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Issue Metrics Action

CodeQL Docker Image CI Python package

This is a GitHub Action that searches for pull requests/issues in a repository and measures the time to first response for each one. It then calculates the average time to first response and writes the issues/pull requests with their time to first response and time to close to a Markdown file. The issues/pull requests to search for can be filtered by using a search query.

This action was developed by the GitHub OSPO for our own use and developed in a way that we could open source it that it might be useful to you as well! If you want to know more about how we use it, reach out in an issue in this repository.

To find syntax for search queries, check out the documentation.

Support

If you need support using this project or have questions about it, please open up an issue in this repository. Requests made directly to GitHub staff or support team will be redirected here to open an issue. GitHub SLA's and support/services contracts do not apply to this repository.

Use as a GitHub Action

  1. Create a repository to host this GitHub Action or select an existing repository.
  2. Create the env values from the sample workflow below (GH_TOKEN, REPOSITORY_URL, SEARCH_QUERY) with your information as repository secrets. More info on creating secrets can be found here. Note: Your GitHub token will need to have read access to the repository in the organization that you want evaluated
  3. Copy the below example workflow to your repository and put it in the .github/workflows/ directory with the file extension .yml (ie. .github/workflows/issue-metrics.yml)

Configuration

Below are the allowed configuration options:

field required default description
GH_TOKEN true The GitHub Token used to scan the repository. Must have read access to all repository you are interested in scanning.
REPOSITORY_URL true The repository to scan for issues.
SEARCH_QUERY true The query by which you can filter issues/prs

Example workflow

name: Monthly issue metrics
on:
  workflow_dispatch:
  schedule:
    - cron: '3 2 1 * *'

jobs:
  build:
    name: issue metrics
    runs-on: ubuntu-latest
    
    steps:

    - name: Run issue-metrics tool
      uses: github/issue-metrics@v1
      env:
        GH_TOKEN: ${{ secrets.GH_TOKEN }}
        REPOSITORY_URL: https://github.com/owner/repo
        SEARCH_QUERY: 'is:issue created:2023-05-01..2023-05-31 -reason:"not planned"'

    - name: Create issue
      uses: peter-evans/create-issue-from-file@v4
      with:
        title: Monthly issue metrics report
        content-filepath: ./issue_metrics.md
        assignees: <YOUR_GITHUB_HANDLE_HERE>

SEARCH_QUERY: Issues or Pull Requests? Open or closed?

This action can be configured to run metrics on pull requests and/or issues. It is also configurable by whether they were open or closed in the specified time window. Further query options are listed in the search documentation. Here are some search query examples:

Issues opened in May 2023:

  • is:issue created:2023-05-01..2023-05-31

Issues closed in May 2023 (may have been open in May or earlier):

  • is:issue closed:2023-05-01..2023-05-31

Pull requests opened in May 2023:

  • is:pr created:2023-05-01..2023-05-31

Pull requests closed in May 2023 (may have been open in May or earlier):

  • is:pr closed:2023-05-01..2023-05-31

Both issues and pull requests opened in May 2023:

  • created:2023-05-01..2023-05-31

Both issues and pull requests closed in May 2023 (may have been open in May or earlier):

  • closed:2023-05-01..2023-05-31

OK, but what if I want both open or closed issues and pull requests? Due to limitations in issue search (no ability for an or pattern), you will need to run the action twice, once for opened and once for closed. Here is an example workflow that does this:

name: Monthly issue metrics
on:
  workflow_dispatch:
  schedule:
    - cron: '3 2 1 * *'

jobs:
  build:
    name: issue metrics
    runs-on: ubuntu-latest

    steps:
    
    - name: Run issue-metrics tool for issues and prs opened in May 2023
      uses: github/issue-metrics:v1
      env:
        GH_TOKEN: ${{ secrets.GH_TOKEN }}
        REPOSITORY_URL: https://github.com/owner/repo
        SEARCH_QUERY: 'created:2023-05-01..2023-05-31 -reason:"not planned"'

    - name: Create issue for opened issues and prs
      uses: peter-evans/create-issue-from-file@v4
      with:
        title: Monthly issue metrics report  for opened issues and prs
        content-filepath: ./issue_metrics.md
        assignees: <YOUR_GITHUB_HANDLE_HERE>
    
    - name: Run issue-metrics tool for issues and prs closed in May 2023
      uses: github/issue-metrics:v1
      env:
        GH_TOKEN: ${{ secrets.GH_TOKEN }}
        REPOSITORY_URL: https://github.com/owner/repo
        SEARCH_QUERY: 'closed:2023-05-01..2023-05-31 -reason:"not planned"'

    - name: Create issue for closed issues and prs
      uses: peter-evans/create-issue-from-file@v4
      with:
        title: Monthly issue metrics report for closed issues and prs
        content-filepath: ./issue_metrics.md
        assignees: <YOUR_GITHUB_HANDLE_HERE>

Example issue_metrics.md output

# Issue Metrics

| Metric | Value |
| --- | ---: |
| Average time to first response | 0:50:44.666667 |
| Average time to close | 6 days, 7:08:52 |
| Number of issues that remain open | 2 |
| Number of issues closed | 1 |
| Total number of issues created | 3 |

| Title | URL | Time to first response | Time to close 
| --- | --- | ---: | ---: |
| Issue Title 1 | https://github.com/user/repo/issues/1 | 0:00:41 | 6 days, 7:08:52 |
| Issue Title 2 | https://github.com/user/repo/issues/2 | 0:05:26 | None |
| Issue Title 3 | https://github.com/user/repo/issues/3 | 2:26:07 | None |

Local usage without Docker

  1. Copy .env-example to .env
  2. Fill out the .env file with a token from a user that has access to the organization to scan (listed below). Tokens should have admin:org or read:org access.
  3. Fill out the .env file with the repository_url of the repository to scan
  4. Fill out the .env file with the search_query to filter issues by
  5. pip install -r requirements.txt
  6. Run python3 ./issue_metrics.py, which will output issue metrics data

License

MIT