Full show notes at https://pythonbytes.fm/episodes/show/226/teaching-python-podcast-on-the-podcast

Python Bytes

#226: Teaching Python podcast on the podcast!

We're back with another GeekOut episode. Richard Campbell, a developer and podcaster who also dives deep into science and tech topics, is back for our third GeekOut episode. This time around, we're diving into renewable energy, energy storage, and just what do we do to keep the lights on with our frying our beloved Earth?

Check out the full episode at https://talkpython.fm/episodes/show/329/renewable-energy-geekout

Talk Python To Me

#329: Geekout: Renewable Energy

We know that Python and data science are growing in lock-step together. But exactly what's happening in the data science space in 2021? Stan Seibert from Anaconda is here to give us a report on what they found with their latest "State of Data Science in 2021" survey. 

Full show notes at https://talkpython.fm/episodes/show/333/state-of-data-science-in-2021

#333: State of Data Science in 2021

Here's a question: What's the most common way to explore data? Would you say pandas and matplotlib? Maybe you went more general and said Jupyter notebooks. How about Excel, or Google Sheets, or Numbers, or some other spreadsheet app? Yeah, my bet is on Excel. And while it has many drawbacks, it makes exploring tabular data very accessible to many people, most of whom aren't even developers or data scientists.

On this episode, we're talking about a tool called Mito. This is an add-in for Jupyter notebooks that injects an Excel-like interface into the notebook. You pass it data via a pandas dataframe (or some other source) and then you can explore it as if you're using Excel. The cool thing is though, just below that, it's writing the pandas code you'd need to do to actually accomplish that outcome in code.

I think this will make pandas and Python data exploration way more accessible to many more people. So if you've been intimidated by pandas, or know someone who has, this could be what you've been looking for. 

Full show notes at https://talkpython.fm/episodes/show/343/do-excel-things-get-notebook-python-code-with-mito

#343: Do Excel things, get notebook Python code with Mito

Do you write web apps in Django? The framework has come a long way lately with versions 3 and 4 adopting many of the modern Python capabilities (async, for example). But there are so many other libraries and apps that you can use to do more with less code in plugin new functionality. I'm happy to have Christopher Trudeau here on talk Python to take us through his 17 favorite libraries you should be using in Django.

Full show notes at https://talkpython.fm/episodes/show/379/17-libraries-you-should-be-using-in-django

#379: 17 Libraries You Should Be Using in Django

When you think data science, Jupyter notebooks and associated tools probably come to mind. But I want to broaden your toolset a bit and encourage you to look around at other tools that are literally at your fingertips. The terminal and shell command line tools.

On this episode, you'll meed Jeroen Janssens. He wrote the book Data Science on The Command Line Book and there are a bunch of fun and useful small utilities that will make your life simpler that you can run immediately in the terminal. For example, you can query a CSV file with SQL right from the command line.

Full show notes at https://talkpython.fm/episodes/show/392/data-science-from-the-command-line

#392: Data Science from the Command Line

At some point, you've probably migrated an app from one framework or major runtime version to another. For example, Django to Flask, Python 2 to Python 3, or even Angular to Vue.js. This can be a big challenge. If you had 100s of active devs and millions of lines of code, it's a huge challenge. We have Ben Bariteau from Yelp here to recount their story moving 3.8M lines of code from Python 2 to Python 3. But this is not just a 2-to-3 story. It has many lessons on how to migrate code in many situations. There are plenty of gems to take from his experience.

Full show notes at https://talkpython.fm/episodes/show/401/migrating-3.8-million-lines-of-python

#401: Migrating 3.8 Million Lines of Python

Clean code is one of those aspects of your programming career that's easy to put on the back burner (sometimes by management more than yourself). But it's important in the short term for writing more debuggable and readable code. And important in the long run for avoiding having your program take on the dreaded "legacy code" moniker. We're fortunate to have Bob Belderbos back on the show. He's been thinking and writing about clean code and Python a lot lately and we'll dive into a bunch of tips you can use right away to make your code cleaner.

Full show notes at https://talkpython.fm/episodes/show/404/clean-code-in-python

#404: Clean Code in Python

Getting started in Python is pretty easy. There's even a t-shirt that jokes about it: I learned Python, it was a good weekend. But to go from know how to create variables and writing loops, to building amazing things like FastAPI or Instagram, well there is this little gap between those two things. On this episode we welcome Eric Matthes to the show. He has thought a lot about teaching Python and comes to share his 10 tips for going from Python beginner to expert.

Full show notes at https://talkpython.fm/episodes/show/427/10-tips-and-ideas-for-the-beginner-to-expert-python-journey

#427: 10 Tips and Ideas for the Beginner to Expert Python Journey

We write tests to show us when there are problems with our code. But what if there are intermittent problems with the tests themselves? That can be big hassle. In this episode, we have Gregory Kapfhammer and Owain Parry on the show to share their research and advice for taming flaky tests.

Full show notes at https://talkpython.fm/episodes/show/429/taming-flaky-tests

#429: Taming Flaky Tests

Every year Python has a new major release. This year it's Python 3.12 and it'll come out on October 2, 2023. That's 4 days from when this episode was published. There is quite process involved to test, build, and ship Python across many platforms and channels. We have Seth Michael Larson here to give us a detailed rundown on what exactly is involved in releasing CPython.

Get the full episode at https://talkpython.fm/episodes/show/431/visualizing-cpython-release-process

#431 Visualizing CPython Release Process

By now, surely you've heard how awesome Pydantic version 2 is. The team led by Samual Colvin spent almost a year refactoring and reworking the core into a high-performance Rust version while keeping the public API in Python and largely unchanged. The main benefit of this has been massive speed ups for frameworks and devs using Pydantic.

But just how much work is it to take a framework deeply built on Pydantic and make that migration? What are some of the pitfalls? On this episode, we welcome back Roman Right to talk about his experience converting Beanie, the popular MongoDB async framework based on Pydantic, from Pydantic v1 to v2. And we'll have some fun talking MongoDB as well while we are at it.

Full show notes at https://talkpython.fm/episodes/show/432/migrating-to-pydantic-2.0-beanie-for-mongodb

#432: Migrating to Pydantic 2.0: Beanie for MongoDB

We all know about Flask and Django. And of course FastAPI made a huge splash when it came on the scene a few years ago. But new web frameworks are being creating all the time. And they have these earlier frameworks to borrow from as well. On this episode we dive into a new framework gaining a lot of traction called Litestar. Will it be the foundation of your next project? Join me as I get to know Litestar with its maintainers: Jacob Coffee, Janek Nouvertné, and Cody Fincher.

Full details at https://talkpython.fm/episodes/show/433/litestar-effortlessly-build-performant-apis

#433 Litestar

Are you building a mobile app and wondering where Python fits in the mix? Are you support others building these apps with backend APIs written in Python? Can you write your entire app, end to end, in Python? I have a great panel put together to discuss exactly this. And they all have a different and unique take on the options. Welcome to Loren Aguey, Harout Boujakjian, Andréas Kühne, Jeyfrin and, Joshua.

Full show notes at https://talkpython.fm/episodes/show/434/building-mobile-apps-backed-with-python

#434 Mobile Apps

Do you worry about your developer / data science supply chain safety? All the packages for the Python ecosystem are much of what makes Python awesome. But the are also a bit of an open door to your code and machine. Luckily the PSF is taking this seriously and hired Mike Fiedler as the full time PyPI Safety & Security Engineer (not to be confused with the Security Developer in Residence staffed by Seth Michael Larson). Mike is here to give us the state of the PyPI security and plans for the future.

Full show details at https://talkpython.fm/episodes/show/435/pypi-security

#435: PyPI Security

How well do you know your Python packaging tools? These are things like pip which install your project's dependencies and their dependencies and so on. In this mix, we have more modern tools such as Poetry, Flit, Hatch and others. And even tools outside of Python itself which may attempt to manage Python itself in addition to the libraries. To make sense of all of this, we welcome back Anna-Lena Popkes for an unbiased evaluation of environment and packaging tools.

Get the full details at https://talkpython.fm/episodes/show/436/an-unbiased-evaluation-of-environment-and-packaging-tools

#436 Packaging Survey

Are you considering or struggling with replacing much of the interactivity of your Django app with frontend JavaScript frameworks? After all, your users do expect an interactive and modern app, right? Before you make a rash decision, you owe it to yourself to check out HTMX. It goes well with Django. We have Christopher Trudeau to run through a whole awesome list of HTMX and Python and tell us about his new HTMX + Django course.

Full details at https://talkpython.fm/episodes/show/437/htmx-for-django-developers-and-all-of-us

#437 Htmx For Django Developers And All Of Us

Jupyter Notebooks and Jupyter Lab have to be one of the most important parts of Python when it comes to bring new users to the Python ecosystem and certainly for the day to day work of data scientists and general scientists who have made some of the biggest discoveries of recent times. And that platform has recently gotten a major upgrade with JupyterLab 4 released and Jupyter Notebook being significantly reworked to be based on the changes from JupyterLab as well. We have an excellent panel of guests, Sylvain Corlay, Frederic Collonval, Jeremy Tuloup, and Afshin Darian here to tell us what's new in these and other parts of the Jupyter ecosystem.

Full show notes at https://talkpython.fm/episodes/show/438/celebrating-jupyterlab-4-and-jupyter-7-releases

#438 Jupyterlab 4 And Jupyter 7

On this episode we have Wolf Vollprecht and Ruben Arts from the pixi project here to talk about pixi, a high performance package manager for Python and other languages that actually manages Python itself too. They have a lot of interesting ideas on where Python packaging should go and are putting their time and effort behind them. Will pixi become your next package manager? Listen in to find out.

Full show details at https://talkpython.fm/episodes/show/439/pixi-a-fast-package-manager

#439 Pixi Package Manager

We all know that LLMs and generative AI has been working its way into many products. It's Jupyter's turn to get a really awesome integration. We have David Qiu here to tell us about Jupyter AI. Jupyter AI provides a user-friendly and powerful way to apply generative AI to your notebooks. It lets you choose from many different LLM providers and models to get just the help you're looking for. And it does way more than just a chat pane in the UI. Listen to find out.

Full show notes at https://talkpython.fm/episodes/show/440/talking-to-notebooks-with-jupyter-ai

#440 Jupyter AI

You've probably heard the term "syntactic sugar", that is, syntax within a programming language that is designed to make things easier to read or to express. It makes the language "sweeter" for human use. It turns out Brett Cannon has spent 2 years diving into and writing about Python's sweet language features and how they really work down inside CPython. He joins me on the show today to dive into a few of the more relevant posts he's written about it.

Full show notes at https://talkpython.fm/episodes/show/441/python-syntactic-sugar

#441 Syntatic Sugar

If you're a fan of Pydantic or dataclasses, you'll definitely be interested in this episode. We are talking about a super fast data modeling and validation framework called msgspec. Some of the types in here might even be better for general purpose use than Python's native classes. Join me and Jim Crist-Harif to talk about his data exchange framework, mspspec.

Full details at https://talkpython.fm/episodes/show/442/ultra-high-speed-message-parsing-with-msgspec

#442: Ultra High Speed Message Parsing with msgspec

This episode is a special crossover from my Python Bytes podcast I cohost with Brian Okken. It's got a different vibe than the interview shows here with short topics coming in fast and quick. If you haven't listened before, I think you're enjoy it.

So here are a bunch of excellent Python tips and tools to close out the year. See you all first week of January.

And while I'm talking directly to you, thank you very very much for taking the time to listen to my shows and support all of my projects. Cheers.

Full show notes at https://talkpython.fm/episodes/show/443/python-bytes-crossover-2023

#443: Python Bytes Crossover 2023

Are you early in your software dev or data science career? Maybe it hasn't even really started yet and you're still in school. On this episode we have Sydney Runkle who has had a ton of success in the Python space and she hasn't even graduated yet. We sit down to talk about what she's done and might do differently again to achieve that success. It's "The Young Coder's Blueprint to Success" on episode 444 of Talk Python To Me.

Full show notes at https://talkpython.fm/episodes/show/444/the-young-coders-blueprint-to-success

#443 Success Blueprint

Machine learning allows computers to find hidden insights without being explicitly programmed where to look or what to look for. Thanks to the work of some dedicated developers, Python has one of the best machine learning platforms called scikit-learn. In this episode, Alexandre Gramfort is here to tell us all about scikit-learn and machine learning. 

Episode #31: Machine Learning with Python and scikit-learn

What's it like to be a beginner in software development? How about learning Python for the first time? This episode is a special panel episode and is the first of a two-part series we are doing on the podcast called Beginners and Experts.

On this first episode, we have a conversation between beginners and experts and how we can close the gap to help beginners get up to speed as quickly as possible. Our panelists are Karly Sindy, Joy Dantong Ma, Tsitsi Flora Munikwa, and Ned Batchelder. 

Full show notes at https://talkpython.fm/203

#203: Beginners and Experts in Software Development

Welcome to part 2 of our beginners and experts series. This one is a panel format with 7 different guests. Each of them a beginner in their own way. We dig deeper into some follow up conversations for part 1 with our panelists.

On this episode, you'll meet Vanessa Angel, Kelly Schuster-Paredes, Dane Parks, Scott Stoltzman, Sergio Sanchez, Alex Kaprosy, and Jason Pecor. 

Full show notes at https://talkpython.fm/episodes/show/205/beginners-and-experts-panel

#205: Beginners and Experts Panel

Has anyone told you that you should get into data science? Have you heard it's a great career? In fact, data scientist is the best job in America according to Glassdoor's 2018 rankings.

That's great. But how do you get a career in data science? Once you land that first job, how do you find the right fit? How do you find the right company? And how do you get more deeply involved in the community?

I have brought two great guests, both highly successful data scientists, on the show today who have been thinking deeply about this. Jacqueline Nolis and Emily Robinson are here to give you real-world, actionable advice on getting into this rewarding career. 

https://talkpython.fm/episodes/show/262/build-a-career-in-data-science

#262: Build a career in data science

We recently covered 10 tips that every Flask developer should know. But we left out a pretty big group in the Python web space: Django developers! And this one is for you. I invited Bob Belderbos, who's been running his SaaS business on Python and Django for several years now, to share his tips and tricks.
The 10 tips

    Django Admin
    ORM magic
    Models
    Debugging/Performance Toolbar
    Extending the User model
    Class based views (CBVs)
    manage.py
    Write your own middleware
    Config variable management with python-decouple and dj-database-url
    Built-in template tags and filters

Full show notes at https://talkpython.fm/episodes/show/277/10-tips-every-django-developer-should-know

#277: 10 tips every Django developer should know

People often ask me how they can find a Python community to be part of. Maybe discussion forum or slack channel. This week, we look at one of the most active communities in Python Discord. It's Python, on a discord server. But it's more than that too.

You'll meet Leon Sandøy who, along with a team of folks, runs Python Discord. Full show notes at https://talkpython.fm/episodes/show/305/python-community-at-python-discord

#305: Python community at Python Discord

Talk Python to Me is a weekly podcast hosted by Michael Kennedy. The show covers a wide array of Python topics as well as many related topics (e.g. MongoDB, AngularJS, DevOps).The format is a casual 30 minute conversation with industry experts.

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