Python Testing (Heavyweight)

Overview

Same philosophy as lightweight testing, but with real infrastructure instead of monkey-patching. Containers, mock servers, custom mock binaries.

When to Use

• Project has external API dependencies
• Features depend on system services (DBus, specific binaries)
• Integration failures are costly to debug
• Lightweight testing can't cover the critical paths

Core Idea

Key Patterns

• Containerized services: docker-compose.test.yml with mock API, test DB
• Mock binaries: real executables that mimic expected behavior
• Session-scoped fixtures: start containers once per test session
• Real DBus: start dbus-daemon --session for tests

Investment Decision

1. Will the project live long enough to justify setup time?
2. Are integration failures actually happening?
3. Can lightweight testing cover 80% of the risk?

If not all three: stick with lightweight.

Reference

See guides/testing-heavyweight.md for container setup, mock binary examples, CI integration, and stateful mock servers.