taxopedia VS Wikipedia-Article-Scraper

Compare taxopedia vs Wikipedia-Article-Scraper 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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taxopedia Wikipedia-Article-Scraper
4 -
7 17
- -
0.0 0.0
over 2 years ago over 1 year ago
Python Python
MIT License MIT License
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.

taxopedia

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

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.

What are some alternatives?

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

graphlan - High-quality circular representations of taxonomic and phylogenetic trees

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

kraken-biom - Create BIOM-format tables (http://biom-format.org) from Kraken output (http://ccb.jhu.edu/software/kraken/, https://github.com/DerrickWood/kraken).

ielex-data-and-tree - Data and scripts for producing a Baysian phylogenetic tree sample of for the Indo-European family which is "good enough", using data from IELex (Dunn et al. 2011).