Skip to main content

pytest xdist plugin for distributed testing and loop-on-failing modes

Project description

PyPI version https://img.shields.io/conda/vn/conda-forge/pytest-xdist.svg Python versions Travis CI build status AppVeyor build status https://img.shields.io/badge/code%20style-black-000000.svg

xdist: pytest distributed testing plugin

The pytest-xdist plugin extends pytest with some unique test execution modes:

  • test run parallelization: if you have multiple CPUs or hosts you can use those for a combined test run. This allows to speed up development or to use special resources of remote machines.

  • --looponfail: run your tests repeatedly in a subprocess. After each run pytest waits until a file in your project changes and then re-runs the previously failing tests. This is repeated until all tests pass after which again a full run is performed.

  • Multi-Platform coverage: you can specify different Python interpreters or different platforms and run tests in parallel on all of them.

Before running tests remotely, pytest efficiently “rsyncs” your program source code to the remote place. All test results are reported back and displayed to your local terminal. You may specify different Python versions and interpreters.

If you would like to know how pytest-xdist works under the covers, checkout OVERVIEW.

Installation

Install the plugin with:

pip install pytest-xdist

or use the package in develop/in-place mode with a checkout of the pytest-xdist repository

pip install --editable .

Speed up test runs by sending tests to multiple CPUs

To send tests to multiple CPUs, use the -n (or -numprocesses) option:

pytest -n NUMCPUS

Pass -n auto to use as many processes as your computer has CPU cores. This can lead to considerable speed ups, especially if your test suite takes a noticeable amount of time.

If a test crashes a worker, pytest-xdist will automatically restart that worker and report the test’s failure. You can use the --max-worker-restart option to limit the number of worker restarts that are allowed, or disable restarting altogether using --max-worker-restart 0.

By default, using --numprocesses will send pending tests to any worker that is available, without any guaranteed order. You can change the test distribution algorithm this with the --dist option. It takes these values:

  • --dist no: The default algorithm, distributing one test at a time.

  • --dist loadscope: Tests are grouped by module for test functions and by class for test methods. Groups are distributed to available workers as whole units. This guarantees that all tests in a group run in the same process. This can be useful if you have expensive module-level or class-level fixtures. Grouping by class takes priority over grouping by module.

  • --dist loadfile: Tests are grouped by their containing file. Groups are distributed to available workers as whole units. This guarantees that all tests in a file run in the same worker.

Making session-scoped fixtures execute only once

pytest-xdist is designed so that each worker process will perform its own collection and execute a subset of all tests. This means that tests in different processes requesting a high-level scoped fixture (for example session) will execute the fixture code more than once, which breaks expectations and might be undesired in certain situations.

While pytest-xdist does not have a builtin support for ensuring a session-scoped fixture is executed exactly once, this can be achieved by using a lock file for inter-process communication.

The example below needs to execute the fixture session_data only once (because it is resource intensive, or needs to execute only once to define configuration options, etc), so it makes use of a FileLock to produce the fixture data only once when the first process requests the fixture, while the other processes will then read the data from a file.

Here is the code:

import json

import pytest
from filelock import FileLock


@pytest.fixture(scope="session")
def session_data(tmp_path_factory, worker_id):
    if not worker_id:
        # not executing in with multiple workers, just produce the data and let
        # pytest's fixture caching do its job
        return produce_expensive_data()

    # get the temp directory shared by all workers
    root_tmp_dir = tmp_path_factory.getbasetemp().parent

    fn = root_tmp_dir / "data.json"
    with FileLock(str(fn) + ".lock"):
        if fn.is_file():
            data = json.loads(fn.read_text())
        else:
            data = produce_expensive_data()
            fn.write_text(json.dumps(data))
    return data

The example above can also be use in cases a fixture needs to execute exactly once per test session, like initializing a database service and populating initial tables.

This technique might not work for every case, but should be a starting point for many situations where executing a high-scope fixture exactly once is important.

Running tests in a Python subprocess

To instantiate a python3.5 subprocess and send tests to it, you may type:

pytest -d --tx popen//python=python3.5

This will start a subprocess which is run with the python3.5 Python interpreter, found in your system binary lookup path.

If you prefix the –tx option value like this:

--tx 3*popen//python=python3.5

then three subprocesses would be created and tests will be load-balanced across these three processes.

Running tests in a boxed subprocess

This functionality has been moved to the pytest-forked plugin, but the --boxed option is still kept for backward compatibility.

Sending tests to remote SSH accounts

Suppose you have a package mypkg which contains some tests that you can successfully run locally. And you have a ssh-reachable machine myhost. Then you can ad-hoc distribute your tests by typing:

pytest -d --tx ssh=myhostpopen --rsyncdir mypkg mypkg

This will synchronize your mypkg package directory to a remote ssh account and then locally collect tests and send them to remote places for execution.

You can specify multiple --rsyncdir directories to be sent to the remote side.

You can specify multiple --rsyncignore glob patterns to be ignored when file are sent to the remote side. There are also internal ignores: .*, *.pyc, *.pyo, *~ Those you cannot override using rsyncignore command-line or ini-file option(s).

Sending tests to remote Socket Servers

Download the single-module socketserver.py Python program and run it like this:

python socketserver.py

It will tell you that it starts listening on the default port. You can now on your home machine specify this new socket host with something like this:

pytest -d --tx socket=192.168.1.102:8888 --rsyncdir mypkg mypkg

Running tests on many platforms at once

The basic command to run tests on multiple platforms is:

pytest --dist=each --tx=spec1 --tx=spec2

If you specify a windows host, an OSX host and a Linux environment this command will send each tests to all platforms - and report back failures from all platforms at once. The specifications strings use the xspec syntax.

Identifying the worker process during a test

New in version 1.15.

If you need to determine the identity of a worker process in a test or fixture, you may use the worker_id fixture to do so:

@pytest.fixture()
def user_account(worker_id):
    """ use a different account in each xdist worker """
    return "account_%s" % worker_id

When xdist is disabled (running with -n0 for example), then worker_id will return "master".

Additionally, worker processes have the following environment variables defined:

  • PYTEST_XDIST_WORKER: the name of the worker, e.g., "gw2".

  • PYTEST_XDIST_WORKER_COUNT: the total number of workers in this session, e.g., "4" when -n 4 is given in the command-line.

The information about the worker_id in a test is stored in the TestReport as well, under the worker_id attribute.

Uniquely identifying the current test run

New in version 1.32.

If you need to globally distinguish one test run from others in your workers, you can use the testrun_uid fixture. For instance, let’s say you wanted to create a separate database for each test run:

import pytest
from posix_ipc import Semaphore, O_CREAT

@pytest.fixture(scope="session", autouse=True)
def create_unique_database(testrun_uid):
    """ create a unique database for this particular test run """
    database_url = f"psql://myapp-{testrun_uid}"

    with Semaphore(f"/{testrun_uid}-lock", flags=O_CREAT, initial_value=1):
        if not database_exists(database_url):
            create_database(database_url)

@pytest.fixture()
def db(testrun_uid):
    """ retrieve unique database """
    database_url = f"psql://myapp-{testrun_uid}"
    return database_get_instance(database_url)

Additionally, during a test run, the following environment variable is defined:

  • PYTEST_XDIST_TESTRUNUID: the unique id of the test run.

Accessing sys.argv from the master node in workers

To access the sys.argv passed to the command-line of the master node, use request.config.workerinput["mainargv"].

Specifying test exec environments in an ini file

You can use pytest’s ini file configuration to avoid typing common options. You can for example make running with three subprocesses your default like this:

[pytest]
addopts = -n3

You can also add default environments like this:

[pytest]
addopts = --tx ssh=myhost//python=python3.5 --tx ssh=myhost//python=python3.6

and then just type:

pytest --dist=each

to run tests in each of the environments.

Specifying “rsync” dirs in an ini-file

In a tox.ini or setup.cfg file in your root project directory you may specify directories to include or to exclude in synchronisation:

[pytest]
rsyncdirs = . mypkg helperpkg
rsyncignore = .hg

These directory specifications are relative to the directory where the configuration file was found.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pytest-xdist-1.34.0.tar.gz (66.2 kB view hashes)

Uploaded Source

Built Distribution

pytest_xdist-1.34.0-py2.py3-none-any.whl (36.8 kB view hashes)

Uploaded Python 2 Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page