125 skills (repositories by apache) · sorted by popularity
Helps contributors develop and fix Airflow’s Java SDK for JVM tasks. Explains public API boundaries, JAR packaging, Python coordination, communication schema updates, and the test commands used to validate changes.
Prepare Apache Airflow provider releases by classifying pending changes, inspecting pull request diffs for compatibility risks, and applying version bumps and changelog entries. Use existing breeze tooling to regenerate release documentation and consult the release manager on uncertain decisions.
Update Flask-AppBuilder in Apache Airflow’s FAB provider, including pinned versions, dependency locks, and documentation. Check compatibility tests and review copied security code, with asset and database migration updates when the upstream release requires them.
Guides preparation and authorized publication of Apache Airflow changes, including existing pull request checks, remote verification, reviews, tests, rebasing, and a prefilled submission page. Also explains how to track work deferred by temporary fixes.
Turn Airflow Improvement Proposals into practical guides checked against current code, or proposed user stories for design review before implementation. Organize use cases, distinguish verified examples from speculative code, and capture specific design questions.
Guides contributors through adding a new programming language to Airflow, covering SDK structure, runtime coordination, communication rules, executable packaging, tests, and the documentation and configuration changes needed for a pull request.
Write and review SQL for reports and metrics in a data warehouse, a store of analytical data. Applies rules for explicit columns, date filters, aggregate names, and limited exploratory results, returning SQL with a brief explanation.
Draft commit messages, pull request titles and descriptions, and GitHub comments or reviews for Apache Airflow contributions. Follows project wording and AI attribution rules, and helps decide whether a change needs a release note.
Assess Airflow Improvement Proposals by comparing Confluence specifications with pull requests, commits, and codebase files. Produce evidence-backed progress reports showing delivered items, remaining work, and specification updates needed across one or more proposals.
Helps add or update translations for the Apache Airflow interface. Covers language setup, translation file generation, consistent terminology, preserved variables and plural forms, and checks for missing, unfinished, or unused entries.
Apply Apache ShardingSphere’s written coding standards during implementation or review, covering naming, Java constructs, tests, and Maven dependencies. Also audit a specified scope without editing files, combining automated checks with manual inspection of applicable rules.
Investigate Apache ShardingSphere issues using official documentation, code, tests, and issue discussions. Distinguish bugs, unsupported usage, duplicates, and enhancement requests, then draft a concise maintainer-style reply explaining the evidence and next action.
Create or improve unit tests for Apache ShardingSphere classes. Cover the target class’s behavior and affected branches, verify explicitly requested coverage goals, and consolidate suitable scenarios into parameterized tests, which run the same checks with different inputs.
Implement, fix, refactor, or remove repository code through a defined workflow. It connects each change to an acceptance criterion, checks effects on existing behavior, and guides focused testing, change review, and verification.
Review Apache ShardingSphere pull requests or authorized downstream changes using repository evidence. Assess code correctness, merge readiness, or CI failures, then produce consolidated findings or a ready-to-copy reply to a review discussion.
Prepare an Apache bRPC release with tracked progress, version updates, release candidate checks, and draft release notes and emails. The workflow leaves signing, publishing, and other external release actions to the release manager.
Format C++ code in the BE and Cloud modules using the project's clang-format v16 rules. Use the provided scripts to fix formatting or check for violations without changing files, then review the resulting differences before committing.
Diagnoses and fixes Java style violations in the FE module using Checkstyle, a tool that checks coding rules. It interprets errors, applies the project's formatting and import restrictions, and reruns checks to verify fixes.
Review Doris code changes using project-specific checklists for data correctness, concurrency, memory safety, compatibility, performance, and tests. Trace related code paths and explain findings with concrete failure scenarios, using query plan trees when reviewing optimizer behavior.
Prepare a clean Doris package and run Docker regression tests, which check whether changes break existing behavior. Restore configuration and startup files from Git, build the test image, and investigate failures using configuration checks and runtime logs.
Run clang-tidy static analysis, which checks code without executing it, on added or modified BE and Cloud C++ files. Focus diagnostics on changed lines, investigate bug, performance, and readability warnings, and verify fixes with another check.
Run TVM's TIRx compiler tests alongside tirx-kernels import and correctness checks. It verifies the local build, selects GPUs, runs parallel tests, saves full logs, and guides failure investigation and result reporting.
Extend and audit TVM's T.ptx instruction table for GPU code generation. It guides instruction definitions, checks generated assembly with CUDA tools, and aligns comments and supported forms with a chosen PTX specification version.
Analyze Git history to find frequently and recently changed files and lines, then rank review targets. Use the results to focus pull request reviews, bug investigations, or security audits on specific code regions and risks.