Writing plugins

It is easy to implement local conftest plugins for your own project or pip-installable plugins that can be used throughout many projects, including third party projects. Please refer to Installing and Using plugins if you only want to use but not write plugins.

A plugin contains one or multiple hook functions. Writing hooks explains the basics and details of how you can write a hook function yourself. pytest implements all aspects of configuration, collection, running and reporting by calling well specified hooks of the following plugins:

In principle, each hook call is a 1:N Python function call where N is the number of registered implementation functions for a given specification. All specifications and implementations follow the pytest_ prefix naming convention, making them easy to distinguish and find.

Plugin discovery order at tool startup

pytest loads plugin modules at tool startup in the following way:

  • by loading all builtin plugins

  • by loading all plugins registered through setuptools entry points.

  • by pre-scanning the command line for the -p name option and loading the specified plugin before actual command line parsing.

  • by loading all conftest.py files as inferred by the command line invocation:

    • if no test paths are specified use current dir as a test path
    • if exists, load conftest.py and test*/conftest.py relative to the directory part of the first test path.

    Note that pytest does not find conftest.py files in deeper nested sub directories at tool startup. It is usually a good idea to keep your conftest.py file in the top level test or project root directory.

  • by recursively loading all plugins specified by the pytest_plugins variable in conftest.py files

conftest.py: local per-directory plugins

Local conftest.py plugins contain directory-specific hook implementations. Hook Session and test running activities will invoke all hooks defined in conftest.py files closer to the root of the filesystem. Example of implementing the pytest_runtest_setup hook so that is called for tests in the a sub directory but not for other directories:

    def pytest_runtest_setup(item):
        # called for running each test in 'a' directory
        print("setting up", item)

    def test_sub():

    def test_flat():

Here is how you might run it:

pytest test_flat.py --capture=no  # will not show "setting up"
pytest a/test_sub.py --capture=no  # will show "setting up"


If you have conftest.py files which do not reside in a python package directory (i.e. one containing an __init__.py) then “import conftest” can be ambiguous because there might be other conftest.py files as well on your PYTHONPATH or sys.path. It is thus good practice for projects to either put conftest.py under a package scope or to never import anything from a conftest.py file.

See also: pytest import mechanisms and sys.path/PYTHONPATH.

Writing your own plugin

If you want to write a plugin, there are many real-life examples you can copy from:

All of these plugins implement hooks and/or fixtures to extend and add functionality.


Make sure to check out the excellent cookiecutter-pytest-plugin project, which is a cookiecutter template for authoring plugins.

The template provides an excellent starting point with a working plugin, tests running with tox, a comprehensive README file as well as a pre-configured entry-point.

Also consider contributing your plugin to pytest-dev once it has some happy users other than yourself.

Making your plugin installable by others

If you want to make your plugin externally available, you may define a so-called entry point for your distribution so that pytest finds your plugin module. Entry points are a feature that is provided by setuptools. pytest looks up the pytest11 entrypoint to discover its plugins and you can thus make your plugin available by defining it in your setuptools-invocation:

# sample ./setup.py file
from setuptools import setup

    # the following makes a plugin available to pytest
    entry_points={"pytest11": ["name_of_plugin = myproject.pluginmodule"]},
    # custom PyPI classifier for pytest plugins
    classifiers=["Framework :: Pytest"],

If a package is installed this way, pytest will load myproject.pluginmodule as a plugin which can define hooks.


Make sure to include Framework :: Pytest in your list of PyPI classifiers to make it easy for users to find your plugin.

Assertion Rewriting

One of the main features of pytest is the use of plain assert statements and the detailed introspection of expressions upon assertion failures. This is provided by “assertion rewriting” which modifies the parsed AST before it gets compiled to bytecode. This is done via a PEP 302 import hook which gets installed early on when pytest starts up and will perform this rewriting when modules get imported. However since we do not want to test different bytecode then you will run in production this hook only rewrites test modules themselves as well as any modules which are part of plugins. Any other imported module will not be rewritten and normal assertion behaviour will happen.

If you have assertion helpers in other modules where you would need assertion rewriting to be enabled you need to ask pytest explicitly to rewrite this module before it gets imported.


Register one or more module names to be rewritten on import.

This function will make sure that this module or all modules inside the package will get their assert statements rewritten. Thus you should make sure to call this before the module is actually imported, usually in your __init__.py if you are a plugin using a package.

Raises:TypeError – if the given module names are not strings.

This is especially important when you write a pytest plugin which is created using a package. The import hook only treats conftest.py files and any modules which are listed in the pytest11 entrypoint as plugins. As an example consider the following package:


With the following typical setup.py extract:

setup(..., entry_points={"pytest11": ["foo = pytest_foo.plugin"]}, ...)

In this case only pytest_foo/plugin.py will be rewritten. If the helper module also contains assert statements which need to be rewritten it needs to be marked as such, before it gets imported. This is easiest by marking it for rewriting inside the __init__.py module, which will always be imported first when a module inside a package is imported. This way plugin.py can still import helper.py normally. The contents of pytest_foo/__init__.py will then need to look like this:

import pytest


Requiring/Loading plugins in a test module or conftest file

You can require plugins in a test module or a conftest.py file like this:

pytest_plugins = ["name1", "name2"]

When the test module or conftest plugin is loaded the specified plugins will be loaded as well. Any module can be blessed as a plugin, including internal application modules:

pytest_plugins = "myapp.testsupport.myplugin"

pytest_plugins variables are processed recursively, so note that in the example above if myapp.testsupport.myplugin also declares pytest_plugins, the contents of the variable will also be loaded as plugins, and so on.


Requiring plugins using a pytest_plugins variable in non-root conftest.py files is deprecated.

This is important because conftest.py files implement per-directory hook implementations, but once a plugin is imported, it will affect the entire directory tree. In order to avoid confusion, defining pytest_plugins in any conftest.py file which is not located in the tests root directory is deprecated, and will raise a warning.

This mechanism makes it easy to share fixtures within applications or even external applications without the need to create external plugins using the setuptools’s entry point technique.

Plugins imported by pytest_plugins will also automatically be marked for assertion rewriting (see pytest.register_assert_rewrite()). However for this to have any effect the module must not be imported already; if it was already imported at the time the pytest_plugins statement is processed, a warning will result and assertions inside the plugin will not be rewritten. To fix this you can either call pytest.register_assert_rewrite() yourself before the module is imported, or you can arrange the code to delay the importing until after the plugin is registered.

Accessing another plugin by name

If a plugin wants to collaborate with code from another plugin it can obtain a reference through the plugin manager like this:

plugin = config.pluginmanager.get_plugin("name_of_plugin")

If you want to look at the names of existing plugins, use the --trace-config option.

Registering custom markers

If your plugin uses any markers, you should register them so that they appear in pytest’s help text and do not cause spurious warnings. For example, the following plugin would register cool_marker and mark_with for all users:

def pytest_configure(config):
    config.addinivalue_line("markers", "cool_marker: this one is for cool tests.")
        "markers", "mark_with(arg, arg2): this marker takes arguments."

Testing plugins

pytest comes with a plugin named pytester that helps you write tests for your plugin code. The plugin is disabled by default, so you will have to enable it before you can use it.

You can do so by adding the following line to a conftest.py file in your testing directory:

# content of conftest.py

pytest_plugins = ["pytester"]

Alternatively you can invoke pytest with the -p pytester command line option.

This will allow you to use the testdir fixture for testing your plugin code.

Let’s demonstrate what you can do with the plugin with an example. Imagine we developed a plugin that provides a fixture hello which yields a function and we can invoke this function with one optional parameter. It will return a string value of Hello World! if we do not supply a value or Hello {value}! if we do supply a string value.

# -*- coding: utf-8 -*-

import pytest

def pytest_addoption(parser):
    group = parser.getgroup("helloworld")
        help='Default "name" for hello().',

def hello(request):
    name = request.config.getoption("name")

    def _hello(name=None):
        if not name:
            name = request.config.getoption("name")
        return "Hello {name}!".format(name=name)

    return _hello

Now the testdir fixture provides a convenient API for creating temporary conftest.py files and test files. It also allows us to run the tests and return a result object, with which we can assert the tests’ outcomes.

def test_hello(testdir):
    """Make sure that our plugin works."""

    # create a temporary conftest.py file
        import pytest

        def name(request):
            return request.param

    # create a temporary pytest test file
        def test_hello_default(hello):
            assert hello() == "Hello World!"

        def test_hello_name(hello, name):
            assert hello(name) == "Hello {0}!".format(name)

    # run all tests with pytest
    result = testdir.runpytest()

    # check that all 4 tests passed

additionally it is possible to copy examples for an example folder before running pytest on it

# content of pytest.ini
pytester_example_dir = .
# content of test_example.py

def test_plugin(testdir):
    testdir.runpytest("-k", "test_example")

def test_example():
$ pytest
=========================== test session starts ============================
platform linux -- Python 3.x.y, pytest-4.x.y, py-1.x.y, pluggy-0.x.y
cachedir: $PYTHON_PREFIX/.pytest_cache
rootdir: $REGENDOC_TMPDIR, inifile: pytest.ini
collected 2 items

test_example.py ..                                                   [100%]

============================= warnings summary =============================
  $REGENDOC_TMPDIR/test_example.py:4: PytestExperimentalApiWarning: testdir.copy_example is an experimental api that may change over time

-- Docs: https://docs.pytest.org/en/latest/warnings.html
=================== 2 passed, 1 warnings in 0.12 seconds ===================

For more information about the result object that runpytest() returns, and the methods that it provides please check out the RunResult documentation.

Writing hook functions

hook function validation and execution

pytest calls hook functions from registered plugins for any given hook specification. Let’s look at a typical hook function for the pytest_collection_modifyitems(session, config, items) hook which pytest calls after collection of all test items is completed.

When we implement a pytest_collection_modifyitems function in our plugin pytest will during registration verify that you use argument names which match the specification and bail out if not.

Let’s look at a possible implementation:

def pytest_collection_modifyitems(config, items):
    # called after collection is completed
    # you can modify the ``items`` list

Here, pytest will pass in config (the pytest config object) and items (the list of collected test items) but will not pass in the session argument because we didn’t list it in the function signature. This dynamic “pruning” of arguments allows pytest to be “future-compatible”: we can introduce new hook named parameters without breaking the signatures of existing hook implementations. It is one of the reasons for the general long-lived compatibility of pytest plugins.

Note that hook functions other than pytest_runtest_* are not allowed to raise exceptions. Doing so will break the pytest run.

firstresult: stop at first non-None result

Most calls to pytest hooks result in a list of results which contains all non-None results of the called hook functions.

Some hook specifications use the firstresult=True option so that the hook call only executes until the first of N registered functions returns a non-None result which is then taken as result of the overall hook call. The remaining hook functions will not be called in this case.

hookwrapper: executing around other hooks

pytest plugins can implement hook wrappers which wrap the execution of other hook implementations. A hook wrapper is a generator function which yields exactly once. When pytest invokes hooks it first executes hook wrappers and passes the same arguments as to the regular hooks.

At the yield point of the hook wrapper pytest will execute the next hook implementations and return their result to the yield point in the form of a Result instance which encapsulates a result or exception info. The yield point itself will thus typically not raise exceptions (unless there are bugs).

Here is an example definition of a hook wrapper:

import pytest

def pytest_pyfunc_call(pyfuncitem):

    outcome = yield
    # outcome.excinfo may be None or a (cls, val, tb) tuple

    res = outcome.get_result()  # will raise if outcome was exception


    outcome.force_result(new_res)  # to override the return value to the plugin system

Note that hook wrappers don’t return results themselves, they merely perform tracing or other side effects around the actual hook implementations. If the result of the underlying hook is a mutable object, they may modify that result but it’s probably better to avoid it.

For more information, consult the pluggy documentation.

Hook function ordering / call example

For any given hook specification there may be more than one implementation and we thus generally view hook execution as a 1:N function call where N is the number of registered functions. There are ways to influence if a hook implementation comes before or after others, i.e. the position in the N-sized list of functions:

# Plugin 1
def pytest_collection_modifyitems(items):
    # will execute as early as possible

# Plugin 2
def pytest_collection_modifyitems(items):
    # will execute as late as possible

# Plugin 3
def pytest_collection_modifyitems(items):
    # will execute even before the tryfirst one above!
    outcome = yield
    # will execute after all non-hookwrappers executed

Here is the order of execution:

  1. Plugin3’s pytest_collection_modifyitems called until the yield point because it is a hook wrapper.
  2. Plugin1’s pytest_collection_modifyitems is called because it is marked with tryfirst=True.
  3. Plugin2’s pytest_collection_modifyitems is called because it is marked with trylast=True (but even without this mark it would come after Plugin1).
  4. Plugin3’s pytest_collection_modifyitems then executing the code after the yield point. The yield receives a Result instance which encapsulates the result from calling the non-wrappers. Wrappers shall not modify the result.

It’s possible to use tryfirst and trylast also in conjunction with hookwrapper=True in which case it will influence the ordering of hookwrappers among each other.

Declaring new hooks

Plugins and conftest.py files may declare new hooks that can then be implemented by other plugins in order to alter behaviour or interact with the new plugin:


called at plugin registration time to allow adding new hooks via a call to pluginmanager.add_hookspecs(module_or_class, prefix).

Parameters:pluginmanager (_pytest.config.PytestPluginManager) – pytest plugin manager


This hook is incompatible with hookwrapper=True.

Hooks are usually declared as do-nothing functions that contain only documentation describing when the hook will be called and what return values are expected.

For an example, see newhooks.py from xdist.

Optionally using hooks from 3rd party plugins

Using new hooks from plugins as explained above might be a little tricky because of the standard validation mechanism: if you depend on a plugin that is not installed, validation will fail and the error message will not make much sense to your users.

One approach is to defer the hook implementation to a new plugin instead of declaring the hook functions directly in your plugin module, for example:

# contents of myplugin.py

class DeferPlugin(object):
    """Simple plugin to defer pytest-xdist hook functions."""

    def pytest_testnodedown(self, node, error):
        """standard xdist hook function.

def pytest_configure(config):
    if config.pluginmanager.hasplugin("xdist"):

This has the added benefit of allowing you to conditionally install hooks depending on which plugins are installed.