54 lines
2.5 KiB
Markdown
54 lines
2.5 KiB
Markdown
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# Overview
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This directory contains scripts that facilitate building and running tests. We are using python scripts as entrypoint for our
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tests because that gives us the opportunity to run tests using the same commandline regardless of the platform you are using.
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# Unit tests (run_tests.py)
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Builds gRPC in given language and runs unit tests. Use `tools/run_tests/run_tests.py --help` for more help.
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###### Example
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`tools/run_tests/run_tests.py -l csharp -c dbg`
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###### Useful options (among many others)
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- `--use_docker` Builds a docker container containing all the prerequisites for given language and runs the tests under that container.
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- `--build_only` Only build, do not run the tests.
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Note: If you get an error such as `ImportError: No module named httplib2`, then you may be missing some Python modules. Install the module listed in the error and try again.
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Note: some tests may be flaky. Check the "Issues" tab for known flakes and other issues.
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The full suite of unit tests will take many minutes to run.
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# Interop tests (run_interop_tests.py)
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Runs tests for cross-platform/cross-language interoperability. For more details, see [Interop tests descriptions](/doc/interop-test-descriptions.md)
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The script is also capable of running interop tests for grpc-java and grpc-go, using sources checked out alongside the ones of the grpc repository.
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###### Example
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`tools/run_tests/run_interop_tests.py -l csharp -s c++ --use_docker` (run interop tests with C# client and C++ server)
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Note: if you see an error like `no space left on device` when running the
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interop tests using Docker, make sure that Docker is building the image files in
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a location with sufficient disk space.
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# Performance benchmarks (run_performance_tests.py)
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Runs predefined benchmark scenarios for given languages. Besides the simple configuration of running all the scenarios locally,
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the script also supports orchestrating test runs with client and server running on different machines and uploading the results
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to BigQuery.
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###### Example
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`tools/run_tests/run_performance_tests.py -l c++ node`
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###### Useful options
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- `--regex` use regex to select particular scenarios to run.
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# Artifacts & Packages (task_runner.py)
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A generalized framework for running predefined tasks based on their labels. We use this to building binary artifacts & distrib packages and testing them)
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###### Example
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`tools/run_tests/task_runner.py -f python artifact linux x64` (build tasks with labels `python`, `artifact`, `linux`, and `x64`)
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