setup-python-dev-env.md

Setup a Local Python Dev Environment

Step-1: Anaconda Python environment

You can install Anaconda by following the guide here.

Step-2: Create a custom environment

We will create an environment for this workshop with all the required libraries installed.

conda create -n data-prep-kit-1 -y python=3.11

Activate the new conda environment

conda activate data-prep-kit-1

Make sure env is swithced to data-prep-kit-1.

Make sure python version is 3.11

python --version

Note: If you are on a linux system install these too

conda install -y gcc_linux-64

conda install -y gxx_linux-64

Get the repo

git   clone  https://github.com/sujee/data-prep-kit-examples

cd  data-prep-kit-examples

install all needed packages

pip install -r requirements.txt

Install a custom kernel

python -m ipykernel install --user --name=data-prep-kit --display-name "dataprepkit"

Start-3: Start Jupyter

jupyter lab

Troubleshooting

If libraries are not loading in Jupyter: Select custom Kernel

When running Jupyter notebooks, if data prep kit libraries are not found, try selecting the custom kernel you created (dataprepkit)