Python Projects Workflow
This is a guide on our recommended workflow for all your python projects.


As part of our template libraries, we have set up a baseline project that anyone can use to get started writing a Kyso template. But it is also applicable for any of your data science projects if you use python and Jupyter notebooks.


Git clone this repository:
git clone
Download and install the Anaconda Python distribution. You can check out our guide on how to install Jupyter with Anaconda, which covers this step.
Then active a conda virtual environment with
conda env create -f environment.yml
conda activate dev

Installing Libraries

Install any libraries you need with
conda install <library>
Make sure to run the following command to save the installed libraries into the environment.yml file, this allows others to run the report easily
conda env export --no-builds > environment.yml


Start programming! Open jupyter with
jupyter lab
and start working.

Publishing & Sharing

Push to Github as per usual. If you are new to Git, we have written a tutorial for beginners, which covers the basics:
To publish your notebooks for discovery, use any of the two methods below:
And that's it! Once your repository is connected to Kyso, every time you push a new commit - updates to existing posts or entirely new projects - these changes will be automatically reflected on your Kyso dashboard.