experimental/cuda-ubi9/: pytest-shard-0.1.2 metadata and description
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| description_content_type | text/markdown |
| license | MIT |
| requires_dist |
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| requires_python | >=3.6 |
| File | Tox results | History |
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pytest_shard-0.1.2-py3-none-any.whl
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pytest-shard
Shards tests based on a hash of their test name enabling easy parallelism across machines, suitable for a wide variety of continuous integration services. Tests are split at the finest level of granularity, individual test cases, enabling parallelism even if all of your tests are in a single file (or even single parameterized test method).
Features
pytest-shard aims for simplicity. When installed, simply run:
$ pytest --shard-id=I --num-shards=N
where I is the index of this shard and N the total number of shards. For example, to split tests across two machines:
# On machine 1:
$ pytest --shard-id=0 --num-shards=2
# On machine 2:
$ pytest --shard-id=1 --num-shards=2
The intended use case is for continuous integration services that allow you to run jobs in parallel. For CircleCI, enable parallelism and then use:
pytest --shard-id=${CIRCLE_NODE_INDEX} --num-shards=${CIRCLE_NODE_TOTAL}
On Travis, you must define the environment variables explicitly, but can use a similar approach.
Alternatives
pytest-xdist allows you to parallelize tests across cores on a single machine, and can also schedule tests on a remote machine. I use pytest-shard to split tests across CI workers, and pytest-xdist to parallelize across CPU cores within each worker.
pytest-shard does not take into account the run time of tests, which can lead to suboptimal allocations. pytest-circleci-parallelized uses test run time, but can only split at the granularity of classes, and is specific to CircleCI.
Please open a PR if there are other promising alternatives that I have overlooked.
Installation
You can install pytest-shard via pip:
$ pip install pytest-shard
Contributions
Contributions are welcome. Test may be run using tox.
License
This software is MIT licensed.