---
id: pluggy
version: "1.6.0"
license: MIT
license_treatment: permissive
maintenance: aging
---

# pluggy — plugin and hook calling mechanisms for python

License: permissive · Maintenance: aging · Popularity: top 100 on PyPI

## Install

pip install pluggy
uv add pluggy
poetry add pluggy

## Description

====================================================
pluggy - A minimalist production ready plugin system
====================================================

|pypi| |conda-forge| |versions| |github-actions| |gitter| |black| |codecov|

This is the core framework used by the `pytest`_, `tox`_, and `devpi`_ projects.

Please `read the docs`_ to learn more!

A definitive example
====================
.. code-block:: python

    import pluggy

    hookspec = pluggy.HookspecMarker("myproject")
    hookimpl = pluggy.HookimplMarker("myproject")


    class MySpec:
        """A hook specification namespace."""

        @hookspec
        def myhook(self, arg1, arg2):
            """My special little hook that you can customize."""


    class Plugin_1:
        """A hook implementation namespace."""

        @hookimpl
        def myhook(self, arg1, arg2):
            print("inside Plugin_1.myhook()")
            return arg1 + arg2


    class Plugin_2:
        """A 2nd hook implementation namespace."""

        @hookimpl
        def myhook(self, arg1, arg2):
            print("inside Plugin_2.myhook()")
            return arg1 - arg2


    # create a manager and add the spec
    pm =...

## AI interpretation — verify before relying

pluggy provides a minimalist plugin system framework that lets you define hook specifications and register plugin implementations to call them, used as the core framework for pytest, tox, and devpi.

Verdict: pluggy is a stable, zero-dependency plugin framework in the top 100 PyPI packages with no known vulnerabilities and permissive MIT licensing. Aging maintenance status (455 days since release) is typical for a mature, feature-complete library; its widespread adoption in pytest-dev projects provides confidence in production readiness.

[View on SkillFed](https://skillfed.io/packages/pluggy) · [View on PyPI](https://pypi.org/project/pluggy/)