Eclipse zenoh Python API

Eclipse zenoh is an extremely efficient and fault-tolerant Named Data Networking (NDN) protocol that is able to scale down to extremely constrainded devices and networks.

Check the website zenoh.io and the roadmap for more detailed information.

How to install it

The Eclipse zenoh-python library is available on Pypi.org. Install the latest available version using pip:

pip install eclipse-zenoh

To install the latest nightly build of the development version do:

pip install eclipse-zenoh-nightly

⚠️WARNING⚠️ zenoh-python is developped in Rust. On Pypi.org we provide binary wheels for the most common platforms (MacOS, Linux x86). But also a source distribution package for other platforms. However, for pip to be able to build this source distribution, there some prerequisites:

• pip version 19.3.1 minimum (for full support of PEP 517). (if necessary upgrade it with command: 'sudo pip install --upgrade pip' )
• Have a Rust toolchain installed (instructions at https://rustup.rs/)

Supported Python versions and platforms

zenoh-python has been tested with Python 3.6, 3.7, 3.8 and 3.9.

It relies on the zenoh Rust API which require the full std library. See the list Rust supported platforms here: https://doc.rust-lang.org/nightly/rustc/platform-support.html .

How to build it

Requirements:

• Python >= 3.7
• pip >= 19.3.1
• Rust and Cargo.

Steps:

• Install developments requirements:

  pip install -r requirements-dev.txt
  

• Ensure your system can find the building tool maturin. For example, it is placed at $HOME/.local/bin/maturin by default on Ubuntu 20.04.

  export PATH="$HOME/.local/bin:$PATH"
  

• Build zenoh-python

  maturin build --release
  

This will automatically build the zenoh Rust API, as well as the zenoh-python API and install it in your Python environement.

Running the Examples

The simplest way to run some of the example is to get a Docker image of the zenoh network router (see https://github.com/eclipse-zenoh/zenoh#how-to-test-it) and then to run the examples on your machine.

Then, run the zenoh-python examples following the instructions in examples/zenoh/README.md