pyparsing VS binarytree

Compare pyparsing vs binarytree and see what are their differences.

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pyparsing binarytree
13 1
2,086 1,801
1.6% -
8.5 0.0
20 days ago 7 months 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.

pyparsing

Posts with mentions or reviews of pyparsing. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-08-24.

binarytree

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

What are some alternatives?

When comparing pyparsing and binarytree you can also consider the following projects:

parsita - The easiest way to parse text in Python

uwsgi-nginx-flask-docker - Docker image with uWSGI and Nginx for Flask applications in Python running in a single container.

iregex - A way to write regex with objects instead of strings.

python-xlib - XLib in pure Python (Py2/Py3 compatible)

attoparsec - A fast Haskell library for parsing ByteStrings

Grok-Introduction-to-Programming-Python - Answers for the Introduction to Programming course on Grok Learning AUS/NZ. It is advised that you only copy if you are stuck and not cheat.

parser - String parser combinators

Scrython - A python wrapper for the Scryfall API

sly - Sly Lex Yacc

phptree - An implementation of tree data structure

Lark - Lark is a parsing toolkit for Python, built with a focus on ergonomics, performance and modularity.

Data-Structures-and-Algorithms-Python - All the essential resources and template code needed to understand and practice data structures and algorithms in python with few small projects to demonstrate their practical application.