The Real Python Podcast

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. Topics: 00:00:00 – Introduction 00:02:19 – Python 3.11.0rc2 is now available 00:03:45 – HTML and CSS for Python Developers 00:08:34 – Evolution of Access Control Explained Through Python 00:17:14 – Sponsor: InfluxDB 00:18:03 – Dangerous Pickles 00:28:08 – Building Command Line Interfaces With argparse 00:34:27 – Video Course Spotlight 00:35:45 – PyPI.org is running a survey 00:49:01 – Visual Python Tkinter GUI Creator 00:50:33 – Python Data Visualization Cookbook 00:52:06 – django-functest: Helpers for Functional Tests in Django 00:57:55 – Thanks and goodbye Show Links: Python Insider: Python 3.11.0rc2 is now available HTML and CSS 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 tutorial, you’ll get an introduction to HTML and CSS for Python programmers. Evolution of Access Control Explained Through Python – Sometimes, writing code can help you explore and understand concepts. This article shows a history of access controls in software, using Python scripts to reimplement the ideas. Dangerous Pickles – A light introduction to the Python pickle protocol, the Pickle Machine, and the construction of malicious pickles. Learn why your code shouldn’t trust arbitrary serialized objects, and discover the dangers of pickle-bombs. Building Command Line Interfaces With argparse – In this step-by-step Python video course, you’ll learn how to take your command line Python scripts to the next level by adding a convenient command line interface that you can write with argparse. Discussion: Python Packaging User Survey PyPI.org is running a survey on the state of Python packaging | Hacker News Projects: Visual Python Tkinter GUI Creator - Chinese Python Data Visualization Cookbook django-functest: Helpers for Functional Tests in Django Additional Links: Axess Lab | Alt-texts: The Ultimate Guide The Python pickle Module: How to Persist Objects in Python – Real Python Understanding pickle in Python | #hsfzxjy# The ultimate guide to Python pickle | Snyk Pickle’s nine flaws | Ned Batchelder pickle — Python object serialization — Python 3.10.7 documentation pickletools — Tools for pickle developers — Python 3.10.7 documentation argparse — Parser for command-line option | Python 3.10.7 documentation Have been testing @pyscript_dev these past few days and finally made something cool. I built an interactive data viz cookbook | Dylan Castillo - Twitter Level up your Python skills with our expert-led courses: Grow Your Python Portfolio With 13 Intermediate Project Ideas Building Command Line Interfaces With argparse Serializing Objects With the Python pickle Module Support the podcast & join our community of Pythonistas

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. Topics: 00:00:00 – Introduction 00:02:10 – Meeting at PyCon US 2022 00:04:32 – Bringing members of team to PyCon 00:05:30 – What are next generation instrumentation platforms? 00:06:35 – What is the lifespan of a platform? 00:09:26 – Has interconnectivity affected upgrades? 00:10:57 – Programming and Python background 00:12:13 – Introduction to MATLAB at university 00:15:18 – Moving away from MATLAB to Python 00:19:39 – How was your transition from Python 2 to 3? 00:21:19 – Debugging methods and logging 00:22:27 – Why did you choose Python? 00:24:26 – Sponsor: Deepgram 00:25:12 – Promoting more use of Python in the organization 00:33:07 – Selling the idea of Python training in the organization 00:37:16 – Moving from scripts to building packages 00:43:48 – From personal project to critical package on PyPI 00:44:29 – Using PyPI or in-house package repository 00:46:27 – Experience with modern packaging tools 00:48:16 – Video Course Spotlight 00:49:32 – Using CircuitPython for personal and work projects 00:56:09 – Use of 3D printing and machining 00:57:33 – Josh’s projects on PyPI 01:02:57 – What are you excited about in the world of Python? 01:05:23 – What do you want to learn next? 01:08:46 – How can people follow your work? 01:09:07 – Thanks and goodbye Show Links: PyPI Profile of joshburnett PyCon 2022 Welcome to PyCon US 2022 MATLAB - MathWorks - MATLAB & Simulink devpi: PyPI server and packaging/testing/release tool Artifactory - Universal Artifact Repository Manager - JFrog loguru · PyPI How to Publish an Open-Source Python Package to PyPI – Real Python Python and TOML: New Best Friends – Real Python PyQtGraph - Scientific Graphics and GUI Library for Python CircuitPython Adafruit MagTag - 2.9 Grayscale E-Ink WiFi Display canaveral · PyPI addcopyfighandler · PyPI PyScript | Run Python in your HTML What exactly is WASI? - Wasm Builders 🧱 WASI - WebAssembly System Interface KiCad EDA - Schematic Capture & PCB Design Software Lessons learned from building a custom CircuitPython board - Stargirl (Thea) Flowers Using Python to vectorize artwork for PCBs - Stargirl (Thea) Flowers Josh Burnett - GitHub Josh Burnett - LinkedIn Level up your Python skills with our expert-led courses: Building Python Project Documentation With MkDocs How to Publish Your Own Python Package to PyPI Python Modules and Packages: An Introduction Support the podcast & join our community of Pythonistas

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. Topics: 00:00:00 – Introduction 00:02:21 – Python releases 3.10.7, 3.9.14, 3.8.14, and 3.7.14 are now available 00:03:51 – How Can You Install a Pre-Release Version of Python? 00:08:13 – Understanding async Python for the Web 00:17:11 – The Magic of Matplotlib Style Sheets 00:24:20 – Sponsor: Platform.sh 00:24:56 – Caching in Python With lru_cache 00:29:41 – Some Ways to Get Better at Debugging 00:38:14 – Video Course Spotlight 00:39:26 – Suggest a Lesser Known Library Deserving Attention 00:44:52 – ruff: An Extremely Fast Python Linter, Written in Rust 00:48:19 – Manim: Python Library for Creating Mathematical Animations 00:51:50 – Thanks and goodbye Show Links: Python releases 3.10.7, 3.9.14, 3.8.14, and 3.7.14 are now available How Can You Install a Pre-Release Version of Python? – If you want to have a peek at what’s coming in the next stable version of Python, then you can install a pre-release version. In this tutorial, you’ll learn how to access the latest Python versions and help test them. Understanding async Python for the Web – “Recently Django 4.1 was released, and the thing most people seem interested in is the expanded 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. The Magic of Matplotlib Stylesheets – With a single line of code, you can integrate a style sheet with your Matplotlib visualization. In this tutorial, you’ll learn how to make your very own custom reusable style sheet. 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. Some Ways to Get Better at Debugging – This is a short summary of a couple of academic papers on how to improve your debugging skills. The suggestions are to learn the codebase, learn the system, learn your tools, learn strategies, and gain experience. Discussions: Suggest a Lesser Known Library Deserving Attention Projects: ruff: An Extremely Fast Python Linter, Written in Rust Manim: Python Library for Creating Mathematical Animations Additional Links: Managing Multiple Python Versions With pyenv – Real Python Your Python Coding Environment on Windows: Setup Guide – Real Python Customizing Matplotlib with style sheets and rcParams — Matplotlib 3.5.3 documentation dhaitz/matplotlib-stylesheets: Stylesheets for Matplotlib Kaggle: Your Home for Data Science wizard zines Rubber Duck Debugging – Debugging software with a rubber ducky pudb · PyPI Humre · PyPI Welcome to Nox — Nox 2022.8.7 documentation Episode #21: Exploring K-means Clustering and Building a Gradebook With Pandas – The Real Python Podcast 3Blue1Brown - YouTube Level up your Python skills with our expert-led courses: Python Basics: Finding and Fixing Code Bugs Python Plotting With Matplotlib Debugging in Python With pdb Support the podcast & join our community of Pythonistas

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. Topics: 00:00:00 – Introduction 00:01:55 – The Recursive Book of Recursion 00:02:55 – A Beginner’s Guide to Recursion - YouTube 00:05:41 – What is recursion? 00:10:17 – Understanding the call stack 00:12:15 – Languages moving from GOTO statements to functions and a stack 00:21:11 – A common recursion example of factorials 00:26:00 – Fibonacci sequence and memoization 00:30:25 – Cautionary advice on applying recursion 00:32:55 – What is recursion useful for? 00:39:56 – Video Course Spotlight 00:41:14 – Recursion and directed acyclic graphs 00:45:46 – Book examples 00:49:50 – Thoughts on tail recursion 00:54:34 – How has the scope of the book evolved? 01:00:34 – Creating examples in two languages 01:02:37 – Upcoming projects 01:05:19 – Examples of the projects in the book 01:10:30 – What are you excited about in the world of Python? 01:14:50 – What do you want to learn next? 01:19:06 – How can people follow your work? 01:19:48 – Thanks and goodbye Show Links: The Recursive Book of Recursion | No Starch Press Recursion for Beginners: A Beginner’s Guide to Recursion - YouTube The Invent with Python Blog Recursion in Python factorial | Definition, Symbol, & Facts | Britannica Fibonacci sequence | Definition, Formula, Numbers, Ratio, & Facts | Britannica A Python Guide to the Fibonacci Sequence – Real Python Directed acyclic graph - Wikipedia Dynamic programming - Wikipedia The Little Schemer : Friedman, Daniel P : Internet Archive Book Review: The Little Schemer - The Invent with Python Blog Droste effect - Wikipedia Episode #33: Going Beyond the Basic Stuff With Python and Al Sweigart – The Real Python Podcast Textualize Episode #80: Make Your Python App Interactive With a Text User Interface (TUI) – The Real Python Podcast BeeWare — Write once. Deploy everywhere. Episode #22: Create Cross-Platform Python GUI Apps With BeeWare – The Real Python Podcast Origami with Jo Nakashima - YouTube Invent with Python Level up your Python skills with our expert-led courses: Grow Your Python Portfolio With 13 Intermediate Project Ideas Caching in Python With lru_cache Exploring the Fibonacci Sequence With Python Support the podcast & join our community of Pythonistas

How does a code completion tool work? What is an Abstract Syntax Tree, and how is it created in Python? How does an AST help you write programs and projects that inspect and modify your Python code? This week on the show, Meredydd Luff, co-founder of Anvil, shares his PyCon talk, “Building a Python Code Completer.” Meredydd talks about his experience building a code completion engine for the Anvil platform. The conversation leads us to discuss how Python parses the code that you type. We examine tokenization, abstract syntax trees, and how parsing has changed in Python. We cover additional projects that you can explore once you have a tool that inspects the Python code you’re writing. Join us as we dive into multiple rabbit holes of research and exploration. Course Spotlight: Python Assignment Expressions and Using the Walrus Operator In this course, you’ll learn about assignment expressions and the walrus operator. The biggest change in Python 3.8 was the inclusion of the := operator, which you can use to assign variables in the middle of expressions. You’ll see several examples of how to take advantage of this feature. Topics: 00:00:00 – Introduction 00:02:11 – Building a Python Code Completer - Talk 00:08:48 – How is recursion being used? 00:10:28 – Abstract Syntax Trees, Parsers, and Tokens 00:14:58 – Sponsor: CData Software 00:15:39 – Is parsing into tokens a separate step? 00:21:45 – What makes the new PEG parser unique? 00:25:32 – Using the AST doesn’t have to be scary. 00:27:33 – More on the PEG parser 00:29:54 – Keeping scope and holding completions 00:39:43 – Video Course Spotlight 00:41:15 – Was this your first expirement in creating a code completer? 00:46:46 – How can adding type hints assist a completer? 00:50:53 – Projects you can build using AST 00:53:02 – Linter project 00:54:15 – Automatic code formatter 00:54:59 – Code testing and the pytest project 00:56:22 – Security tools 00:57:11 – Friendlier tracebacks 00:59:57 – Code completion vs GitHub Copilot 01:04:14 – Code completion in a text editor vs IDE 01:08:53 – What are you excited about in the world of Python? 01:09:54 – What do you want to learn next? 01:11:20 – How can people follow your work? 01:12:31 – Thanks and goodbye Show Links: Talk - Meredydd Luff: Building a Python Code Completer - YouTube Anvil | Build Web Apps with Nothing but Python Episode #63: Create Web Applications Using Only Python With Anvil – The Real Python Podcast “Writing a PEG parser for fun and profit” - Guido van Rossum (North Bay Python 2019) - YouTube PEG Parsing Series Overview. My series of blog posts about PEG | by Guido van Rossum Abstract syntax tree - Wikipedia Parse tree - Wikipedia ast — Abstract Syntax Trees — Python 3.10.6 documentation Full Grammar specification — Python 3.10.6 documentation Python AST Explorer Examples of working with ASTs — Green Tree Snakes 1.0 documentation bellybutton: Custom Python linting through AST expressions black · PyPI pytest: helps you write better programs — pytest documentation friendly-traceback: Friendlier Python tracebacks. Raspberry Pi Pico – Raspberry Pi Raspberry Pi Pico W : ID 5526 : $6.00 : Adafruit Industries, Unique & fun DIY electronics and kits State management - Wikipedia Recoil Meredydd Luff (@meredydd) / Twitter Level up your Python skills with our expert-led courses: Python Assignment Expressions and Using the Walrus Operator Testing Your Code With pytest Writing Beautiful Pythonic Code With PEP 8 Support the podcast & join our community of Pythonistas

Have you attempted to set up a Python development environment on Windows before? Would it be helpful to have an easy-to-follow guide to get you started? 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 tutorial that covers configuring a Windows coding environment. The guide contains valuable suggestions, best practices, and powerful coding tools. It also covers how to use a package manager, the new Windows Terminal, PowerShell Core, and a program to manage multiple versions of Python. Christopher covers another Real Python tutorial about using TOML in Python. TOML is a configuration format for building and distributing your own packages. We discuss how TOML parsing will be added to Python’s standard library in version 3.11. We cover several other articles and projects from the Python community, on topics including technical writing for developers, a news round-up, a farewell to obsolete Python libraries, uncommon uses of Python in commonly used libraries, a prettier ls, and a project for advanced hot reloading in Python. Course Spotlight: Python Basics: Finding and Fixing Code Bugs In this Python Basics video course, you’ll learn how to identify and fix logic errors, or bugs, in your Python code. You’ll use the built-in debugging tools in Python’s Integrated Development and Learning Environment to practice locating and resolving bugs in an example function. Topics: 00:00:00 – Introduction 00:02:13 – Python 3.10.6 Released 00:02:41 – Python 3.11.0rc1 Released 00:03:13 – Django 4.1 Released 00:04:07 – 10 malicious Python packages exposed in latest repository attack 00:05:12 – Protestware: Why Developers Sabotage Their Own Code 00:06:41 – Python and TOML: New Best Friends 00:16:19 – Say Goodbye to These Obsolete Python Libraries 00:25:51 – Video Course Spotlight 00:27:26 – Uncommon Uses of Python in Commonly Used Libraries 00:37:56 – Your Python Coding Environment on Windows: Setup Guide 00:48:20 – Technical Writing for Developers 00:55:24 – reloadium: Advanced Hot Reloading for Python 00:58:07 – pls: A Prettier ‘ls’ 01:00:56 – Thanks and goodbye News: Python 3.10.6 Released Python 3.11.0rc1 Released Django 4.1 Released 10 malicious Python packages exposed in latest repository attack | Ars Technica Protestware: Why Developers Sabotage Their Own Code Topic Links: Python and TOML: New Best Friends – TOML is a configuration file format that’s becoming increasingly popular in the Python community. In this tutorial, you’ll learn the syntax of TOML and explore how you can work with TOML files in your own projects. Say Goodbye to These Obsolete Python Libraries – It’s time to say goodbye to os.path, random, pytz, namedtuple and many more obsolete Python libraries. Start using the latest and greatest ones instead. Uncommon Uses of Python in Commonly Used Libraries – To learn more about writing maintainable Python, Eugene has been reading code from some of the more popular Python libraries. This blog post talks about some of the coding patterns he has encountered along the way. Your Python Coding Environment on Windows: Setup Guide – With this opinionated guide to setting up a basic, fully featured, and flexible setup for Python coding and contributing to open-source projects when working from Windows, you’ll go from a fresh install to ready to contribute, and even check out a PowerShell script to automate much of the process. Discussion: Technical Writing for Developers – “The way we write about and around code is arguably as important as the code itself.” This article outlines how programming and writing come together to take your developer skills to the next level. Projects: reloadium: Advanced Hot Reloading for Python pls: A Prettier ‘ls’ Additional Links: Python 3.11 Preview: TOML and tomllib – Real Python Why you should be using pathlib No really, pathlib is great Episode #116: Exploring Functional Programming in Python With Bruce Eckel – The Real Python Podcast Episode #101: Tools for Setting Up Python on a New Machine – The Real Python Podcast pls: Documentation Level up your Python skills with our expert-led courses: Python Basics: Finding and Fixing Code Bugs Practical Recipes for Working With Files in Python Debugging in Python With pdb Support the podcast & join our community of Pythonistas

What’s the big breakthrough for Natural Language Processing (NLP) that has dramatically advanced machine learning into deep learning? What makes these transformer models unique, and what defines “attention?” This week on the show, Jodie Burchell, developer advocate for data science at JetBrains, continues our talk about how machine learning (ML) models understand and generate text. This episode is a continuation of the conversation in episode #119. Jodie builds on the concepts of bag-of-words, word2vec, and simple embedding models. We talk about the breakthrough mechanism called “attention,” which allows for parallelization in building models. We also discuss the two major transformer models, BERT and GPT3. Jodie continues to share multiple resources to help you continue exploring modeling and NLP with Python. Course Spotlight: Building a Neural Network & Making Predictions With Python AI In this step-by-step course, you’ll build a neural network from scratch as an introduction to the world of artificial intelligence (AI) in Python. You’ll learn how to train your neural network and make predictions based on a given dataset. Topics: 00:00:00 – Introduction 00:02:20 – Where we left off with word2vec… 00:03:35 – Example of losing context 00:06:50 – Working at scale and adding attention 00:12:34 – Multiple levels of training for the model 00:14:10 – Attention is the basis for transformer models 00:15:07 – BERT (Bidirectional Encoder Representations from Transformers) 00:16:29 – GPT (Generative Pre-trained Transformer) 00:19:08 – Video Course Spotlight 00:20:08 – How far have we moved forward? 00:20:41 – Access to GPT-2 via Hugging Face 00:23:56 – How to access and use these models? 00:30:42 – Cost of training GPT-3 00:35:01 – Resources to practice and learn with BERT 00:38:19 – GPT-3 and GitHub Copilot 00:44:35 – DALL-E is a transformer 00:46:13 – Help yourself to the show notes! 00:49:19 – How can people follow your work? 00:50:03 – Thanks and goodbye Show Links: Recurrent neural network - Wikipedia Long short-term memory - Wikipedia Vanishing gradient problem - Wikipedia Vanishing Gradient Problem | What is Vanishing Gradient Problem? Attention Is All You Need | Cornell University Visualizing A Neural Machine Translation Model (Mechanics of Seq2seq Models With Attention) – Jay Alammar Standing on the Shoulders of Giant Frozen Language Models | Cornell University #datalift22 Embeddings paradigm shift: Model training to vector similarity search by Nava Levy - YouTube Transformer Neural Networks - EXPLAINED! (Attention is all you need) - YouTube BERT 101 - State Of The Art NLP Model Explained How GPT3 Works - Easily Explained with Animations - YouTube Write With Transformer (GPT2 Live Playground Tool) - Hugging Face Language Model with Alpa (GPT3 Live Playground Tool) OPT-175B Big Data | Music OpenAI API 🤗 (Hugging Face)Transformers Notebooks GitHub Copilot: Fly With Python at the Speed of Thought GitHub Copilot learned about the daily struggle of JavaScript developers after being trained on billions of lines of code. | Marek Sotak on Twitter Jodie Burchell’s Blog - Standard error Jodie Burchell 🇦🇺🇩🇪 (@t_redactyl) / Twitter JetBrains: Essential tools for software developers and teams Level up your Python skills with our expert-led courses: Building a Neural Network & Making Predictions With Python AI Learn Text Classification With Python and Keras The pandas DataFrame: Working With Data Efficiently Support the podcast & join our community of Pythonistas

Is there someone in your life you’d like to inspire to learn Python? Mission Encodeable is a website designed to teach people to code, built by two high-school students. This week on the show, Anna and Harry Wake talk about creating their site and motivating people to start coding. We discuss why they decided to build the site. Anna and Harry initially felt that the site would be for other students but soon realized it could be helpful for anyone interested in starting to code in Python. We cover the project-based approach and how they implemented the interactive browser-based tool replit.com. We talk about learning Python in the classroom and how they found additional books and tutorials to supplement their coding education. Anna and Harry also created a resource hub to help teachers take advantage of the site. Course Spotlight: Rock, Paper, Scissors With Python: A Command Line Game In this course, you’ll learn to program rock paper scissors in Python from scratch. You’ll learn how to take in user input, make the computer choose a random action, determine a winner, and split your code into functions. Topics: 00:00:00 – Introduction 00:02:17 – Personal backgrounds 00:02:51 – What’s the goal for the site? 00:03:54 – How did you come up with the idea? 00:05:08 – Where have you shared it? 00:06:39 – Projects for each level 00:09:28 – How has the response been? 00:10:10 – Using replit 00:12:56 – Sponsor: CData Software 00:13:37 – Design of the site and other tools to create it 00:15:49 – Learning Python and classes at school 00:17:41 – Did remote school inspire more online exploration? 00:19:16 – Myths of how kids learn programming 00:23:32 – More about projects 00:27:57 – Video Course Spotlight 00:29:27 – What other areas of Python do you want to explore? 00:33:08 – Teachers using the site 00:37:11 – What other resources have you used to learn Python? 00:38:52 – What are you excited about in the world of Python? 00:40:01 – What do you want to learn next? 00:42:06 – Thanks and goodbye Show Links: Mission Encodeable | Free coding tutorials for young people Replit - The collaborative browser based IDE Make Your First Python Game: Rock, Paper, Scissors! – Real Python Figma: the collaborative interface design tool. React – A JavaScript library for building user interfaces Coding with Minecraft - Al Sweigart The Recursive Book of Recursion - Al Sweigart Codewars - Achieve mastery through coding practice and developer mentorship Advent of Code 2021 Object-Oriented Programming (OOP) in Python 3 – Real Python Python Arcade Craig’n’Dave “Unscripted” - Mission Encodeable - YouTube Hello World issue 19 — Hello World LearningDust: LearningDust 3.15 - Anna & Harry Wake Teaching Python Episode 93: Mission Encodeable Mission Encodeable (@missionencode) / Twitter Level up your Python skills with our expert-led courses: Grow Your Python Portfolio With 13 Intermediate Project Ideas Getting Started With Django: Building a Portfolio App Rock, Paper, Scissors With Python: A Command Line Game Support the podcast & join our community of Pythonistas

How do you process and classify text documents in Python? What are the fundamental techniques and building blocks for Natural Language Processing (NLP)? This week on the show, Jodie Burchell, developer advocate for data science at JetBrains, talks about how machine learning (ML) models understand text. Jodie explains how ML models require data in a structured format, which involves transforming text documents into columns and rows. She covers the most straightforward approach, called binary vectorization. We discuss the bag-of-words method and the tools of stemming, lemmatization, and count vectorization. We jump into word embedding models next. Jodie talks about WordNet, Natural Language Toolkit (NLTK), word2vec, and Gensim. Our conversation lays a foundation for starting with text classification, implementing sentiment analysis, and building projects using these tools. Jodie also shares multiple resources to help you continue exploring NLP and modeling. Course Spotlight: Learn Text Classification With Python and Keras In this course, you’ll learn about Python text classification with Keras, working your way from a bag-of-words model with logistic regression to more advanced methods, such as convolutional neural networks. You’ll see how you can use pretrained word embeddings, and you’ll squeeze more performance out of your model through hyperparameter optimization. Topics: 00:00:00 – Introduction 00:02:47 – Exploring the topic 00:06:00 – Perceived sentience of LaMDA 00:10:24 – How do we get started? 00:11:16 – What are classification and sentiment analysis? 00:13:03 – Transforming text in rows and columns 00:14:47 – Sponsor: Snyk 00:15:27 – Bag-of-words approach 00:19:12 – Stemming and lemmatization 00:22:05 – Capturing N-grams 00:25:34 – Count vectorization 00:27:14 – Stop words 00:28:46 – Text Frequency / Inverse Document Frequency (TFIDF) vectorization 00:32:28 – Potential projects for bag-of-words techniques 00:34:07 – Video Course Spotlight 00:35:20 – WordNet and NLTK package 00:37:27 – Word embeddings and word2vec 00:45:30 – Previous training and too many dimensions 00:50:07 – How to use word2vec and Gensim? 00:51:26 – What types of projects for word2vec and Gensim? 00:54:41 – Getting into GPT and BERT in another episode 00:56:11 – How to follow Jodie’s work? 00:57:36 – Thanks and goodbye Show Links: Why Google’s “sentient” AI LaMDA is nothing like a person. On NYT Magazine on AI: Resist the Urge to be Impressed | Emily M. Bender | Medium ELIZA - Wikipedia eliza.py - Python 2 version by Daniel Connelly dabraude/Pyliza: Python3 Implementation of Eliza magneticpoetry.com Natural Language Processing With Python’s NLTK Package – Real Python Practical Text Classification With Python and Keras – Real Python Sentiment Analysis: First Steps With Python’s NLTK Library – Real Python NLTK: Natural Language Toolkit spaCy · Industrial-strength Natural Language Processing in Python Natural Language Processing With spaCy in Python - Real Python Stemming - Wikipedia Lemmatization - Wikipedia Binary/Count Vectorization: sklearn.feature_extraction.text.CountVectorizer— scikit-learn TFIDF: sklearn.feature_extraction.text.TfidfVectorizer — scikit-learn Porter Stemmer: nltk.stem.porter module — NLTK Snowball Stemmer: nltk.stem.snowball module — NLTK WordNet Lemmatizer: nltk.stem.wordnet module — NLTK Lemmatizer · spaCy API Documentation Applying Bag of Words and Word2Vec models on Reuters-21578 Dataset Elvin Ouyang’s Blog UCI Machine Learning Repository: Reuters-21578 Text Categorization Collection Data Set The Illustrated Word2vec – Jay Alammar A Complete Guide to Using WordNET in NLP Applications Gensim: Topic modeling for humans Core Tutorials — gensim Find Open Datasets and Machine Learning Projects | Kaggle Engineering All Hands: Vectorise all the things! - YouTube PyCon Portugal 2022 NDC Oslo 2022 | Conference for Software Developers Jodie Burchell’s Blog - Standard error Jodie Burchell 🇦🇺🇩🇪 (@t_redactyl) / Twitter JetBrains: Essential tools for software developers and teams Level up your Python skills with our expert-led courses: Data Cleaning With pandas and NumPy Reading and Writing Files With pandas Learn Text Classification With Python and Keras Support the podcast & join our community of Pythonistas

How do you start building your project documentation? What if you had a tool that could do the heavy lifting and automatically write large portions directly from your code? 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 step-by-step project from Martin Breuss about MkDocs. The project walks you through generating nice-looking and modern documentation from Markdown files and your existing code’s docstrings. The final step is to deploy your freshly generated documentation to a GitHub repository. Christopher talks about a pair of articles arguing for and against using Python dictionaries. The first article, “Just Use Dictionaries,” pushes to keep things simple, while the second article, “Don’t Let Dicts Spoil Your Code,” contends that complex projects require something more specific. We cover several other articles and projects from the Python community, including discussing the recent beta release of Python 3.11, 2FA for PyPI, procedural music composition with arvo, building a tic-tac-toe game with Python and Tkinter, common issues encountered while coding in Python, a type-safe library to generate SVG files, and a lightweight static analysis tool for your projects. Course Spotlight: Dictionaries and Arrays: Selecting the Ideal Data Structure In this course, you’ll learn about two of Python’s data structures: dictionaries and arrays. You’ll look at multiple types and classes for both of these and learn which implementations are best for your specific use cases. Topics: 00:00:00 – Introduction 00:02:39 – Python 3.11 Release May Be Delayed 00:03:39 – The cursed release of Python 3.11.0b4 is now available 00:05:01 – PyPI 2FA Security Key Giveaway 00:08:01 – Build Your Python Project Documentation With MkDocs 00:14:12 – Don’t Let Dicts Spoil Your Code 00:16:22 – Just Use Dictionaries 00:20:12 – Sponsor: Snyk.io 00:20:51 – Procedural Music Composition With arvo 00:29:10 – Build a Tic-Tac-Toe Game With Python and Tkinter 00:33:59 – Video Course Spotlight 00:35:35 – Most Common Issue You Have Coding With Python? 00:45:00 – svg.py: Type-Safe Library to Generate SVG Files 00:48:27 – semgrep: Lightweight Static Analysis for Many Languages 00:53:46 – Thanks and goodbye News: Python 3.11 Release May Be Delayed The cursed release of Python 3.11.0b4 is now available - Python.org. “We’ve begun rolling out a 2FA requirement”: PyPI on Twitter PyPI 2FA Security Key Giveaway Topic Links: Build Your Python Project Documentation With MkDocs – In this tutorial, 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. Don’t Let Dicts Spoil Your Code – The dict is the go-to data structure for Python programmers, but its loose relationship to the data can be problematic in large data streams. Learn more about why and when you might choose a different data structure. Just Use Dictionaries – Using simple data structures is an important part of keeping it simple, and Python is all about simplicity. Less code means fewer problems. Just use dictionaries. You probably don’t need classes. Procedural Music Composition With arvo – By using the music21 and avro libraries, you can create musical scores programmatically. This article runs you through which libraries you need and how you can compose your own music. Build a Tic-Tac-Toe Game With Python and Tkinter – In this step-by-step project, you’ll learn how to create a tic-tac-toe game using Python and the Tkinter GUI framework. Tkinter is cross-platform and is available in the Python standard library. Creating a game in Python is a great and fun way to learn something new and exciting! Discussion: Most Common Issue You Have Coding With Python? Projects: svg.py: Type-Safe Library to Generate SVG Files semgrep: Lightweight Static Analysis for Many Languages Additional Links: Getting 2FA Right in 2019 | Trail of Bits Blog autoDocstring - Python Docstring Generator - Visual Studio Marketplace styleguide | Style guides for Google-originated open-source projects Writing docstrings — Sphinx-RTD-Tutorial documentation Django Ninja arvo: Python library for procedural music composition Getting Started with arvo: a Procedural Music Composition Library - YouTube music21: a Toolkit for Computer-Aided Musicology music21: GitHub Free music composition and notation software | MuseScore Code Generation | MusicXML 4.0 Python GUI Programming With Tkinter – Real Python Tcl Developer Site tkinter — Python interface to Tcl/Tk — Python 3.10.5 documentation svg-xsd-schema: XSD schema for SVG SVG: Scalable Vector Graphics | MDN Level up your Python skills with our expert-led courses: Records and Sets: Selecting the Ideal Data Structure Documenting Code in Python Dictionaries and Arrays: Selecting the Ideal Data Structure Support the podcast & join our community of Pythonistas