temporal-python-testing

Test Temporal Python workflows using pytest by isolating workflows and activities with time-skipping and mocking. This approach validates orchestration logic locally without waiting for real time delays.

Replay testing ensures backward-compatibility by replaying production histories against new Temporal workflow code. This verifies that updates do not break existing, long-running workflow instances.

Mock activities in Temporal Python integration tests by replacing external dependencies with mocked implementations. This validates workflow orchestration logic without requiring actual external service connections.

Yes, time-skipping allows you to test long-running Temporal workflows by automatically advancing mock clocks. This lets unit tests execute workflows with sleep timers instantly rather than waiting.

Set up a local Temporal server for Python testing using Docker Compose and configure pytest. This environment provides the infrastructure to run and validate workflow integration tests efficiently during local development.

Temporal workflow tests fail after code updates when changes break determinism or backward compatibility. Use replay testing against production histories to identify incompatible modifications in your workflow logic.