Python Links

Visual Studio Code

• Visual Studio Code (Windows) - Setting up a Python Development Environment and Complete Overview, by Corey Schafer

• Visual Studio Code (Mac) - Setting up a Python Development Environment and Complete Overview, by Corey Schafer

Python Beginner Tutorials

• 5 Common Python Mistakes and How to Fix Them, by Corey Schafer

• Python Quick Tip: F-Strings - How to Use Them and Advanced String Formatting, by Corey Schafer

• Python Tutorial for Beginners 4: Lists, Tuples, and Sets, by Corey Schafer

• Python Tutorial for Beginners 5: Dictionaries - Working with Key-Value Pairs, by Corey Schafer

• Python Tutorial for Beginners 7: Loops and Iterations - For/While Loops, by Corey Schafer

• Python Tutorial for Beginners 8: Functions, by Corey Schafer

• 10 Python Tips and Tricks For Writing Better Code, by Corey Schafer

• Python Tutorial: Using Try/Except Blocks for Error Handling, by Corey Schafer

• Python 3.7: Encode String Method

Modules from Standard Library

• Python Tutorial: OS Module - Use Underlying Operating System Functionality, by Corey Schafer

• Python Tutorial: Calling External Commands Using the Subprocess Module, by Corey Schafer

• Python Tutorial: re Module - How to Write and Match Regular Expressions (Regex), by Corey Schafer

• Python Tutorial: CSV Module - How to Read, Parse, and Write CSV Files, by Corey Schafer

Advanced Python

• Transforming Code into Beautiful, Idiomatic Python, by Raymond Hettinger

• Python Tutorial: Duck Typing and Asking Forgiveness, Not Permission (EAFP), by Corey Schafer

• Python Tutorial: Unit Testing Your Code with the unittest Module, by Corey Schafer

• Python Tutorial: Decorators - Dynamically Alter The Functionality Of Your Functions, by Corey Schafer

• Python Tutorial: VENV (Windows) - How to Use Virtual Environments with the Built-In venv Module: Corey Schafer again. Virtual environments are kind of an isolated development sandbox, solving a similar problem as containers do, but much more lightweight and Python only.

NumPy and Data Science Tutorials

• Complete Python NumPy Tutorial (Creating Arrays, Indexing, Math, Statistics, Reshaping), by Keith Galli

• Solving real world data science tasks with Python Pandas!, by Keith Galli

• Intro to Data Visualization in Python with Matplotlib! (line graph, bar chart, title, labels, size), by Keith Galli

PyPI (Installing Modules that don’t come as Batteries)

• Python Tutorial: pip - An in-depth look at the package management system, by Corey Schafer

• Packaging, Deployment, PyPI, and pip: Chris Wilcox (of Google) talking about packaging and deployment, and related topics

Git, and Github

• Git Tutorial for Beginners: Command-Line Fundamentals, by Corey Schafer

• Git Tutorial: Fixing Common Mistakes and Undoing Bad Commits, by Corey Schafer

• Git & GitHub Crash Course For Beginners, by Brad Traversy

Conference Talks

David Beazley

• Built in Super Heroes. David Beazley in an entertaining keynote to the “PyData Chicago 2016” conference. He has a number of very good and entertaining (and very advanced) videos. You have to spend an entire evening with him though.

• The Fun of Reinvention - David Beazley - Pycon Israel 2017. David Beazley with an entertaining keynote about typing, type annotations, metaprogramming, contracts.

• Keynote - David Beazley. David Beazley live coding a Web Assembly interpreter. PyCon India 2019.

• David Beazley: Generators: The Final Frontier - PyCon 2014: David Beazley again a bit (a whopping four hours) more precise on that topic.

• Modules and Packages. David Beazley has a three hour (!) really cool and in-depth look into the seemingly simple import mechanism.

• Modules and Packages: Live and Let Die (Screencast). David Beazley dissecting the module loading mechanism (a whopping three hours long).

• Curious Course on Coroutines and Concurrency. David Beazley, entertaining as always. Tutorial session given at PyCon Chicago 2009. (Three hours!)

• Iterations of Evolution: The Unauthorized Biography of the For-Loop. David Beazley giving lessons in history. How for evolved from the beginning until where we are today.

• Understanding the Python GIL: David Beazley dissecting the Global Interpreter Lock, explaining why multiprocessing is better. At around minute 45, in the questions/answers, there is a mention that using NumPy operations in multiple threads is truly parallel.

Raymond Hettinger

• Transforming Code into Beautiful, Idiomatic Python. Raymond Hettinger, reiterating his favorite phrase: “There must be a better way”. (Hettinger is a “Python Core Developer”.)

• Raymond Hettinger - Super considered super! - PyCon 2015. Raymond Hettinger, revolving around super() and MRO.

• Raymond Hettinger, Keynote on Concurrency, PyBay 2017: Raymond Hettinger covering most if not all aspects and possiblities of concurrency. Very informative, very concise, covering

  • Multithreading

  • Multiprocessing

  • Async; I didn’t even mention that. asyncio. Me big fan.