project-chip/connectedhomeip

Parallelize code generation for jinja files and code formatting

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#38,775 opened on 2025年5月6日

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good first issuestale

説明

We want to have fast iteration speed on code generation. https://github.com/project-chip/connectedhomeip/blob/master/scripts/py_matter_idl/matter/idl/generators/cpp/sdk/sdk_generator.py#L120 currently generates a LOT of files and could benefit from paralelization

Update code logic to do parallel generation and test out if this improves runtime (i.e. if it is worth it - this issue was created on the assumption that it is, however we should verify that).

We also do file formatting and those seem to call one single exec to format many files at once. We should investigate if splitting files per cpu count improves formatting (i.e. is clang-format and kotlin-format single threaded or multi-threaded?)

コントリビューターガイド

技術スタック
pythoncppkotlin
領域
toolingbuild system
Issue 種別
performance
難度新しい貢献者にとっての実装難度です。1 は非常に小さな変更、5 は専門的な作業です。
3
推定時間経験ある貢献者が調査、実装、テスト、pull request 準備にかけるおおよその時間範囲です。
3-5 days
活動状況Issue が今どれだけ取り組みやすいかを示します。新しい、活発、古い、ブロック中、またはメンテナー入力待ちなどです。
fresh
明確さ期待される変更、受け入れ条件、次の手順がどれだけ明確かを示します。
mostly clear
前提条件
PythonConcurrency basicsBuild system
初心者向け度初回貢献者にどれだけ取り組みやすいかを 1-100 で推定したスコアです。
45
調査方針
Investigate the file scripts/py matter idl/matter/idl/generators/cpp/sdk/sdk generator.py at line 120 to understand the current sequential generation. Implement parallel generation using Python's concurrent.futures module. Measure runtime before and after to confirm improvement. Additionally, examine clang format and kotlin format to determine if they are single threaded; if so, split the file list by CPU count and format in parallel. Report the performance results in the issue.