<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Cookiecutter on DataThrillz</title><link>https://datathrillz.com/tags/cookiecutter/</link><description>Recent content in Cookiecutter on DataThrillz</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 25 Jan 2021 18:09:45 +0000</lastBuildDate><atom:link href="https://datathrillz.com/tags/cookiecutter/index.xml" rel="self" type="application/rss+xml"/><item><title>Creating Projects from Cookiecutter Templates</title><link>https://datathrillz.com/posts/2021-01-25-creating-projects-from-cookiecutter-templates/</link><pubDate>Mon, 25 Jan 2021 18:09:45 +0000</pubDate><guid>https://datathrillz.com/posts/2021-01-25-creating-projects-from-cookiecutter-templates/</guid><description>&lt;p&gt;Ever want to generate a new repo based on a predefined template? Now you can using &lt;a href="https://cookiecutter.readthedocs.io/en/1.7.2/README.html"&gt;Cookiecutter&lt;/a&gt;! I will show you how to easily spin up a fresh Cookiecutter repo for your latest data science project in Python.&lt;/p&gt;
&lt;p&gt;Cookiecutter is an awesome command-line tool and Python package that creates projects (aka populates repo folders) based on cookiecutters (or project templates). What does this mean? Goodbye to manually copying and pasting old project repos. Now, you can automatically clone one of the thousands of cookiecutters or you can create your own.&lt;/p&gt;</description></item></channel></rss>