pytest-paraflow 0.1.0

Deterministic pytest test sharding across CI machines

pytest-paraflow

pytest-paraflow is a pytest plugin for deterministic test sharding across machines.

Features

• Deterministic sharding by test identity (stable hash-based assignment).
• Group-based sharding via markers so related tests stay together.
• Dynamic shard count derived from total test count and desired shard size.

Install

uv add pytest-paraflow

Usage

Enable sharding by passing --paraflow-shard-id and either --paraflow-num-shards or --paraflow-target-shard-size.

Static shard count

pytest --paraflow-shard-id=0 --paraflow-num-shards=4

Dynamic shard count

pytest --paraflow-shard-id=1 --paraflow-target-shard-size=200

For N collected tests, shard count is calculated as ceil(N / target_shard_size).

Group tests by marker

import pytest

@pytest.mark.paraflow_group("db")
def test_a():
    ...

@pytest.mark.paraflow_group("db")
def test_b():
    ...

pytest \
  --paraflow-shard-id=0 \
  --paraflow-num-shards=3 \
  --paraflow-group-marker=paraflow_group

Marker behavior:

• Tests with the same marker value are assigned to the same shard.
• @pytest.mark.paraflow_group(...) is only used when --paraflow-group-marker=paraflow_group is provided.
• Without --paraflow-group-marker, paraflow falls back to per-test (nodeid) sharding.
• --paraflow-group-marker=smoke with @pytest.mark.smoke groups all smoke tests together (single group key).
• --paraflow-group-marker=smoke with @pytest.mark.smoke("db") groups by value (for example db, api).
• --paraflow-group-marker is repeatable. If multiple configured markers exist on one test, the first configured marker wins.

CLI options

• --paraflow-shard-id: current shard index (zero-based).
• --paraflow-num-shards: total shard count.
• --paraflow-target-shard-size: desired tests per shard for dynamic sizing.
• --paraflow-group-marker: marker name used for grouping (repeatable).

Configuration defaults

CLI option defaults are loaded from Settings (src/pytest_paraflow/config/settings.py). You can configure them via environment variables:

• PYTEST_PARAFLOW__SHARD_ID
• PYTEST_PARAFLOW__NUM_SHARDS
• PYTEST_PARAFLOW__TARGET_SHARD_SIZE
• PYTEST_PARAFLOW__GROUP_MARKER (JSON array, for example ["paraflow_group", "smoke"])

CLI values always override environment defaults.

GitHub Actions (matrix sharding)

Example workflow template: examples/paraflow-matrix-example.yml. Copy it into .github/workflows/ in your repository to enable CI.

It runs pytest in 4 shards via matrix (shard_id: [0, 1, 2, 3]) and limits concurrent shard jobs with:

• strategy.max-parallel: 2
• --paraflow-shard-id=${{ matrix.shard_id }}
• --paraflow-num-shards=4

Validation rules

• --paraflow-shard-id is required whenever sharding is enabled.
• One of --paraflow-num-shards or --paraflow-target-shard-size is required.
• --paraflow-shard-id must be in [0, total_shards - 1].