A wrapper library for Hacker News Search API (provided by Algolia)
Project description
HackerNews / Algolia Python Library
This is a simple library to interface with HN Search API (provided by Algolia).
Install instructions
$ pip install python-hn
Usage
Search by date
from hn import search_by_date, PostType
# Search everything (stories, comments, etc)
search_by_date(q='lisp', author='pg', created_at__lt='2018-01-01')
# Search only stories
search_by_date(q='lisp', author='pg', tags=PostType('story'), created_at__lt='2018-01-01')
# Search stories *or* comments (see tags below)
search_by_date(
q='lisp', author='pg',
tags=(PostType('story') | PostType('comment')),
created_at__lt='2018-01-01')
Parameters received by search_by_date
:
q
(optional): The query string to search forauthor
(optional): Author's usernametags
: Tags to apply (see section Tags below)hits_per_page
(optional, default=1000): Number of posts to return per request.**filters
: Other filters to apply (date, points, number of comments). See section Filters below.
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:
# Stories by `pg` or comments by `patio11`
tags = (PostType('story') & Author('pg')) | (PostType('comment') & Author('patio11'))
# All the comments in the story `6902129`
tags = PostType('story') & StoryID('6902129')
The available tags are:
PostType
: with optionsstory
,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. Exampleponts__lt=100
lte
(<=
): Lower than or equals to. Exampleponts__lte=100
gt
(>
): Greater than. Examplecreated_at__gt='2018'
(created after 2018-01-01).gte
(>=
): Greater than or equals to. Examplenum_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]
Project details
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