Learn how to implement a Change Log in GitHub

Learn how to implement a Change Log in GitHub

A Change Log is an essential documentation tool that tracks changes, improvements, and fixes across different releases of a project. Implementing a change log helps maintain a clear record of updates for both internal and external stakeholders. There are various methods and tools available to automate or manually manage this process.

1. Automated Change Log Tooling

Automated tools simplify the process of generating change logs by gathering commit data, pull requests, and issues from repositories.

Popular Automated Change Log Tools:

1. Semantic Versioning Tools: Automatically tag and categorize commits based on version numbers.

2. GitHub Actions: Use workflows to generate change logs based on repository data.

3. Changelog Tools: Tools like or help automate this process.

2. Using Native GitHub Commands

Generating Change Logs with GitHub Commands:

1. Using GitHub CLI: Install GitHub CLI (gh) and use the following command:

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   gh release view --json body
   

   This extracts the release notes from a specific release.

2. Using GitHub REST API: Retrieve change logs from releases using:

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   curl -X GET -H "Accept: application/vnd.github.v3+json" https://api.github.com/repos/owner/repo/releases
   

3. Git Changelog Tools

Several Git-based tools can generate change logs from commit messages and pull requests.

Popular Git Changelog Generators:

1. Conventional Commits: Follows a specific commit message convention (e.g., feat:, fix:, docs:) to automatically categorize changes.

2. GitHub Changelog Generator: github-changelog-generator is a popular tool for generating changelogs from issues and pull requests:

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   github-changelog-generator --token <your_github_token> --future-release <next_version>
   

4. Should You Use Autogenerated Log-Based Data?

Using autogenerated data for change logs can save time and ensure consistency, but it has some considerations:

Pros:

1. Efficiency: Automates the process, reducing manual effort.

2. Consistency: Ensures a standard format across releases.

3. Accuracy: Pulls data directly from commit messages, PRs, and issues, minimizing errors.

Cons:

1. Complexity: Setup and configuration can be complex, especially for large repositories.

2. Customizability: Automated tools may lack flexibility for unique use cases or custom formats.

3. Dependency: Relies on well-structured commit messages and issue descriptions.

5. Workflow Example for Change Log Generation

1. Commit Messages: Ensure commits follow a consistent format:

   • feat: add new feature X

   • fix: resolve bug Y

   • docs: update README.md

2. GitHub Actions Workflow: Use a GitHub Actions workflow to trigger change log generation upon new releases:

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   on:
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   release:
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      types: [created]
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   jobs:
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   generate-changelog:
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      name: Generate Changelog
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      runs-on: ubuntu-latest
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      steps:
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      - name: Checkout Repository
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         uses: actions/checkout@v3
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      - name: Generate Changelog
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         uses: github-changelog-generator@1.15.1
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         with:
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         token: ${{ secrets.GITHUB_TOKEN }}
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         future-release: ${{ github.ref_name }}
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   ---
   

Summary

Automated tools and native GitHub commands streamline the creation of change logs, helping maintain accurate and up-to-date documentation. While autogenerated data offers efficiency and consistency, manual customization may be necessary for specific needs. Combining both approaches allows for a flexible yet effective change log management process.