Practical Python Programming

Overview

Welcome!

When I first learned Python nearly 25 years ago, I was immediately struck by how I could productively apply it to all sorts of messy work projects. Fast-forward a decade and I found myself teaching others the same fun. The result of that teaching is this course--A no-nonsense treatment of Python that has been actively taught to more than 400 in-person groups since 2007. Traders, systems admins, astronomers, tinkerers, and even a few hundred rocket scientists who used Python to help land a rover on Mars--they've all taken this course. Now, I'm pleased to make it available under a Creative Commons license. Enjoy!

GitHub Pages | GitHub Repo.

--David Beazley (https://dabeaz.com), @dabeaz

What is This?

The material you see here is the heart of an instructor-led Python training course used for corporate training and professional development. It has been in continual development since 2007 and battle tested in real-world classrooms. Usually, it's taught in-person over the span of three or four days--requiring approximately 25-35 hours of intense work. This includes the completion of approximately 130 hands-on coding exercises.

Target Audience

Students of this course are usually professional scientists, engineers, and programmers who already have experience in at least one other programming language. No prior knowledge of Python is required, but knowledge of common programming topics is assumed. Most participants find the course challenging--even if they've already been doing a bit of Python programming.

Course Objectives

The goal of this course is to cover foundational aspects of Python programming with an emphasis on script writing, data manipulation, and program organization. By the end of this course, students should be able to start writing useful Python programs on their own or be able to understand and modify Python code written by their coworkers.

Requirements

To complete this course, you need nothing more than a basic installation of Python 3.6 or newer and time to work on it.

What This Course is Not

This is not a course for absolute beginners on how to program a computer. It is assumed that you already have programming experience in some other programming language or Python itself.

This is not a course on web development. That's a different circus. However, if you stick around for this circus, you'll still see some interesting acts--just nothing involving animals.

This is not a course for software engineers on how to write or maintain a one-million line Python application. I don't write programs like that, nor do most companies who use Python, and neither should you. Delete something already!

Take me to the Course Already!

Ok, ok. Point your browser HERE!

Community Discussion

Want to discuss the course? You can join the conversation on Gitter. I can't promise an individual response, but perhaps others can jump in to help.

Acknowledgements

Llorenç Muntaner was instrumental in converting the course content from Apple Keynote to the online structure that you see here.

Various instructors have presented this course at one time or another over the last 12 years. This includes (in alphabetical order): Ned Batchelder, Juan Pablo Claude, Mark Fenner, Michael Foord, Matt Harrison, Raymond Hettinger, Daniel Klein, Travis Oliphant, James Powell, Michael Selik, Hugo Shi, Ian Stokes-Rees, Yarko Tymciurak, Bryan Van de ven, Peter Wang, and Mark Wiebe.

I'd also like to thank the thousands of students who have taken this course and contributed to its success with their feedback and discussion.

Questions and Answers

Q: Are there course videos I can watch?

No. This course is about you writing Python code, not watching someone else.

Q: How is this course licensed?

Practical Python Programming is licensed under a Creative Commons Attribution ShareAlike 4.0 International License.

Q: May I use this material to teach my own Python course?

Yes, as long as appropriate attribution is given.

Q: May I make derivative works?

Yes, as long as such works carry the same license terms and provide attribution.

Q: Can I translate this to another language?

Yes, that would be awesome. Send me a link when you're done.

Q: Can I live-stream the course or make a video?

Yes, go for it! You'll probably learn a lot of Python doing that.

Q: Why wasn't topic X covered?

There is only so much material that you can cover in 3-4 days. If it wasn't covered, it was probably because it was once covered and it caused everyone's head to explode or there was never enough time to cover it in the first place. Also, this is a course, not a Python reference manual.

Q: Do you accept pull requests?

Bug reports are appreciated and may be filed through the issue tracker. Pull requests are not accepted except by invitation. Please file an issue first.

Clases y ejercicios del curso de python diactodo por la UNSAM

Programación en Python En el marco del proyecto de Inteligencia Artificial Interdisciplinaria, la Escuela de Ciencia y Tecnología de la UNSAM vuelve a

Maximiliano Villalva 3 Jan 06, 2022
Contains the assignments from the course Building a Modern Computer from First Principles: From Nand to Tetris.

Contains the assignments from the course Building a Modern Computer from First Principles: From Nand to Tetris.

Matheus Rodrigues 1 Jan 20, 2022
Yu-Gi-Oh! Master Duel translation script

Yu-Gi-Oh! Master Duel translation script

715 Jan 08, 2023
A document format conversion service based on Pandoc.

reformed Document format conversion service based on Pandoc. Usage The API specification for the Reformed server is as follows: GET /api/v1/formats: L

David Lougheed 3 Jul 18, 2022
A Sublime Text plugin to select a default syntax dialect

Default Syntax Chooser This Sublime Text 4 plugin provides the set_default_syntax_dialect command. This command manipulates a syntax file (e.g.: SQL.s

3 Jan 14, 2022
Dynamic Resume Generator

Dynamic Resume Generator

Quinten Lisowe 15 May 19, 2022
Generate a backend and frontend stack using Python and json-ld, including interactive API documentation.

d4 - Base Project Generator Generate a backend and frontend stack using Python and json-ld, including interactive API documentation. d4? What is d4 fo

Markus Leist 3 May 03, 2022
Feature Store for Machine Learning

Overview Feast is an open source feature store for machine learning. Feast is the fastest path to productionizing analytic data for model training and

Feast 3.8k Dec 30, 2022
sphinx builder that outputs markdown files.

sphinx-markdown-builder sphinx builder that outputs markdown files Please ★ this repo if you found it useful ★ ★ ★ If you want frontmatter support ple

Clay Risser 144 Jan 06, 2023
A PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.

Deep SAD: A Method for Deep Semi-Supervised Anomaly Detection This repository provides a PyTorch implementation of the Deep SAD method presented in ou

Lukas Ruff 276 Jan 04, 2023
Tutorial for STARKs with supporting code in python

stark-anatomy STARK tutorial with supporting code in python Outline: introduction overview of STARKs basic tools -- algebra and polynomials FRI low de

121 Jan 03, 2023
A Power BI/Google Studio Dashboard to analyze previous OTC CatchUps

OTC CatchUp Dashboard A Power BI/Google Studio dashboard analyzing OTC CatchUps. File Contents * ├───data ├───old summaries ─── *.md ├

11 Oct 30, 2022
Bring RGB to life in Neovim

Bring RGB to life in Neovim Change your RGB devices' color depending on Neovim's mode. Fast and asynchronous plugin to live your vim-life to the fulle

Antoine 40 Oct 27, 2022
A swagger tool for tornado, using python to write api doc!

SwaggerDoc About A swagger tool for tornado, using python to write api doc! Installation pip install swagger-doc Quick Start code import tornado.ioloo

aaashuai 1 Jan 10, 2022
Zero configuration Airflow plugin that let you manage your DAG files.

simple-dag-editor SimpleDagEditor is a zero configuration plugin for Apache Airflow. It provides a file managing interface that points to your dag_fol

30 Jul 20, 2022
Modified fork of CPython's ast module that parses `# type:` comments

Typed AST typed_ast is a Python 3 package that provides a Python 2.7 and Python 3 parser similar to the standard ast library. Unlike ast up to Python

Python 217 Dec 06, 2022
30 Days of google cloud leaderboard website

30 Days of Cloud Leaderboard This is a leaderboard for the students of Thapar, Patiala who are participating in the 2021 30 days of Google Cloud Platf

Developer Student Clubs TIET 13 Aug 25, 2022
FireEye Related Projects

FireEye FireEye Related Projects Tor-IP-Collector Simple python script that will collect a list of TOR IPs from the SecOps Institute Github and inject

Taran Ulrich 2 Nov 12, 2022
Seamlessly integrate pydantic models in your Sphinx documentation.

Seamlessly integrate pydantic models in your Sphinx documentation.

Franz Wöllert 71 Dec 26, 2022
Python document object mapper (load python object from JSON and vice-versa)

lupin is a Python JSON object mapper lupin is meant to help in serializing python objects to JSON and unserializing JSON data to python objects. Insta

Aurélien Amilin 24 Nov 09, 2022