gh-profiler 0.6.4

Examine a GitHub user's profile, to help quickly decide how much to invest in their contributions.

gh-profiler

Many of us have received waves of open source contributions where many of the new "contributions" aren't worth engaging with. gh-profiler lets you quickly see a snapshot of the submitter's profile, and recent PR activity.

This meant to give you some quick context about how much to invest in reviewing the PR. It's not meant to give an immediate signal to close the PR or issue.

[!NOTE] You don't need Python if you want to run gh-profiler each time a PR or issue is opened in a repository. You can copy the profiler_contributors.yml file and paste it into your own .github/workflows/ directory. From that point forward, you'll see a comment on each new PR and issue with a concise summary of the user that opened the PR or issue. Example

Running as a tool

If you have uv installed, you can run this as a tool against any GitHub user:

$ uvx gh-profiler <redacted>
GitHub user: <redacted>
🟡 Some concerns found with user's profile.
   🟡 Account age: 6 months
   🟢 Profile information:
        name: <redacted>
        blog: <redacted>
        email: <redacted>
      Empty fields: company, location, bio

🟢 No concerns found with recent PR activity.
   🟢 Fewer than 10 PRs opened in the last 21 days.

🔴 Significant concerns found with recent issue activity.
   🔴 79 new issues opened in the last 21 days.
   🟢 0 issues closed as NOT_PLANNED.
   🔴 71 issues opened with the same title:
        📋 Documentation Enhancement Suggestion (71)

If you're working in your local project directory, you can simply provide a PR or issue number. The tool will look up the PR or issue, identify the user who opened it, and give a report on that user:

$ uvx gh-profiler 8
Issue #8: Accept a username or an issue/ pr number.
Author: ehmatthes
  🟢 Account age: 13 years
  ...

Installing and then running

You can also install the project, and then run the bare gh-profiler command:

(.venv) $ pip install gh-profiler
(.venv) $ gh-profiler ehmatthes
GitHub user: ehmatthes
  🟢 Account age: 13 years
  ...

When you've installed the project, you can also run it as a module:

$ python -m gh_profiler <username>

Verbose output

The -v or --verbose flag will print some of the rationales for evaluating flags:

$ uv run gh-profiler <redacted> -v

Flag adjusted: Set account age flag green. This user has a newer account,
  but they have no other concerning activity.

Flags adjusted: Set profile info and overall profile flags green. This user has not
  opened any recent PRs or issues, so they have no concerning activity.

--- Summary ---

GitHub user: <redacted>
🟢 No concerns found with user's profile.
   🟢 Account age: 20 minutes
   🟢 Profile information:
      Empty fields: name, company, blog, location, email, bio
...

Concise output

If you want just the simplest summary, you can pass the --concise flag:

$ uvx gh-profiler <redacted> --concise
GitHub user: <redacted>
🟡 Some concerns found with user's profile.
🟢 No concerns found with recent PR activity.
🔴 Significant concerns found with recent issue activity.

For a more detailed report, run `gh-profiler <redacted>`.

False positives

Some checks are in place to ensure that people who are not engaged in clear problematic behavior don't raise red or yellow flags. For example, a new user who opens a bunch of identical issues or PRs will have a red flag for the account age. But a new user who does not show any other signs of problematic behavior will have their account age flag set to green.

If you see an example of red or yellow flags being raised with no clear indication of problematic behavior, please consider opening an issue.

GitHub Actions

gh-profiler can write a GitHub Action that will automatically run gh-profiler --concise any time a new PR or issue is opened on your project. The output will be written as a comment on the new PR or issue.

The --generate-workflow flag does this by writing a profile_contributors.yml file to .github/workflows:

$ uvx gh-profiler --generate-workflow
This will generate a GitHub action that will automatically run gh-profiler
whenever someone opens a new issue or PR in your repository. The profile
output will be written as a comment on the issue or PR.

The workflow will be written at the following location:
  /.../.github/workflows/profile_contributors.yml

Are you sure you want to do this? (y/n) y

The new workflow file was written:
  /.../.github/workflows/profile_contributors.yml

To start seeing profiles when new issues and PRs are opened:
- Commit the workflow file to your main branch.
- Push your main branch to GitHub.
  ...

Talks & discussion

This is a list of talks and discussions related to gh-profiler.

• PyCon US 2026 lightning talk (video not released yet)
• Real Python episode 296 (brief overview of project)

Maintaining

--redact

For live demos and screenshots, you can pass the --redact flag. The username and profile information sections will show "<redacted>" in place of identifying information:

$ uv run gh-profiler 39 --redact
Issue #39: Add a `--redact` flag
Author: <redacted>
  🟢 Account age: 13 years

  🟢 Profile information:
      name: <redacted>
      blog: <redacted>
      ...

Add/ modify a requirement

• Add or modify a requirement by modifying pyproject.toml, or running uv add <package>.
• For a dev dependency, run uv add --dev <package>.
• Then run uv lock.

Running tests

Run all tests except end-to-end tests:

$ uv run pytest

End-to-end tests are slower, and flakier because they make actual API calls. It's best to run a specific e2e test:

$ uv run pytest tests/e2e_tests -k full
$ uv run pytest tests/e2e_tests -k concise

There's a shell script that runs all of these tests. It works on macOS and probably linux, but may not work on Windows.

$ ./test_all.sh

Profiling

$ uv run python -m cProfile -s cumtime -m gh_profiler ehmatthes > profile.txt

Style notes

• When composing output messages, prefer terse messages over verbose messages:
  • "0 issues closed as NOT_PLANNED." over "0 issues have been closed as NOT_PLANNED."

Benchmarking

To track overall real-world performance over time, use the benchmarking script:

$ uv run developer_resources/benchmark.py
$ uv run developer_resources/benchmark.py <target>

New releases

Update changelog and bump version, then:

$ uv lock
# Commit all changes.
$ git tag vX.Y.Z
$ git push origin vX.Y.Z
$ rm -rf dist/*
$ uv build
$ uv publish