Python Projects Workflow

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

Introduction
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.
Installation
Git clone this repository:
git clone https://github.com/kyso-io/template
Download and install the Anaconda Python distribution. You can check out our guide on how to install Jupyter with Anaconda, which covers this step.
Installing Jupyter with Anaconda
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
Usage
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:
Introduction to Git
To publish your notebooks for discovery, use any of the two methods below:
Kyso Command Line Tool
Kyso's Git Integration
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.

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Installing Jupyter with Anaconda

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Using SQL in Jupyterlab

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