You probably have heard of the bestselling Python book, “Automate the Boring Stuff with Python.” What are the next steps after starting to dabble in the Python basics? Maybe you’ve completed some tutorials, created a few scripts, and automated repetitive tasks in your life. This week on the show, we have author Al Sweigart to talk about his new book, “Beyond the Basic Stuff with Python: Best Practices for Writing Clean Code.”

We discuss several topics covered in his new book, including using the command line, setting environment variables, formatting code, naming, and starting with version control. We talk about learning Python by creating games and highlight a couple of Python myths. I also ask Al about his earlier books, and about his idea of creating a curriculum around conference talks.

Course Spotlight: Unicode in Python: Working With Character Encodings

In this course, you’ll get a Python-centric introduction to character encodings and Unicode. Handling character encodings and numbering systems can at times seem painful and complicated, but this guide is here to help with easy-to-follow Python examples.

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Do you have gaps in your Python learning path? If you’re like me, you may have followed a completely random route to learn Python. This week on the show, David Amos is here to talk about the release of the Real Python book, “Python Basics: A Practical Introduction to Python 3”. The book is designed not only to get beginners up to speed but also to help fill in the gaps many intermediate learners may still have.

David has been working on the book for the last two years, and we dive into all the resources that come with it. These include code challenges, quizzes, and multiple projects that are designed to help you cement your learning. We also discuss the people and processes involved in creating, reviewing, and updating the book.

Spotlight: Python Basics: A Practical Introduction to Python 3

Go from beginner to intermediate in Python with this complete curriculum, up-to-date for Python 3.9. Python Basics includes exercises, interactive quizzes, and sample projects, so you’ll always know what to focus on next in order to build a strong Python foundation.

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The Python return statement is such a fundamental part of writing functions. Is it possible you missed some best practices when writing your own return statements? This week on the show, David Amos returns with another batch of PyCoder’s Weekly articles and projects. We also talk functional programming again with an article on the Python map function and processing iterables without a loop.

We cover several other articles and projects from the Python community including, interactive data visualization with Pygal, everything you need to know about namedtuples, PEP 638 syntactic macros, python for kids, the new Nvidia Jetson board, and a reinforcement learning project named football.

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Interactive Data Visualization in Python With Pygal – Pygal is an overlooked library for creating interactive plots that can be turned into SVGs with an optimal resolution for printing or displaying on webpages. Learn how it works in this introductory tutorial.

Python’s map(): Processing Iterables Without a Loop – In this step-by-step tutorial, you’ll learn how Python’s map() works and how to use it effectively in your programs. You’ll also learn how to use list comprehension and generator expressions to replace map() in a Pythonic and efficient way.

Everything You Need to Know About Python’s NamedTuples – Are you using NamedTuple in your code? If you aren’t, learn what they are and why you should consider using them in this comprehensive tutorial.

PEP 638: Syntactic Macros – This brand new PEP, which is still in draft mode, proposes adding support for syntactic macros to Python. Syntactic macros are compile-time functions that extend the language’s syntax without adding any new complexity to the language as a whole.

The Python return Statement: Usage and Best Practices – In this step-by-step tutorial, you’ll learn how to use the Python return statement when writing functions. Additionally, you’ll cover some good programming practices related to the use of return. With this knowledge, you’ll be able to write readable, robust, and maintainable functions in Python.

Python for Kids – In this ten part series, senior software engineer Kevin Thomas presents a kid-friendly comprehensive Python development tutorial utilizing a micro:bit development board. The GitHub repo contains all of the sample code as well as links to each tutorial in the series on LinkedIn. The first seven parts are published and the last three are coming soon!

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Build a Face Recognition System With the Nvidia Jetson Nano 2GB and Python – The Nvidia Jetson Nano is a single board computer similar to a Raspberry Pi. The Jetson Nano really packs a punch, however, thanks to its onboard Nvidia Maxwell GPU.

football: Reinforcement Learning Environment Where Agents Learn to Play Football

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Python 3.9 has arrived! This week on the show, former guest and Real Python author Geir Arne Hjelle returns to talk about his recent article, “Python 3.9: Cool New Features for You to Try”. Also joining the conversation is Real Python video course instructor and author Christopher Trudeau. Christopher has created a video course, which was released this week also, based on Geir Arne’s article. We talk about time zones, merging dictionaries, the new parser, type hints, and more.

Geir Arne and Christopher not only cover the new features, but they also offer advice about ways you might incorporate them into your code. We discuss what you should think about before updating your code.

Course Spotlight: Cool New Features in Python 3.9

In this course, you’ll explore some of the coolest and most useful features in the newly released Python 3.9. You’ll learn how Python 3.9 makes it easier to work with time zones, dictionaries, decorators, and several other techniques that will make your code cleaner and more efficient.

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If you use Python, then you probably have used pip to install additional packages from the Python package index. Part of the magic behind pip is the dependency resolver, and there is a new version of it in the latest version of pip. This week on the show, we have Sumana Harihareswara and Georgia Bullen, who have been working on the recent releases of pip. Sumana is the project manager for pip, and Georgia has been working on pip’s user experience (UX).

The resolver is how pip determines what to install, and in what order, based on package requirements. We talk about how you can help, from updating to the latest release, testing out the new resolver with your projects, and answering surveys about your experiences. A ton of work has gone into making the updates this year. We also talk about the funding of projects like this in the open-source community.

Course Spotlight: A Beginner’s Guide to Pip

This course is a great introduction to pip for those who are getting started Python, and for those who want to understand more about what is happening when you install new packages into your environment. It’s a worthy investment of your time to understand the fundamentals of pip.

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A big decision a developer has to make is what tool to use to write code? Would you like an editor that understands Python, and is there to help with suggestions, definitions, and analysis of your code? For many developers, its the free tool, Visual Studio Code. This week on the show, we have Savannah Ostrowski, program manager for the Python Language Server and Python in Visual Studio. We discuss Pylance, a new language server with fast, feature-rich language support for Python in VS Code.

Savannah explains what a language server is and the types of features it can provide. This includes type information, code completion, automatic-imports, dead code analysis, code navigation, and more. We also have a discussion about type checking in Python, which led to how Pylance leverages the static type checking tool Pyright, and what are type stubs (.pyi files).

Course Spotlight: Python Type Checking

In this course, you’ll look at Python type checking. Traditionally, types have been handled by the Python interpreter in a flexible but implicit way. Recent versions of Python allow you to specify explicit type hints that can be used by different tools to help you develop your code more efficiently.

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What is an effective way to prepare for a Python interview? Would you like a set of problems that increase in difficulty to practice and hone your Python skills? This week on the show, we have Jim Anderson to talk about his new Real Python article, “Python Practice Problems: Get Ready for Your Next Interview.” This article provides several problems, which include skeleton code, unit tests, and solutions for you to compare your work.

David Amos also joins us this week, and he has brought another batch of PyCoder’s Weekly articles and projects from the Python community. We cover these topics: Structural Pattern Matching, Common Python Data Structures, A Tax Attorney Uses Python, Discover the Role of Python in Space Exploration, and Five Pairs of Magic Methods in Python That You Should Know.

Course Spotlight: How to Implement a Python Stack

In this course, you’ll learn how to implement a Python stack. You’ll see how to recognize when a stack is a good choice for data structures, how to decide which implementation is best for a program, and what extra considerations to make about stacks in a threading or multiprocessing environment.

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Python Practice Problems: Get Ready for Your Next Interview – Are you a Python developer brushing up on your skills before an interview? If so, then this tutorial will usher you through a series of Python practice problems meant to simulate common coding test scenarios.

“Structural Pattern Matching”; for Python, Part 2 – The saga of PEP 622 continues with updates to the proposed structure of the match statement—which has some similarities to a switch statement—and a discussion on the best way to document objections to a PEP.

Common Python Data Structures (Guide) – In this tutorial, you’ll learn about Python’s data structures. You’ll look at several implementations of abstract data types and learn which implementations are best for your specific use cases.

A Tax Attorney Uses Python – See how one tax attorney uses Python to automate grueling and repetitive tasks and improve his business. While the article is non-technical, it’s always fun to see how Python is used in diverse fields.

Discover the Role of Python in Space Exploration – In this learning path from Microsoft, you’ll get an introduction to Python, and be inspired to learn, discover, and create using Python-based data science and machine learning to help generate knowledge about the world beyond Earth.

5 Pairs of Magic Methods in Python That You Should Know – Magic, or “dunder,” methods are an important part of creating custom classes in Python. Learn about some commonly used magic methods by exploring hem in pairs that are frequently used together.

python-adventure: Original Colossal Caves Adventure Game, but in Python 3

clifford: Geometric Algebra for Python

pippi: Computer Music With Python

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Why is Python pulling in so many new programmers? Maybe some of that growth is from Python being a full-spectrum language. This week on the show we have Michael Kennedy, the host of the podcast “Talk Python to Me”. Michael reflects on five years of podcasting about Python, and many of the changes he has seen in the Python landscape.

We discuss several stories about the different ways Python is being used, and how that is drawing in many new programmers. Michael covers some potential Python stumbling blocks of Async, the Python Global Interpreter Lock (GIL), building desktop apps, and type checking. We also talk about how podcasts can act as a form of language immersion.

Course Spotlight: Editing Excel Spreadsheets in Python With openpyxl

In this course, you’ll learn how to handle spreadsheets in Python using the openpyxl package. You’ll learn how to manipulate Excel spreadsheets, extract information from spreadsheets, create simple or more complex spreadsheets, including adding styles, charts, and so on.

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Wouldn’t it be nice to a use a form of version control for data? Something that would allow you to track and version your datasets and models. Well, that’s what the tool called DVC is designed to do. This week on the show, David Amos is here and he’s brought another batch of PyCoder’s Weekly articles and projects.

David starts with a Real Python article titled, “Data Version Control With Python and DVC”. We also cover several other articles and projects from the Python community including: where to get exposure to well-written code, delegation – composition and inheritance, good Python project ideas for high school students, never run Python in your downloads folder, and more.

We also have a special guest this week. I talk to Sadie Parker, who recently joined the Real Python team to help create and edit transcripts for all the Real Python video courses. We talk about how to take advantage of all the features this new resource provides. Sadie also discusses how she uses Python to speed up and simplify the editing process. The transcripts and closed captions are now live on the website for all new courses, and we are working through the back catalog.

Course Spotlight: Parallel Iteration With Python’s zip() Function

In this course, you’ll learn how to use the Python zip() function to solve common programming problems. You’ll learn how to traverse multiple iterables in parallel and create dictionaries with just a few lines of code.

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Data Version Control With Python and DVC – In this tutorial, you’ll learn to use DVC, a powerful tool that solves many problems encountered in machine learning and data science. You’ll find out how data version control helps you to track your data, share development machines with your team, and create easily reproducible experiments!

Where Do You Go to Get Exposure to Well-Written Code? – Maybe someone needs to start a Python reading club…

Delegation: Composition and Inheritance in Object-Oriented Programming – Delegation is often considered one of the three pillars of object-oriented programming. Learn how to use this powerful concept in Python.

What Are Some Good Python Project Ideas for High School Students? – Honestly, some of these ideas are good for any beginning Pythonista!

Never Run Python in Your Downloads Folder – Learn about security issues that exploit how Python interacts with PATH and why you should always think twice about your current working directory.

present: A Terminal-Based Presentation Tool With Colors and Effects

Mini Raspberry Pi Boston Dynamics–inspired Robot – See how one Redditor taught themselves robotics by building a miniature version of a Boston Dynamic’s robot dog “Spot” using a Raspberry Pi, C++, and Python.

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Have you wondered, how should I package my Python code? You’ve written the application, but now you need to distribute it to the machines it’s intended to run on. It depends on what the code is, the libraries it depends on, and with whom do you want to share it. This week on the show we have Itamar Turner-Trauring, creator of the website pythonspeed.com. We discuss his article “Options for Packaging Your Python Code: Wheels, Conda, Docker, and More,” covering the how of sharing your code.

Itamar also briefly discusses his Python memory profiler named Fil. We talk about his recent PyCon 2020 presentation, “Small Big Data: What to do When Your Data Doesn’t Fit in Memory.” We also cover several of the resources available on his website for data scientists that want to get deeper into Docker.

Course Spotlight: Python Coding Interviews: Tips & Best Practices

In this step-by-step course, you’ll learn how to take your Python coding interview skills to the next level and use Python’s built-in functions and modules to solve problems faster and more easily.

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