add mac arm ci automation

[sklarsa]

Summary by CodeRabbit

• Chores
  • Added CI coverage for macOS ARM (Apple Silicon), running tests across Python 3.10–3.13 to improve platform validation.
  • Added dedicated NumPy compatibility validation in the test pipeline, exercising multiple Python/NumPy combinations to ensure reliability across dependency versions.

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[coderabbitai]

Caution

Review failed

The head commit changed during the review from 0df3d3f to 476b60f.

Walkthrough

Adds a new GitHub Actions workflow to run macOS ARM (Apple Silicon) tests with two jobs: a multi‑Python build/test job and a NumPy compatibility matrix test job targeting macOS ARM64 runners.

Changes

Cohort / File(s)	Summary
CI workflow — macOS ARM tests .github/workflows/test-macos-arm.yaml	New workflow defining two jobs: test (matrix Python 3.10–3.13 on macOS ARM64; steps: checkout, setup-python, install Rust, install Cython, install deps, proj.py build, proj.py test 1 with JAVA_HOME set) and test-numpy-compat (matrix of Python and NumPy versions; installs Rust and uv, runs tests pinned to specific NumPy versions targeting test/test.py -v TestBufferProtocolVersionV2).

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~10 minutes

• Check runner image and macOS/version label (ARM64 runner correctness)
• Verify Python matrix entries and setup-python usage
• Confirm Rust, Cython, and dependency install steps and order
• Validate JAVA_HOME export and test invocation commands
• Review NumPy compatibility matrix entries and targeted test path

Poem

🐰 I hopped into CI, swift and keen,
ARM64 leaves a shiny sheen,
Python versions, NumPy too,
Tests run through the morning dew —
A tiny rabbit cheers: “All green!” 🎉

Pre-merge checks and finishing touches

✅ Passed checks (3 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title 'add mac arm ci automation' directly and clearly describes the main change: adding CI automation for macOS ARM. It is concise, specific, and accurately reflects the primary purpose of the pull request.
Docstring Coverage	✅ Passed	No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check.

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[coderabbitai]

Actionable comments posted: 0

🧹 Nitpick comments (1)

.github/workflows/test-macos-arm.yaml (1)

31-40: Consider extracting Rust and toolchain setup to a reusable workflow.

Both jobs install Rust identically (lines 31–34 and 84–87). This duplication can be reduced by extracting the common setup steps into a reusable workflow or a composite action, improving maintainability.

📜 Review details

Configuration used: CodeRabbit UI

Review profile: CHILL

Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between 3cd70bf and 8594de5.

📒 Files selected for processing (1)

• .github/workflows/test-macos-arm.yaml (1 hunks)

🧰 Additional context used

🧠 Learnings (1)

📓 Common learnings

Learnt from: amunra
Repo: questdb/py-questdb-client PR: 120
File: ci/run_tests_pipeline.yaml:85-85
Timestamp: 2025-11-28T17:46:34.703Z
Learning: In the py-questdb-client repository, Python version testing is handled by cibuildwheel configuration in pyproject.toml. The ci/run_tests_pipeline.yaml pipeline is specifically for testing against various numpy versions, not for comprehensive Python version coverage.

⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (15)

• GitHub Check: questdb.py-questdb-client-release (cibuildwheel windows_i686)
• GitHub Check: questdb.py-questdb-client-release (cibuildwheel windows_x86_64)
• GitHub Check: questdb.py-questdb-client-release (cibuildwheel macos_x64)
• GitHub Check: questdb.py-questdb-client-release (cibuildwheel linux_x64_cpython_musllinux)
• GitHub Check: questdb.py-questdb-client-release (cibuildwheel linux_x64_pypy)
• GitHub Check: questdb.py-questdb-client-release (cibuildwheel linux_x64_cpython_manylinux_x86_64)
• GitHub Check: questdb.py-questdb-client-release (cibuildwheel start_linux_arm64_agent_aws)
• GitHub Check: questdb.py-questdb-client-tests (Building and testing on windows-msvc-2019)
• GitHub Check: questdb.py-questdb-client-tests (Building and testing on mac)
• GitHub Check: questdb.py-questdb-client-tests (Building and testing on linux-qdb-master)
• GitHub Check: questdb.py-questdb-client-tests (Building and testing on linux-old-pandas)
• GitHub Check: questdb.py-questdb-client-tests (Building and testing on linux)
• GitHub Check: questdb.py-questdb-client-tests (Building and testing TestsAgainstVariousNumpyVersion2x)
• GitHub Check: questdb.py-questdb-client-tests (Building and testing TestsAgainstVariousNumpyVersion1x)
• GitHub Check: Test numpy compatibility (3.11, 2.0.0)

🔇 Additional comments (4)

.github/workflows/test-macos-arm.yaml (4)

51-51: Verify that JAVA_HOME_17_ARM64 is available on macOS-13-xlarge ARM64 runners.

The environment variable JAVA_HOME_17_ARM64 may not be available on this runner. Please confirm it exists or consider using an alternative approach to set JAVA_HOME. You can check GitHub's documentation or test this in a workflow run to verify availability.

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92-93: Verify the uv run --python python syntax is correct.

The command uv run --python python may not work as intended. The --python flag typically requires a specific path, version identifier, or interpreter name that uv can resolve. Verify that this selects the correct Python version or use an explicit path (e.g., --python python3.10).

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92-93: The numpy compatibility test only runs a single test class.

The test command runs only TestBufferProtocolVersionV2 instead of the full test suite. If this is intentional for targeted numpy validation, this should be documented in a comment. If it's an oversight, consider running the full test suite with the numpy version matrix.

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36-40: Inconsistent toolchain setup between jobs.

The test job installs Cython and uses python3 proj.py test, while test-numpy-compat skips Cython and uses uv run. Clarify whether Cython is required for the numpy compatibility tests or if the different invocation methods serve different purposes.

Also applies to: 89-93