Python Unit Tests

Use this skill before adding, changing, or reviewing Python unit tests. The goal is hermetic tests: behavior-focused, deterministic, isolated, and cheap to run.

Consult these only when the branch needs more context:

• docs/coding-agents/testing.md
• docs/coding-agents/code-quality-rules.md
• docs/development/testing.md
• misc/auto-fixes/fix_template.md

Steps

1. Scope the behavior. Identify the code under test, the caller-visible outcome, and the smallest test file next to it: dimos/core/foo.py gets dimos/core/test_foo.py. Completion: every new or changed test has a named behavior target and lives beside the code it covers.
2. Build a hermetic setup. Use module-level imports, Arrange-Act-Assert structure, fixtures for shared or resource-owning setup, and context managers for one-test local resources. Completion: setup owns all cleanup, restores global state, reuses existing fixtures when they match, and contains no fixed sleeps.
3. Assert the contract. Use small examples and exact expected values. Completion: every test has an unconditional assertion that proves behavior a caller depends on.
4. Mock the boundary. Mock only slow, nondeterministic, or external boundaries. Completion: patches use mocker.patch, mocker.patch.object, or monkeypatch; no direct method assignment or __new__ fixture shells remain.
5. Validate tightly. Run the smallest command that can fail for the change, then broaden only when the edit justifies it. Completion: the relevant pytest command has run, and mypy/pre-commit have run only when production source typing or broad quality gates changed.

Test shape