How do you define open source software? What are the challenges an open source project and maintainers face? How do maintainers receive financial, legal, security, or other types of help? This week on the show, we have Josh Simmons from Tidelift and the Open Source Initiative to help answer these questions.

Josh does open source ecosystem strategy for Tidelift. We talk about what Tidelift is and how they support maintainers. We also discuss the types of support maintainers need and the barriers that can block that support.

Josh also serves as President of the Open Source Initiative. OSI is actively involved in open source community-building and education. He talks about how collectives and foundations can be powerful tools in the open source ecosystem.

Course Spotlight: Python Inner Functions

In this step-by-step course, you’ll learn what inner functions are in Python, how to define them, and what their main use cases are. You’ll see how to write helper functions, create closure factory functions, and how to add behavior to existing functions with decorators.

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Have you heard of FastAPI? An application programming interface is vital to make your software accessible to users across the internet. FastAPI is an excellent option for quickly creating a web API that implements best practices. This week on the show, David Amos is back, and he’s brought another batch of PyCoder’s Weekly articles and projects.

We share an introduction to FastAPI written by the framework’s author, Sebastián Ramírez. The goal behind the article is to get you started creating production-ready APIs.

David covers an article about the Python import system and how it remains a mystery for many Python developers. We share some additional Real Python resources on the import system and statements.

We cover several other articles and projects from the Python community including, a buffet of specialized data types with Python’s collections module, maps with Django using GeoDjango, PostGIS, and Leaflet, moving SciPy to the Meson build system, what’s new in Python 3.11, a community-maintained Python framework for creating mathematical animations, and easily make PDFs with pdfme.

Course Spotlight: Python Modules and Packages: An Introduction

In this course, you’ll explore Python modules and Python packages, two mechanisms that facilitate modular programming. See how to write and import modules so you can optimize the structure of your own programs and make them more maintainable.

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Python’s collections: A Buffet of Specialized Data Types – Python has a number of useful data types beyond the built-in lists, tuples, dicts, and sets. In this tutorial, you’ll learn all about the series of specialized container data types in the collections module from the Python standard library. Learning the collections module is a great way to level up your Python programming knowledge!

Maps With Django: GeoDjango, PostGIS, and Leaflet – This quickstart guide shows you how to create a web map using Django’s GeoDjango module. Data for the map is stored in a PostgreSQL database using the PostGIS extension, and Leaflet, a lightweight JavaScript library for interactive maps, is used on the front-end. You’ll not only learn how to set up the Django application and display the map but also add markers to the map and automatically center the map on the application user’s location.

Moving SciPy to the Meson Build System – In accordance with PEP 632, distutils will be deprecated in Python 3.10 and in Python 3.12 it will be removed. This posed a big problem for SciPy, since it’s build system depends on NumPy’s distutils module — an extension of Python’s built-in distutils. The SciPy maintainers set out to find a new build system and settled on Meson, which solves a number of build issues and even scores a 4x speed-up on build times!

What’s New In Python 3.11 – Python 3.10 is still in beta, but work on Python 3.11 has already begun. Big changes include some major improvements to tracebacks as well as a new cube root function in the math module.

Behind the Scenes: How the Python Import System Works – Importing a Python module is probably one of the most used language features. But Python’s import system remains a mystery to many Python developers, even folks with years of experience. This in-depth article explores how the import system works from the top down. You’ll learn everything from the difference is between absolute and relative imports to how Python searches for modules and packages and resolves naming conflicts.

Using FastAPI to Build Python Web APIs – In this guide, written by FastAPI creator Sebastián Ramírez, you’ll learn the main concepts of FastAPI and how to use it to quickly create web APIs that implement best practices by default. By the end of it, you will be able to start creating production-ready web APIs.

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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.

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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.

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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!

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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?

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