The Real Python Podcast

Are you still sprinkling print statements throughout your code while writing it? Print statements are often clunky and offer only a limited view of the state of your code. Have you thought there must be a better way? This week on the show, we have Nina Zakharenko to discuss her conference talk titled “Goodbye Print, Hello Debugger.” We talk about how to get started debugging your code by adding a single keyword. Nina discusses the differences between debugging on the command line vs using the tools included with an Integrated Development Environment(IDE). She also shares tricks and best practices. If you haven’t seen Nina’s conference talk, it’s a great starting point. We also talk about working through the last 18 months and how to recharge your creative batteries. We briefly discuss two other presentations Nina gave about CircuitPython and getting started with electronics and Python. 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 00:01:46 – Follow up on PyCascades 2021 and 2022 00:02:45 – Election to the PSF Board 00:05:06 – Current levels of burnout 00:09:09 – Possible ways to recharge 00:12:18 – Goodbye Print, Hello Debugger 00:14:46 – What are the types of things you can examine the state of? 00:18:01 – Where to start? 00:22:37 – Sponsor: Sentry 00:23:39 – Why is debugging not shown as often in Python? 00:26:49 – Debugging in VSCode 00:29:37 – Adding breakpoints in Flask or Django Templates 00:31:32 – What is pdb and how does it compare to ipdb? 00:39:40 – What are common debugging mistakes? 00:43:50 – Video Course Spotlight 00:44:48 – Why include a disclaimer about the talk? 00:46:13 – Where did you learn about debugging? 00:49:23 – Nina’s conference talks about CircuitPython 00:58:33 – What are you excited about in the world of Python? 00:59:51 – What do you want to learn next? 01:04:02 – Social info 01:04:27 – Thanks and goodbye Show Links: Nina Zakharenko - Personal Website PyCascades 2021 Python Software Foundation - Become a Member Nina Zakharenko - Goodbye Print, Hello Debugger! - PyCon 2020 pdb — The Python Debugger: Python 3 Docs IPython: Interactive Computing Pre-commit: A framework for managing and maintaining multi-language pre-commit hooks Python Morsels: Write better Python code in 30 minutes each week Find & Fix Code Bugs in Python: Debug With IDLE: Real Python Article Python Basics: Finding and Fixing Code Bugs: Real Python Video Course Light Up Your Life With Python and LEDs - PyCon 2019 - YouTube More Fun With Hardware and CircuitPython - IoT, Wearables, and more! - PyCon 2021 - YouTube CircuitPython: The easiest way to program microcontrollers Circuit Playground Express by Adafruit Device Simulator Express: A VS code extension IoT for Beginners - A Curriculum The Big Book of Small Python Projects - Al Sweigart Kreg® Pocket-Hole Jig 320 Conquer your cuts with the Adaptive Cutting System Nina’s Twitter Level up your Python skills with our expert-led courses: Debugging in Python With pdb The pandas DataFrame: Working With Data Efficiently Documenting Python Projects With Sphinx and Read The Docs - Archived Support the podcast & join our community of Pythonistas

How is Python being used today, and what can you do with the language? Do you want to develop software, dive into data science and math, automate parts of your job and digital life, or work with electronics? This week on the show, David Amos is back, and he’s brought another batch of PyCoder’s Weekly articles and projects. We talk about a Real Python article that covers the incredible variety of ways you can use Python. David shares an article about the pythonic way to count objects using the Counter class from the collections module. We discuss the ways it can lead to cleaner and more efficient code. We cover several other articles and projects from the Python community including, the inaugural CPython developer-in-residence, typeclasses in Python, GitHub Copilot writes a text-based game, friendlier tracebacks in REPLs (including Jupyter), 120+ interactive interview challenges, a module that helps you build complex pipelines of batch jobs, and a tool for plotting in the terminal. Course Spotlight: Understanding Python List Comprehensions Python list comprehensions make it easy to create lists while performing sophisticated filtering, mapping, and conditional logic on their members. In this course, you’ll learn when to use a list comprehension in Python and how to create them effectively. Topics: 00:00:00 – Introduction 00:02:01 – Łukasz Langa Is the Inaugural CPython Developer-in-Residence 00:05:03 – What Can I Do With Python? 00:11:19 – Typeclasses in Python 00:17:59 – Sponsor: Sentry 00:19:01 – Copilot Writes a Text-Based Game in Python 00:27:31 – Python’s Counter: The Pythonic Way to Count Objects 00:34:14 – interactive-coding-challenges: 120+ Interactive Python Coding Interview Challenges With Anki Flashcards 00:38:11 – Video Course Spotlight 00:39:11 – Friendlier Tracebacks in REPLs (Including Jupyter) 00:49:37 – luigi: Python Module That Helps You Build Complex Pipelines of Batch Jobs 00:52:13 – plotext: Plotting in the Terminal 00:55:24 – Thanks and goodbye Show Links: Łukasz Langa Is the Inaugural CPython Developer-in-Residence What Can I Do With Python? – You’ve finished a course or finally made it to the end of a book that teaches you the basics of programming with Python. You’ve learned about variables, lists, tuples, dictionaries, for and while loops, conditional statements, object-oriented concepts, and more. So, what’s next? What can you do with Python nowadays? Typeclasses in Python – Sometimes you need to change the behavior of a function based on the type of argument passed to it. This is a classic example of polymorphism in programming. In this article, you’ll learn how this is typically done in Python, compare that to polymorphism in other languages, and see how the new classes library can make the whole process easier. Copilot Writes a Text-Based Game in Python – GitHub’s new Copilot feature has a lot of people talking. The project’s goal is to be an AI pair programmer — a tool that can suggest entire lines of code or even entire functions! In this amusing article, one developer who gained access to Copilot’s technical preview shares how the AI wrote an entire text-based adventure game that turned out to be the solution to an exercise from a Python instructional book. Python’s Counter: The Pythonic Way to Count Objects– In this step-by-step tutorial, you’ll learn how to use Python’s Counter to count several repeated objects at once. You’ll also learn how to use Counter objects to enhance other computations that you do in Python. interactive-coding-challenges: 120+ Interactive Python Coding Interview Challenges With Anki Flashcards Friendlier Tracebacks in REPLs (Including Jupyter) – Tracebacks are often the start of any Python debugging journey. But tracebacks can be difficult to read and confusing to beginners. The friendly-traceback project aims to lift the veil of confusion for tracebacks by providing more helpful error messages with lots of context. New updates to the project include better tracebacks in Jupyter Notebooks! Projects: luigi: Python Module That Helps You Build Complex Pipelines of Batch Jobs plotext: Plotting in the Terminal Additional Links: I am the new CPython Developer in Residence: Łukasz Langa Python Success Stories: python.org Using FastAPI to Build Python Web APIs: Real Python Article GitHub Copilot GitHub Copilot: Fly With Python at the Speed of Thought Anki: Powerful, Intelligent Flash Cards friendly-traceback Status of PEP657 in Python 3.11 by Pablo Galindo Episode 69: Planning a Faster Future at the Python Language Summit Metaflow: A Framework for Real-life Data Science Lessons from a real Machine Learning project, part 1: from Jupyter to Luigi Data pipelines, Luigi, Airflow: everything you need to know Level up your Python skills with our expert-led courses: Records and Sets: Selecting the Ideal Data Structure Understanding Python List Comprehensions Python Coding Interviews: Tips & Best Practices Support the podcast & join our community of Pythonistas

Do you wonder what the future may hold for the Python language? Are there speed improvements coming soon? What if you could be in the room while the core developers discuss Python’s future? This week on the show, we have Joanna Jablonski, who was invited to the Python Language Summit 2021 as a journalist to summarize and document the event. A small group of core developers from the Python community gather to work toward a healthy future for the language. Through presentations and group discussions, they share insights, ideas, and potential problems. Joanna has been the executive editor at Real Python and she was invited to write a series of blog posts for the Python Software Foundation (PSF) that summarize the presentations and deeper conversations of the summit. We walk through the two days and discuss the topics covered. Several of the presentations focused on performance and speeding up CPython. There were conversations about packaging, documentation, the standard library, handling exceptions, testing, and more. Course Spotlight: Defining and Calling Python Functions In this course, you’ll learn how to define and call your own Python function. You’ll also learn about passing data to your function and returning data from your function back to its calling environment. Topics: 00:00:00 – Introduction 00:01:58 – What is the Python Language Summit? 00:06:44 – How do you summarize the talks? 00:08:17 – Terminology and technological level of the conversations 00:13:02 – PEP 654 — Exception Groups and except* 00:16:10 – Sponsor: Sentry 00:17:12 – Progress on Running Multiple Python Interpreters in Parallel in the Same Process 00:18:15 – CPython Performance Improvements at Instagram 00:20:41 – Making CPython Faster 00:23:22 – HPy — Present and Future 00:25:07 – Lightning Talks, Round 1 00:31:03 – Video Course Spotlight 00:32:34 – The Challenges of Packaging Python for a Linux Distro 00:36:12 – The Python Documentation Work Group 00:39:11 – What Is the stdlib? 00:42:07 – What Should I Work on as a Core Dev? 00:44:34 – Fuzzing and Testing Python With Properties 00:46:00 – Lightning Talks, Round 2 00:53:41 – What are you excited about in the world of Python? 00:54:46 – What do you want to learn next? 00:55:57 – Shout out and social connections 00:56:57 – Thanks and goodbye Show Links: Joanna Jablonski: Real Python Profile Joanna Jablonski - Personal Site Joanna’s Twitter The 2021 Python Language Summit The 2021 Python Language Summit: Welcome, Introductions, Guidelines PEP 654 — Exception Groups and except* Progress on Running Multiple Python Interpreters in Parallel in the Same Process CPython Performance Improvements at Instagram Making CPython Faster HPy — Present and Future Lightning Talks, Round 1 The Challenges of Packaging Python for a Linux Distro The Python Documentation Work Group What Is the stdlib? What Should I Work on as a Core Dev? Fuzzing and Testing Python With Properties Lightning Talks, Round 2 Additional Links: PEP 654 – Exception Groups and except*: Python Developer’s Guide PEP Index Cinder: Instagram’s internal performance-oriented production version of CPython 3.8 CircuitPython: The easiest way to program microcontrollers ABI - Application Binary Interface Tiers of Execution in a high-performance interpreter for CPython Mort, Elvis, Einstein, and You: Coding Horror Ren’Py: A visual novel engine Level up your Python skills with our expert-led courses: Python Inner Functions Defining and Calling Python Functions Test-Driven Development With pytest Support the podcast & join our community of Pythonistas

Are you ready to expand your Python knowledge into the intermediate to advanced territory? What tools are awaiting your discovery inside Python’s functools module? This week on the show, David Amos is back, and he’s brought another batch of PyCoder’s Weekly articles and projects. We discuss an article about the functools module, which adds functionality for caching, function overloading, better definitions for decorated functions, and more. David talks about a new Real Python article about working with complex numbers in Python. We also cover a tutorial about troubleshooting memory problems in Python. We cover several other articles and projects from the Python community including, DevOps interview questions, correlation analysis in Python, pivot and plot data with pandas, how to use Python and OpenCV to play online chess with a real chessboard, and generating hardware pinout diagrams as SVG images. Course Spotlight: Python Decorators 101 In this course on Python decorators, you’ll learn what they are and how to create and use them. Decorators provide a simple syntax for calling higher-order functions in Python. By definition, a decorator is a function that takes another function and extends the behavior of the latter function without explicitly modifying it. Topics: 00:00:00 – Introduction 00:01:56 – The Future of FastAPI and Pydantic Is Bright 00:04:33 – Simplify Complex Numbers With Python 00:10:37 – Functools: The Power of Higher-Order Functions in Python 00:18:40 – Sponsor: Sentry 00:19:42 – How to Pivot and Plot Data With Pandas 00:23:06 – devops-exercises: DevOps Interview Questions 00:32:09 – Video Course Spotlight 00:33:25 – Correlation Analysis 101 in Python 00:39:28 – How to Troubleshoot Memory Problems in Python 00:46:16 – Use Python and OpenCV to Play Online Chess With a Real Chessboard 00:49:28 – pinout: Generate Hardware Pinout Diagrams as SVG Images 00:54:21 – Thanks and goodbyes Show Links: The Future of FastAPI and Pydantic Is Bright – Not long ago there was some chatter on the internet about a change in Python 3.10 that would impact Python projects that check types at runtime. The discussion centered around FastAPI and Pydantic and had some folks worried about the future of those projects. In this article, FastAPI’s creator explains what the discussion was all about and why the future of FastAPI and Pydantic remains bright. Simplify Complex Numbers With Python – In this tutorial, you’ll learn about the unique treatment of complex numbers in Python. Complex numbers are a convenient tool for solving scientific and engineering problems. You’ll experience the elegance of using complex numbers in Python with several hands-on examples. Functools: The Power of Higher-Order Functions in Python – The functools module is one of the “hidden gems” of the Python standard library. This article takes you on a tour of everything in functools. You’ll learn how to implement caching, function overloading, and a whole lot more. How to Pivot and Plot Data With Pandas – One of the challenges of working with data is knowing how to manipulate the data format for a particular analysis. And there’s no single correct format. You need to know how to melt, pivot, and transpose data into a format that fits whatever you’re analyzing. If you enjoy this article, be sure to also check out Stefanie’s Pandas Workshop. devops-exercises: DevOps Interview Questions Correlation Analysis 101 in Python – Correlation analysis is a useful part of exploratory data analysis. It can help you identify potential relationships between various features of your data. In this helpful guide, you’ll learn how to do correlation analysis in a pandas DataFrame. You’ll see how to display a correlation matrix as a heatmap and explore some guidelines for identifying when correlation might imply causation. How to Troubleshoot Memory Problems in Python – Memory problems can be frustrating. They’re hard to diagnose and fix, and memory issues in Python applications can be especially frustrating thanks to the language’s garbage collection system. In this article, you’ll learn a six-step process for troubleshooting memory problems that the EvalML team used to solve a tricky problem with their library. Projects: play-online-chess-with-real-chess-board: Use Python and OpenCV to Play Online Chess With a Real Chessboard pinout: Generate Hardware Pinout Diagrams as SVG Images Additional Links: functools: Python 3 Documentation Primer on Python Decorators: Real Python Guide Caching in Python Using the LRU Cache Strategy: Real Python Article Caching in Python With lru_cache: Real Python Video Course Measuring Memory Usage in Python: It’s Tricky! Fritzing: Electronics Made Easy KiCad EDA: A Cross Platform and Open Source Electronics Design Automation Suite PcbDraw: Convert your KiCAD boards into nice looking 2D drawings Four stages of competence: Wikipedia article Level up your Python skills with our expert-led courses: Python Decorators 101 Python Inner Functions Plot With pandas: Python Data Visualization Basics Support the podcast & join our community of Pythonistas

How well do you know your software supply chain? When you PIP install a package, what steps can you take to minimize the risk of installing something malicious? This week on the show, we have Dustin Ingram, a director of the Python Software Foundation (PSF) and a maintainer of the Python Package Index (PyPI). We talk about Dustin’s PyCon 2021 talk titled “Secure Software Supply Chains for Python”. Dustin shares the types of attacks you should be aware of and how you can make your supply chain more trustworthy. We cover tools, techniques, and best practices. Dustin also discusses what it takes to keep the Python Package Index running and the players working to keep it going into the future. 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. Topics: 00:00:00 – Introduction 00:01:51 – Developer Advocate at Google 00:04:34 – A director of the PSF 00:06:27 – A maintainer of PyPI 00:12:29 – Secure Software Supply Chains for Python - PyCon 2021 00:15:53 – Do I need to be a security expert as a Python developer? 00:17:23 – Typo-squatting of package names 00:19:46 – Sponsor: Scout APM 00:20:52 – Dependency confusion and private repos 00:26:00 – What are some best practices? 00:31:55 – How to lessen the scale of “I don’t know what I don’t know”? 00:36:33 – Tools and techniques that can help 00:44:11 – Video Course Spotlight 00:45:30 – Namespaces on PyPI 00:53:03 – What does it take to power the Python Package Index? 01:01:57 – What are you excited about in the world of Python? 01:03:55 – What do you want to learn next? 01:05:52 – What is something you thought you knew about Python, but were wrong about it? 01:08:46 – Shout outs and social information 01:10:16 – Thanks and goodbye Show Links: Dustin Ingram: Personal Website Python on Google Cloud Cloud Run: Develop and deploy highly scalable containerized applications on a fully managed serverless platform Python Software Foundation PSF Membership FAQ PyPI: The Python Package Index Secure Software Supply Chains for Python: PyCon 2021 - YouTube pip Documentation: Requirements Files pip Documentation: Hash-Checking Mode PEP-0440: Direct references for pip pip-tools: pip-tools keeps your pinned dependencies fresh PyPA: Python Packaging User Guide The Update Framework (TUF) tuf: A secure updater framework for Python pipx: Install and Run Python Applications in Isolated Environments How to Publish an Open-Source Python Package to PyPI - Real Python Article Poetry: Python packaging and dependency management made easy PyUp: Python Dependency Security Dependabot: Automated dependency updates Why Package Signing is not the Holy Grail: Donald Stufft Dependency Confusion: How I Hacked Into Apple, Microsoft and Dozens of Other Companies What Is Pip? A Guide for New Pythonistas - Real Python Article A ‘Worst Nightmare’ Cyberattack: The Untold Story Of The SolarWinds Hack Security scanners for Python and Docker: from code to dependencies What does it take to power the Python Package Index? Level up your Python skills with our expert-led courses: A Beginner's Guide to pip How to Publish Your Own Python Package to PyPI Python Modules and Packages: An Introduction Support the podcast & join our community of Pythonistas

Are you ready to practice your Python skills some more? There is a new set of practice problems prepared for you to tackle, and this time they’re based on working with CSV files. This week on the show, David Amos is back, and he’s brought another batch of PyCoder’s Weekly articles and projects. David shares an article about functional programming with a focus on the “filter” function. The tutorial covers how to process an iterable and extract the items that satisfy a given condition. It also covers combining filter with other functional tools, and compares it to coding with Pythonic tools like list comprehensions and generator expressions. We cover several other articles and projects from the Python community including, Excel, Python, and the future of data science, a Bayesian analysis of Lego prices in Python, why can’t comments appear after a line continuation character, teaching Python on the Raspberry Pi400 at the public library, a cross-platform editor designed for writing novels built with Python and Qt, and a text user interface with rich as the renderer. Spotlight: Python vs JavaScript for Python Developers Python and JavaScript are two of the most popular programming languages in the world. In this course, you’ll take a deep dive into the JavaScript ecosystem by comparing Python vs JavaScript. You’ll learn the jargon, language history, and best practices from a Python developer’s perspective. Topics: 00:00:00 – Introduction 00:02:29 – Excel, Python, and the Future of Data Science 00:07:50 – Python Practice Problems: Parsing CSV Files 00:17:09 – Sponsor: Digital Ocean’s App Platform 00:17:45 – A Bayesian Analysis of Lego Prices in Python With PyMC3 00:23:02 – Why Can’t Comments Appear After a Line Continuation Character? 00:28:40 – Python’s filter(): Extract Values From Iterables 00:34:57 – Video Course Spotlight 00:36:24 – How I Teach Python on the Raspberry Pi 400 at the Public Library 00:46:23 – novelWriter: Cross-Platform Editor Designed for Writing Novels Built With Python and Qt 00:48:02 – textual: A Text User Interface With Rich as the Renderer 00:54:58 – Thanks and goodbye Show Links: Excel, Python, and the Future of Data Science – What’s the most widely used tool in data science? Is it pandas or NumPy? Is it the Python language itself? Not really. It’s Excel. You might argue that data scientists aren’t using Excel as their primary tool, and you might be right. But Excel enables non-technical users, like small business owners, to gain insights into their data. In this article, Anaconda CEO Peter Wang discusses his goal of making Python and PyData the “conceptual successor” to Excel. Python Practice Problems: Parsing CSV Files – In this tutorial, you’ll prepare for future interviews by working through a set of Python practice problems that involve CSV files. You’ll work through the problems yourself and then compare your results with solutions developed by the Real Python team. A Bayesian Analysis of Lego Prices in Python With PyMC3 – Follow along with this in-depth analysis of LEGO prices to see Bayesian analysis in action. Along the way, you’ll how pooled and unpooled linear models can be used to determine if a LEGO set is fairly priced. The article is quite technical, so experience with Bayesian statistics is recommended. Why Can’t Comments Appear After a Line Continuation Character? – Chaining together many object methods can create long tines that break the PEP 8 79-character line length recommendation. You can use \ to break the chain of methods onto individual lines, but if you want to leave comments at the end of some of the lines, you’re out of luck. There’s another pattern, though, that solves this. Python’s filter(): Extract Values From Iterables – In this step-by-step tutorial, you’ll learn how Python’s filter() works and how to use it effectively in your programs. You’ll also learn how to use list comprehension and generator expressions to replace filter() and make your code more Pythonic. How I Teach Python on the Raspberry Pi 400 at the Public Library – Community-based programming courses are a great way to introduce folks to computer programming that otherwise may not have the means to do so. One of the barriers to learning to code is cost. You need a computer to program on, after all. But with the advent of tiny computers like the Raspberry Pi, computers aimed at education are more affordable than ever. Projects: novelWriter: Cross-Platform Editor Designed for Writing Novels Built With Python and Qt textual: A Text User Interface With Rich as the Renderer Additional Links: Episode 27: Preparing for an Interview With Python Practice Problems PyMC3: Probabilistic Programming in Python Black: The uncompromising code formatter My review of the Raspberry Pi 400 Will McGugan’s Blog: Introducing Textual Level up your Python skills with our expert-led courses: Python vs JavaScript for Python Developers Python's map() Function: Transforming Iterables Functional Programming in Python Support the podcast & join our community of Pythonistas

The popularity of Python is continuing to grow Developers across the globe are embracing the language. How is Python being used in all of these different countries? How does an organization like the Python Software Foundation (PSF) work toward the goals in its mission statement for supporting and growing this international community? This week on the show, we have Marlene Mhangami, a PSF board member and part of the Diversity and Inclusion Work Group. Marlene lives in Zimbabwe on the continent of Africa. She has been organizing events not only locally in Zimbabwe but across all of Africa. She is the chair of Pycon Africa and has given talks at Pycon US, Pycon UK, and Pycon India. She has been working locally as an organizer and educator. We talk about the challenges of teaching technology and programming to a population of young people. Some of these students don’t have access to computers. She is also currently pursuing a computer science degree with the University of London. Along with her studies, she is also interning with NVidia. She is working with them on the RAPIDS project with a focus on the cuDF library. Spotlight: Introduction to Sorting Algorithms in Python In this course, you’ll learn all about five different sorting algorithms in Python from both a theoretical and a practical standpoint. You’ll also learn several related and important concepts, including Big O notation and recursion. Topics: 00:00:00 – Introduction 00:02:05 – Connecting during PyCon 2021 00:03:08 – Roles with the Python Software Foundation (PSF) 00:05:39 – Python in Africa 00:10:31 – School overseas and return to Zimbabwe to build a Python community 00:13:47 – Teaching technology and Python to students who don’t have computers 00:22:14 – Sponsor: Digital Ocean’s App Platform 00:22:50 – Work with the PSF and building geographic diversity 00:27:49 – PSF work groups 00:32:10 – Organizing PyCon Africa 2019 and bringing a continent of communities together 00:35:51 – How is Python being used in Africa? 00:38:05 – Video Course Spotlight 00:39:24 – Working with NVidia RAPIDS and cuDF 00:43:57 – What are you excited about in the world of Python? 00:46:12 – What do you want to learn next? 00:52:45 – What is something you thought you knew about Python but were wrong about it? 00:59:41 – Thanks and goodbye Show Links: Marlene Mhangami: Personal Website Python Software Foundation PSF Membership PyCon US 2021: YouTube Playlist Real Python Interview With Marlene Mhangami PyCon Africa Conference 2019 Highlights & Interviews: YouTube Django Girls RAPIDS: Open GPU Data Science 10 Minutes to Data Science: Transitioning Between RAPIDS cuDF and CuPy Libraries Level up your Python skills with our expert-led courses: Using pandas to Make a Gradebook in Python Hands-On Python 3 Concurrency With the asyncio Module Introduction to Sorting Algorithms in Python Support the podcast & join our community of Pythonistas

Are you looking for an in-depth data science project to practice your skills on? Perhaps you would like to add new tools to your Python web development projects instead? This week on the show, David Amos is back, and he’s brought another batch of PyCoder’s Weekly articles and projects. David shares an article about how to go about detecting deforestation from satellite images. He covers how a data science team built a machine learning (ML) solution to do just that, using FastAI for the modeling and Streamlit to create a dashboard. We also discuss a Real Python article about building a blog using Django, Vue.js, and GraphQL. GraphQL is a great tool to enhance your API to make it more flexible. The step by step project walks you through turning your Django blog data models into a GraphQL API. We cover several other articles and projects from the Python community including, the tools and tech used to run a one-woman hardware company, visualizing data in Python using plt.scatter(), why the sad face when using Black, how to iterate over dataframe rows (and should you?), pipx is now a PyPA member project, and real-time lossless audio compression in Python with pyFLAC. Spotlight: Explore Your Dataset With Pandas In this step-by-step course, you’ll learn how to start exploring a dataset with Pandas and Python. You’ll learn how to access specific rows and columns to answer questions about your data. You’ll also see how to handle missing values and prepare to visualize your dataset in a Jupyter Notebook. Topics: 00:00:00 – Introduction 00:02:11 – Build a Blog Using Django, Vue, and GraphQL 00:10:06 – Detecting Deforestation From Satellite Images 00:16:35 – Sponsor: Digital Ocean’s App Platform 00:17:11 – The Tools and Tech I Use to Run a One-Woman Hardware Company 00:29:13 – Visualizing Data in Python Using plt.scatter() 00:34:24 – Why the Sad Face? 00:40:20 – Video Course Spotlight 00:41:26 – How to Iterate Over DataFrame Rows (And Should You?) 00:48:31 – pyFLAC: Real-Time Lossless Audio Compression in Python 00:53:47 – pipx: Install and Run Python Applications in Isolated Environments 00:59:59 – Thanks and goodbye Show Links: Build a Blog Using Django, Vue, and GraphQL – In this step-by-step project, you’ll build a blog from the ground up. You’ll turn your Django blog data models into a GraphQL API and consume it in a Vue application for users to read. You’ll end up with an admin site and a user-facing site you can continue to refine for your own use. Detecting Deforestation From Satellite Images – How would you go about detecting deforestation — a contributor to climate change — from satellite images? In this article, you’ll learn how one team built a machine learning (ML) solution to do just that, using FastAI for the modeling and Streamlit to create a dashboard. The article discusses methodology and results, and is a great read about building an ML solution. The project code is available on GitHub. The Tools and Tech I Use to Run a One-Woman Hardware Company – Winterbloom makes open-source, boutique synthesizers. There’s a lot that goes into running a hardware company. Someone has to design the hardware, code the firmware, write the documentation, not to mention administrate the company. Winterbloom does all of this with just one engineer — Stargirl Flowers. Learn what tools and tech Stargirl uses to run her company, and how Python fits into the big picture in more ways than one. Visualizing Data in Python Using plt.scatter() – In this tutorial, you’ll learn how to create scatter plots in Python, which are a key part of many data visualization applications. You’ll get an introduction to plt.scatter(), a versatile function in the Matplotlib module for creating scatter plots. Why the Sad Face? – The Black autoformatter adopts some conventions that might surprise you the first time you use it. One of those conventions — the “sadface dedent” — moves closing parentheses in function signatures and other block headers to their own lines. This creates a line containing nothing but “):”, which looks like a sad face emoji. Łukasz Langa, Black’s creator, explains why Black does this. How to Iterate Over DataFrame Rows (And Should You?) – How to iterate over pandas DataFrame rows is one of the top voted questions with the pandas tag on Stack Overflow. That question is also the most copied answer with a code block on the entire site. Clearly, lots of people want to iterate over the rows in a DataFrame. But should you do this, or are there better options? Projects pyFLAC: Real-Time Lossless Audio Compression in Python pipx: Install and Run Python Applications in Isolated Environments Additional Links: Django: The Web Framework for Perfectionists With Deadlines Vue.js: The Progressive JavaScript Framework GraphQL: A query language for your API GraphQL? Here is what you need to know! - Syntax FM Episode FastAI: Simplifies training fast and accurate neural nets using modern best practices Streamlit: The fastest way to build and share data apps Winterbloom: Magical Musical Machines Black: The uncompromising code formatter pyFLAC: Real-Time Lossless Audio Compression in Python pipx Is Now a PyPA Member Project Level up your Python skills with our expert-led courses: Using Jupyter Notebooks How to Set Up a Django Project Explore Your Dataset With pandas Support the podcast & join our community of Pythonistas

This podcast discusses Anvil, a platform that allows Python developers to create web applications without learning additional languages. They cover the history of Anvil and its open-source nature. They also talk about Python libraries available to developers, working with PDFs and files, and the modularity of code and user management. The episode also mentions high school students creating projects, a video course spotlight, and the difference between server code and client code.

Discussions on selecting the ideal data structure in Python, using named tuples for cleaner code, unraveling the 'pass' and 'with' statements, typing code in Pallets projects, the value of reading and understanding other people's code, and using Python as a calculator and with new TI 84 calculator. Also explores Python usage on different devices and building a spell-checking library.