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Compare Cpython Versions Agent Skill

> Compare CPython source code between two Python versions to identify changes in headers and structs. Use this when adding support for a new Python version to understand what changed between versions.

1k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
646
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/DataDog/dd-trace-py --skill compare-cpython-versions

What it tells the agent to use

found in the instruction text
WebSearch reads your files

The instruction itself

12 sections, as written by the author

Compare CPython Versions Skill

This skill helps compare CPython source code between two Python versions to identify

changes in headers, structs, and APIs that affect our codebase.

When to Use This Skill

Use this skill when:

  • Adding support for a new Python version
  • Need to understand what changed between versions
  • Investigating compatibility issues
  • Have a list of headers/structs from find-cpython-usage skill

Key Principles

  • Compare systematically - Focus on headers and structs identified in Step 1
  • Use multiple methods - Git diff, manual diff, or AI-assisted comparison
  • Document changes - Note all breaking changes and API modifications
  • Check context - Understand why changes were made (PEPs, GitHub issues)

How This Skill Works

Step 1: Prepare CPython Repository

# Create ~/dd directory if it doesn't exist
mkdir -p ~/dd

# Clone CPython repository if needed (to ~/dd/cpython)
if [ ! -d ~/dd/cpython ]; then
    git clone https://github.com/python/cpython.git ~/dd/cpython
    cd ~/dd/cpython
    git fetch --tags
else
    cd ~/dd/cpython
    # Update existing repository
    git fetch --tags
    git fetch origin
fi

Step 2: Compare Specific Headers

Using the list of headers from find-cpython-usage, compare each header between

the old version and new version. Replace OLD_VERSION and NEW_VERSION with the

actual version tags (e.g., v3.13.0, v3.14.0):

# Compare specific headers between versions
git diff OLD_VERSION NEW_VERSION -- Include/internal/pycore_frame.h
git diff OLD_VERSION NEW_VERSION -- Include/frameobject.h

# Compare all internal headers
git diff OLD_VERSION NEW_VERSION -- 'Include/internal/pycore*.h'

# Compare specific struct definitions
git diff OLD_VERSION NEW_VERSION -- Include/internal/pycore_frame.h | grep -A 20 "struct _PyInterpreterFrame"

Step 3: Identify Changes

For each header/struct, look for:

Struct Changes:

  • Field additions
  • Field removals
  • Field type changes
  • Field reordering
  • Struct moves to different headers

API Changes:

  • Removed functions/structures
  • New functions/structures
  • Changed function signatures
  • Deprecated APIs

Header Changes:

  • Headers moved to different locations
  • Headers split or merged
  • New headers introduced

Step 4: Analyze Impact

For each change identified:

  • Understand the change:
  • Why was it changed? (Check Python's What's New, PEPs, or GitHub issues)
  • Is it a breaking change or backward compatible?
  • What's the replacement API?
  • Find the specific commit(s) that introduced the change:
     # Find commits that modified a specific file between versions
     git log OLD_VERSION..NEW_VERSION -- Include/internal/pycore_frame.h

     # Find commits that mention a specific struct or function
     git log OLD_VERSION..NEW_VERSION --all --grep="_PyInterpreterFrame" -- Include/

     # Show the commit that introduced a specific change
     git log -p OLD_VERSION..NEW_VERSION -S "struct _PyInterpreterFrame" -- Include/
  • Find related GitHub issues:
  • Check commit messages for issue references (e.g., gh-123923, #123923)
  • Search CPython GitHub issues: https://github.com/python/cpython/issues
  • Look for "What's New" documentation: https://docs.python.org/3/whatsnew/
  • Check PEPs if the change is part of a larger feature
  • Assess impact:
  • Which files in our codebase are affected?
  • What functionality might break?
  • Are there alternative approaches?
  • Document findings:
  • Create a summary document of key changes
  • Note any breaking changes
  • List files that need updates

Step 5: Use AI Tools (Optional)

You can use AI coding assistants to help analyze differences by:

  • Providing header file contents from both versions
  • Asking about specific struct changes
  • Understanding migration paths

Common Change Patterns

When comparing versions, look for these types of changes (examples):

Struct Field Changes:

  • Field type changes (e.g., pointer types → tagged pointer types)
  • Field renamed
  • Field removed and replaced with different mechanism
  • Field reordering

Header Moves:

  • Internal headers moved to new locations
  • Structs moved between headers
  • Headers split or merged

API Deprecations:

  • Internal functions removed
  • Public API replacements available
  • Function signature changes

Output Format

After running this skill, you should have:

  • A list of all changed headers
  • A list of all changed structs with details
  • Impact assessment for each change
  • Files in our codebase that need updates
  • find-cpython-usage skill: Use to identify what to compare

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