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:
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git clone https://github.com/kyso-io/template
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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
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conda env create -f environment.yml
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conda activate dev
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Installing Libraries
Install any libraries you need with
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conda install <library>
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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
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conda env export --no-builds > environment.yml
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Usage
Start programming! Open jupyter with
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jupyter lab
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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, import the repository to Kyso:
Connect a Github repo to Kyso
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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