How to make your system ZenML Ready

ZenML comes as a Python library so it is necessary to have a python>=3.7,<= 3.10 installed on your local machine.
Virtual environments let’s you have a stable, reproducible, and portable environment. You are in control of which package versions are installed and when they are upgraded.
I use Anaconda to create and manage my Python envionments but you can also use pyenv-virtualenv or python -m venv.

1. Let’s create a new environment called zenml_playground.

conda create --name zenml_playground python=3.8

2. Activate the virtual environment.

conda activate zenml_playground

3. Install ZenML inside the virtual environment.

pip install zenml

4. [Optional] In order to get access to the ZenML dashboard locally you need to launch ZenML Server and Dashboard locally. For this, you need to install ZenML Server separately.

pip install "zenml[server]"

5. To verify if the installation is completed start Python interpreter and try to import zenml.

import zenml
print(zenml.__version__)

If you see a ZenML version displayed on your command prompt then you are all set to explore ZenML Steps and Pipelines.