pytest-shard-cloudc 1.0.1

Shard tests to support parallelism across multiple machines.

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pytest-shard-cloudc

This is a fork of AdamGleave/pytest-shard by Cloud Chen. Modifications include: Allure report integration, multi-shard result merging, nox-based tooling, and modernized packaging with pyproject.toml.

pytest-shard splits your test suite across multiple machines or CI workers at individual test-case granularity. By default it sorts tests by node ID and assigns them round-robin across shards, so parallelism works even when all tests live in a single file or a single parameterized method.

Install from PyPI with pip install pytest-shard-cloudc.

How It Works

See Sharding Modes for separate diagrams that explain how roundrobin, hash, and duration assign tests to shards.

What it does

Capability	Description
Round-robin sharding (default)	Sorts tests by node ID and interleaves across shards, guaranteeing shard counts differ by at most 1
Hash-based sharding	Assigns each test deterministically via SHA-256(node_id) % N — per-test stable even as the suite grows
Duration-based sharding	Greedy bin-packing using a .test_durations file (compatible with pytest-split) to minimise the longest shard
Zero configuration	Just add --shard-id and --num-shards — no config files, no test ordering required
Any granularity	Splits at the individual test level, not at the file or class level
CI-agnostic	Works with GitHub Actions, CircleCI, Travis CI, or any system that runs parallel jobs
Allure integration	Collect results per shard, merge them, and view a unified Timeline report

Documentation

Guide	Description
Sharding Modes	Detailed behavior of roundrobin, hash, and duration, including .test_durations, verbose shard reports, and mode selection guidance.
Demo Sessions	How contributors can run the bundled demo suites locally with nox.
Allure Report Integration	How to collect Allure results across shards, merge them into one report, run shards in parallel locally, and integrate with GitHub Actions / CircleCI. Includes a worked example with 30 tests across 3 parallel shards and a Timeline screenshot.

Quick start

Installation

pip install pytest-shard-cloudc

Split tests across N machines

# Machine 0
pytest --shard-id=0 --num-shards=3

# Machine 1
pytest --shard-id=1 --num-shards=3

# Machine 2
pytest --shard-id=2 --num-shards=3

Each machine runs roughly 1/N of the test suite. Together they cover 100% of tests.

Choose a sharding mode

# Round-robin (default) — guaranteed count balance
pytest --shard-id=0 --num-shards=3 --shard-mode=roundrobin

# Hash — per-test stable assignment, stateless
pytest --shard-id=0 --num-shards=3 --shard-mode=hash

# Duration — bin-packing by recorded test times, minimises longest shard
pytest --shard-id=0 --num-shards=3 --shard-mode=duration --durations-path=.test_durations

See Sharding Modes for detailed trade-offs, .test_durations generation, and mode selection guidance.

GitHub Actions example

jobs:
  test:
    runs-on: ubuntu-latest
    strategy:
      matrix:
        shard_id: [0, 1, 2]
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with: { python-version: "3.11" }
      - run: pip install pytest-shard-cloudc
      - run: pytest --shard-id=${{ matrix.shard_id }} --num-shards=3

CircleCI example

jobs:
  test:
    parallelism: 3
    steps:
      - run: pytest --shard-id=${CIRCLE_NODE_INDEX} --num-shards=${CIRCLE_NODE_TOTAL}

More guides

• For mode behavior, .test_durations, verbose shard reports, and selection strategy, see Sharding Modes.
• For contributor-facing demo commands, see Demo Sessions.
• For report generation and parallel execution screenshots, see Allure Report Integration.

Alternatives

pytest-xdist parallelizes tests across CPU cores on a single machine and supports remote workers. A common pattern is to combine both: use pytest-shard to split work across CI nodes, and pytest-xdist to parallelize within each node.

pytest-circleci-parallelized splits by test run time rather than test count, but only at class granularity and only for CircleCI.

Contributions

Contributions are welcome. The package requires Python 3.11 or newer. Install the development toolchain and run the full check suite:

pip install -e .[dev]
nox

The Allure integration test also requires the allure CLI to be available on PATH.

License

MIT licensed.

Original work Copyright 2019 Adam Gleave. Modifications Copyright 2026 Cloud Chen.