This example demonstrates how to structure a Durable Task Python project so that orchestrators and activities are defined separately from infrastructure code, enabling fast, fully in-process unit tests using the in-memory backend.

You can copy this entire folder into a new directory and run it as a standalone project.

in_memory_backend_example/
├── README.md
├── requirements.txt
├── src/
│   ├── __init__.py
│   ├── workflows.py   # Orchestrators & activities (pure logic, no infra)
│   └── app.py          # Runs workflows against a real DTS backend
└── test/
    ├── __init__.py
    └── test_workflows.py  # Unit tests using the in-memory backend

• src/workflows.py — All orchestrator and activity definitions live here. They import only from durabletask and have no dependency on a particular backend, making them portable and testable.

• src/app.py — The entry point that wires up the real Durable Task Scheduler (or emulator) client and worker, registers the workflow functions, and schedules an orchestration.

• test/test_workflows.py — Pytest tests that exercise every workflow path using create_test_backend(). No sidecar, emulator, or Azure resources are needed.

1. Copy this folder to a new location and cd into it:

   cd in_memory_backend_example

2. Create and activate a virtual environment:

   Bash:

   python -m venv .venv
   source .venv/bin/activate

   PowerShell:

   python -m venv .venv
   .\.venv\Scripts\Activate.ps1

3. Install dependencies:

   pip install -r requirements.txt

From the in_memory_backend_example/ directory:

pytest test/

Start the DTS emulator, then from the in_memory_backend_example/ directory:

python -m src.app