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Parallel pytest where session fixtures run once for the whole run, not once per worker

Project description

pytest-parallex

Run pytest in parallel with scope="session" fixtures that actually run once.

pip install pytest-parallex
pytest --parallel=fork

This is not mainly a speed tool — see below. It's a simpler model: one container for the run instead of one per worker, and fixtures you can write the obvious way.

Why

xdist starts each worker as a separate interpreter, and each one runs its own session. So a scope="session" fixture runs once per worker. The xdist docs say this and suggest a FileLock workaround. You can't fix it in your conftest — there's no point in xdist's design where one process could build something and hand it to the others.

Forking gives you that point. --parallel=fork collects the tests, runs your session fixtures, and then forks. Each child inherits the already-built fixtures through copy-on-write and uses them without re-running anything.

Counting how many times the fixture body actually runs:

$ pytest -n 4                                  # pytest-xdist
8 passed        session fixture ran 4 times

$ pytest --parallel=fork --parallel-workers=4  # pytest-parallex
8 passed        session fixture ran 1 time
@pytest.fixture(scope="session")
def postgres():
    with PostgresContainer("postgres:16") as pg:   # runs once
        yield pg.get_connection_url()              # every worker gets this URL

One container, one login, one compiled asset per run, and no lockfile.

Modes

pytest --parallel=fork --parallel-workers=8
mode isolation scope="session" runs use when
fork process per worker, warm once, in the controller Linux/macOS, and the process is quiet at fork time
thread shared address space once tests are I/O-bound and don't mind sharing globals
async shared address space once same as thread, driven from an event loop
process fresh interpreter per worker once per worker tests mutate process-global state, or you're on Windows

--parallel-workers defaults to auto (CPU count).

Is it faster than xdist?

Usually not by much, and sometimes it's slower. Speed isn't the reason to use this.

Both tools run your tests on N processes, so the parallelism is the same. Measured on 16 cores:

suite xdist parallex fork
4 modules, 64 quick tests 1.64s 1.13s fork saves worker startup
4 modules, 32 slow tests 2.75s 4.32s fork is 1.6x slower
8 modules, 2s session fixture 3.16s 2.49s barely different

The one where fork loses is the important one to understand. xdist hands out individual tests; fork hands out whole modules. So if you have fewer modules than cores, fork can't fill the machine — 4 modules means 4 workers no matter what you pass to --parallel-workers.

And the row that looks like it should be a blowout isn't. xdist boots that 2-second fixture in all 8 workers, but it boots them at the same time, on cores that were idle anyway. 8 boots cost about 2 seconds of wall clock, not 16. Running it once saves you real CPU, but CPU you weren't using isn't time you get back. (Same for imports — that's why fork's startup saving is a flat ~1.5–2.3s that doesn't grow with your suite. On a 3s local run you notice it; on a 292s CI suite it's under 1%.)

So why use it?

Because scope="session" means session, and that gets you two things.

One copy of the resource, not N. Eight xdist workers boot eight Postgres containers. That's 8x the memory, 8x the disk, 8x the pressure on the Docker daemon — and if you're paying per seat, per API call, or per licence, 8x that too. Here it's one, and each worker gets a database on it. The wall clock barely moves; the resource bill does.

You write the fixture the obvious way. No FileLock, no shared tmpdir, no "am I worker gw0" branch. The fixture that says it runs once runs once.

If your session fixtures are cheap and your suite has plenty of modules, xdist is fine and you should keep using it.

docs/benchmarks.md has the method and three measurements that looked convincing and were wrong.

Fork safety

fork() only copies the calling thread. Whatever the other threads were holding — a lock, a half-written buffer, a connection mid-handshake — gets copied in that state and belongs to nobody in the child. This is the usual way forked children deadlock, and CPython 3.12 warns about it.

parallex checks first and refuses, naming what's in the way:

--parallel=fork requires a quiet process at fork time, but 1 non-main thread(s)
are running (Thread-1 (_monitor)). Move the offending setup into a fixture so it
runs after the fork, or use --parallel=process.

Logging QueueListener threads are the common case (litestar starts one at import, as does anything using QueueHandler), so those get stopped and restarted around the fork for you.

This puts one constraint on a session fixture: what it builds has to survive a fork. An address survives — a URL, a path, a port. A live connection, a thread, or an event loop doesn't. So keep the server in the controller and open connections per worker:

@pytest.fixture(scope="session")
def db_url():                     # controller: owns the server, survives the fork
    with PostgresContainer("postgres:16") as pg:
        yield pg.get_connection_url()

@pytest.fixture                   # per test: owns the connection, can't survive a fork
def db(db_url):
    conn = psycopg.connect(db_url)
    yield conn
    conn.close()

If a session fixture can't survive the fork, --parallex-no-session-scope leaves them all to the workers and you're back to xdist's behaviour.

Fixtures that differ per worker

Some session fixtures are supposed to differ between workers — usually one that gives each worker its own database. Running that in the controller breaks things: every worker gets the same database, and a per-test create_all/drop_all wipes the other workers' schemas while they're using them.

A fixture that asks for worker_id, directly or through another fixture, is per-worker and stays in the workers. Everything else scope-session runs once in the controller. There's no new syntax for this because suites already write it:

@pytest.fixture(scope="session")
def postgres_server():                          # controller: one container
    with PostgresContainer("postgres:16") as pg:
        yield pg.get_connection_url()

@pytest.fixture(scope="session")
def database_url(worker_id, postgres_server):   # per worker: asks for worker_id
    url = f"{postgres_server}/test_{worker_id}"
    create_database(url)
    yield url
    drop_database(url)

One container for the run, one database per worker on it. Under xdist you'd need the filelock recipe to approximate this.

worker_id is xdist's fixture name and that's on purpose — it's what lets existing suites work unchanged. If you have both plugins installed, --parallel takes the name so you get a real per-worker id, and a plain pytest -n 4 still gets xdist's. parallex_worker_id is an alias if you'd rather be explicit; it marks a fixture per-worker the same way.

Fixtures

fixture gives you
worker_id 'f0', 'w1', 'a2'… or 'main'. Asking for it marks a fixture per-worker
parallex_worker_id the same value, under a name xdist can't shadow
parallex_mode the active mode, or None
parallex_setup_data whatever pytest_parallex_setup returned

Hooks

# conftest.py
def pytest_parallex_setup(config):
    """Runs once in the controller, before any worker starts. Pre-fork, so no I/O handles."""
    return {"token": build_expensive_thing()}

def pytest_parallex_teardown(config, data):
    """Runs once in the controller, after every worker has finished."""

def pytest_parallex_auto_num_workers(config):
    """Override --parallel-workers=auto. Defaults to os.cpu_count()."""
    return 8

Limitations

  • --maxfail won't cut a fork run short. Workers finish the group they claimed and the controller replays the reports afterwards, so the count is right but the run isn't stopped early.
  • fork splits work by module, so a suite in a single file uses one worker regardless of --parallel-workers.
  • fork is Linux and macOS only. On Windows use --parallel=process.
  • thread and async don't get around the GIL. They help suites that wait, not suites that compute.
  • Needs pytest 8.1 or newer. (8.0 changed the signature of an internal we rely on.)

Developing

uv sync                # toolchain
make install-hooks     # one-time, after cloning
make check             # lint + typecheck + test, same as CI

Releasing

The version in pyproject.toml is the source of truth, and releases are automated:

  1. The pre-commit hook bumps the patch version when a commit touches src/ (run make install-hooks once after cloning). Doc, test and config commits don't bump. For a minor or major release, do it deliberately: make bump TYPE=minor.
  2. version-guard enforces the same rule in CI, so --no-verify and unhooked clones don't get around it.
  3. :release runs on a green main pipeline and publishes via OIDC trusted publishing if the version isn't on PyPI yet. Merging a version bump to main is the release — no tag, no second pipeline.

License

MIT

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