 3.9+
• Orange3
• orange3-text
• ilpost-api-wrapper

License

MIT