Talk Python To Me

Have you heard of Flutter? It's a modern and polished UI framework to write mobile apps, desktop apps, and even web apps. While interesting, you may have kept your distance because Flutter is a Dart language-based framework. But with the project we're covering today, Flet, many Flutter UIs can now be written in pure Python. Flet is a very exciting development in the GUI space for Python devs. And we have the creator, Feodor Fitsner, here to take us through it.

PyPI has been in the news for a bunch of reasons lately. Many of them good. But also, some with a bit of drama or mixed reactions. On this episode, we have Dustin Ingram, one of the PyPI maintainers and one of the directors of the PSF, here to discuss the whole 2FA story, securing the supply chain, and plenty more related topics. This is another important episode that people deeply committed to the Python space will want to hear.

Pydantic has become a core building block for many Python projects. After 5 years, it's time for a remake. With version 2, the plan is to rebuild the internals (with benchmarks already showing a 17x performance improvement) and clean up the API. Sounds great, but what does that mean for us? Samuel Colvin, the creator of Pydantic, is here to share his plan for Pydantic v2.

Every year, the Python core developers and a few other key players in the Python ecosystem meet to discuss the pressing issues and important advancements at an event called the Python Language Summit. While Python is a community known for openness, this meeting is typically held behind closed doors mostly for efficiency's sake. On this episode, we'll give you a look behind that door. We have Alex Waygood here on this episode to break it down for us and give a look inside the summit.

Every year, the PSF and JetBrains team up to do a Python community survey. The most recent one was Fall of 2021. For this episode, I've gathered a great group of Python enthusiasts to discuss the results. I think you'll really enjoy the group discussion on this episode.

Deploying and managing your application after you create it can be a big challenge. Cloud platforms such as Azure have literally hundreds of services. Which ones should you choose? How do you link them together? In this episode, Anthony Shaw and Shayne Boyer share a new CLI tool and template they've created for jump starting you use of modern Python apps and deploying them to Azure. We're talking FastAPI, Beanie and MongoDB, async and await, Bicep DevOps, automated CI/CD pipelines and more. Plus we catch up on other Python work happening that Anthony is involved with. If you're interested in deploying or structuring modern Python apps, you'll find some interesting take aways from our conversation.

Often when we learn about or work with Math, it's done so in a very detached style. You might learn the rules and techniques for differentiation, for example. But how often do you get to apply them to meaningful and interesting problems? In this episode, we have Vince Knight and Geraint Palmer on to discuss solving a wide variety of applied and approachable math problems using Python. Whether you're deeply into math or not so much, I think there is a lot to enjoy from this episode.

I'm sure you're familiar with package managers for your OS even if you don't use them. On macOS we have Homebrew, Chocolatey on Windows, and apt, yum, and others on Linux. But if you want to install Python applications, you typically have to fallback to managing them with pip. Maybe you install them for your account with the --user flag. But with pipx you get a clean, isolated install for every Python application that you use. And if you distribute Python apps, pipx is a definitely worth considering as a channel.

You may have heard of the Bloomberg terminal. It's expensive software that can monitor and analyze real-time financial market data and place trades on the electronic trading platform. But have you heard of OpenBB? It's similar software for real-time and long term analysis for finance and investing. The difference is it's open source and built entirely with Python and gives you access to analyze a massive amount of real-time and historical data using the full Python data science stack. On this episode, we have one of the cofounders, James Maslek here to give us a look inside this cool piece of Python-based software.

Python is undergoing a performance renaissance. We already have Python 3.11 20-40% faster than even Python 3.10. On this episode, we'll dive into a new proposal to make Python even more efficient using lazy imports laid out in PEP 690. We have all three folks involved on the episode: Carl Meyer, Germán Méndez Bravo, and Barry Warsaw. Are you ready to get into making Python faster still? Let's dive in.

How do you test whether your web sites are working well? Unit tests are great. But for web apps, the number of pieces that have to click together "just so" are many. You have databases, server code (such as a Flask app), server templates (Jinja for example), CSS, Javascript, and even deployment topologies (think nginx + uvicorn). Unit tests won't cover all of that integration. But Playwright does. Playwright is a modern, Pythonic take on testing webs apps using code driving a browser core to interact with web apps the way real users and API clients do. I think you'll find a lot to like there. And we have Pandy Knight from Automation Panda here to break it down for us.

Despite Python being overwhelmingly popular and positive, there are major areas of computing where Python is not present. Most notably on mobile and on the frontend side of the web. PyScript, a new project launched by Fabio Pliger from Anaconda, just might change that. It was made public and announced at PyCon just two weeks ago by Peter Wang and now has over 10,000 GitHub stars. But what is hype vs. reality vs. projected hopes and dreams? We're going to find out on this episode. Fabio is here to tell us all about his new project.

Does your app have a database? Does that database play an important role in how the app operations and users perceive its quality? Most of you probably said yes to the first, and definitely to the second. But what if your DB isn't doing as well as it should? How would you know? And once you know, what do you do about it? On this episode, we're joined by Michael Christofides, co-creator of pgMustard, to discuss and explore the EXPLAIN command for Postgres and other databases as well as all the recommendations you might dig into as a result of understanding exactly what's happening with you queries.

How much time do you spend solving negative engineering problems? And can a framework solve them for you? Think of negative engineering as things you do to avoid bad outcomes in software. At the lowest level, this can be writing good error handling with try / except. But it's broader than that: logging, observability (like Sentry tools), retries, failover (as in what you might get from Kubernetes), and so on. We have a great chat with Chris White about Prefect, a tool for data engineers and data scientists meaning to solve many of these problems automatically. But it's a conversation applicable to a broader software development community as well.

We're all familiar with the data science tools like numpy, pandas, and others. These are numerical tools working with floating point numbers, often to represent real-world systems. But what if you exactly specify the equations, symbolically like many of us did back in Calculus and Differential Equations courses? With SymPy, you can do exactly that. Create equations, integrate, differentiate, and solve them. Then you can convert those solutions into Python (or even C++ and Fortran code). We're here with two of the core maintainer: Ondřej Čertík and Aaron Meurer to learn all about SymPy.