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    Technology

    The Real Python Podcast

    A 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.

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    Copyright: © 2020 Real Python

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    Latest Episodes:
    Going Beyond the Basic Stuff With Python and Al Sweigart Oct 30, 2020
    Show notes

    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.

    Topics:

    • 00:00:00 – Introduction
    • 00:01:35 – Early access release of the new book
    • 00:03:20 – Other books Al has written
    • 00:09:54 – Automate the Boring Stuff as an advice book
    • 00:15:29 – Books about writing Python with games
    • 00:17:36 – Making a book less intimidating
    • 00:19:10 – Helping readers through random things a programmer needs to learn
    • 00:23:09 – Environment variables and the command line
    • 00:28:05 – Naming
    • 00:34:59 – Code formatting
    • 00:36:45 – Why do you enjoy teaching Python concepts with games?
    • 00:42:54 – Video Course Spotlight
    • 00:44:15 – Minimal amount you should know about Git
    • 00:47:08 – Jargon and being clear about terminology
    • 00:50:13 – Al’s first book diving into Object-Oriented Programming
    • 00:59:57 – Python myths covered in the book
    • 01:09:08 – What is something you thought you knew about Python, but were wrong about it?
    • 01:13:12 – What is something you are excited about in the world of Python?
    • 01:18:55 – What do you want to learn next?
    • 01:22:08 – Creating an curriculum from conference talks
    • 01:26:42 – Thanks and goodbye

    Show Links:

    • Al Sweigart - Website
    • Beyond the Basic Stuff with Python
    • Automate the Boring Stuff with Python
    • Invent with Python
    • Xkcd comic “Real Programmers”
    • Resources to learn git
    • Fluent Python by Luciano Ramalho
    • Ozymandias: Wikipedia article
    • Ned Batchelder - Facts and Myths: PyCon 2015
    • Al Sweigart -The Amazing Mutable, Immutable Tuple: PyCascades 2019
    • BeeWare - Write once. Deploy everywhere.
    • What Professional Games Use Pygame?
    • Codename Mallow -Written in PyGame
    • Unity of Command - Written in PyGame
    • A Curriculum for Python Packaging: Al Sweigart’s Blog

    Level up your Python skills with our expert-led courses:

    • Introduction to Git and GitHub for Python
    • Unicode in Python: Working With Character Encodings
    • Mastering Python's Built-in time Module

    Support the podcast & join our community of Pythonistas


    Our New "Python Basics" Book & Filling the Gaps in Your Learning Path Oct 23, 2020
    Show notes

    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.

    Topics:

    • 00:00:00 – Introduction
    • 00:01:36 – Python Basics: A Practical Introduction to Python 3
    • 00:02:39 – How has feedback helped the process?
    • 00:04:17 – Who is the intended audience?
    • 00:06:02 – Covering how to get Python installed on different platforms?
    • 00:11:05 – What topics does the book cover?
    • 00:14:12 – What can be previewed on Real Python?
    • 00:15:03 – What format can you get the book in?
    • 00:18:30 – Code challenges included!
    • 00:21:33 – What other resources are provided to help with cementing your learning?
    • 00:22:41 – What versions of Python are covered?
    • 00:23:08 – How does the book fit into the Real Python learning eco-system?
    • 00:29:35 – Spotlight: How to get a preview of the book!
    • 00:30:38 – What has the writing process been like?
    • 00:33:21 – What does didactic mean, in terms of reviewing materials?
    • 00:39:23 – What were areas you were excited about updating?
    • 00:41:29 – Were there important things you felt needed to be added?
    • 00:45:55 – Who worked on the book?
    • 00:47:13 – What are you excited about in the world of Python?
    • 00:48:13 – What do you want to learn next?
    • 00:49:40 – Thanks and goodbye

    Show Links:

    • Python Basics: A Practical Introduction to Python 3
    • Python 3 Installation & Setup Guide
    • Create and Modify PDF Files in Python
    • Python GUI Programming With Tkinter
    • Object-Oriented Programming (OOP) in Python 3
    • A Practical Introduction to Web Scraping in Python

    Level up your Python skills with our expert-led courses:

    • Unicode in Python: Working With Character Encodings
    • Grow Your Python Portfolio With 13 Intermediate Project Ideas
    • Cool New Features in Python 3.9

    Support the podcast & join our community of Pythonistas


    Python Return Statement Best Practices and Working With the map() Function Oct 16, 2020
    Show notes

    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.

    Topics:

    • 00:00:00 – Introduction
    • 00:01:33 – Interactive Data Visualization in Python With Pygal
    • 00:06:40 – Python’s map(): Processing Iterables Without a Loop
    • 00:12:51 – Everything You Need to Know About Python’s NamedTuples
    • 00:19:46 – PEP 638: Syntactic Macros
    • 00:26:43 – Video Course Spotlight
    • 00:27:57 – The Python return Statement: Usage and Best Practices
    • 00:34:42 – Python for Kids
    • 00:38:03 – Build a Face Recognition System With the Nvidia Jetson Nano
    • 00:42:32 – football: Reinforcement Learning Environment
    • 00:45:51 – Thanks and goodbye

    Show Links:

    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!

    Projects:

    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

    Additional Links:

    • Pygal: Sexy python charting
    • Bokeh: Interactive visualization library
    • Common Python Data Structures (Guide) - Real Python article
    • The Ultimate Guide to Data Classes in Python 3.7 - Real Python article
    • PEP 572 – Assignment Expressions - Walrus Operator
    • Python’s reduce(): From Functional to Pythonic Style - Real Python article
    • NVIDIA Jetson Nano
    • Google Research Football with Manchester City F.C.

    Level up your Python skills with our expert-led courses:

    • Exploring Basic Data Types in Python
    • Defining Main Functions in Python
    • Command Line Interfaces in Python

    Support the podcast & join our community of Pythonistas


    Exploring the New Features of Python 3.9 Oct 09, 2020
    Show notes

    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.

    Topics:

    • 00:00:00 – Introduction
    • 00:02:02 – Proper Time Zone support
    • 00:05:38 – What to do if your OS does not have tzdata?
    • 00:07:11 – How do you add time zone info to your Python code?
    • 00:08:24 – Historic changes to time zones
    • 00:10:48 – New operators for updating dictionaries
    • 00:15:44 – Geir Arne’s PyCon 2020 decorators tutorial
    • 00:18:02 – Changes to decorator syntax
    • 00:24:08 – Annotated type hints
    • 00:32:36 – Video Course Spotlight
    • 00:33:26 – The PEG parser
    • 00:37:51 – Potential for new enhancements in upcoming releases
    • 00:42:40 – String methods to remove prefixes and suffixes
    • 00:44:22 – Type hint lists and dictionaries directly
    • 00:47:29 – Topological Sort
    • 00:52:03 – Greatest Common Divisor (GCD) and Least Common Multiple (LCM)
    • 00:53:50 – New HTTP status codes
    • 00:58:29 – Should you upgrade?
    • 01:07:58 – Potential issue with Python 3.10 versioning
    • 01:10:18 – What are you excited about in the world of Python?
    • 01:12:52 – What do you want to learn next?
    • 01:14:08 – Thanks and goodbyes

    Show Links:

    • Python 3.9: Cool New Features for You to Try: Real Python article
    • Cool New Features in Python 3.9: Real Python video course
    • dateutil - Powerful extensions to datetime
    • Paul Ganssle: Blog
    • IANA - Internet Assigned Numbers Authority: Time Zone Database
    • Dictionaries in Python: Real Python article
    • PEP 584 – Add Union Operators To dict: python.org
    • Primer on Python Decorators: Real Python article
    • PEP 614 – Relaxing Grammar Restrictions On Decorators: python.org
    • Introduction to Decorators: Power Up Your Python Code - PyCon 2020 Online Tutorial
    • Python Type Checking (Guide) - Annotations:Real Python article
    • PEP 484 – Type Hints: python.org
    • PEP 593 – Flexible function and variable annotations: python.org
    • PEP 617 – New PEG parser for CPython: python.org
    • PEG Parsing Series Overview: Guido van Rossum
    • PEP 622 – Structural Pattern Matching: python.org
    • PEP 616 – String methods to remove prefixes and suffixes: python.org
    • PEP 585 – Type Hinting Generics In Standard Collections: python.org
    • Topological sorting: Wikipedia article
    • graphlib — Functionality to operate with graph-like structures: docs.python.org
    • Greatest common divisor: Wikipedia article
    • Least common multiple: Wikipedia article
    • Hypertext Transfer Protocol (HTTP) Status Code Registry
    • Hyper Text Coffee Pot Control Protocol (HTCPCP/1.0)
    • PEP 602 – Annual Release Cycle for Python: Łukasz Langa - python.org
    • Porting to Python 3.9: docs.python.org
    • CPython Internals: Your Guide to the Python3 Interpreter
    • Panel: A high-level app and dashboarding solution for Python
    • PyQt: GUI Library
    • Pandas
    • Python and PyQt: Building a GUI Desktop Calculator - Real Python article
    • GIS in Python
    • GeoPandas

    Level up your Python skills with our expert-led courses:

    • Python Decorators 101
    • Python Type Checking
    • Cool New Features in Python 3.9

    Support the podcast & join our community of Pythonistas


    Resolving Package Dependencies With the New Version of Pip Oct 02, 2020
    Show notes

    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.

    Show Topics:

    • 00:00:00 – Introduction
    • 00:01:41 – Pip updates and changes to dependency resolver
    • 00:08:49 – Different types of wheels
    • 00:11:12 – Pinning package dependencies
    • 00:13:19 – Work on the user experience (UX) of pip
    • 00:15:45 – Documentation at Python packaging authority and thanks to Thea Flowers
    • 00:16:21 – Types of issues that need resolving
    • 00:20:48 – Need for reporting issues
    • 00:23:41 – Pip usability survey and dependency recipes to test
    • 00:27:21 – Call out to open source maintainers to test
    • 00:29:32 – Video Course Spotlight
    • 00:30:43 – How is this UX work different from Simply Secure
    • 00:34:59 – How do you present errors to users?
    • 00:41:14 – Pip release timeline for 2020 and into 2021
    • 00:46:38 – The dynamics of responsibility and power
    • 00:49:43 – What’s involved in getting more funding into open source?
    • 00:54:10 – Grant writing for the PSF
    • 00:57:53 – Call to action: How to help with pip?
    • 01:00:54 – What are you excited about in the world of Python?
    • 01:04:52 – What do you want to learn next?
    • 01:08:22 – Thanks and goodbyes

    Show Links:

    • New pip resolver to roll out this year: Python Software Foundation
    • Changes to the pip dependency resolver in 20.2 (2020): Python Packaging Authority
    • Changes are coming to pip: YouTube
    • Sign-up for pip UX Studies!
    • Upgrade to pip 20.2, plus, changes coming in 20.3: Python Insider
    • Pip team midyear report: July 13, 2020
    • An Overview of Packaging for Python: PyPA
    • pip dependency resolver changes: Test & Code Podcast
    • What Are Python Wheels and Why Should You Care?: Real Python article
    • Python Wheels and Pass by Reference in Python: Real Python Podcast Ep23
    • Options for Packaging Your Python Application: Wheels, Docker, and More: Real Python Podcast Ep24
    • UX Research & Design: 2020 Work on Improving pip’s user experience
    • Simple Secure: User Research
    • Roadmap update for TUF (The Update Framework) support
    • Exploring CircuitPython with Thea Flowers: Real Python Podcast Ep5
    • PyPA - Packaging Problems Issue Tracker: Github
    • PEP 458 - Secure PyPI downloads with signed repository metadata
    • Fixing conflicting dependencies: PyPA
    • Finish dependency resolver for pip: Github
    • Announcing the PSF Project Funding Working Group: PSF
    • Sponsor PyPI and related projects
    • Tidelift: Managed open source. Backed by maintainers.
    • Apply for Grants To Fund Open Source Work: changeset
    • Open collective: Make your community sustainable
    • Sustain: Holding a space for conversations about sustaining Open Source
    • Answer these surveys to improve pip’s usability: Python Software Foundation
    • Breaking Release Bottlenecks – What Changeset Can Do
    • On The Art of Python 2019
    • Python Grab Bag: A Set of Short Plays
    • “Apply for Grants to Fund Open Source Work” - Sumana Harihareswara: PyOhio 2020
    • PyGotham TV: 2020
    • Get paid to write Free software: Cristina - PyGotham 2020

    Level up your Python skills with our expert-led courses:

    • How to Publish Your Own Python Package to PyPI
    • Python Modules and Packages: An Introduction
    • A Beginner's Guide to pip

    Support the podcast & join our community of Pythonistas


    Using Pylance to Write Better Python Inside of Visual Studio Code Sep 25, 2020
    Show notes

    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.

    Topics:

    • 00:00:00 – Introduction
    • 00:01:47 – Current Role at Microsoft
    • 00:03:01 – Background with Python
    • 00:04:21 – Origins of Pylance
    • 00:06:53 – What is a language server?
    • 00:09:56 – Diving deeper into the features individually
    • 00:14:42 – Code navigation and diagnostics
    • 00:15:43 – Methods of defining types and stub files
    • 00:17:28 – What are examples of stub files?
    • 00:21:16 – Comparing Pyright to Mypy
    • 00:23:56 – Video Course Spotlight
    • 00:25:02 – Auto-imports are a contentious feature
    • 00:28:36 – Code actions and dead code analysis
    • 00:31:46 – Pylance working with Jupyter notebooks in VSCode
    • 00:33:30 – Multiple workspaces
    • 00:36:16 – Why do you like to work on developer tools?
    • 00:39:35 – How does a tool like Pylance help a beginner?
    • 00:42:31 – What are you excited about in the world of Python?
    • 00:46:25 – What do you want to learn next?
    • 00:49:24 – Thanks and goodbyes

    Show Links:

    • Announcing Pylance: Fast, feature-rich language support for Python in Visual Studio Code
    • Pylance introduces five new features that enable type magic for Python developers
    • Python in Visual Studio Code – September 2020 Release
    • Pylance and Python in VS Code: Visual Studio Code v1.49 Release Party - YouTube
    • Language Server Protocol
    • Language Server Protocol: Github
    • How the Language Server Protocol Affects the Future of IDEs
    • typeshed: External type annotations for the Python standard library and Python builtins, as well as third party packages
    • Pyright: Static type checker for Python
    • PEP 561 – Distributing and Packaging Type Information
    • Visual Studio IntelliCode: Provides AI-assisted development features for Python
    • Creating Stubs For Python Modules
    • Python Type Checking: Real Python video course
    • Feather Huzzah: Adafruit
    • Circuit Playground Express: Adafruit
    • Circuit Python: The easiest way to program microcontrollers
    • Big Honking Button: Winterbloom
    • Arduino With Python: How to Get Started - Real Python video course

    Level up your Python skills with our expert-led courses:

    • Python Type Checking
    • Finding the Perfect Python Code Editor
    • Arduino With Python: Getting Started

    Support the podcast & join our community of Pythonistas


    Preparing for an Interview With Python Practice Problems Sep 18, 2020
    Show notes

    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.

    Topics:

    • 00:00:00 – Introduction
    • 00:01:37 – Python Practice Problems
    • 00:08:19 – Structural Pattern Matching
    • 00:14:16 – Common Python Data Structures
    • 00:17:49 – Video Course Spotlight
    • 00:18:42 – A Tax Attorney Uses Python
    • 00:23:36 – Discover the Role of Python in Space Exploration
    • 00:26:33 – Thanks for the Reviews!
    • 00:27:28 – 5 Pairs of Magic Methods in Python That You Should Know
    • 00:36:56 – python-adventure: Original Colossal Caves Adventure Game
    • 00:41:06 – clifford: Geometric Algebra for Python
    • 00:43:45 – pippi: Computer Music With Python
    • 00:46:24 – Thanks and Goodbye

    Show Links:

    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

    Additional Links:

    • Python Coding Interviews: Tips & Best Practices: Real Python Course
    • The Singleton Pattern: A “Creational Pattern” from the Gang of Four book
    • The Python heapq Module: Using Heaps and Priority Queues: Real Python Article
    • How to Implement a Python Stack: Real Python Article
    • Python Stacks, Queues, and Priority Queues in Practice: Real Python Article
    • codespell: Fix common misspellings in text files.

    Level up your Python skills with our expert-led courses:

    • A Conceptual Primer on OOP in Python
    • Implementing a Stack in Python
    • Working With Linked Lists in Python

    Support the podcast & join our community of Pythonistas


    5 Years Podcasting Python With Michael Kennedy: Growth, GIL, Async, and More Sep 11, 2020
    Show notes

    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.

    Topics:

    • 00:00:00 – Introduction
    • 00:01:34 – Changes in the Python landscape over the last 5 years
    • 00:08:09 – Changing the perspective from scripts to applications
    • 00:10:48 – Python as a full-spectrum language
    • 00:17:13 – What are the areas of growth for Python
    • 00:22:09 – Stories highlights from Talk Python
    • 00:27:48 – Stack Overflow Developer Surveys
    • 00:33:22 – Enterprise use and contributions to Python
    • 00:38:04 – Video Course Spotlight
    • 00:39:20 – A monk learns Python and OpenCV
    • 00:48:18 – Things that have been hard to do in Python
    • 00:52:07 – How is the GIL part of the problem?
    • 00:56:37 – Leave a review, it will help the show, Thanks!
    • 00:57:04 – More on Async in Python
    • 01:03:38 – Recent courses developed
    • 01:10:05 – Who listens to a Python podcast?
    • 01:13:06 – What are you excited about in the world of Python?
    • 01:17:46 – What do you want to learn next?
    • 01:23:17 – What is something you thought you knew about Python, but were wrong about it?
    • 01:26:58 – Thanks and goodbye

    Show Links:

    • Talk Python To Me
    • Brit uni’s AI algorithm clocks 50 exoplanets hidden in Kepler space ‘scope archives
    • Fifty new planets confirmed in machine learning first
    • Apple MainStage: Nine Inch Nails – YouTube
    • Stack Overflow Trends: See how technologies have trended over time
    • Stack Overflow: Most Loved, Dreaded, and Wanted Languages
    • Enterprise Software with Python: Mahmoud Hashemi - Talk Python Ep54
    • Python in digital humanities research: Cornelis van Lit - Talk Python Ep230
    • PEP 554 – Multiple Interpreters in the Stdlib
    • Machine Learning at the Large Hadron Collider: Talk Python Ep144
    • Python at the Large Hadron Collider and CERN: Talk Python Ep29
    • 12 of the Biggest Spreadsheet Fails in History: Oracle Blog
    • FastAPI: Modern, fast (high-performance), web framework for building APIs with Python
    • Starlette: Lightweight ASGI framework/toolkit
    • Unsync: Unsynchronize asyncio by using an ambient event loop in a separate thread
    • Python Type Checking: Real Python Video Course
    • pydanctic: Data validation and settings management using Python type annotations

    Level up your Python skills with our expert-led courses:

    • Hands-On Python 3 Concurrency With the asyncio Module
    • Python Type Checking
    • Editing Excel Spreadsheets in Python With openpyxl

    Support the podcast & join our community of Pythonistas


    Data Version Control in Python and Real Python Video Transcripts Sep 04, 2020
    Show notes

    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.

    Topics:

    • 00:00:00 – Introduction
    • 00:02:01 – Data Version Control With Python and DVC
    • 00:08:57 – Where Do You Go to Get Exposure to Well-Written Code?
    • 00:13:13 – Delegation: Composition and Inheritance in Object-Oriented Programming
    • 00:21:46 – What Are Some Good Python Project Ideas for High School Students?
    • 00:26:53 – Video Course Spotlight
    • 00:27:48 – Never Run Python in Your Downloads Folder
    • 00:35:55 – present: A Terminal-Based Presentation Tool With Colors and Effects
    • 00:37:36 – Mini Raspberry Pi Boston Dynamics–inspired Robot
    • 00:41:48 – Sadie Parker and Transcripts for Real Python Video Courses
    • 00:59:26 – Thanks and Goodbye

    Show Links:

    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.

    Additional Links:

    • Python 3 Module of the Week
    • The Algorithms - Python
    • Awesome Python Applications
    • James Powell: So you want to be a Python expert? | PyData Seattle 2017
    • Boston Dynamics: Spot
    • WebVTT (Web Video Text Tracks): Wikipedia article
    • webvtt-py: Python module for reading/writing WebVTT files
    • pysrt: SubRip (.srt) subtitle parser and writer
    • Srt: A tiny library for parsing, modifying, and composing SRT files

    Level up your Python skills with our expert-led courses:

    • Parallel Iteration With Python's zip() Function
    • Grow Your Python Portfolio With 13 Intermediate Project Ideas
    • Editing Excel Spreadsheets in Python With openpyxl

    Support the podcast & join our community of Pythonistas


    Options for Packaging Your Python Application: Wheels, Docker, and More Aug 28, 2020
    Show notes

    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.

    Topics:

    • 00:00:00 – Introduction
    • 00:01:36 – About the naming of pythonspeed.com
    • 00:03:47 – Fil - Python Memory Profiler
    • 00:06:44 – Small Big Data: What to do when your data doesn’t fit in memory - PyCon 2020
    • 00:12:17 – Options for packaging your Python code: Wheels, Conda, Docker, and more
    • 00:15:13 – Python Wheels
    • 00:19:22 – pipx: Install and Run Python Applications in Isolated Environments
    • 00:20:52 – PEX, and friends
    • 00:24:51 – System Package, RPM or DEB
    • 00:29:42 – Conda Packaging and conda-forge
    • 00:36:09 – Video Course Spotlight
    • 00:37:23 – Self-contained executable: PyInstaller, PyOxidizer, Briefcase
    • 00:43:45 – Container image (Docker, Singularity)
    • 00:54:55 – Why alpine may not be the best choice
    • 01:05:28 – Singularity
    • 01:07:50 – What are you excited about in the world of Python?
    • 01:10:40 – What do you want to learn next?
    • 01:13:54 – Thanks and Goodbye

    Show Links:

    • Python => Speed: Ship Better Python Software, Faster
    • Code Without Rules: Helping You Become a Productive Programmer and Get Work/Life Balance
    • Talk Python to Me – Episode #274: Profiling Data Science Code with FIL
    • Fil: A New Python Memory Profiler for Data Scientists and Scientists
    • Small Big Data: What to do When Your Data Doesn’t Fit in Memory - PyCon 2020
    • Episode 16: Thinking in Pandas: Python Data Analysis the Right Way
    • Options for Packaging Your Python Code: Wheels, Conda, Docker, and More
    • What Are Python Wheels and Why Should You Care?: Real Python article
    • pipx — Install and Run Python Applications in Isolated Environments
    • pex: A Library and Tool for Generating .pex (Python EXecutable) Files
    • WTF is PEX?: Twitter Lightning Talk - YouTube
    • RPM (Red Hat Package Manager): Wikipedia article
    • DEB (Debian Package - file format): Wikipedia article
    • Conda: Package, Dependency and Environment Management for Any Language
    • conda-forge: A community-led collection of recipes, build infrastructure and distributions for the conda package manager
    • PyInstaller: Freezes (packages) Python applications into stand-alone executables
    • PyOxidizer: A utility for producing binaries that embed Python
    • Briefcase: Convert a Python project into a standalone native application
    • Docker: Get Started with Docker
    • Just Enough Docker Packaging: Book
    • Episode 8: Docker + Python for Data Science and Machine Learning
    • Using Alpine can make Python Docker builds 50× slower
    • Introduction to Singularity
    • Docker vs. Singularity for data processing: UIDs and filesystem access
    • Best practices for production-ready Docker packaging: EuroPython 2020 talk
    • EuroPython 2020 Talk: Brian Track Stream - Unedited - Starts @08:33:45
    • Statistical Rethinking: A Bayesian Course with Examples
    • Bayes Theorem: 3Blue1Brown - YouTube

    Level up your Python skills with our expert-led courses:

    • How to Publish Your Own Python Package to PyPI
    • Documenting Code in Python
    • Python Coding Interviews: Tips & Best Practices

    Support the podcast & join our community of Pythonistas


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