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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.

    Advertise

    Copyright: © 2020 Real Python

    • Apple Podcasts
    • Google Play
    • Spotify

    Latest Episodes:
    Constraint Programming & Exploring Python's Built-in Functions Jul 19, 2024
    Show notes

    What are discrete optimization problems? How do you solve them with constraint programming in Python? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder’s Weekly articles and projects

    Christopher discusses an article about constraint programming using Python. He describes the fundamentals and how the problems resemble logic problems you may have experienced in school. The article shows how to solve a weekly work scheduling problem using the open-source CP-SAT package.

    We discuss Leodanis Pozo Ramos’s recent tutorial, “Python’s Built-in Functions: A Complete Exploration.” These functions are available for use directly in your code without importing.

    We also share several other articles and projects from the Python community, including a news roundup, spotting ships with satellites, grappling with Apple’s App Store rejecting Python applications, considering changes to Python’s security model, discussing pivoting from one development path to another, prettifying Jinja and Django templates, and generating static sites with Python.

    This episode is sponsored by Sentry.

    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
    • 00:02:35 – Polars 1.0 Released
    • 00:03:26 – Psycopg 3.2 Released
    • 00:04:06 – Django security releases issued: 5.0.7 and 4.2.14
    • 00:04:40 – PyBay 2024 Call for Proposals
    • 00:05:16 – Python’s Built-in Functions: A Complete Exploration
    • 00:12:10 – Satellites Spotting Ships
    • 00:16:02 – Sponsor: Sentry
    • 00:17:09 – Python Grapples With Apple App Store Rejections
    • 00:20:27 – Python’s Security Model After the xz-utils Backdoor
    • 00:25:38 – Video Course Spotlight
    • 00:26:56 – Constraint Programming Using CP-SAT and Python
    • 00:31:40 – Any Web Devs Successfully Pivoted to AI/ML Development?
    • 00:43:12 – aurora: Static Site Generator Implemented in Python
    • 00:45:14 – Running Prettier Against Django or Jinja Templates
    • 00:46:58 – Thanks and goodbye

    News:

    • Polars 1.0 Released
    • Psycopg 3.2 Released
    • Django security releases issued: 5.0.7 and 4.2.14
    • PyBay 2024 Call for Proposals

    Show Links:

    • Python’s Built-in Functions: A Complete Exploration – In this tutorial, you’ll learn the basics of working with Python’s numerous built-in functions. You’ll explore how you can use these predefined functions to perform common tasks and operations, such as mathematical calculations, data type conversions, and string manipulations.
    • Satellites Spotting Ships – Umbra Space has released a data set consisting of satellite based radar images of shipping. This article from Mark shows you how to grab the data, visualize, and annotate it.
    • Python Grapples With Apple App Store Rejections – A string that is part of the urllib parser module in Python references a scheme for apps that use the iTunes feature to install other apps, which is disallowed. Auto scanning by Apple is rejecting any app that uses Python 3.12 underneath. A solution has been proposed for Python 3.13.
    • Python’s Security Model After the xz-utils Backdoor – The backdoor introduced to the xz-utils compression project through social engineering was one of the topics at the Python Language Summit. Participants discussed what can be done to prevent similar social engineering attacks on the Python source.
    • Constraint Programming Using CP-SAT and Python – Constraint programming is the process of looking for solutions based on a series of restrictions, like employees over 18 who have worked the cash before. This article introduces the concept and shows you how to use open source libraries to write constraint solving code.

    Discussion:

    • Any Web Devs Successfully Pivoted to AI/ML Development?

    Projects:

    • aurora: Static Site Generator Implemented in Python
    • Running Prettier Against Django or Jinja Templates – “Prettier” is a JavaScript based linting tool for templates. For folks not familiar with the world of npm, it can be a bit daunting to get it going. Simon fiddled with it so you don’t have to and posted how he got it working on his system.

    Additional Links:

    • Episode #209: Python’s Command-Line Utilities & Music Information Retrieval Tools – The Real Python Podcast
    • Python Module Index — Python 3.12.4 documentation
    • Built-in Functions — Python 3.12.4 documentation
    • Briefcase— BeeWare
    • Ask HN: What’s Prolog like in 2024? - Hacker News
    • Episode #199: Leveraging Documents and Data to Create a Custom LLM Chatbot – The Real Python Podcast
    • PEP 730 – Adding iOS as a supported platform | peps.python.org

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

    • Parallel Iteration With Python's zip() Function
    • Python Inner Functions
    • Jinja Templating

    Support the podcast & join our community of Pythonistas


    Digging Into Graph Theory in Python With David Amos Jul 12, 2024
    Show notes

    Have you wondered about graph theory and how to start exploring it in Python? What resources and Python libraries can you use to experiment and learn more? This week on the show, former co-host David Amos returns to talk about what he’s been up to and share his knowledge about graph theory in Python.

    David started a Ph.D. program studying mathematics, with a focus on graph theory. Though life interrupted his pursuit after three years, he is still passionate about the subject. He’s been using these skills to create documentation and teach users as part of RelationalAI’s education team.

    David has also been exploring the Julia programming language. He wrote about it on his blog, created videos, and started a podcast on the topic. He shares his excitement about learning new techniques from different languages and how these ideas can enhance your coding in Python.

    This episode is sponsored by Sentry.

    Course Spotlight: Defining Python Constants for Code Maintainability

    In this video course, you’ll learn how to properly define constants in Python. By coding a bunch of practical example, you’ll also learn how Python constants can improve your code’s readability, reusability, and maintainability.

    Topics:

    • 00:00:00 – Introduction
    • 00:02:09 – What have you been up to?
    • 00:03:31 – Exploring the Julia language
    • 00:07:24 – Where do you see Julia being used?
    • 00:10:17 – Cross pollination of languages
    • 00:12:45 – Connecting with RelationalAI
    • 00:16:33 – Sponsor: Sentry
    • 00:17:42 – Digging into graph theory
    • 00:21:54 – Edges as connections
    • 00:24:55 – Defining terms
    • 00:31:30 – Storing graph information
    • 00:41:55 – Applications once the graph is built
    • 00:49:07 – Video Course Spotlight
    • 00:50:40 – Additional resources to learn more
    • 00:53:59 – What are you excited about in the world of Python?
    • 00:58:05 – What do you want to learn next?
    • 01:00:25 – How can people follow your work online?
    • 01:02:55 – Thanks and goodbye

    Show Links:

    • RelationalAI - a knowledge graph coprocessor for your data cloud.
    • The Julia Programming Language
    • Talk Julia - YouTube
    • Five Minutes To Julia. David Amos - Medium Member Link
    • Five Minutes To Julia. David Amos - Medium Friend Link
    • Getting Started with RelationalAI - RelationalAI Docs
    • Example Notebooks - RelationalAI Docs
    • The Hunt for the Missing Data Type - Hillel Wayne
    • Introduction to Graph Theory: Richard J Trudeau
    • The Fascinating World of Graph Theory: Arthur Benjamin, Gary Chartrand, Ping Zhang
    • NetworkX — NetworkX documentation
    • Embeddings and Vector Databases With ChromaDB – Real Python
    • Episode #199: Leveraging Documents and Data to Create a Custom LLM Chatbot – The Real Python Podcast
    • Graph Theory With Python - David’s YouTube Playlist
    • David Amos (@somacdivad@hachyderm.io) - Hachyderm.io
    • David Amos - LinkedIn
    • David Amos – Medium

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

    • Using Jupyter Notebooks
    • Python Basics: Setting Up Python
    • Defining Python Constants for Code Maintainability

    Support the podcast & join our community of Pythonistas


    Python Doesn't Round Numbers the Way You Might Think Jul 05, 2024
    Show notes

    Does Python round numbers the same way you learned back in math class? You might be surprised by the default method Python uses and the variety of ways to round numbers in Python. Christopher Trudeau is back on the show this week, bringing another batch of PyCoder’s Weekly articles and projects.

    Christopher discusses his recent video course, “Rounding Numbers in Python.” He covers rounding bias and how to avoid introducing it into your dataset. We dig into the various rounding strategies and how to implement them in Python.

    We also share several other articles and projects from the Python community, including a news roundup, a fast Python linter for error-free and maintainable code, the decline of the user interface, more thoughts on Python in Excel, a discussion about calendar versioning for Python, a financial database as a Python module, and a project to prettify the colors of your terminal user interfaces.

    This episode is sponsored by Sentry.

    Course Spotlight: Rounding Numbers in Python

    In this video course, you’ll learn about the mistakes you might make when rounding numbers and how to best manage or avoid them. It’s a great place to start for the early to intermediate Python developer who’s interested in using Python for finance, data science, or scientific computing.

    Topics:

    • 00:00:00 – Introduction
    • 00:02:06 – NumPy 2.0.0 Release Notes
    • 00:02:52 – Python 3.13.0 beta 3 released
    • 00:03:05 – Announcing the PSF Board Candidates for 2024!
    • 00:03:27 – Prohibiting Outlook Email Domains
    • 00:04:31 – Ruff: A Python Linter for Error-Free and Maintainable Code
    • 00:09:31 – Sponsor: Sentry
    • 00:10:35 – The Decline of the User Interface
    • 00:19:14 – My Thoughts on Python in Excel
    • 00:26:30 – Rounding Numbers in Python
    • 00:30:53 – Video Course Spotlight
    • 00:32:13 – PEP 2026: Calendar Versioning for Python
    • 00:42:37 – Financial Database as a Python Module
    • 00:45:34 – prettypretty: Build Awesome Terminal User Interfaces
    • 00:47:48 – Thanks and goodbye

    News:

    • NumPy 2.0.0 Release Notes — NumPy v2.0 Manual – The long awaited 2.0 release of NumPy landed this week. Not all the docs are up to date yet, but this final draft of the release notes shows you what is included.
    • Python Insider: Python 3.13.0 beta 3 released
    • Python Software Foundation News: Announcing the PSF Board Candidates for 2024!
    • Prohibiting Outlook Email Domains – Due to an inordinate amount of bot accounts coming from outlook.com and hotmail.com, PyPI has disallowed new account sign-ups with email addresses from these domains.

    Show Links:

    • Ruff: A Python Linter for Error-Free and Maintainable Code – Ruff is an extremely fast, modern linter with a simple interface, making it straightforward to use. It also aims to be a drop-in replacement for other linting and formatting tools, like Pylint, isort, and Black. It’s no surprise it’s quickly becoming one of the most popular Python linters.
    • The Decline of the User Interface – “Software has never looked cooler, but user interface design and user experience have taken a sharp turn for the worse.”
    • My Thoughts on Python in Excel – Microsoft’s new Python in Excel functionality was released almost a year ago. Having now had time to play with it, Felix gives his take.
    • Rounding Numbers in Python – In this video course, you’ll learn about the mistakes you might make when rounding numbers and how to best manage or avoid them. It’s a great place to start for the early to intermediate Python developer who’s interested in using Python for finance, data science, or scientific computing.

    Discussion:

    • PEP 2026: Calendar Versioning for Python – This PEP proposes updating the versioning scheme for Python to include the calendar year. This aims to make the support lifecycle clear by making it easy to see when a version was first released, and easier to work out when it will reach end of life (EOL).
    • Associated discussion
    • Semantic Versioning 2.0.0 - Semantic Versioning
    • Calendar Versioning — CalVer

    Projects:

    • FinanceDatabase: Financial Database as a Python Module
    • prettypretty: Build Awesome Terminal User Interfaces

    Additional Links:

    • The Humane Interface - Wikipedia
    • Python Resources for working with Excel - Working with Excel Files in Python
    • Episode #186: Exploring Python in Excel – The Real Python Podcast
    • Cash rounding - Wikipedia

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

    • Editing Excel Spreadsheets in Python With openpyxl
    • Python Basics: Numbers and Math
    • Rounding Numbers in Python

    Support the podcast & join our community of Pythonistas


    Creating a Guitar Synthesizer & Generating WAV Files With Python Jun 28, 2024
    Show notes

    What techniques go into synthesizing a guitar sound in Python? What higher-level programming and Python concepts can you practice while building advanced projects? This week on the show, we talk with Real Python author and core team member Bartosz Zaczyński about his recent step-by-step project, Build a Guitar Synthesizer: Play Musical Tablature in Python.

    Bartosz shares how he had built an early prototype of the guitar synth using a different language. He describes recreating the Karplus-Strong algorithm in Python to create the plucked guitar sounds. We discuss teaching advanced Python concepts while guiding readers through constructing a complete project.

    We also dig into reading and writing WAV files in Python, using Spotify’s pedalboard library, implementing Poetry in a project, and designing a file format for guitar tablature.

    This episode is sponsored by Mailtrap.

    Course Spotlight: Playing and Recording Sound in Python

    In this course, you’ll learn about libraries that can be used for playing and recording sound in Python, such as PyAudio and python-sounddevice. You’ll also see code snippets for playing and recording sound files and arrays, as well as for converting between different sound file formats.

    Topics:

    • 00:00:00 – Introduction
    • 00:02:04 – Reading and writing WAV files in Python
    • 00:04:48 – What did you want to learn about the topic?
    • 00:08:02 – Finding new ways to explain Python concepts
    • 00:09:52 – Turning audio into plots and visualizations
    • 00:12:11 – Using Python for synthesis and the guitar synth project
    • 00:13:19 – What is your music background?
    • 00:18:36 – Sponsor: Mailtrap
    • 00:19:11 – First prototype of the project
    • 00:22:23 – What does the project cover?
    • 00:25:08 – Audio examples of the output
    • 00:26:31 – Digging into the algorithm
    • 00:31:40 – Convolution reverb
    • 00:34:15 – Physical modeling and pedalboard
    • 00:38:08 – Video Course Spotlight
    • 00:39:31 – What Python concepts are you practicing?
    • 00:41:11 – Using Python poetry
    • 00:43:00 – Why use YAML for the TAB files?
    • 00:46:13 – What does it mean to be a polyglot programmer?
    • 00:48:37 – Potential upcoming Real Python resources
    • 00:52:10 – How can people follow your work online?
    • 00:52:30 – What do you want to learn next?
    • 00:54:56 – Thanks and goodbye

    Show Links:

    • Build a Guitar Synthesizer: Play Musical Tablature in Python – Real Python
    • Reading and Writing WAV Files in Python – Real Python
    • Episode #200: Avoiding Error Culture and Getting Help Inside Python – The Real Python Podcast
    • ActionScript - Wikipedia
    • Apache Flex® - Home Page
    • Too Many Zooz - Official Website
    • Watch Reverb - Watch the Sound With Mark Ronson (Season 1, Episode 3) - Apple TV+
    • Longest Reverb In the World - Inchindown - YouTube
    • Karplus–Strong string synthesis - Wikipedia
    • Physical modeling synthesis - Wikipedia
    • pedalboard: 🎛 🔊 A Python library for audio - Spotify
    • Poetry - Python dependency management and packaging made easy
    • Dependency Management With Python Poetry – Real Python
    • YAML: The Missing Battery in Python – Real Python
    • Guitar Tabs with Rhythm - Songsterr
    • It Starts with Food - The Whole30® Program
    • Bartosz Zaczyński - LinkedIn

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

    • Histogram Plotting in Python: NumPy, Matplotlib, Pandas & Seaborn
    • Playing and Recording Sound in Python
    • Simulating Real-World Processes in Python With SimPy

    Support the podcast & join our community of Pythonistas


    Python's Command-Line Utilities & Music Information Retrieval Tools Jun 21, 2024
    Show notes

    What are the built-in Python modules that can work as useful command-line tools? How can these tools add more functionality to Windows machines? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder’s Weekly articles and projects.

    Christopher shares an article by Trey Hunner about Python’s extensive collection of command-line utilities? The piece digs into general-purpose tools that format JSON data or start a simple web server and additional utilities for working with your Python code from the terminal.

    We cover a set of Jupyter Notebooks for teaching and learning the art of music processing and Music Information Retrieval (MIR). The notebooks are resources for working through the textbook, “Fundamentals of Music Processing: Audio, Analysis, Algorithms, Applications.”

    We also share several other articles and projects from the Python community, including a news roundup, a discussion of CRUD operations, a description of Python’s built-in bytes sequence, favorite essays on development and programming, Python resources for working with Excel, and a project for creating finite state machines in Python.

    This episode is sponsored by APILayer.

    Course Spotlight: Binary, Bytes, and Bitwise Operators in Python

    In this course, you’ll learn how to use Python’s bitwise operators to manipulate individual bits of data at the most granular level. With the help of hands-on examples, you’ll see how you can apply bitmasks and overload bitwise operators to control binary data in your code.

    Topics:

    • 00:00:00 – Introduction
    • 00:02:21 – Python 3.12.4 Released
    • 00:02:52 – Python 3.13.0 Beta 2 Released
    • 00:03:01 – PEP 712 Rejected
    • 00:04:18 – Django in Action - Mr. Trudeau’s Book has Launched!
    • 00:06:23 – What Are CRUD Operations?
    • 00:10:12 – Python’s Many Command-Line Utilities
    • 00:14:04 – Sponsor: APILayer
    • 00:14:55 – Notebooks for Fundamentals of Music Processing
    • 00:22:55 – bytes: The Lesser-Known Python Built-in Sequence
    • 00:26:57 – Video Course Spotlight
    • 00:28:34 – Essays on Programming I Think About a Lot
    • 00:41:28 – Python Resources for Working With Excel
    • 00:46:13 – Python Finite State Machines Made Easy
    • 00:50:10 – Thanks and goodbye

    News:

    • Python 3.12.4 Released – See the full list of changes in this release
    • Python 3.13.0 Beta 2 Released
    • PEP 712 Rejected – This Python Enhancement Proposal “Adding a ‘converter’ parameter to dataclasses.field” was determined to have an insufficient number of use cases.
    • Django in Action

    Show Links:

    • What Are CRUD Operations? – CRUD operations are the cornerstone of application functionality. Whether you access a database or interact with a REST API, you usually want to create, retrieve, update, and delete data. In this tutorial, you’ll explore how CRUD operations work in practice.
    • Python’s Many Command-Line Utilities – This article describes every command-line tool included with Python, each of which can be run with python -m module_name.
    • Notebooks for Fundamentals of Music Processing – This is a collection of Python Notebooks for teaching and learning the fundamentals of music processing. Examples include illustrations, sound samples, math, and more.
    • bytes: The Lesser-Known Python Built-in Sequence – The bytes data type looks a bit like a string, but it isn’t a string. This article explores it and also looks at the main Unicode encoding, UTF-8

    Discussion:

    • Essays on Programming I Think About a Lot – A collection of essays on software from a variety of sources. Content includes how to choose your tech stack, products, abstractions, and more.
    • Falsehoods programmers believe about time - Infinite Undo
    • Falsehoods programmers believe about email
    • Falsehoods programmers believe about geography – Thias の blog
    • awesome-falsehood: 😱 Falsehoods Programmers Believe In

    Projects:

    • Python Resources for Working With Excel
    • Python Finite State Machines Made Easy

    Additional Links:

    • SQLite and SQLAlchemy in Python: Move Your Data Beyond Flat Files – Real Python
    • Unicode in Python: Working With Character Encodings – Real Python
    • Fundamentals of Music Processing - Editions of the Book
    • Editing Excel Spreadsheets in Python With openpyxl – Real Python
    • My thoughts on Python in Excel
    • The Microsoft Excel superstars throw down in Vegas

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

    • Playing and Recording Sound in Python
    • Unicode in Python: Working With Character Encodings
    • Binary, Bytes, and Bitwise Operators in Python

    Support the podcast & join our community of Pythonistas


    Detecting Outliers in Your Data With Python Jun 14, 2024
    Show notes

    How do you find the most interesting or suspicious points within your data? What libraries and techniques can you use to detect these anomalies with Python? This week on the show, we speak with author Brett Kennedy about his book “Outlier Detection in Python.”

    Brett describes initially getting involved with detecting outliers in financial data. He discusses various applications and techniques in security, manufacturing, quality assurance, and fraud. We also dig into the concept of explainable AI and the differences between supervised and unsupervised learning.

    This episode is sponsored by APILayer.

    Course Spotlight: Using k-Nearest Neighbors (kNN) in Python

    In this video course, you’ll learn all about the k-nearest neighbors (kNN) algorithm in Python, including how to implement kNN from scratch. Once you understand how kNN works, you’ll use scikit-learn to facilitate your coding process.

    Topics:

    • 00:00:00 – Introduction
    • 00:01:56 – Describing the book
    • 00:03:22 – How did you get involved in outlier detection?
    • 00:06:50 – Initially looking at the data to spot errors
    • 00:08:22 – Amount of fraud and financial errors
    • 00:09:50 – Understanding the nature of the outliers
    • 00:12:15 – Industries that would be interested in detection
    • 00:18:21 – Sponsor: APILayer.com
    • 00:19:15 – Who is the intended audience for the book?
    • 00:22:16 – Differences between supervised vs unsupervised learning
    • 00:25:48 – Autonomous vehicles detecting anomalous imagery
    • 00:29:08 – What is explainable AI?
    • 00:36:21 – Video Course Spotlight
    • 00:37:43 – Detecting an outlier across multiple columns
    • 00:44:32 – Detection of LLM and bot activity
    • 00:49:49 – Proving you are a human checkbox
    • 00:52:25 – What are Python libraries for outlier detection?
    • 00:53:57 – Creating synthetic data to work through examples
    • 00:57:10 – Tools developed and described in the book
    • 01:01:29 – How to find the book
    • 01:02:27 – What are you excited about in the world of Python?
    • 01:04:55 – What do you want to learn next?
    • 01:05:52 – How can people follow your work online?
    • 01:06:16 – Thanks and goodbye

    Show Links:

    • Outlier Detection in Python
    • Episode #169: Improving Classification Models With XGBoost – The Real Python Podcast
    • XGBoost Documentation — xgboost 1.7.6 documentation
    • SHAP (SHapley Additive exPlanations) Documentation
    • I’m a teacher and this is the simple way I can tell if students have used AI to cheat in their essays - Daily Mail Online
    • pyod: A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
    • DeepOD: Deep learning-based outlier/anomaly detection
    • scikit-learn: machine learning in Python — scikit-learn 1.5.0 documentation
    • DataConsistencyChecker: A Python tool to examine datasets for consistency
    • Brett Kennedy - LinkedIn
    • Brett-Kennedy - GitHub

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

    • Starting With Linear Regression in Python
    • Data Cleaning With pandas and NumPy
    • Using k-Nearest Neighbors (kNN) in Python

    Support the podcast & join our community of Pythonistas


    Decomposing Software Problems & Avoiding the Trap of Clever Code Jun 07, 2024
    Show notes

    How do you effectively break a software problem into individual steps? What are signs you’re writing overly clever code? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder’s Weekly articles and projects.

    We discuss an article about de-warping images of book pages. We both found the piece a good study on decomposing a complex software problem.

    Christopher discusses an article titled “Clever code is probably the worst code you could write.” Early in a programming career, it’s easier to write complex and difficult-to-read code. The real challenge is progressing towards writing clearer and readable code.

    We also share several other articles and projects from the Python community, including a news roundup, what the __pycache__ folder is for in Python, what’s new in Django 5.1, a discussion about software engineering hiring and firing, a project for setting up repeated tasks, and a simple way to create reusable template components in Django.

    This episode is sponsored by Sentry.

    Course Spotlight: Efficient Iterations With Python Iterators and Iterables

    In this video course, you’ll learn what iterators and iterables are in Python. You’ll learn how they differ and when to use them in your code. You’ll also learn how to create your own iterators and iterables to make data processing more efficient.

    Topics:

    • 00:00:00 – Introduction
    • 00:02:18 – PEP 667: Consistent Views of Namespaces (Accepted)
    • 00:03:08 – PEP 649 Re-targeted to 3.14
    • 00:03:50 – Untold Stories From 6 Years Working on Python Packaging
    • 00:04:38 – What Is the __pycache__ Folder in Python?
    • 00:09:57 – Sponsor: Sentry
    • 00:11:04 – What’s New in Django 5.1
    • 00:17:48 – Page Dewarping
    • 00:26:55 – Video Course Spotlight
    • 00:28:26 – Clever Code Is Probably the Worst Code You Could Write
    • 00:33:19 – Software Engineering Hiring and Firing
    • 00:51:22 – Metronomes: An Easy Way to Set Up Regular Tasks
    • 00:52:26 – django-web-components: Create reusable template components in Django
    • 00:54:03 – Thanks and goodbye

    News:

    • PEP 667: Consistent Views of Namespaces (Accepted)
    • PEP 649 Re-targeted to 3.14 – Python Enhancement Proposal 649: Deferred Evaluation Of Annotations Using Descriptors has been re-targeted to the Python 3.14 release
    • Untold Stories From 6 Years Working on Python Packaging – Sumana gave the closing keynote address at PyCon US this year and this posting shares all the links and references from the talk.

    Show Links:

    • What Is the __pycache__ Folder in Python? – In this tutorial, you’ll explore Python’s __pycache__ folder. You’ll learn about when and why the interpreter creates these folders, and you’ll customize their default behavior. Finally, you’ll take a look under the hood of the cached .pyc files.
    • What’s New in Django 5.1 – Django 5.1 has gone alpha so the list of features targeting this release has more or less solidified. This article introduces you to what is coming in Django 5.1.
    • Page Dewarping – This article shows the techniques behind a page flattening algorithm. It starts with images of a book’s page which are curled from the spine of the book, and creates a resulting PDF that is a flat version.
    • Clever Code Is Probably the Worst Code You Could Write – When you come across a clever bit of code, it is hard not to admire it, but often times, clear, readable code is the hardest code to write.

    Discussion:

    • Software Engineering Hiring and Firing – This article is a deep dive on the hiring and firing practices in the software field, and unlike most articles focuses on senior engineering roles. It isn’t a “first job” post, but a “how the decision process works” article.

    Projects:

    • Metronomes: An Easy Way to Set Up Regular Tasks
    • django-web-components: A simple way to create reusable template components in Django

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

    • For Loops in Python (Definite Iteration)
    • Getting Started With Django: Building a Portfolio App
    • Efficient Iterations With Python Iterators and Iterables

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    Building Python Unit Tests & Exploring a Data Visualization Gallery May 31, 2024
    Show notes

    How do you start adding unit tests to your Python code? Can the built-in unittest framework cover most or all of your needs? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder’s Weekly articles and projects.

    We dig into a recent tutorial by Leodanis Pozo Ramos about writing unit tests using Python’s unittest. The tutorial covers organizing your tests, exploring assert methods, creating test fixtures, and debugging failing tests.

    We explore a collection of Python data visualizations and tutorials from the Python Graph Gallery. The website features hundreds of charts and graphs built using popular plotting libraries. Each chart type features a foundational tutorial that introduces the structure and application.

    We also share several other articles and projects from the Python community, including a news roundup, the new REPL coming in Python 3.13, a pytest daemon to 10X test iteration speed, a discussion about software friction, a Raspberry Pi document scanner, and a project for controlling time per iteration loop.

    Course Spotlight: Building a Python GUI Application With Tkinter

    In this video course, you’ll learn the basics of GUI programming with Tkinter, the de facto Python GUI framework. Master GUI programming concepts such as widgets, geometry managers, and event handlers. Then, put it all together by building two applications: a temperature converter and a text editor.

    Topics:

    • 00:00:00 - Introduction
    • 00:02:08 - Python Software Foundation Board Election Dates for 2024
    • 00:02:35 - 2023 PSF Annual Impact Report
    • 00:03:03 - Python’s unittest: Writing Unit Tests for Your Code
    • 00:09:41 - What’s New in Python 3.13
    • 00:10:38 - The New REPL in Python 3.13
    • 00:13:39 - Best Python Chart Examples
    • 00:15:27 - Animation with text that highlights important events
    • 00:16:39 - Sankey Diagram with Python and Plotly
    • 00:18:55 - Video Course Spotlight
    • 00:20:25 - Pytest Daemon: 10X Local Test Iteration Speed
    • 00:23:58 - Software Friction
    • 00:35:41 - A Raspberry Pi Document Scanner
    • 00:39:00 - pacemaker: For Controlling Time Per Iteration Loop in Python
    • 00:41:55 - Thanks and goodbye

    News:

    • Python Software Foundation Board Election Dates for 2024
    • 2023 PSF Annual Impact Report

    Show Links:

    • Python’s unittest: Writing Unit Tests for Your Code – In this tutorial, you’ll learn how to use the unittest framework to create unit tests for your Python code. Along the way, you’ll also learn how to create test cases, fixtures, test suites, and more.
    • What’s New in Python 3.13 – Python 3.13 has gone into beta, which means the feature freeze is now in place. This is the official listing of the new features in 3.13. This release includes changes to the REPL, new typing features, experimental support for disabling the GIL, dead battery removal, and more.
    • The New REPL in Python 3.13 – Python 3.13 just hit feature freeze with the first beta release, and it includes a host of improvements to the REPL. Automatic indenting, block-level editing, and more make the built-in REPL more powerful and easier to use.
    • Best Python Chart Examples
    • Animation with text that highlights important events - Python Graph Gallery
    • Sankey Diagram with Python and Plotly - Python Graph Gallery
    • Pytest Daemon: 10X Local Test Iteration Speed – Discord has a large Python monolith with lots of imports, which now takes 13 seconds to start up. On the server that’s not a problem but to run a test it is. Ruby’s solution is to have a daemon that hot loads a test on a process that already has the imports completed.

    Discussion:

    • Software Friction – Friction is everywhere in software development. Two setbacks are more than twice as bad as one setback. This article discusses the sources of software friction and what you can do about it.

    Projects:

    • A Raspberry Pi Document Scanner
    • pacemaker: For Controlling Time Per Iteration Loop in Python

    Additional Links:

    • unittest — Unit testing framework — Python 3.12.3 documentation
    • Testing with Python (part 1): the basics - Bite code!
    • Sankey Diagrams – A Sankey diagram says more than 1000 pie charts
    • tidytuesday: Official repo for the #tidytuesday project
    • tidytuesday - dataset_announcements
    • Chaos Monkey
    • OpenCV: OpenCV modules
    • How to Train Your Robot

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

    • Creating PyQt Layouts for GUI Applications
    • Testing Your Code With pytest
    • Building a Python GUI Application With Tkinter

    Support the podcast & join our community of Pythonistas


    Considering Accessibility & Assistive Tech as a Python Developer May 17, 2024
    Show notes

    What’s it like to learn Python as a visually impaired or blind developer? How can you improve the accessibility of your Python web applications and learn current guidelines? This week on the show, Real Python community member Audrey van Breederode discusses her programming journey, web accessibility, and assistive technology.

    Audrey shares her background as a system administrator and instructor. While she was learning Python, she discovered Real Python. Audrey provided some feedback about the built-in video player’s accessibility. Dan reached out and worked with Audrey on some website improvements for the visually impaired.

    We discuss navigating modern websites and using assistive technology. Audrey also provides resources Python developers can use to improve the accessibility of their applications.

    Course Spotlight: HTML and CSS Foundations for Python Developers

    There’s no way around HTML and CSS when you want to build web apps. Even if you’re not aiming to become a web developer, knowing the basics of HTML and CSS will help you understand the Web better. In this video course, you’ll get an introduction to HTML and CSS for Python programmers.

    Topics:

    • 00:00:00 – Introduction
    • 00:03:12 – Work background
    • 00:08:30 – Language for assistive tools and programming
    • 00:10:30 – What led you to learning Python?
    • 00:13:48 – Screen readers, braille display, and white space
    • 00:17:22 – Discovering Real Python
    • 00:22:41 – Accessibility survey and navigating websites
    • 00:30:04 – Digging deeper into learning Python
    • 00:35:42 – Video Course Spotlight
    • 00:37:03 – Navigating changes in code
    • 00:39:53 – Working with the terminal
    • 00:42:14 – Accessibility of Python GUI libraries
    • 00:44:22 – Django framework
    • 00:47:11 – Screen readers and JAWS
    • 00:53:19 – What are you excited about in the world of assistive technology?
    • 00:57:03 – What are you excited about in the world of Python?
    • 00:59:11 – What do you want to learn next?
    • 01:00:09 – Thanks and goodbye

    Show Links:

    • JAWS® – Freedom Scientific
    • What is JAWS? - YouTube
    • Retinal detachment - Wikipedia
    • Focus 80 Blue 5th Gen – Freedom Scientific
    • WebAIM: Screen Reader User Survey #10 Results
    • Web Content Accessibility Guidelines (WCAG) 2.2
    • SecureCRT - The rock-solid Telnet and SSH client for Windows, macOS, and Linux
    • P1 Monitor docker container for smart meters - Marcel Claassen
    • Python Basics: Introduction to Python (Learning Path) – Real Python
    • The web framework for perfectionists with deadlines - Django
    • Surf’s Up! Surfing the Internet with JAWS
    • NV Access - Download NVDA
    • Picture Smart Challenges – Freedom Scientific

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

    • Getting Started With Django: Building a Portfolio App
    • Python Basics: Dictionaries
    • HTML and CSS Foundations for Python Developers

    Support the podcast & join our community of Pythonistas


    Querying OpenStreetMaps via API & Lazy Evaluation in Python May 10, 2024
    Show notes

    Would you like to get more practice working with APIs in Python? How about exploring the globe using the data from OpenStreetMap? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder’s Weekly articles and projects.

    We share an article from the Pybites blog about building queries using the Overpass API for OpenStreetMap. The post explores the data structures, tags, query formats, and how to use Overpass in Python.

    Christopher discusses a Real Python article by recent guest Stephen Gruppetta about lazy evaluation in Python. The piece covers the advantages of generator expressions or functions and the potential disadvantages of using lazy versus eager evaluation methods.

    We also share several other articles and projects from the Python community, including a news roundup, handling control-c in asyncio, preventing data leakage in pandas and scikit-learn, discussing the Django developer survey results, asking developers why they aren’t shipping faster, using UV to install into isolated environments, and a couple of tools for retrying in Python.

    This episode is sponsored by Sentry.

    Course Spotlight: How to Set Up a Django Project

    In this course, you’ll learn the necessary steps that you’ll need to take to set up a new Django project. You’ll learn the basic setup for any new Django project, which needs to happen before programming the specific functionality of your project.

    Topics:

    • 00:00:00 – Introduction
    • 00:02:33 – PyPy v7.3.16 Release
    • 00:02:54 – PEP 745: Python 3.14 Release Schedule
    • 00:03:31 – The BASIC programming language turns 60
    • 00:05:24 – Asyncio Handle Control-C (SIGINT)
    • 00:07:37 – OpenStreetMaps, Overpass API and Python
    • 00:11:53 – What’s Lazy Evaluation in Python?
    • 00:16:10 – Sponsor: Sentry
    • 00:17:17 – How to Prevent Data Leakage in pandas & scikit-learn
    • 00:24:09 – Django Developers Survey 2023 Results
    • 00:33:07 – Video Course Spotlight
    • 00:34:21 – I Asked 100 Devs Why They Aren’t Shipping Faster?
    • 00:47:03 – pipxu: Install in Isolated Environments Using UV
    • 00:49:05 – tenacity: Retrying Library for Python
    • 00:50:04 – stamina: Production-Grade Retries for Python
    • 00:52:00 – Thanks and goodbye

    News:

    • PyPy v7.3.16 Release
    • PEP 745: Python 3.14 Release Schedule
    • The BASIC programming language turns 60 - Ars Technica

    Show Links:

    • Asyncio Handle Control-C (SIGINT) – When the user presses CTRL-C on the keyboard, the OS raises an interrupt signal to your program. When writing concurrent code this can get complicated as the signal goes to the process. This article shows you how to handle capturing CTRL-C elegantly when using asyncio.
    • OpenStreetMaps, Overpass API and Python – OpenStreetMaps (OSM) is an open source mapping project that allows people to browse the world map and to plan routes. Not only does it have the expected web interface, but it also has an API known as Overpass. This article shows you two ways to use Python to query Overpass.
    • What’s Lazy Evaluation in Python? – This tutorial explores lazy evaluation in Python and looks at the advantages and disadvantages of using lazy and eager evaluation methods. By the end of this tutorial, you’ll clearly understand which approach is best for you, depending on your needs.
    • How to Prevent Data Leakage in pandas & scikit-learn – How you impute missing values in machine learning data sets can affect the quality of your training. This article teaches you what data leakage is and what steps you should take to avoid it.

    Discussion

    • Django Developers Survey 2023 Results
    • I Asked 100 Devs Why They Aren’t Shipping Faster? – Daksh asked 100 developers why they aren’t shipping faster and this blog post shares what he learned. Problems include dependency bugs, overly complicated code bases, waiting on requirements, and more.

    Projects:

    • pipxu: Install in Isolated Environments Using UV
    • tenacity: Retrying Library for Python
    • stamina: Production-Grade Retries for Python

    Additional Links:

    • NASA’s Voyager 1 spacecraft finally phones home after 5 months of no contact - Space
    • Python & APIs: A Winning Combo for Reading Public Data – Real Python
    • Loading Data from OpenStreetMap with Python and the Overpass API - Nikolai Janakiev
    • Leakage (machine learning) - Wikipedia
    • Djangonaut Space - Where Contributors launch!
    • Debris That Fell Off a Boeing 767 Found Outside the House of Lawyer

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

    • Getting Started With Django: Building a Portfolio App
    • Python Generators 101
    • How to Set Up a Django Project

    Support the podcast & join our community of Pythonistas


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