Setup

Last Update : 07 August, 2023 | Published : 20 February, 2023 | 1 Min Read

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.

Let’s create a new environment called zenml_playground.
```
conda create --name zenml_playground python=3.8
```
Activate the virtual environment.
```
conda activate zenml_playground
```
Install ZenML inside the virtual environment.
```
pip install zenml
```
[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]"
```
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.

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