find-cpython-usage
Automates the identification of CPython internal API dependencies for codebase maintenance and version upgrades.
Install
mkdir -p .claude/skills/find-cpython-usage && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/7885" && unzip -o skill.zip -d .claude/skills/find-cpython-usage && rm skill.zipInstalls to .claude/skills/find-cpython-usage
Activation
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Find all CPython internal headers and structs used in the codebase, particularly for profiling functionality. Use this when adding support for a new Python version to identify what CPython internals we depend on.Key capabilities
- →Search CPython internal headers
- →Identify struct field access
- →Locate native extension dependencies
- →Document CPython API usage
How it works
It uses grep patterns to scan C, C++, and Cython files for internal CPython headers and direct struct field access.
Inputs & outputs
When to use find-cpython-usage
- →Check Python version compatibility
- →Find CPython internal API usage
- →Refactor profiling code
About this skill
Find CPython Internal Usage Skill
This skill helps identify all CPython internal headers and structures used in the codebase, which is essential when adding support for new Python versions.
When to Use This Skill
Use this skill when:
- Adding support for a new Python version
- Investigating CPython API dependencies
- Understanding what internal APIs the profiler uses
- Preparing to compare CPython versions
Key Principles
- Focus on internal headers - These are most likely to change between versions
- Check all native extensions - CPython internals are used in profiling, AppSec, and internal modules
- Look for struct field access - Direct field access is version-sensitive
- Document findings - Keep track of what you find for comparison
How This Skill Works
Step 1: Find CPython Header Includes
Search for CPython header includes across all C/C++/Cython files:
# Find all CPython internal header includes
grep -r "include.*internal/pycore" ddtrace/ --include="*.c" --include="*.cpp" --include="*.h" --include="*.hpp" --include="*.pyx"
# Find all CPython cpython header includes
grep -r "include.*cpython" ddtrace/ --include="*.c" --include="*.cpp" --include="*.h" --include="*.hpp" --include="*.pyx"
# Find all Python.h includes (indicates CPython API usage)
grep -r "#include.*Python\.h" ddtrace/ --include="*.c" --include="*.cpp" --include="*.h" --include="*.hpp" --include="*.pyx"
# Find frameobject.h includes (common CPython API)
grep -r "#include.*frameobject\.h" ddtrace/ --include="*.c" --include="*.cpp" --include="*.h" --include="*.hpp" --include="*.pyx"
# Find PyO3 FFI usage in Rust (Rust extensions may use CPython internals)
grep -r "pyo3_ffi::\|pyo3::ffi::" src/native/ --include="*.rs" || true
Note: These patterns search across all native extension files (.c, .cpp, .h, .hpp, .pyx, .rs)
regardless of their location in the codebase. Check setup.py to see which extensions are built.
Rust extensions use PyO3 which may access CPython internals through the pyo3_ffi module.
Step 2: Find Struct Field Access
Search for direct struct field access and struct definitions across all native files:
# Find struct field accesses (arrow operator)
grep -r "->f_\|->[a-z_]*\." ddtrace/ --include="*.c" --include="*.cpp" --include="*.h" --include="*.hpp"
# Find struct definitions
grep -r "struct.*Py" ddtrace/ --include="*.c" --include="*.cpp" --include="*.h" --include="*.hpp"
# Find common CPython struct usage
grep -r "PyFrameObject\|PyThreadState\|_PyInterpreterFrame" ddtrace/ --include="*.c" --include="*.cpp" --include="*.h" --include="*.hpp" --include="*.pyx"
grep -r "PyFrameObject\|PyThreadState\|PyInterpreterState" src/native/ --include="*.rs" || true
# Find PyCodeObject usage
grep -r "PyCodeObject" ddtrace/ --include="*.c" --include="*.cpp" --include="*.h" --include="*.hpp" --include="*.pyx"
grep -r "PyCodeObject" src/native/ --include="*.rs" || true
Look for patterns like:
- Frame structure access (
PyFrameObject,_PyInterpreterFrame) - Thread state access (
PyThreadState) - Code object access (
PyCodeObject) - Generator/coroutine structures
- Asyncio task structures
Step 3: Identify Common Structures
Common CPython structures we typically access:
Frame structures:
PyFrameObject/struct _frame_PyInterpreterFrame
State structures:
PyThreadStatePyInterpreterState_PyRuntimeState
Code structures:
PyCodeObject
Generator structures:
PyGenObjectPyAsyncGenASend
Asyncio structures:
FutureObjTaskObj
Step 4: Document Findings
Create a list of:
- All headers that are included
- All structs that are accessed
- All struct fields that are used directly
This will be used in the next step to compare against the new Python version.
Native Extensions Using CPython APIs
To find all native extensions that may use CPython APIs, check setup.py:
# View all native extensions defined in setup.py
grep -A 5 "Extension\|CMakeExtension\|Cython.Distutils.Extension\|RustExtension" setup.py
The setup.py file defines all native extensions (C, C++, CMake, Cython, and Rust) that
are built for the project. Not all extensions use CPython internals - focus on those
that access frame objects, thread state, or internal structures when searching for
CPython API usage.
Note: Rust extensions use PyO3 bindings which may access CPython internals through
pyo3_ffi module. Search Rust source files (.rs) for CPython API usage as well.
Common Headers to Look For
The grep commands above will identify which CPython headers are actually used in the codebase. Common patterns include:
Public Headers:
- Headers matching
*.hinInclude/directory (e.g.,frameobject.h,unicodeobject.h) - Headers in
Include/cpython/directory (e.g.,cpython/genobject.h)
Internal Headers (require Py_BUILD_CORE):
- Headers matching
internal/pycore*.hpattern - These are most likely to change between Python versions
Focus on headers that are actually found by the grep commands rather than maintaining a hardcoded list, as the headers used may change over time.
Output Format
After running this skill, you should have:
- A list of all CPython headers included in the codebase
- A list of all CPython structs accessed
- A list of struct fields accessed directly
- Files that use each header/struct
This information can then be used with the compare-cpython-versions skill to identify what changed.
Related
- compare-cpython-versions skill: Use findings from this skill to compare versions
When not to use it
- →High-level Python application development
- →Non-native codebases
Limitations
- →Limited to native extensions
- →Requires manual review of grep results
How it compares
It automates the discovery of version-sensitive internal API dependencies instead of manual code inspection.
Compared to similar skills
find-cpython-usage side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| find-cpython-usage (this skill) | 1 | 8mo | Review | Advanced |
| python-error-handling | 1 | 2mo | No flags | Intermediate |
| debugging-streamlit | 7 | 5mo | Review | Intermediate |
| python-observability | 1 | 2mo | No flags | Intermediate |
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