cookiecutter VS awesome-python

Sometimes I use this to abstract boilerplate https://github.com/cookiecutter/cookiecutter

It can use a repo as a template.

It supports some interactive questions to choose options but mostly it is jinja templates.

Having libraries would be another option.

Install the cookiecutter package using the following command:

Consider taking a look at cookiecutter to generate projects from templates. There is also cookiecutter-django. As for your environment variables you should have an example .env file containing all the environment variables required by your project (without setting them) that can be safely pushed into your repository for you and other developers to copy into the actual .env file that'll be used by your project (add this file to .gitignore)

The Python Cookiecutter library revolutionizes project development by offering streamlined approach to creating template projects and improving developer experience.

We use cookie cutter templates (the Python project, https://github.com/cookiecutter/cookiecutter ), we prompt for the module & version etc

Why not use cookiecutter or a similar tool designed for making these sorts of project templates?

Is it common? I don't know. Is it useful? Absolutely. There is a tool called cookiecutter that allows you to define your own setup. For example, my cookiecutter setup for a python library is here. You can see what it's like by first installing the cookiecutter cli and then running

Also cookiecutter.

Visual Cookiecutter enhances the functionality of cookiecutter by offering unique features such as required fields, conditional input parameters, optional descriptions, and the ability to fix mistakes easily. This package seamlessly integrates with cookiecutter so that all existing templates work out-of-the-box.

Python: https://github.com/vinta/awesome-python

6) Awesome Python: Embrace the power of Python with this extensive collection of awesome libraries, frameworks, resources, and software. Whether you're a seasoned Pythonista or just starting your journey, this repository is your ultimate guide to maximizing the potential of this versatile language. (https://github.com/vinta/awesome-python)

- https://github.com/vinta/awesome-python

🎇 Repository Link: Awesome Python

Explore here.

I know of curated lists like https://github.com/vinta/awesome-python but they are nowhere close to alternativeto.net in terms of information (relations) and community involvement.

https://github.com/vinta/awesome-python

There are a lot of python packages for engineering and scientific applications (as well as other applications in general, and, thanks to the inherently collaborative nature of free software, they are only growing in quantity and quality. Many MATLAB toolboxes already have Python equivalents.