---

name: django-test-profiling description: Profile and measure slow Django test suites with Django's runner, pytest-django, shell timing, py-spy, cProfile, pytest durations, and profiler visualizations. Use when a Django project has slow tests, unclear test-runtime bottlenecks, CI timing problems, startup overhead, database setup overhead, or a request to find the slowest tests before optimizing. license: MIT compatibility: Codex, Claude Code, and other Agent Skills-compatible clients. metadata: version: "0.1.0" displayName: Django Test Profiling category: Django tags: django,testing,profiling,pytest,performance

Django Test Profiling

Use this skill before changing a Django test suite for speed. Measurement decides which optimization is worth doing; otherwise it is easy to spend time on harmless settings while the real cost sits in startup, database setup, fixture construction, or a small set of slow tests.

Measurement Workflow

1. Capture a full wall-clock baseline.

   • Prefer shell timing because it includes Python startup, Django import time, test discovery, database setup, and teardown.
   • Record the exact command, environment, and repeat count.

2. Separate framework phases when possible.

   • For Django's runner, use --timing to see database setup and teardown.
   • For pytest, compare shell timing with pytest --durations.

3. Find the slowest tests.

   • For pytest-django, start with pytest --durations 20.
   • For Django's runner, use an existing slow-test plugin or a small custom runner only when the project does not already have one.

4. Profile only after you know where the time goes.

   • Use py-spy first for a low-overhead whole-run view.
   • Use cProfile when you need exhaustive Python call data.

5. Convert the result into a ranked action list.

   • Identify whether the expensive part is startup, database creation, repeated setup, test data, query count, I/O, cache/file/storage access, or a specific test body.
   • Hand off to django-test-performance, django-test-data, or django-test-parallelization when the next step fits those skills.

Commands

time python manage.py test
python manage.py test --timing
pytest --durations 20

For profiling command variants and interpretation guidance, read profiler-commands.md.

Decision Rules

• Treat shell timing as the authoritative user-visible duration.
• Use Django --timing when database setup or teardown may dominate.
• Optimize the slowest measured tests first, not the tests that look suspicious.
• Put noisy duration reports in CI logs when they distract from normal local runs.
• Use py-spy --subprocesses when the test runner uses child processes.
• Sort cProfile by cumulative time first; inspect self-time only after you understand the caller chain.

Common Mistakes

• Trusting a framework's final "ran in X seconds" line as the complete runtime.
• Comparing Django runner timing and pytest timing as if they measure identical phases.
• Profiling everything before finding slow tests.
• Reading unsorted cProfile output and chasing import internals.
• Expecting sampling profiles to catch every short hot path.
• Optimizing a helper without checking how often it is reached by tests.

Verification

Before reporting findings, include:

• The exact baseline command and measured wall-clock time.
• The slowest tests or slowest phases.
• The profiler used, if any, and why it was appropriate.
• The top 3 practical next actions, ordered by expected impact.