Wikipedia-Article-Scraper VS SerializeThis

Compare Wikipedia-Article-Scraper vs SerializeThis and see what are their differences.

Wikipedia-Article-Scraper

A complete Python text analytics package that allows users to search for a Wikipedia article, scrape it, conduct basic text analytics and integrate it to a data pipeline without writing excessive code. (by kohjiaxuan)
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Wikipedia-Article-Scraper SerializeThis
- 1
17 0
- -
0.0 10.0
over 1 year ago over 1 year ago
Python Python
MIT License GNU General Public License v3.0 only
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Wikipedia-Article-Scraper

Posts with mentions or reviews of Wikipedia-Article-Scraper. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning Wikipedia-Article-Scraper yet.
Tracking mentions began in Dec 2020.

SerializeThis

Posts with mentions or reviews of SerializeThis. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing Wikipedia-Article-Scraper and SerializeThis you can also consider the following projects:

tf-idf - Term Frequency-Inverse Document Frequency from Scratch

twscrape - 2024! Twitter API scrapper with authorization support. Allows you to scrape search results, User's profiles (followers/following), Tweets (favoriters/retweeters) and more.

Scweet - A simple and unlimited twitter scraper : scrape tweets, likes, retweets, following, followers, user info, images...

automation-samples - Using clicknium to automate platforms like Linkedin, twitter, Slack, Youtube in python.