/configure:memory-profiling

Check and configure memory profiling infrastructure for Python projects using pytest-memray.

When to Use This Skill

Use this skill when...

Use another approach when...

Setting up memory profiling for a Python project from scratch

Project is not Python — memray/pytest-memray are Python-only

Adding pytest-memray integration for CI memory regression detection

Profiling CPU performance — use cProfile or py-spy instead

Configuring memory leak detection in test suites

Running load/stress tests — use

/configure:load-tests

Setting memory thresholds and allocation benchmarks for CI

Quick one-off memory check — run

uv run pytest --memray

directly

Enabling native C extension stack tracking for deep profiling

Profiling production systems live — use memray standalone or Grafana

Context

Project root: !

pwd

Python project: !

find . -maxdepth 1 ( -name 'pyproject.toml' -o -name 'setup.py' )

pytest-memray installed: !

grep -r 'pytest-memray' pyproject.toml requirements*.txt

memray installed: !

grep -r 'memray' pyproject.toml requirements*.txt

Conftest fixtures: !

grep -l 'memray' tests/conftest.py

Memory test files: !

find tests -maxdepth 2 -name 'memory' -o -name 'memray'

Benchmark tests: !

find tests -maxdepth 2 -type d -name 'benchmarks'

CI workflows: !

find .github/workflows -maxdepth 1 -name 'memory'

Memory reports dir: !

find . -maxdepth 1 -type d -name 'memory-reports'

Parameters

Parse from

$ARGUMENTS

:

--check-only

Report memory profiling compliance status without modifications

--fix

Apply all fixes automatically without prompting

--threshold

Set default memory threshold in MB (default: 100)

--native

Enable native stack tracking for C extensions

Supported tools:

Tool

Best For

pytest-memray (recommended)

Test-integrated profiling, CI/CD memory limits, leak detection

memray standalone

Deep analysis, flame graphs, production profiling

tracemalloc

Quick debugging, no dependencies, lightweight

Execution

Execute this memory profiling configuration check:

Step 1: Verify this is a Python project

Read the context values. If no

pyproject.toml

or

setup.py

is found, report "Not a Python project" and stop.

Step 2: Check latest tool versions

Use WebSearch or WebFetch to verify current versions:

pytest-memray

Check

PyPI

memray

Check

PyPI

Step 3: Analyze current memory profiling setup

Check for complete setup:

pytest-memray installed as dev dependency

memray backend installed

pytest configuration in pyproject.toml (markers, addopts)

Memory limit tests using

@pytest.mark.limit_memory

Leak detection enabled (

--memray-leak-detection

)

Native tracking configured (if

--native

flag)

CI/CD integration configured

Reports directory exists

Step 4: Generate compliance report

Print a compliance report covering:

Installation status (pytest-memray, memray, pytest versions)

Configuration (pytest integration, markers, leak detection, native tracking)

Test coverage (memory limit tests, allocation benchmarks)

CI/CD integration (workflow, threshold, artifact upload, trend tracking)

End with overall issue count and recommendations.

If

--check-only

is set, stop here.

Step 5: Install and configure pytest-memray (if --fix or user confirms)

Install pytest-memray:

uv add --group dev pytest-memray

Install native support if

--native

:

uv add --group dev pytest-memray[native]

Update

pyproject.toml

with pytest configuration (markers, filterwarnings)

Create

memory-reports/

directory

Use configuration templates from

REFERENCE.md

Step 6: Create memory profiling test files

Add memory fixtures to

tests/conftest.py

(reports dir setup, threshold fixture, data generator)

Create

tests/test_memory_example.py

with example memory limit tests

Create

tests/benchmarks/test_memory_benchmarks.py

for trend tracking

Use test templates from

REFERENCE.md

Step 7: Add package scripts

Add memory profiling commands to Makefile or pyproject.toml:

test-memory

:

uv run pytest --memray

test-memory-report

Run with bin output + generate flame graph test-memory-leaks : uv run pytest --memray --memray-leak-detection test-memory-native : uv run pytest --memray --native Step 8: Configure CI/CD integration Create .github/workflows/memory-profiling.yml with: Memory profiling on PRs (detect regressions) Scheduled weekly benchmarks for trend tracking Flame graph generation PR comment with results Use workflow template from REFERENCE.md Step 9: Update standards tracking Update .project-standards.yaml : components : memory_profiling : "2025.1" memory_profiling_tool : "pytest-memray" memory_profiling_threshold_mb : 100 memory_profiling_leak_detection : true memory_profiling_ci : true memory_profiling_native : false Step 10: Print final compliance report Print a summary of packages installed, configuration applied, test files created, commands available, CI/CD configured, and next steps for the user. For detailed test templates, CI workflows, and standalone memray commands, see REFERENCE.md . Agentic Optimizations Context Command Quick compliance check /configure:memory-profiling --check-only Auto-fix all issues /configure:memory-profiling --fix Run memory tests uv run pytest --memray Detect memory leaks uv run pytest --memray --memray-leak-detection Run with native tracking uv run pytest --memray --native Generate flamegraph uv run memray flamegraph output.bin -o flamegraph.html Flags Flag Description --check-only Report status without offering fixes --fix Apply all fixes automatically without prompting --threshold Set default memory threshold in MB (default: 100) --native Enable native stack tracking for C extensions Examples

Check compliance and offer fixes

/configure:memory-profiling

Check only, no modifications

/configure:memory-profiling --check-only

Auto-fix with custom threshold

/configure:memory-profiling --fix --threshold 200

Enable native tracking for C extensions

/configure:memory-profiling

--fix

--native

Error Handling

Not a Python project

Skip with message, suggest manual setup

pytest not installed

Offer to install pytest first

memray not supported

Note platform limitations (Linux/macOS only)

Native tracking unavailable

Warn about missing debug symbols

CI workflow exists

Offer to update or skip See Also /configure:tests - Configure testing frameworks /configure:coverage - Code coverage configuration /configure:load-tests - Load and performance testing /configure:all - Run all compliance checks pytest-memray docs : https://pytest-memray.readthedocs.io memray docs : https://bloomberg.github.io/memray