Python Tutorials

By Ryan Wiles


To provide an already technical, but new to Python, audience with a broad yet concise guide to the entire Python ecosystem. Giving them the background and knowledge to select the right tools to manage their environment, develop their applications, package their work, and deploy their code without having to spend a huge amount of time researching each topic individually.

The Tutorials

These tutorials are currently a work in progress. The general outline is presented below. If there’s not a link to that section, then the work for that section is not yet far enough along to share. The sections that have enough done to be helpful will have their links enabled, but at the moment expect frequent changes as I expand, edit, and revise things. The same goes for pages in the sub-sections. More things will be added and linked as they become far enough along to share.

Why am I doing this

There are already tons of quality Python tutorials available online, so why bother creating yet another one?

Basically, I felt that something was missing in the tutorials I’ve seen out there. Python is both a scripting language used by System Administrators as well as a general purpose programming language. People use Python to automate tasks, write games, perform back-end processing, run web applications, do Data Science (both local analysis and running on clusters analyzing large data sets), for research into and running AI algorithms, and training/using ML algorithms. Basically, there is a large ecosystem of tools and libraries built up around Python that can be daunting to learn.

Most of the tutorials that I’ve seen either focus on either just learning the Python language or how to get started on one of the above tracts. For people who have been using Python for a long time, these tutorials may not tell them much if anything new. But for people who are new to python, I wanted to provide a consolidated high-level introduction to Python. Quickly getting them up to speed on both the language and the broader Python ecosystem. My hypothesis is that by presenting the reader with this broad view in a hopefully organized fashion, it will help them to quickly understand the what’s our there, best way to best set up their environment, choose the right tools, start writing high-quality Pythonic code, and be able to correctly package up their work to either share or deploy it.

© 2018 Ryan Wiles