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A Python reviewer that reports only on changed code can keep inherited warnings from drowning out feedback on a small patch. The key is defining “changed”: a Git comparison point determines which files or lines are in scope, and a separate rule determines whether findings may involve surrounding, unchanged code.
The title describes a tool, but the available documentation does not establish that tool’s implementation or behavior. Avouch offers a documented example of one possible design—not evidence about the tool in the title. The useful takeaway is how to build or assess a focused review workflow, and where its limits are.
What should “only reviews the code you changed” mean?
It is not one scope setting. A reviewer may inspect changed files, changed lines, or the functions and classes that contain those lines. Those choices produce different results: a file-level rule can flag an issue anywhere in a touched file, while a changed-line rule may ignore a defect just outside the diff.
The tool must also define the comparison point. Locally, “changed” might mean edits relative to HEAD, staged changes, or a broader range. For a pull request, it might mean the changes relative to the target branch. Untracked files need an explicit policy too; they may not appear in a normal comparison unless the tool adds them separately.
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These details belong in the tool’s documentation and command output. Without them, a quiet report is ambiguous: it could mean the code passed, or that the relevant code was outside the selected scope.
One documented design: Git selects, Python’s AST inspects
Avouch’s repository documents a concrete approach. Its default local review compares changes with HEAD and includes untracked files. It uses Git to determine the changed file set, then parses changed Python files with Python’s standard ast module. Many of its findings are limited to functions or classes whose source spans overlap added or changed lines.
This combines two scopes: Git identifies the files, and source-line overlap narrows certain findings within them. It is a practical architecture for a Python-focused checker, but it should not be attributed to the tool named in the title. The available information does not establish that tool’s comparison base, untracked-file policy, parsing method, rules, or output format.
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What a focused reviewer can—and cannot—tell you
Useful signal
A changed-code reviewer can apply structural or project-specific rules to a smaller review surface. By keeping findings on untouched legacy code out of the immediate report, it can make new feedback easier to triage. That is a scope trade-off, not evidence that the tool is more accurate or catches more bugs.
Context can cross the diff
A changed line may interact with an unchanged caller, shared state, configuration, or another file. A finding rule restricted to touched lines—or even to a function that overlaps them—can miss behavior that depends on those relationships. A useful review therefore retains enough surrounding code to reason about the change and does not treat “not reported” as “not a problem.”
How it fits with linting, type checks, tests, and pull-request review
Different tools answer different questions. Ruff’s FAQ describes Ruff as a linter, not a type checker, and recommends pairing it with a type checker such as mypy, Pyright, or Pyre because they catch different issues. Do not assume these tools use the same changed-line scope as a custom reviewer unless that behavior has been configured and verified.
- Changed-code reviewer: Can focus project-specific structural rules on a Git-defined change set.
- Linter: Flags classes of code-quality issues; it is not a substitute for type checking.
- Type checker: Checks type-related problems that lint rules may not cover.
- Tests: Exercise behavior, including cases static checks may not model.
- Human review: Evaluates intent, design, and interactions that automated checks may miss.
The Python Developer’s Guide advises reproducing reported problems, checking corner cases, and stating the system and version actually tested. Those are useful habits for reviewing any proposed fix: a focused static report does not establish that behavior works across relevant cases.
For pull requests, reporting is a separate concern from analysis. reviewdog documents using unified diff input and sending diagnostics or suggestions through supported review reporters. GitHub’s review workflow supports comments and suggestions, approvals, and requests for changes; see About pull request reviews. A local CLI, CI annotations, and inline PR comments are different delivery choices, not proof that the checks themselves are equivalent.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.When to use local focused checks or hosted review
A local changed-code checker suits a developer who wants quick, targeted feedback before pushing, especially in a repository with a large legacy baseline. A hosted pull-request review can be more convenient when feedback should appear alongside the diff for collaborators. These approaches can coexist: local checks provide fast feedback, while CI and reviewers assess the proposed change in the shared PR context.
GitHub describes Copilot code review as reviewing pull-request changes and suggesting fixes. Automatic review options depend on user or repository configuration and plan or license eligibility, which can change. GitHub cautions that Copilot may miss problems or make mistakes and recommends validating its feedback and supplementing it with human review. It is a hosted PR-review option, not a drop-in equivalent to a local Python-only checker.
For any implementation, the practical checklist is short: document the Git base and treatment of untracked files; state whether rules apply to files, changed lines, or enclosing scopes; show findings with useful file and line locations; and keep linting, type checking, tests, and human review in the workflow where they add coverage.
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