/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: !find . -maxdepth 1 $ -name 'pyproject.toml' -o -name 'requirements*.txt' $ -exec grep 'pytest-memray' {} +
memray installed: !find . -maxdepth 1 $ -name 'pyproject.toml' -o -name 'requirements*.txt' $ -exec grep 'memray' {} +
Conftest fixtures: !find . -path '*/tests/*' -maxdepth 2 -name 'conftest.py' -exec grep -l 'memray' {} +
Memory test files: !find . -path '*/tests/*' -maxdepth 3 -name '*memory*' -o -name '*memray*'
Benchmark tests: !find . -path '*/tests/*' -maxdepth 3 -type d -name 'benchmarks'
CI workflows: !find . -path '*/.github/workflows/*' -maxdepth 3 -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 <mb>: 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 <mb>`	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

configure-memory-profiling