pants VS cloudpickle

Compare pants vs cloudpickle and see what are their differences.

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pants cloudpickle
35 5
3,098 1,576
2.5% 1.9%
9.8 6.0
3 days ago 20 days ago
Python Python
Apache License 2.0 GNU General Public License v3.0 or later
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.

pants

Posts with mentions or reviews of pants. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-04-02.

cloudpickle

Posts with mentions or reviews of cloudpickle. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-07-29.
  • No-GIL mode coming for Python
    7 projects | news.ycombinator.com | 29 Jul 2023
    I believe you just pass objects instead, like you would in OOP, and take the hit of pickling and unpickling them every time.

    If you really want to pass lambdas, you can use a third party library to pickle them

    https://github.com/cloudpipe/cloudpickle

    Yes, this is not great.

  • Is it possible pickle a function with its dependencies?
    4 projects | /r/Python | 6 May 2023
    That was my understanding as well but then I found this package -- cloudpickle which seems to serialize both data and functionality?
  • Issue with sklearn
    2 projects | /r/learnpython | 8 Apr 2022
  • I'm learning monads by implementing IO in different languages
    3 projects | /r/functionalprogramming | 18 Nov 2021
    It used in production for several months now. We use it to train data science models. The main goal was to make multiprocessing code easier. It actually works great with multiprocessing, especially if you use a library able to serialize lambda functions such as https://github.com/cloudpipe/cloudpickle . I have yet to write a tutorial on how to use multiprocessing and cloudpickle to distribute work to all the worker processes. Thanks for letting me know about pfun. I've never heard of it. Having a look at its documentation, our goals seem to be very close. The features I wanted above all where:

What are some alternatives?

When comparing pants and cloudpickle you can also consider the following projects:

Bazel - a fast, scalable, multi-language and extensible build system

extrainterpreters - Utilities for using Python's PEP 554 subinterpreters

megalinter - 🦙 MegaLinter analyzes 50 languages, 22 formats, 21 tooling formats, excessive copy-pastes, spelling mistakes and security issues in your repository sources with a GitHub Action, other CI tools or locally.

pex - A tool for generating .pex (Python EXecutable) files, lock files and venvs.

please - High-performance extensible build system for reproducible multi-language builds.

raffiot.py - Robust And Fast Functional IO Toolkit

pyflow - An installation and dependency system for Python

scala-cli - Scala CLI is a command-line tool to interact with the Scala language. It lets you compile, run, test, and package your Scala code (and more!)

pyupgrade - A tool (and pre-commit hook) to automatically upgrade syntax for newer versions of the language.

nix - Nix, the purely functional package manager

Buck - A fast build system that encourages the creation of small, reusable modules over a variety of platforms and languages.

problems - Discussions about problems with the current C Api