HackerNews / Algolia Python Library

This is a simple library to interface with HN Search API (provided by Algolia).

Install | Basic Usage | Development | Roadmap

👉 Note: As an example, I used this library to download ALL Hacker News posts and made it available as a public dataset in Kaggle.

Install instructions

$ pip install python-hn

Usage

from hn import search_by_date

# Search everything (stories, comments, etc) containing the keyword 'python'
search_by_date('python')

# Search everything (stories, comments, etc) from author 'pg' and keyword 'lisp'
search_by_date('lisp', author='pg', created_at__lt='2018-01-01')

# Search only stories
search_by_date('lisp', author='pg', stories=True, created_at__lt='2018-01-01')

# Search stories *or* comments
search_by_date(q='lisp', author='pg', stories=True, comments=True, created_at__lt='2018-01-01')

Tags

Tags are part of HN Search API provided by Algolia. You can read more in their docs. They can form complex queries, for example:

# All the comments in the story `6902129`
tags = PostType('comment') & StoryID('6902129')

The available tags are:

• PostType: with options story, comment, poll, pollopt, show_hn, ask_hn, front_page.
• Author: receives the username as param (Author('pg')).
• StoryID: receives the story id (StoryID('6902129'))

Filters

Filters can be applied to restrict the search by:

• Creation Date: created_at
• Points: points
• Number of comments: num_comments

They can accept >, <, >=, <= operators with a syntax similar to Django's.

• lt (<): Lower than. Example ponts__lt=100
• lte (<=): Lower than or equals to. Example ponts__lte=100
• gt (>): Greater than. Example created_at__gt='2018' (created after 2018-01-01).
• gte (>=): Greater than or equals to. Example num_comments__gte=50.

Examples (See Algolia docs for more info):

# Created after October 1st, 2018
search_by_date(created_at__gt='2018-10')

# Created after October 1st, 2017 and before January 1st 2018
search_by_date(created_at__gt='2018-10', created_at__lt='2018')

# Stories with *exactly* 1000 points
search_by_date(tags=PostType('story'), points=1000)

# Comments with more than 50 points
search_by_date(tags=PostType('comment'), points__gt=50)

# Stories with 100 comments or more
search_by_date(tags=PostType('story'), num_comments__gt=100)

Search

[TODO]

Development

I'm in the process of updating this project and migrating to uv. You should be able to just do:

$ uv run py.test