cadence-python-client 0.2.3

Python framework for authoring Cadence workflows and activities

Python framework for Cadence

Cadence is a distributed, scalable, durable, and highly available orchestration engine we developed at Uber Engineering to execute asynchronous long-running business logic in a scalable and resilient way.

If you'd like to propose a new feature, first join the CNCF Slack workspace in the #cadence-users channel to start a discussion.

cadence-python-client is the Python framework for authoring workflows and activities.

Disclaimer

This SDK is currently an early work-in-progress (WIP) and is NOT ready for production use.

• This project is still in active development
• APIs and interfaces are subject to change without notice

Installation

Install from PyPI:

pip install cadence-python-client

Or with uv:

uv add cadence-python-client

The core package supports Python >=3.11,<3.14.

Clone the repository if you want to develop locally:

git clone https://github.com/cadence-workflow/cadence-python-client.git
cd cadence-python-client

Development

Setup

1. Install protobuf (required):

   # macOS
   brew install protobuf@29
   
   # Linux/Other
   # Install protobuf 29.x via your package manager
   

2. Install uv (recommended):

   # macOS
   brew install uv
   
   # Linux/Other
   curl -LsSf https://astral.sh/uv/install.sh | sh
   source $HOME/.local/bin/env  # Add to your shell profile for persistence
   

3. Create virtual environment and install dependencies:

   uv sync --all-extras
   

   Or if you prefer traditional pip:

   python3.11 -m venv venv
   source venv/bin/activate  # Windows: venv\Scripts\activate
   pip install -e ".[dev]"
   

Generate Protobuf and gRPC Files

Run the generation script only if you change files under idls/proto/:

# Recommended
make generate

# Or run the script directly
uv run python scripts/generate_proto.py

This will:

• Generate Python protobuf files in cadence/api/v1/
• Generate gRPC service files in cadence/api/v1/
• Refresh the package imports for the generated modules

Test

Run the main checks:

make lint
make type-check
make test

Run integration tests with Docker:

make integration-test

You can also verify the generated files manually:

uv run python cadence/sample/simple_usage_example.py
uv run python cadence/sample/grpc_usage_example.py

Development Commands

The current repository workflow is centered on make targets:

make install
make generate
make lint
make type-check
make test
make integration-test
make pr

License

Apache 2.0 License, please see LICENSE for details.