pytest-parallex 0.1.9

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

pytest-parallex

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

pip install pytest-parallex
pytest --parallel=fork

The draw is the fixture model — one container for the run instead of one per worker, and fixtures you write the obvious way. It's also usually faster than xdist, because it forks warm instead of booting an interpreter per worker.

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: see the caveat below), process 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, Windows, or macOS

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

Is it faster than xdist?

Usually yes, though speed isn't the main reason to reach for it.

Both tools run your tests on N processes. The difference is startup: xdist spawns a fresh interpreter per worker and re-imports your suite in each; fork forks warm from a process that already imported everything, at about a millisecond per worker. So when both fill the machine, fork tends to come out ahead. Measured on 16 cores:

suite	xdist	parallex fork
4 modules, 64 quick tests	1.39s	0.33s	fork skips 16 interpreter boots
4 modules, 32 slow tests	2.62s	1.30s	~2x
1 module, 16 slow tests	2.02s	0.76s	the case fork used to lose

That last row used to be fork's worst: it dealt work by whole module, so a single big file ran on one worker while xdist spread it across all of them. Now a module whose tests use only function and session fixtures is dealt test-by-test, so it fills the machine like xdist does — minus the per-worker interpreter startup.

The honest limit that remains: a module that owns a module- or class-scoped fixture stays on one worker, because that is what keeps the fixture set up once for the module. Such a module can't use more than one core no matter what you pass to --parallel-workers. If one giant module with a module fixture dominates your runtime, xdist (which re-runs that fixture per worker) can still spread it wider — at the cost of running it N times.

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.

docs/benchmarks.md has the method, and the measurements that looked convincing and were wrong before the numbers above were re-taken.

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.

• a module that owns a module- or class-scoped fixture runs on one worker (that's what keeps the fixture set up once for it). Modules using only function and session fixtures are split across workers freely.

• fork is Linux-first. On Windows use --parallel=process. On macOS it works with a caveat: since High Sierra the Objective-C runtime kills a forked child that touches an Apple framework initialized before the fork — you see a "Python quit unexpectedly" dialog per worker, and the real message (objc[pid]: +[...] may have been in progress in another thread when fork() was called ... Crashing instead) only on stderr. Ordinary imports arm it (urllib's proxy lookup, ssl/keychain). It's why multiprocessing defaults to spawn on macOS since Python 3.8. Apple's escape hatch for the +initialize crash:

  export OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YES   # in your shell profile
  

  It must be set before Python starts, so the plugin can't set it for you — it warns on macOS when it's missing. It disarms only the +initialize check, not every framework-after-fork hazard, so on macOS --parallel=process is the dependable choice (confirmed working on a real suite); treat fork there as an experiment.

• 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