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  1. Getting Started

Installation

Installing ZenML and getting started.

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Last updated 22 days ago

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Install ZenML

ZenML is a Python package that can be installed directly via pip:

pip install zenml

Note that ZenML currently supports Python 3.9, 3.10, 3.11, and 3.12. Please make sure that you are using a supported Python version.

ZenML comes bundled with a web dashboard that lives inside a . In order to get access to the dashboard locally, you need to launch the . For this, you need to install the optional dependencies for the ZenML Server:

pip install "zenml[server]"

We highly encourage you to install ZenML in a virtual environment. At ZenML, we like to use or to manage our Python virtual environments.

A change in how forking works on Macs running on Apple Silicon means that you should set the following environment variable, which will ensure that your connections to the server remain unbroken:

export OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YES

pip install zenml

You can read more about this . This environment variable is needed if you are working with a local server on your Mac, but if you're just using ZenML as a client / CLI and connecting to a deployed server, then you don't need to set it.

ZenML also publishes nightly builds under the . These are built from the latest (to which work ready for release is published) and are not guaranteed to be stable. To install the nightly build, run:

pip install zenml-nightly
2

Verifying Installations

Once the installation is completed, you can check whether the installation was successful either through Bash or Python:

zenml version
import zenml

print(zenml.__version__)

If you would like to learn more about the current release, please visit our

Running with Docker

zenml is also available as a Docker image hosted publicly on . Use the following command to get started in a bash environment with zenml available:

docker run -it zenmldocker/zenml /bin/bash

If you would like to run the ZenML server with Docker:

docker run -it -d -p 8080:8080 zenmldocker/zenml-server

Deploying the server

Though ZenML can run entirely as a pip package on a local system, complete with the dashboard. You can do this easily:

pip install "zenml[server]"
zenml login --local  # opens the dashboard locally 

However, advanced ZenML features are dependent on a centrally deployed ZenML server accessible to other MLOps stack components. You can read more about it . For the deployment of ZenML, you have the option to either it or register for a free account.

sister repository
ZenML Server and Dashboard locally
virtualenvwrapper
pyenv-virtualenv
here
zenml-nightly package name
develop branch
PyPi package page.
DockerHub
here
self-host
ZenML Pro