transitions VS parsimonious

Compare transitions vs parsimonious and see what are their differences.

transitions

A lightweight, object-oriented finite state machine implementation in Python with many extensions (by pytransitions)

parsimonious

The fastest pure-Python PEG parser I can muster (by erikrose)
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transitions parsimonious
7 5
5,304 1,749
1.4% -
7.4 3.3
3 months ago 2 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.

transitions

Posts with mentions or reviews of transitions. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-09-26.

parsimonious

Posts with mentions or reviews of parsimonious. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-09-11.

What are some alternatives?

When comparing transitions and parsimonious you can also consider the following projects:

xstate-python - XState for Python

blinker - A fast Python in-process signal/event dispatching system.

Tenacity - Retrying library for Python

riprova - Versatile async-friendly retry package with multiple backoff strategies

Blinker Herald - The Blinker Herald includes helpers to easily emit signals using the excellent blinker library.

cppimport - Import C++ files directly from Python!

import_string

attrs - Python Classes Without Boilerplate

pluginbase - A simple but flexible plugin system for Python.

Tryton - Mirror of tryton

Throttler - 🔀⏳ Easy throttling with asyncio support

magenta - Magenta: Music and Art Generation with Machine Intelligence