temporal-python-testing

Test Temporal workflows with pytest by configuring WorkflowEnvironment to enable time-skipping, allowing fast and deterministic execution of workflow logic without real-time delays. This approach uses ActivityEnvironment for unit testing and mocked activities for integration scenarios.

Mocking activities in Temporal Python tests involves using ActivityEnvironment to isolate workflow logic and inject controlled responses or failures. This ensures deterministic integration testing by validating how workflows handle mocked activity failures and edge cases without external dependencies.

A local Temporal server is required for end-to-end integration testing and local development setup. However, unit tests utilizing time-skipping and ActivityEnvironment can run deterministically without a live server, providing faster feedback during development.

Replay testing validates Temporal workflow determinism by replaying production event histories against the current workflow code to ensure consistent execution. This technique catches non-deterministic changes in workflow logic by comparing replayed outputs against recorded historical state transitions.

You can integrate Temporal pytest tests into CI/CD pipelines by executing time-skipping unit tests and replay tests as automated validation steps. The provided testing patterns support continuous integration by ensuring workflow determinism and validating failure scenarios on every code change.