Stay ConnectedA weekly Python podcast hosted by Christopher Bailey with interviews, coding tips, and conversation with guests from the Python community.
The show covers a wide range of topics including Python programming best practices, career tips, and related software development topics. Join us every Friday morning to hear what’s new in the world of Python programming and become a more effective Pythonista.
Copyright: © 2020 Real Python
What if you didn’t have to worry about managing user passwords as a Python developer? That’s where the WebAuthn protocol and new hardware standards are heading. This week on the show, Dan Moore from FusionAuth returns to discuss a password-less future.
WebAuthn is a way to authenticate users using biometric, secure authentication methods. Dan dives into passkeys, ceremonies, authenticators, and hardware standards. We also cover several projects and libraries that can help you get started with WebAuthn in Python.
Course Spotlight: Refactoring: Prepare Your Code to Get Help
In this Code Conversation video course, you’ll explore the steps you can take to get help when you’re stuck while coding. You’ll investigate how to clean up your code to focus on the question you have. Along the way, you’ll learn how to handle errors and use custom exceptions.
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How do you create a computer opponent for a simple game within Python? Would you also like to learn how to adapt the game to run in a web browser or graphical user interface (GUI)? This week on the show, Christopher Trudeau is here, bringing another batch of PyCoder’s Weekly articles and projects.
Christopher shares a recent Real Python step-by-step project for creating a tic-tac-toe game engine. He talks about how to build the game engine and adapt it for different front ends. The tutorial also shows how to implement an unbeatable computer player using the minimax algorithm.
We discuss an article about how to avoid repeating yourself when creating decorators with multiple parameters. We talk about how you can stop copying and pasting code several times by assigning the decorator to a new variable.
We share several other articles and projects from the Python community, including a news roundup, a deep dive into Python’s doctest, several Python command line tricks, type annotations via automated refactoring, a new way to draw boxes in the terminal, a collection of projects for beginners with source code, a minimalist PDF creation library, and a tool for sensible logging in Python.
Course Spotlight: Python Decorators 101
In this course on Python decorators, you’ll learn what they are and how to create and use them. Decorators provide a simple syntax for calling higher-order functions in Python. By definition, a decorator is a function that takes another function and extends the behavior of the latter function without explicitly modifying it.
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Our TOPPODCAST Picks python -m you can do all sorts of things from the command line, including starting a webserver, opening a browser, parsing JSON, compressing files, and much more.Discussion:
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log2d, a third-party wrapper for the Python logging library.Additional Links:
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Python 3.11 is here! Our regular guests, Geir Arne Hjelle and Christopher Trudeau, return to talk about the new version. Geir Arne wrote a series of preview tutorials earlier this year, and his annual piece, titled “Python 3.11: Cool New Features for You to Try,” was published on October 24. Christopher’s video course came out the next day, covering the topics from the tutorial with visual examples of Python 3.11 in action.
Geir Arne and Christopher collaborated to create code examples for the new features. We discuss better error messages, faster code execution, task and exception groups, typing features, and native TOML support.
We dive into the updates and offer advice about ways to incorporate them into your projects. We also consider when you should start running Python 3.11.
Course Spotlight: Cool New Features in Python 3.11 – Real Python
In this video course, you’ll explore what Python 3.11 brings to the table. You’ll learn how Python 3.11 is the fastest and most user-friendly version of CPython yet, and learn about improvements to the typing system and to the asynchronous features of Python.
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Does your company have a plan for growing an internal Python community? What are the attributes to look for when bringing someone into your department? This week on the show, Pablo Galindo Salgado returns to talk about building community through the Python Guild at Bloomberg and managing the release of Python 3.11.
Pablo describes how the Python Guild started and currently operates inside Bloomberg. We talk about how it fosters community and acts as a way to promote internally developed tools across disparate teams. We also discuss how work groups use it to find new internal candidates for their teams.
Pablo talks about his role as release manager for Python 3.10 and 3.11. He shares the intense journey the team has had this year in preparing for the release of 3.11. He details updating testing strategies to work with the new specializing adaptive interpreter.
Course Spotlight: Python Basics: Strings and String Methods
In Python, collections of text are called strings. In this course, you’ll learn about this fundamental data type and the string methods that you can use to manipulate strings. Along the way, you’ll learn ways to work with strings of numbers, and how to format strings for printing.
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Where should you use an ellipsis in Python? How does it behave as a placeholder in a script, project, or stub file? What are the next goals for the Faster CPython project? This week on the show, Christopher Trudeau is here, bringing another batch of PyCoder’s Weekly articles and projects.
We talk about a Real Python article that covers when you should use an ellipsis in Python. We discuss the similarities with the pass keyword and how it’s used for type hints within stub files.
Christopher shares resources covering the goals of the Faster CPython project. We’re on the cusp of the release of Python 3.11, but the project keeps moving forward as they look at ways to continue speeding up Python.
We share several other articles and projects from the Python community, including a news roundup, alternatives for hosting Python-based applications, ways to create custom Python strings, a discussion about aging programmers, a structural diff that understands syntax, and a project for refurbishing and modernizing Python codebases.
Course Spotlight: Providing Multiple Constructors in Your Python Classes
In this video course, you’ll learn how to provide multiple constructors in your Python classes. To this end, you’ll learn different techniques, such as checking argument types, using default argument values, writing class methods, and implementing single-dispatch methods.
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str vs UserStringNews:
@override, which would be used as a type hint for methods in a subclass that override a parent’s method. This type hint would introduce a level of safety if the parent method is refactored without corresponding changes to the child method.Show Links:
Ellipsis constant can come in handy for you.str vs UserString – In this tutorial, you’ll learn how to create custom string-like classes in Python by inheriting from the built-in str class or by subclassing UserString from the collections module.Discussion:
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Have you used a memory profiler to gauge the performance of your Python application? Maybe you’re using it to troubleshoot memory issues when loading a large data science project. What could running a profiler show you about a codebase you’re learning? This week on the show, Pablo Galindo Salgado returns to talk about Memray, a powerful tracing memory profiler.
Pablo developed Memray while working at Bloomberg to track memory allocations beyond Python code into native extensions and the interpreter itself. It’s a compelling tool that provides fine-grain reports to help you understand where memory is used.
Pablo shares the reporting that Memray provides, including live mode, flame graphs, and a pytest plug-in. We also discuss how a tracing memory profiler can help you understand a new codebase.
He walks through how he developed the first prototype internally and eventually moved the project into open source. This is the first part of my conversation with Pablo. In a couple of weeks, you’ll get the second part, where we talk about Python guilds inside large companies and his work as the release manager for Python 3.10 and 3.11.
Course Spotlight: SQLite and SQLAlchemy in Python: Moving Your Data Beyond Flat Files
In this video course, you’ll learn how to store and retrieve data using Python, SQLite, and SQLAlchemy as well as with flat files. Using SQLite with Python brings with it the additional benefit of accessing data with SQL. By adding SQLAlchemy, you can work with data in terms of objects and methods.
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pytest plug-inShow Links:
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Have you ever used code to help explain a topic? How can Python scripts be used to understand the intricacies of access control? This week on the show, Christopher Trudeau is here, bringing another batch of PyCoder’s Weekly articles and projects.
Christopher talks about an article that explores the evolution of access control by reimplementing the concepts with Python scripts. The experiment moves across the various access forms, starting with control lists, roles, and attributes, then ending with purpose-based access control (PBAC).
We also cover a post about how to create dangerous pickles. We discuss where malicious code can hide within the serialization process and how decompiling code can be an education tool.
We share several other articles and projects from the Python community, including command line interface (CLI) creation with argparse, HTML and CSS for Python developers, a Python packaging user survey, a visual Python Tkinter GUI creator, a PyScript-based data visualization cookbook, and a project for writing functional test helpers in Django.
Course Spotlight: Serializing Objects With the Python pickle Module
In this course, you’ll learn how you can use the Python pickle module to convert your objects into a stream of bytes that can be saved to a disk or sent over a network. You’ll also learn the security implications of using this process on objects from an untrusted source.
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Are you interested in using Python in an industry outside of software development? Would adding a few custom software tools increase efficiency and make your coworkers’ jobs easier? This week on the show, Josh Burnett talks about using Python as a mechanical engineer.
I met Josh at PyCon US 2022 in Salt Lake City, which he attended for the first time with several coworkers. He suggested we do an episode to shed some light on ways that Python is being used professionally by people who aren’t primarily programming for a living.
Josh works as a mechanical engineer for an equipment manufacturer, where he needs to perform repetitive tasks and generate copious logs. He explains how he moved his team away from MATLAB and toward Python.
We discuss his progression from writing scripts to developing packages and eventually hosting his work on PyPI. He also shares his explorations with CircuitPython for personal and professional projects.
Course Spotlight: Building Python Project Documentation With MkDocs
In this video course, you’ll learn how to build professional documentation for a Python package using MkDocs and mkdocstrings. These tools allow you to generate nice-looking and modern documentation from Markdown files and, more importantly, from your code’s docstrings.
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Have you thought the standard output from Matplotlib is a bit generic looking? Would you like a quick way to add style and consistency to your data visualizations? This week on the show, Christopher Trudeau is here, bringing another batch of PyCoder’s Weekly articles and projects.
We cover an article about the magic of creating style sheets for Matplotlib. You can quickly customize plots and graphs with a single line of code. We share additional resources for you to try out new styles and learn what parameters are customizable.
Christopher covers an article about using async for web development in Python. The creation of Python generators inspired the development of async functionality. He discusses recent changes and async additions within Python web frameworks.
We cover several other articles and projects from the Python community, including how to install a pre-release version of Python, cache in Python with lru_cache, and get better at debugging, along with suggestions of libraries that deserve attention, a Python library for creating mathematical animations, and an extremely fast Python linter that’s written in Rust.
Course Spotlight: Python Debugging With pdb
In this hands-on course, you’ll learn the basics of using pdb, Python’s interactive source code debugger. pdb is a great tool for tracking down hard-to-find bugs, and it allows you to fix faulty code more quickly.
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async support. The Python web ecosystem has been seeing new frameworks pop up which are fully async, or support going fully async, from the start.” Learn more about async and its use in web frameworks.@lru_cache decorator to cache the results of your functions using the LRU cache strategy. This is a powerful technique you can use to leverage the power of caching in your implementations.Discussions:
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Have you wanted to understand recursion and how to use it in Python? Are you familiar with the call stack and how it relates to tracebacks? This week on the show, Al Sweigart talks about his new book, “The Recursive Book of Recursion.”
Recursion is one of those concepts held as a tenet of high-level computer science priesthood. Al explains the fundamentals of writing recursive functions and a critical missing piece in understanding how they operate, the call stack. After completing his research, he concluded that it’s a technique that you should understand but rarely use.
He also shares the few cases where recursion is an appropriate solution. Along the way, we talk about directed acyclic graphs, solving mazes, exploring file trees, and creating fractal images.
Course Spotlight: Caching in Python With lru_cache
Caching is an essential optimization technique. In this video course, you’ll learn how to use Python’s @lru_cache decorator to cache the results of your functions using the LRU cache strategy. This is a powerful technique you can use to leverage the power of caching in your implementations.
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