Stay ConnectedA weekly Python podcast hosted by Christopher Bailey with interviews, coding tips, and conversation with guests from the Python community.
The show covers a wide range of topics including Python programming best practices, career tips, and related software development topics. Join us every Friday morning to hear what’s new in the world of Python programming and become a more effective Pythonista.
Copyright: © 2020 Real Python
Would you like a fast way to share your data science project results as an interactive dashboard instead of a Jupyter notebook? Streamlit is a library for creating simple web apps and dashboards using just Python. This week on the show, Christopher Trudeau is here, bringing another batch of PyCoder’s Weekly articles and projects.
We talk about the article “Forget About Jupyter Notebooks - Showcase Your Research Using Dashboards.” It covers the basics of turning a data science script into an interactive dashboard using Streamlit. We also share some additional resources to get you started with the library.
Christopher discusses an article covering ways to make life easier when working with Python regular expressions. He talks about composing verbose regexes using f-strings and potentially reusing these patterns.
We cover several other articles and projects from the Python community, including a news roundup, a step-by-step project to build a URL shortener with FastAPI, the fact that Python’s functions are sometimes classes, an automatic water pistol pigeon deterrent project, a discussion about music playlists for coding, a project for Python metadata extraction without execution, and a powerful audio-to-MIDI converter library.
Course Spotlight: Using Python Class Constructors
In this video course, you’ll learn how class constructors work in Python. You’ll also explore Python’s instantiation process, which has two main steps: instance creation and instance initialization.
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Our TOPPODCAST Picks list() or enumerate()? Think of them as functions? They’re not—they’re classes. Sometimes we call classes functions in Python. Why? And what’s a “callable”?openCV reading the camera image from an old iPhone. See all the details.Discussion:
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What do you do when your data science project doesn’t fit within your computer’s memory? One solution is to distribute it across multiple worker machines. This week on the show, Guido Imperiale from Coiled talks about Dask and managing large data science projects through distributed computing.
We talk about projects where an orchestration system like Dask will help. Dask is designed to take advantage of parallel computing, spreading the work and data across multiple machines. Many familiar techniques for working with pandas and NumPy data are supported with Dask equivalents.
We also discuss the differences between managed and unmanaged memory. Guido shares advice on how to tackle memory issues while working with Dask.
This week we also talk briefly with Jodie Burchell, who will be a guest host on upcoming episodes. As a data scientist, Jodie will be bringing new topics, projects, and discussions to the show.
Course Spotlight: Exploring Scopes and Closures in Python
In this Code Conversation video course, you’ll take a deep dive into how scopes and closures work in Python. To do this, you’ll use a debugger to walk through some sample code, and then you’ll take a peek under the hood to see how Python holds variables internally.
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What are the differences between the various Python game frameworks? Would it help to see a couple of game examples across several libraries to understand the distinctions? This week on the show, Christopher Trudeau is here, bringing another batch of PyCoder’s Weekly articles and projects.
We discuss a Real Python article by previous guest Jon Fincher titled “Top Python Game Engines”. Jon compares five different game frameworks and provides example projects and thorough commentary for each.
We talk about a blog post by recent guest Adam Johnson about determining if a project is well maintained. He suggests twelve questions to decide whether to add a new dependency to your project.
We cover several other articles and projects from the Python community, including a news roundup, Python decorator patterns, finding the smallest and largest values with min() and max(), a discussion about the most-used Python packages, the pony object-relational mapper, and a project to read PEPs in your console.
Course Spotlight: Using Pygame to Build an Asteroids Game in Python
In this course, you’ll build a clone of the Asteroids game in Python using Pygame. Step by step, you’ll add images, input handling, game logic, sounds, and text to your program.
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Would you like a way to send structured serialized data between different platforms and languages? What if the data was self-documenting, could automatically generate Python code, and would validate itself? This week on the show, Liran Haimovitch talks about protocol buffers and communicating with microservices through Remote Procedure Calls (RPC).
Protocol buffers, aka protobuf, are a language-neutral, platform-neutral system for serializing structured data. Liran talks about how they go beyond text-based protocols like JSON, providing the benefits above, along with faster transmissions and a smaller footprint.
Liran shares how his company uses protobuf to communicate between their tools. We also discuss using gRPC to communicate between microservices and scaling infrastructure in either direction.
Course Spotlight: Testing Your Code With pytest
In this video course, you’ll learn how to take your testing to the next level with pytest. You’ll cover intermediate and advanced pytest features such as fixtures, marks, parameters, and plugins. With pytest, you can make your test suites fast, effective, and less painful to maintain.
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Did you know you can add testing to your Python code while simultaneously documenting it? Using docstrings, you can create examples of how your functions should interact in a Python REPL and test them with the built-in doctest module. This week on the show, Christopher Trudeau is here, bringing another batch of PyCoder’s Weekly articles and projects.
Christopher shares an article by previous guest Mike Driscoll about testing with doctest. This is a great way to get started with testing your own code, and it offers the added benefit of documenting functionality.
We talk about the recent Real Python article “Pagination for a User-Friendly Django App.” Spreading your content across multiple pages can significantly improve the user experience of your web application. This article takes you through configuring Django’s built-in pagination tool and how to combine it with other web tools.
We discuss a recent article about Python type hints and the author’s disappointment. We also include reactions from a couple of online communities.
We cover several other articles and projects from the Python community, including why it’s important to close files in Python, how dunder methods are awesome, a bidirectional Python dictionary, prettier git diffs, and a command-line game to learn git.
Spotlight: Python Coding Interviews: Tips & Best Practices
In this step-by-step course, you’ll learn how to take your Python coding interview skills to the next level and use Python’s built-in functions and modules to solve problems faster and more easily.
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__repr__, __str__, operator overloading, and getting your classes working with Python functions like len().doctest module allows you to write unit tests through REPL-like sessions in your docstrings. Learn how to write and execute doctest code. Also available in video.Discussion:
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Have you heard about the projects working toward getting Python to run in the browser? Maybe you would like to try it out for yourself, by building an interactive Python REPL with Pyodide and WebAssembly (WASM). This week on the show, Christopher Trudeau is here, and he’s brought another batch of PyCoder’s Weekly articles and projects.
We talk about a step-by-step project that shows you how to build a Python code editor in the browser using WebAssembly through Pyodide and CodeMirror. You’re going to be hearing a lot about Pyodide in the coming months, and here’s a chance for you to play around while building a small project.
Christopher shares an article about the power of Python f-strings. It covers some lesser-known features like variable debugging, nesting, and detailed formatting.
We also have a couple of topics up for discussion this week. They’re both related to finding work as a Python developer.
We cover several other articles and projects from the Python community, including the 2038 date problem, a primer about Python virtual environments, how to build a site connectivity checker in Python, a free book on digital signal processing in Python, and a project to build a voice-activated, password-protected wooden box.
Spotlight: Using Python’s datetime Module
Have you ever wondered about working with dates and times in Python? In this video course, you’ll learn all about the built-in Python datetime library. You’ll also learn about how to manage time zones and daylight saving time, and how to do accurate arithmetic on dates and times.
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venv module, as well as the reasoning behind using virtual environments.Discussions:
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Are you using an Object-Relational Mapper (ORM) for your Python projects? What if it could work with SQL or No-SQL databases and be fully type-safe? This week on the show, Robert Craigie talks about Prisma Client Python.
Prisma Client Python is built on top of Prisma, which was created for TypeScript and Node.js. It uses a schema file to declare your application’s data models and relationships in a human-readable form. The schema file allows you to easily switch the database type.
Prisma Client is different from other Python ORMs. It is fully type-safe and can be used with or without async.
We talk about how Robert started the project and what types of challenges he’s faced. He also shares areas of improvement and how to contribute to the project.
We also have a conversation with several Real Python core team members about PyCon US 2022. We will have a booth at the conference where we hope you’ll come and connect with us. The team also shares what to expect from PyCon and what they’re excited about this year.
Course Spotlight: Python REST APIs With FastAPI
In this course, 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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Do you know the difference between creating a class instance and initializing it? Would you like an interactive tour of the Python Pillow library? This week on the show, Christopher Trudeau is here, and he’s brought another batch of PyCoder’s Weekly articles and projects.
We talk about the recent Real Python tutorial “Image Processing With the Python Pillow Library.” It walks you through manipulating, filtering, and creating images from scratch.
Christopher shares an article about Python class constructors, exploring the two-step instance creation and initialization process.
We also have a couple of discussions this week. The first is about contributing to open source projects. The second topic is about searching large codebases before adding features.
We cover several other articles and projects from the Python community, including the counter-intuitive rise of Python in scientific computing, preparation for interview questions, a project for adding pointer hell to Python, and a fast and powerful graphical user interface tool kit for Python with minimal dependencies.
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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What goes into creating those enhanced error messages in the latest versions of Python? How does the new PEG parser help to pinpoint where errors have occurred? This week on the show, Pablo Galindo Salgado talks about the work that goes into creating these improvements.
Pablo is a core CPython developer and is the release manager for Python versions 3.10 and 3.11. He is also serving his second term on the Python Steering Council.
Pablo is pleasantly surprised by the positive feedback for the new error messages in Python 3.10. He shares some of the upcoming enhancements for 3.11. We talk about how the new PEG parser allows for greater context when defining errors and pinpointing where they occur.
We talk about how he started contributing to CPython. He also shares some of the programming experiences he had while studying physics at university.
Course Spotlight: Starting With Linear Regression in Python
In this video course, you’ll get started with linear regression in Python. Linear regression is one of the fundamental statistical and machine learning techniques, and Python is a popular choice for machine learning.
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Do you understand how a hash table works? What if you could learn about building one while practicing test-driven development? What are best practices when designing a REST API? This week on the show, Christopher Trudeau is here, and he’s brought another batch of PyCoder’s Weekly articles and projects.
We talk about the recent Real Python article “Build a Hash Table in Python With TDD.” The tutorial shows how to implement a hash table prototype from scratch in Python. It also provides a hands-on crash course in test-driven development.
Christopher shares an article on designing REST APIs and provides some of his own best practices. We cover authentication implementation, good naming conventions, versioned APIs, and ways to specify dates.
We cover several other articles and projects from the Python community, including a news roundup, a PEP on removing dead batteries from the standard library, a comparison of the Python list vs tuple, a guide to writing user-friendly CLIs in Python, just enough Cython to be useful, a cross-platform TUI and ASCII animation package, and code for running black on Python code blocks in documentation files.
Course Spotlight: Command Line Interfaces in Python
Command-line arguments are the key to converting your programs into useful and enticing tools that are ready to be used in the terminal of your operating system. In this course, you’ll learn their origins, standards, and basics, and how to implement them in your program.
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list and tuple are similar and how they’re different, including storage and speed differences and how to choose between them.argparse, Click, Typer, Docopt, and Fire.Projects:
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