Talk Python To Me (SoundCloud): Recent Episodes
Michael Kennedy
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
So, you've got this amazing machine learning model you created. And you want to share it and let your colleagues and users experiment with it on the web. How do you get started? Learning Flask or Django? Great frameworks, but you might consider Gradio which is a rapid development UI framework for ML models. On this episode, we have Freddy Boulton, to introduce us all to Gradio.Full show notes at https://talkpython.fm/episodes/show/430/python-language-summit-2023
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
Have you heard of Django? It's this little web framework that, well, kicked off much of Python's significance in the web space back in 2005. And that makes Django officially an adult. That's right, Django is now 18. And Django continues to lead the way on how community should be done for individual projects such as web frameworks. We have Carlton Gibson and Will Vincent back on the show this episode to discuss a bit of the Django history, Django trends in 2023, a little HTMX + Django, and lots more.
Full episode details at https://talkpython.fm/episodes/show/428/django-trends-in-2023
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
One of the most exciting initiatives in the Python space these days is pyscript which enables Python running natively in your browser. With consistent support from the folks at Anaconda, this project has been making solid strides since its initial release. On this episode we catch up with Fabio Pliger and Nicholas Tollervey to see where they are with the pyscript project.
Full episode details at https://talkpython.fm/episodes/show/426/whats-new-in-pyscript-august-2023
Understanding how your Python application is using memory can be tough. First, Python has it's own layer of reused memory (arenas, pools, and blocks) to help it be more efficient. And many important Python packages are built in natively compiled languages like C and Rust often times making that section of your memory opaque. But with Memray, you can way deeper insight into your memory usage. We have Pablo Galindo Salgado and Matt Wozniski back on the show to dive into Memray, the sister project to their pystack one we recently covered.
Full show notes and links at https://talkpython.fm/episodes/show/425/memray-the-endgame-python-memory-profiler
If you want to share your data science results as interactive web apps, you could learn Flask or Django and a bunch of other web technologies. Or, you could pick up one of the powerful frameworks for deploying data science specifically. And if you're searching through that space, you've likely hear of Shiny -- but that's just for the R side of data science, right? Not any longer. Joe Cheng is here to introduce us to the recently released Shiny for Python. And it looks like a very solid new framework on the block.
Get the full details at https://talkpython.fm/episodes/show/424/shiny-for-python.
Python is used for a wide variety of software projects. One area it's really gained a huge amount of momentum is in the computational space (including data science). On this episode we welcome back Allen Downey to dive into a particular slice of this space: simulation problems and Python in Physics and Engineering in general.
Full details at https://talkpython.fm/episodes/show/423/solving-10-different-simulation-problems-with-python
When you use a SQL database like Postgres, you have to understand the subtleties of isolation levels from "read committed" to "serializable." And distributed databases like MongoDB offer a range of consistency levels, from "eventually consistent" to "linearizable" and many options in between. Plus, it's easy enough to confuse "isolation" with "consistency!" We have A. Jesse Jiryu Davis from MongoDB back on the podcast to break it all down for us.
Full episode details at https://talkpython.fm/episodes/show/420/database-consistency-isolation-for-python-devs
Here's the situation. You have a Python app that is locked or even has completely crashed and all you're left with is a core dump on the server. Now what? It's time for PyStack! You can capture a view of your app as if you've set a breakpoint and even view the callstack and locals across language calls (for example from Python to C++ and back). We have the maintainers, Pablo Galindo Salgado and Matt Wozniski, here to dive into PyStack. You'll definitely want to have this tool in your toolbox.
Full show notes and links at https://talkpython.fm/episodes/show/419/debugging-python-in-production-with-pystack
Think about the different APIs and databases your application works with. Every one of them requires either an API key or a database connection string that itself contains a password. How do you let your application access this sensitive information without storing it in source code or putting in other compromising locations? We have Glyph Lefkowitz on the show to share his security fable as well as just good advice for keeping secrets out of Python code.
Full show notes at https://talkpython.fm/episodes/show/418/how-to-keep-a-secret-in-python-apps
Large language models and chat-based AIs are kind of mind blowing at the moment. Many of us are playing with them for working on code or just as a fun alternative to search. But others of us are building applications with AI at the core. And when doing that, the slightly unpredictable nature and probabilistic nature of LLMs make writing and testing Python code very tricky. Enter promptimize from Maxime Beauchemin and Preset. It's a framework for non-deterministic testing of LLMs inside our applications. Let's dive inside the AIs with Max.Full show notes at https://talkpython.fm/episodes/show/417/test-driven-prompt-engineering-for-llms-with-promptimize
If you're looking for fun data sets for learning, for teaching, maybe a conference talk, or even if you're just really into them, sports offers up a continuous stream of rich data that many people can relate to. Yet, accessing that data can be tricky. Sometimes it's locked away in obscure file formats. Other times, the data exists but without a clear API to access it. On this episode, we talk about PySport - something of an awesome list of a wide range of libraries (mostly but not all Python) for accessing a wide variety of sports data from the NFL, NBA, F1, and more. We have Koen Vossen, maintainer of PySport to talk through some of the more popular projects.Full show notes at https://talkpython.fm/episodes/show/416/open-source-sports-analytics-with-pysport
The release of Pydantic 2.0, its partial rewrite in Rust, and its refactoring into Pydantic core and top-level Pydantic in Python is big news. In fact, the alpha of Pydantic 2 was just released. Of course, these changes will have potentially wide ranging (and positive!) effects on libraries that are built upon Pydantic such as FastAPI, Beanie, and others. That's why this chance I had to catch up with Samuel Colvin from Pydantic and Sebastián Ramírez from FastAPI together, live from PyCon 2023. It's a super fun and wide ranging interview I'm sure you'll enjoy. Plus, there is a bit of an easter egg in the middle.Full show notes at https://talkpython.fm/episodes/show/415/future-of-pydantic-and-fastapi
At PyCon 2023, there was a section of the expo floor dedicated to new Python-based companies called Startup Row. I wanted to bring their stories and the experience of talking with these new startups to you. So in this episode, we'll talk with founders from these companies for 5 to 10 minutes each.Full episode details at https://talkpython.fm/episodes/show/414/a-stroll-down-startup-lane
Did you make this year's PyCon event in the US? There was a lot of excitement this time around in Salt Lake City. In this episode I'll bring you a bunch of experiences we had this year. It starts where frequent guest Jay Miller turns the tables and interviews me at the Microsoft booth on the expo hall floor in front of a live audience. Then you'll hear from Mario Munoz, Nick Muoh, Chris Williams, Ray McLendon, and Sean Tibor about their time at the conference.Full show notes at https://talkpython.fm/episodes/show/413/live-from-pycon-2023
What if we distributed CPython, the runtime, in the same way we distributed Python packages - as prebuilt binary wheels that only need to be downloaded and unzipped to run? For starters, that would mean we could ship and deploy Python apps without worrying whether Python itself is available or up-to-date on the platform. Nathaniel Smith has just proposed a PEP to do just that, PEP 711. And we'll dive into that with him next.Full episode at https://talkpython.fm/episodes/show/412/pep-711-distributing-python-binaries
AI has taken the world by storm. It's gone from near zero to amazing in just a few years. We have ChatGPT, we have Stable Diffusion. But what about Jupyter Notebooks and pandas? In this episode, we meet Justin Waugh, the creator of Sketch. Sketch adds the ability to have conversational AI interactions about your pandas data frames (code and data). It's pretty powerful and I know you'll enjoy the conversation.Full show notes at https://talkpython.fm/episodes/show/410/the-intersection-of-tabular-data-and-generative-ai
We all know that privacy regulations are getting more strict. And that many of our users no longer believe that "privacy is dead". But for even medium-sized organizations, actually tracking how we are using personal info in our myriad of applications and services is very tricky and error prone. On this episode, we have Thomas La Piana from the Fides project to discuss privacy in our applications and how Fides can enforce and track privacy requirements in your Python apps.Full show notes at https://talkpython.fm/episodes/show/409/privacy-as-code-with-fides
So you know about dependencies and testing, right? If you're talking to a DB in your app, you have to decide how to approach that with your tests. There are lots of solid options you might pick and they vary by goals. Do you mock out the DB layer for isolation or do you use a test DB to make it as real as possible? Do you just punt and use the real DB for expediency? What if your dependency was a huge array of radio telescopes and a rack of hundreds of bespoke servers? That's the challenge on deck today were we discuss testing radio astronomy with pytest with our guest James Smith. He's a Digital Signal Processing engineer at the South African Radio Astronomy Observatory and has some great stories and tips to share.Full show notes at https://talkpython.fm/episodes/show/405/testing-in-radio-astronomy-with-python-and-pytest
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
Imagine a world with free and unlimited clean energy. That's the musings of a great science fiction story. But nuclear fusion (the kind that powers the sun) has always been close at hand, we see the sun every day, and yet impossibly far away as a technology. We took a major step towards this becoming a reality with the folks at the Lawrence Livermore National Labratory in the US achieved "ignition" where they got significantly more energy out than they put in. And Python played a major role in this research and experiment. We have Jay Salmonson here to give us a look at the science and the Python code of this discovery.I've also linked to a 5-minute YouTube video explaining all the tooling of this massive machine. If you have the time, it's worth watching before listening further.Full episode show notes at https://talkpython.fm/episodes/show/403/fusion-ignition-breakthrough-and-python
When you think about processing tabular data in Python, what library comes to mind? Pandas, I'd guess. But there are other libraries out there and Polars is one of the more exciting new ones. It's built in Rust, embraces parallelism, and can be 10-20x faster than Pandas out of the box.We have Polars' creator, Ritchie Vink here to give us a look at this exciting new data frame library.Full show notes at https://talkpython.fm/episodes/show/402/polars-a-lightning-fast-dataframe-for-python
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
Our code quality tools (linters, test frameworks, and others) play an important role in keeping our code error free and conforming to the rules our teams have chosen. But when these tools become sluggish and slow down development, we often avoid running them or even turn them off. On this episode, we have Charlie Marsh here to introduce Ruff, a fast Python linter, written in Rust. To give you a sense of what he means with fast, common Python linters can take 30-60 seconds to lint the CPython codebase. Ruff takes 300 milliseconds. I ran it on the 20,000 lines of Python code for our courses web app at Talk Python Training, and it was instantaneous. It's the kind of tool that can change how you work. I hope you're excited to learn more about it.Full episode at https://talkpython.fm/episodes/show/400/ruff-the-fast-rust-based-python-linter
Monorepos are contrary to how many of us have been taught to use source control. To start a project or app, the first thing we do is create a git repo for it. This leads to many focused and small repositories. A quick check of my GitHub account shows there are 179 non-fork repositories. That's a lot but I think many of us work that what.But it's not like this with monorepos. There you create one (or a couple) repositories for your entire company. This might have 100s or 1,000s of employees working on multiple projects within the single repo. Famously, Google, Meta, Microsoft, and Airbnb all employ very large monorepos with varying strategies of coordination.On this episode, we have David Vujic here to give us his perspective on monorepos as well as highlight an architectural pattern and set of tools for accomplishing this in Python.https://talkpython.fm/episodes/show/399/monorepos-in-python
The iconic and first ever image of a black hole was recently released. It took over a decade of work and is a major achievement for astronomy and broadens our understanding of the universe for all of us. Would it surprise you to know that Python played a major part in this discovery? Of course it did, and Dr. Sara Issaoun is here to give us the full story.Full show notes at https://talkpython.fm/episodes/show/398/imaging-black-holes-with-python
The beauty of open source software and libraries is that you're not stuck with a single option some vendor is offering. This is especially true when that support is poor and antiquated. Almost any capability you think of has multiple options even for a single language such as Python. Just think about how many web frameworks you can pick today.But therein lies a new problem: If there are 10 options, how do you choose? Do go for the oldest and potentially most stable? How about the most updated one? Maybe that hot new version that has the fastest adoption curve.It's not easy. But luckily we have an excellent panel here to discuss exactly that. You'll hear from Emily Morehouse, Cecil Phillip, Kim van Wyk, Łukasz Langa, Gareth Thomas, and Dan Gerlanc.Full show notes at https://talkpython.fm/episodes/show/397/evaluating-new-open-source-tech-panel
Full show notes at https://talkpython.fm/episodes/show/396/ai-goes-on-trial-for-writing-code-crossover
If you maintain any projects on places like GitHub, you know that having a classy readme is important and that maintaining a change log can be helpful for you and consumers of the project. It can also be a pain. That's why I'm excited to welcome back Ned Batchelder to the show. He has a lot of tools to help here as well as some opinions we're looking forward to hearing. We cover his tools and a bunch of others he and I found along the way.Full show notes at https://talkpython.fm/episodes/show/395/tools-for-readme.md-creation-and-maintenance
Jupyter is an amazing environment for exploring data and generating executable reports with Python. But there are many external tools, extensions, and libraries to make it so much better and make you more productive. On this episode, we are going to cover a ton of them. We have Markus Schanta, the maintainer of the awesome-jupyter list on the show and we'll highlight a bunch of Jupyter gems.Full show notes at https://talkpython.fm/episodes/show/394/awesome-jupyter-libraries-and-extensions-in-2022
Space science is one of the few sciences that can spark wonder and imagining in almost anyone. It also happens to be the domain of Python with many missions, telescopes, and analysis happening with Python playing a major role. On this episode we have Thomas Albin who has worked on several recent space missions. He has created a delightful YouTube channel called Space Science with Python. It's approachable and yet concrete and realistic. We are going to dive into some of his videos and see how Python can model things like astroid fly-bys and render comets in 3D.Full show notes at https://talkpython.fm/episodes/show/393/space-science-with-python
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
No Python announcement of 2022 was met with more fanfare than pyscript. This project, announced at PyCon 2022, allows you to write Python files and run them in your browser in place of JavaScript or even with interactions between Python and JavaScript. There was just one catch: The runtime download was a 9MB WebAssembly file. That made it's uses quite limited.
On this episode, we dive into some news that might change that calculus. The MicroPython and PyScript folks have been teaming up to get PyScript running in the browser on MicroPython. Yes, that's the embedded chip Python. Here's the good news: MicroPython's WebAssembly is just 300k to download and loads in under 100ms. Now that could unlock some possibilities.
We have Brett Cannon, Nicholas Tollervey, and Fabio Pliger on the show to discuss.
Full show notes at https://talkpython.fm/episodes/show/391/pyscript-powered-by-micropython
Wondering what Mastodon is all about? More importantly, what does it offer Python developers and other open source folks compared to Twitter? There is a huge amount of interest in the tech community about what's happening at Twitter and whether they should expand to or even move to a new location. So I decided to put together a set of experienced Python developers who have been Mastodon inhabitants for a long time to discuss what this unexpected shift means for one of our important online watering holes.
On this episode you'll meet Gina Häußge, Simon Willison, and Juan Luis Cano Rodríguez. We're going to have a great time talking about the technology and the culture of Mastodon from this Python perspective.
https://talkpython.fm/episodes/show/390/mastodon-for-python-devs
If you're a fan of Python's async and await keywords and the powers they unlock, then this episode is for you. We have Timo Furrer here to share a whole bunch of asyncio related Python packages. Timo runs the awesome-asyncio list and he and I picked out some of our favorites to share with you.
Full show notes at https://talkpython.fm/episodes/show/389/18-awesome-asyncio-packages-in-python
Python 3.11 is here! Keeping with the annual release cycle, the Python core devs have released the latest version of Python. And this one is a big one. It has more friendly error messages and is massively faster than 3.10 (between 10 to 60% faster) which is a big deal for a year over year release of a 30 year old platform.
On this episode, we have Irit Katriel, Pablo Galindo Salgado, Mark Shannon, and Brandt Bucher all of whom participated in releasing Python this week on the show to tell us about that process and some of the highlight features.
Full show notes at https://talkpython.fm/episodes/show/388/python-3.11-is-here-and-its-fast
Python's data science and data visualization capabilities are certainly one of the reasons for Python's meteoric rise over the past 10 years. But often thens visuals have been corralled into notebooks used by data scientists themselves or into static web pages. Recently, a host of excellent dashboard build and hosting frameworks have come along to turn these visuals into interactive apps for everyone. On this episode, we'll talk about H20 Wave. One of these excellent dashboard frameworks. We have Martin Turoci from H2O.ai here to tell us about Wave.
Full show notes at https://talkpython.fm/episodes/show/386/realtime-web-apps-and-dashboards-with-h2o-wave
Do you love Python's async and await but feel that you could use more flexibility and higher-order constructs like running a group of tasks and child tasks as a single operation, or streaming data between tasks, combining async tasks with multiprocessing or threads, or even async file support? You should check out AnyIO. On this episode we have Alex Grönholm the creator of AnyIO here to give us the whole story.
Full show notes at https://talkpython.fm/episodes/show/385/higher-level-python-asyncio-with-anyio
Do you struggle to know where to start in the wide range of Python's visualization frameworks? Not sure when to use Plotly vs. Matplotlib vs. Altair? Then this episode is for you. We have Chris Moffitt, a Talk Python course author and founder of Practical Business Python, back on the show to discuss getting started with Python's data visualization frameworks.
Full show notes at https://talkpython.fm/episodes/show/384/python-data-visualization-where-to-start
For all the amazing powers of Python, deploying packaged apps that leverage native OS-level capabilities isn't one of them. But it can be done and we have a great guest, Rhet Turnbull, here to tell us how he built his distributable macOS app Textinator that uses macOS's native vision recognition framework through Python.
Full show notes at https://talkpython.fm/episodes/show/383/textinator-and-building-macos-apps-with-python
When you think data exploration using Python, Jupyter notebooks likely come to mind. They are excellent for those of us who gravitate towards Python. But what about your everyday power user? Think of that person who is really good at Excel but has never written a line of code? They can still harness the power of modern Python using a cool application called Superset.
This open source Python-based web app is all about connecting to live data and creating charts and dashboards based on it using only UI tools. It's super popular too with almost 50,000 GitHub stars. Its creator, Max Beauchemin is here to introduce it to us all.
Full show notes at https://talkpython.fm/episodes/show/382/apache-superset-modern-data-exploration-platform
We are on the edge of a major jump in Python performance. With the work done by the Faster CPython team and Python 3.11 due out in around a month, your existing Python code might see an increase of well over 25% in speed with no changes. One of the main reasons is its new specializing, adaptive interpreter.
This episode is about that new feature and a great tool called Specialist which lets you visualize how Python is speeding up your code and where it can't unless you make minor changes. Its creator, Brandt Bucher is here to tell us all about.
Full show notes at https://talkpython.fm/episodes/show/381/python-perf-specializing-adaptive-interpreter
Terminals seem like the very lowest common denominator for software platforms. They have to work over SSH. They only show text. You can't do much with them. Or can you? Will McGugan and team have been building Textual (based on Rich) which looks more like an animated web app than a terminal app. And he has learned a bunch of lessons trying to maximize terminal based apps. He's here to share his 7 lessons he's learned while building a modern TUI (text user interface) framework.
Full episode details at https://talkpython.fm/episodes/show/380/7-lessons-from-building-a-modern-tui-framework
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
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.
Full show notes at https://talkpython.fm/episodes/show/378/flet-flutter-apps-in-python
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.
Full show notes at https://talkpython.fm/episodes/show/376/pydantic-v2-the-plan
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.
Full show notes at https://talkpython.fm/episodes/show/375/python-language-summit-2022
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.
We have Gina Häußge, Emily Morehouse-Valcarcel, Tonya Sims, Brett Cannon, Jay Miller, and Paul Everitt to help us with the 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.
Full show notes at https://talkpython.fm/episodes/show/373/reinventing-azures-python-cli
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.
Full show notes at https://talkpython.fm/episodes/show/372/applied-mathematics-with-python
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.
Full show notes at https://talkpython.fm/episodes/show/371/pipx-installable-isolated-python-applications
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.
Full show notes at https://talkpython.fm/episodes/show/370/openbb-pythons-open-source-investment-platform
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.
Full show notes and links at https://talkpython.fm/episodes/show/369/getting-lazy-with-python-imports-and-pep-690
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.
Full show notes over at https://talkpython.fm/episodes/show/367/say-hello-to-pyscript-webassembly-python
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.
Full show notes at https://talkpython.fm/episodes/show/366/optimizing-postgresql-db-queries-with-pgmustard
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.
Full episode at https://talkpython.fm/episodes/show/365/solving-negative-engineering-problems-with-prefect
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.
Full episode page over at https://talkpython.fm/episodes/show/364/symbolic-math-with-python-using-sympy
Are you coming to Python from another language and ecosystem? It can seem a bit daunting at first. But Python is very welcoming and has a massive array of tools and libraries. In this episode, I speak to my friend Cecil Philip who does both Python and .NET development. We discuss what it's like coming to Python from .NET as well as a whole bunch of compare and contrasts across the two ecosystems.
Check out the episode show page at https://talkpython.fm/episodes/show/363/python-for-.net-and-c-developers
What would a modern Python project look like? Maybe it would use Poetry rather than pip directly for its package management. Perhaps its test automation would be controlled with Nox. You might automate its release notes with Release Drafter. The list goes on and on. And that list is the topic of this episode. Join me and Claudio Jolowicz as we discuss his Hypermodern Python project and template.
Full show notes at https://talkpython.fm/episodes/show/362/hypermodern-python-projects
Python's place is climate research is an important one. In this episode, you'll meet Joe Hamman and Ryan Abernathy, two researchers using powerful cloud computing systems and Python to understand how the world around us is changing. They are both involved in the Pangeo project which brings a great set of tools for scaling complex compute with Python.
Full episode details at https://talkpython.fm/episodes/show/361/pangeo-data-ecosystem
Python has come a long way since it was released in 1991. It originally released when the Standard Library was primary the totality of functionality you could leverage when building your applications. With the addition of pip and the 368,000 packages on PyPI, it's a different world where what we need and expect from the Standard Library. Brett Cannon and Christian Heimes have introduced PEP 594 which is the first step in trimming outdated and unmaintained older modules from the Standard Library. Join us to dive into the history and future of Python's Standard Library.
Full episode show notes over at https://talkpython.fm/episodes/show/360/removing-pythons-dead-batteries-in-just-5-years
Are you working on or considering a machine learning project? On this episode, we'll meet three people from the MLOps community: Demetrios Brinkmann, Kate Kuznecova, and Vishnu Rachakonda. They are here to tell us about the lifecycle of a machine learning project. We'll talk about getting started with prototypes and choosing frameworks, the development process, and finally moving into deployment and production.
Full show notes at https://talkpython.fm/episodes/show/359/lifecycle-of-a-machine-learning-project
Pandas is a great library that allows you to accomplish a ton of filtering and processing in condensed syntax. But how well do you understand what's happening? Sam Lau and Philip Guo built a great site to help use visually explore how Pandas is processing your dataset with your specific syntax. It's called PandasTutor, and Sam is here to tell us about it.
Get the full show notes at https://talkpython.fm/episodes/show/358/understanding-pandas-visually-with-pandastutor
Telescopes have been fundamental in our understanding of our place in the universe. And when you think about images that have shaped our modern view of space, you probably think about Hubble. But just this year, the JWST or James Web Space Telescope, was launch. JWST will go far beyond what Hubble has discovered. And did you know Python is used extensively in the whole data pipeline of JWST? We have two great guests here to tell us about it: Megan Sosey and Mike Swam.
Full show notes at https://talkpython.fm/episodes/show/357/python-and-the-james-webb-space-telescope
Have you been considering launching a product or even a business based on Python's AI / ML stack? We have a great guest on the episode this week, Dylan Fox, who is the cofounder of AssemblyAI and has been building his startup successfully over the past few years. He has interesting stories of 100s of GPUs in the cloud, evolving ML models, and much more that I know you'll enjoy hearing.
Full show notes at https://talkpython.fm/episodes/show/356/tips-for-ml-ai-startups
What database are you using in your apps these days? If you like most Python people, it's probably PostgreSQL. If you roll with NoSQL like me, you're probably using MongoDB. Maybe you're even using a graph database focused more on relationships.
But there's a new Python database in town, and as you learn in during this episode, many critical Python libraries have come into existence because of it. This database is called EdgeDB. EdgeDB is built upon Postgres, implemented mostly in python, and is something of a marriage of a traditional relational database and an ORM.
Python's async and await keywords, uvloop - the high performance asyncio event loop, and asyncpg all have ties back to the creation of EdgeDB.
Yury Selivanov, the co-founder & CEO of EdgeDB, PSF fellow, and Python core developer is here to tell use about EdgeDB along with the history of many of these impactful language features and packages.
Full show notes at https://talkpython.fm/episodes/show/355/edgedb-building-a-database-in-python
When you think about the power of Python, the clean language or powerful standard library may come to mind. You might certainly point to the external packages too. But what about the relative ease of picking up new libraries or even parts of the standard library? Documentation plays an important role there. And the tools in the Python space for building solid documentation and even publishing articles and books involving live code are huge assets.
In this episode, we have Paul Everitt, Pradyun Gedam, Chris Holdgraf, and Chris Sewell to update us on Sphinx, MyST-Parser, ExecutableBooks, JupyerBook, Sphinx Themes, and much more.
Full show notes at https://talkpython.fm/episodes/show/354/sphinx-myst-and-python-docs-in-2022
Two frameworks that have taken the Python world by storm are FastAPI and Pydantic. Once you already have your data exchange modeled in Pydantic, you might want to use that code for storing it in the database. And, if you have DB models you might want to somehow use them to power and document the APIs built with FastAPI.
But the popular ORMs, such as SQLAlchemy and others, far predate Pydantic. But could they be put together?
Sebastián Ramírez is here to tell us the answer is yes. We're covering his project SQLModel which is the marriage between Pydantic and SQLAlchemy.
Full show notes at https://talkpython.fm/episodes/show/353/sqlmodel-the-new-orm-for-fastapi-and-beyond
Do we talk about running Python in production enough? I can tell you that the Talk Python infrastructure (courses, podcasts, APIs, etc.) get a fair amount of traffic, but they look nothing like what Google, or Instagram, or insert [BIG TECH NAME] here's deployments do. Yet, mostly, we hear about interesting feats of engineering at massive scale that is impressive but often is also outside of the world most Python devs need for their companies and services.
I have three great guests who do think we should talk more about small to medium-sized Python deployments: Emily Moorehouse, Hynek, and Glyph.
I think you'll enjoy the conversation. They each bring their own interesting perspectives.
Check out the episode page at https://talkpython.fm/episodes/show/352/running-python-in-production
For 30 years, Python was overseen by Guide van Rossum since he created and released it around in 1990. When he retired in 2018 he left the creation of the new governing body up to the core developers. After a few stressful months, they concept of the steering council became the way forward.
On this episode, I welcome the outgoing steering council to give us a look back and how this past year has gone. We welcome Barry Warsaw, Carol Willing, Brett Cannon, Pablo Galindo Salgado, and Thomas Wouters to the show. They are going to give us a rundown on of the important decisions for 2021.
Full show notes at https://talkpython.fm/episodes/show/350/python-steering-council-2021-retrospective
This podcast episode you're listening to right now was delivered to you, in part, by MongoDB and Python powering our web apps and production processes. But if you're using pymongo, the native driver from MongoDB to talk to the server, you're doing it wrong. Basing your app on a foundation of exchanging raw dictionaries is a castle of sand. BTW, see the joke at the end of the show about this.
You should be using an ODM. This time we're talking about Beanie which is one of the exciting, new MongoDB Object Document Mappers which is based on Pydantic and is async-native. Join me as I discuss this project with its creator: Roman Right.
Get the full show notes at https://talkpython.fm/episodes/show/349/meet-beanie-a-mongodb-odm-pydantic
I'm always on the look out for a good Python UI framework. This episode focuses on Dear PyGui.
Dear PyGui: A fast and powerful Graphical User Interface Toolkit for Python with minimal dependencies, created by Jonathan Hoffstadt and Preston Cothren. They are here to tell us all about it
Check it out at https://talkpython.fm/episodes/show/348/dear-pygui-simple-yet-fast-python-gui-apps
The team at Instagram dropped a performance bomb on the Python world when they open-sourced Cider, their performance oriented fork of CPython. It contains a number of performance optimizations, including bytecode inline caching, eager evaluation of coroutines, a method-at-a-time JIT, and an experimental bytecode compiler that uses type annotations to emit type-specialized bytecode that performs better in the JIT.
While it's not a general purpose runtime we can all pick up and use, it contains many powerful features and optimizations that may make their way back to mainline Python.
We welcome Dino Viehland to dive into Cinder.
Full show notes at https://talkpython.fm/episodes/show/347/cinder-specialized-python-that-flies
Do you enjoy the "final 2 questions" I always ask at the end of the show? I think it's a great way to track the currents of the Python community. This episode focuses in on one of those questions: "What notable PyPI package have you come across recently? Not necessarily the most popular one but something that delighted you and people should know about?"
Our guest, Antonio Andrade put together a GitHub repository cataloging guests' response to this question over the past couple of years. So I invited him to come share the packages covered there. We touch on over 40 packages during this episode so I'm sure you'll learn a few new gems to incorporate into your workflow.
Check out the full show notes at https://talkpython.fm/episodes/show/346/20-recommended-packages-in-review
You know that feeling when one of your developer friends or colleague tells you about some amazing tool, library, or shell environment that you never heard of that you just have to run out and try right away? This episode is jam-packed full of those moments. We welcome back Jay Miller to discuss tools and tips for developer productivity. The title says 10 tips, but we actually veer into many more along the way. I think you'll really enjoy this useful and light-hearted episode.
Full show notes over at https://talkpython.fm/episodes/show/345/10-tips-and-tools-for-developer-productivity
SQLAlchemy is the most widely used ORM (Object Relational Mapper) for Python developers. It's been around since February 2006. But we might be in for the most significant release since the first one: SQLAlchemy 2.0. This version adds async and await support, new context-manager friendly features everywhere, and even a unified query syntax. Mike Bayer is back to give us a glimpse of what's coming and why Python's database story is getting stronger.
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
At PyCon 2017, Jake Vanderplas gave a great keynote where he said, "Python is a mosaic." He described how Python is stronger and growing because it's being adopted and used by people with diverse technical backgrounds. In this episode, we're adding to that mosaic by diving into how Python is being used in the architecture, engineering, and construction industry. Our guest, Gui Talarico, has worked as an architect who help automate that world by bringing Python to solve problems others were just doing by point-and-click tooling. I think you'll enjoy this look into that world. We also touch on his project pyairtable near the end as well.
Full show notes at https://talkpython.fm/episodes/show/342/python-in-architecture-as-in-actual-buildings
Do you do anything with Jupyter notebooks? If you do, there is a very good chance you're working with the pandas library. This is one of THE primary tools of anyone doing computational work or data exploration with Python. Yet, this library is massive and knowing the idiomatic way to use it can be hard to discover.
That's why I've invited Bex Tuychiev to be our guest. He wrote an excellent article highlighting 25 idiomatic Pandas functions and properties we should all keep in our data toolkit. I'm sure there is something here for all of us to take away and use pandas that much better.
Full show notes at https://downloads.talkpython.fm/podcasts/talkpython/341-25-pandas-functions.mp3
Is Python slow? We touched on that question with Guido and Mark last episode. This time we welcome back friend of the show, Anthony Shaw. Here's there to share the massive amount of work he's been doing to answer that question and speed things up where they answer is yes. He's just released version 1.0 of the Pyjion project.
Pyjion is a drop-in JIT compiler for Python 3.10. Pyjion uses the power of the .NET 6 cross-platform JIT compiler to optimize Python code on the fly, with NO changes to your source code required. It runs on Linux, macOS, and Windows, x64 and ARM64.
There has a been a bunch of renewed interested in making Python faster. While for some of us, Python is already plenty fast. For others, such as those in data science, scientific computing, and even the large tech companies, making Python even a little faster would be a big deal.
This episode is the first of several that dive into some of the active efforts to increase the speed of Python while maintaining compatibility with existing code and packages.
Who better to help kick this off than Guido van Rossum and Mark Shannon? They both join us to share their project to make Python faster. I'm sure you'll love hearing what they are up to.
Full show notes at https://talkpython.fm/episodes/show/339/making-python-faster-with-guido-and-mark
How do you build and maintain a complex suite of Python packages? Of course, you want to put them on PyPI. The best format there is as a wheel. This means that when developers use your code, it comes straight down and requires no local tooling to install and use.
But if you have compiled dependencies, such as C or FORTRAN, then you have a big challenge. How do you automatically compile and test against Linux, macOS (Intel and Apple Silicon), Windows, and so on? That's the problem cibuildwheel is solving.
On this episode, you'll meet Henry Schreiner. He is developing tools for the next era of the Large Hadron Collider (LHC) and is an admin of Scikit-HEP. Of course, cibuildwheel is central to this process.
Full show notes at https://talkpython.fm/episodes/show/338/using-cibuildwheel-to-manage-the-scikit-hep-packages
Have you heard of Kedro? It's a Python framework for creating reproducible, maintainable and modular data science code.
We all know that reproducibility and related topics are important ones in the data science space. The freedom to pop open a notebook and just start exploring is much of the magic.
Yet, that free-form style can lead to difficulties in versioning, reproducibility, collaboration, and moving to production. Solving these problems is the goal of Kedro. And we have 3 great guests from the Kedro community here to give us the rundown: Yetunde Dada, Waylon Walker, and Ivan Danov.
Full show notes at https://talkpython.fm/episodes/show/337/kedro-for-maintainable-data-science
Have you heard of the package Rich? This library allows you to create very, well, rich terminal-based UIs in Python. When you think of what you can typically build with basic print statements, that may seem quite limited. But with Rich, imagine justified tables, progress bars, rendering of markdown, and way more.
This is one of the fastest growing projects in the Python space these days. And the creator, Will McGugan is here to give is the whole history and even a peak at the future of Rich and a follow on library called Textual.
Full show notes at https://talkpython.fm/episodes/show/336/terminal-magic-with-rich-and-textual
Gene therapy holds the promise to permanently cure diseases that have been considered life-long challenges. But the complexity of rewriting DNA is truly huge and lives in its own special kind of big-data world.
On this episode, you'll meet David Born, a computational biologist who uses Python to help automate genetics research and helps move that work to production.
Full episode notes over at https://talkpython.fm/episodes/show/335/gene-editing-with-python
On this episode, Rob Emanuele and Tom Augspurger join us to talk about building and running Microsoft's Planetary Computer project. This project is dedicated to providing the data around climate records and the compute necessary to process it with the mission of help use all understand climate change better. It combines multiple petabytes of data with a powerful hosted Jupyterlab notebook environment to process it.
Full show notes at https://talkpython.fm/episodes/show/334/microsoft-planetary-computer
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
Does it seem like your Python projects are getting bigger and bigger? Are you feeling the pain as your codebase expands and gets tougher to debug and maintain? Patrick Viafore is here to help us write more maintainable, longer-lived, and more enjoyable Python code.
Full show notes at https://talkpython.fm/episodes/show/332/robust-python
Python is a technology and community built upon the goodwill and volunteer time of 1,000s of contributors from the core devs inside CPython to the authors of 100,000s of external packages on PyPI.
Until recently, the only full time folks have been at the PSF doing very important work but that work has been largely outside of CPython the technology. In July, 2021, the PSF created the Python Developer in Residence position. The first person in that role is Łukasz Langa and he's here to tell us how it's going and how it will benefit Python at large.
If you are working with data pipelines, you definitely need to give Apache Airflow a look. This pure-Python workflow framework is one of the most popular and capable out there. You create your workflows by writing Python code using clever language operators and then you can monitor them and even debug them visually once they get started.
Stop writing manual code or cron-job based code to create data pipelines check out Airflow. We're joined by three excellent guests from the Airflow community: Jarek Potiuk, Kaxil Naik, and Leah Cole.
Full show notes at https://talkpython.fm/episodes/show/330/apache-airflow-open-source-workflow-with-python
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
ORMs are one of the main tools to put first-class data access in the hands on non-SQL-loving developers and even for those who do love SQL, making them way more productive. When you hear about ORMs in Python, we often hear about either SQLAlchemy and Django ORM. And we should, they are great. But there are newer ORMs that take better advantage of modern Python.
On this episode, you'll meet Daniel Townsend. He's the creator of Piccilo ORM. A great ORM that is async first, but also has synchronous APIs. It has a super clean query syntax. And, it's easy to learn.
Full show notes at https://talkpython.fm/episodes/show/328/piccolo-a-fast-async-orm-for-python
You've heard me talk to wide cast of people building amazing things with Python. Some of them are building bio-reactors to remove carbon from the air with AI and Python. Others are optimizing aerodynamics and race strategy at the highest levels of automobile racing.
This episode is different. Rather than seeing how far we can push Python to the edges of technology, we are diving in to the tiny Python applications that might never be released publicly and yet can transform our day to day lives with simple automation on an individual level.
We have 4 great guests with us here today: Rivers Cuomo, Jay Miller, Kim van Wyk, and Rusti Gregory. They will each share a couple of apps and the underlying packages they used to build them. I know this will be a super motivational episode for many of you. I hope that after listening, you'll transform something tedious and error-prone in your live to an instantaneous button click solution with Python.
Check it out at https://talkpython.fm/episodes/show/327/little-automation-tools-in-python
Did you know I'm a fan of GUIs. You know, they are kind of like web pages, but they run on your computer, they have their own windows, and you can even use them offline! On this episode, we'll dive into wxPython with Mike Driscoll. He's back on the podcast to share his hard-won experience on building and distributing Python Window-based applications.
Full show notes at https://talkpython.fm/episodes/show/326/building-desktop-apps-with-wxpython
When you think about embedded programming, does it bring low-level languages and tools to mind? Maybe Embedded C or even Assembly language? Thanks to the groundbreaking work by Damien George back in 2014 to create MicroPython, Python is one of the very solid choices for building tiny programmable devices.
On this episode, we welcome back Damien George from MicroPython along with Scott Shawcroft from CircuitPython and Adafruit. We'll talk about how these two frameworks are solving similar problems with slightly different philosophies. More importantly, they are working closely to bring MicroPython and CircuitPython more in sync.
Full show notes at https://talkpython.fm/episodes/show/325/micropython-circuitpython
Python is used to solve a large and varied set of problems. One of its core pillars is web APIs. Another one is ML and data science. Those two important pieces were brought together in an unexpected yet magically-futuristic way by Rod Senra's team working with the Gatorade Sports Science Institute.
They created a patch that you wear while working out once or twice. It analyzes your perspiration. Combines with it other factors like running distance, sleep quality, and more. Then provides recommendations, using Python, about how to get more effective fitness.
Full show notes at https://talkpython.fm/episodes/show/324/gatorade-powered-python-apis
You've got your Python API or app running in a Docker container. Great! Are you ready to ship it to that hosted cluster service and head off to production? Not so fast. Have you considered how you'll manage evolving dependencies and addressing security updates over time? Not just for the base OS but for installed packages? How about your pip installed dependencies? Are you running as root? If you don't know, the answer is yes.
We'll discuss these issues and many more with Itamar Turner-Trauring on this episode.
Full show notes over at https://talkpython.fm/episodes/show/323/best-practices-for-docker-in-production
Are you interested in getting ahead in data science? On this episode, you'll meet Sanyam Bhutani who studied computer science but found his education didn't prepare him for getting a data science-focused job. That's where he started his own path of self-education and advancement. Now he's working at an AI startup and ranking high on Kaggle.
Have you wanted to add more interactivity and liveness to your web application? If you built it using Flask, Django, or some other Python web framework, that thought probably didn't fill you with joy. Because it might mean that you need to change a bunch of code and rewrite a significant bit of your app using a full-on front-end framework like Vue.js or React.js.
In this episode, we meet Carson from Big Sky Software. He's the creator of HTMX. This front-end JavaScript library let's you leverage the server side aspects of your Python web app and add amazing interactivity but keep the logic on the server, near the database, and implemented in Python.
You're going to love it.
In this episode, we cover how Python is being used to understand the electrical markets and grid in Australia. Our guest, Jack Simpson, has used Python to uncover a bunch of interesting developments as the country has adopted more and more solar energy. We round out the episode looking at some best practices for high-performance, large-data processing in Pandas and beyond.
In addition to that, we also spend some time on how Jack used Python and Open CV (computer vision) to automate the study of massive bee colonies and behaviors. Spoiler alert: That involved gluing Wing Ding fonts to the backs of bees!
Full show notes at https://talkpython.fm/episodes/show/320/python-in-the-electrical-energy-sector
One of the true superpowers of Python is the libraries over at the Python Package Index. They are all just a "pip install" away. Yet, like all code that you run on your system, it is done with some degree of trust. How do we know that all of those useful packages are trustworthy?
That's the topic of this episode. Bentz Tozer and John Speed Meyers are here to share their research into typosquatting on PyPI and other sneaky deeds. But we also discuss some potential solutions and fixes.
Check it out at https://talkpython.fm/319
Machine learning has made huge advancements in the past couple of years. We now have ML models helping doctors catch disease early. Google is using ML to suggest traffic routes in their maps app that will lesson the amount of gasoline used in the trip. And many more examples. But there is a heavy cost for training machine learning models.
In this episode, you'll meet Victor Schmidt, Jonathan Wilson, and Boris Feld. They work on the CodeCarbon project together. This project offers a Python package and dashboarding tool to help you understand and minimize your ML model's environmental impact.
Full shown notes at https://talkpython.fm/episodes/show/318/measuring-your-ml-impact-with-codecarbon
When you think of government software development and projects, do you fast apps and modern tech stacks jump to mind? Probably not. So you'll be delighted to hear from our guest, Laura Beaufort. She's the Tech Lead at the US Federal Election Commission.
She and her team have built a very modern tech stack running modern Flask web apps with APIs powered by SQLAlchemy and Flask-RESTFUL. The app is available open-source on GitHub. And they deploy it with continuous delivery out to cloud.gov.
There are lots of lessons to learn for governmental agencies around the world as well as private organizations, small and large.
Full show notes at https://talkpython.fm/episodes/show/317/python-at-the-us-federal-election-commission
Flask is one of the most popular Python web frameworks. And they have huge news to share with us. Flask 2.0 just released after a ton of work. And it's as big of a deal as the version number suggests. Async changes are coming, Python 3.5 and below (including Python 2) support has been dropped and much much more. Join me as I discuss Flask 2.0 with David Lord and Philip Jones.
Have you heard that FastAPI is awesome? We have Michael Herman back on the show to help us make it even more awesome with his FastAPI awesome list. He's categorized many extensions and other libraries working with FastAPI to help you be even more efficient with this framework.
Here's an episode that I did not see coming! Sebastian Witowski and I put together a live stream ask me anything (AMA) as a follow up to some of the ideas around his recent course, Modern Python Projects. We dove deep in comparisons of Poetry vs. pip vs pyenv and answered questions like do you need to use Docker? When should you? and so on.
After the AMA was over, I realized it would also make a great podcast too. So here go you! This is our AMA with Sebastian around all the ideas of modern Python workflows. I hope you enjoy it!
Check out the full show notes at https://talkpython.fm/episodes/show/314/ask-us-about-modern-python-projects-and-tools
Data validation and conversion is one of the truly tricky part of getting external data into your app. This might come from a REST API, a file on disk, or somewhere else. This includes checking for required fields, correct data types, converting from compatible types (for example, strings to numbers), and much more. Pydantic is one of the best ways to do this in modern Python using dataclass-like constructs and type annotations to make it all seamless and automatic.
We welcome Samuel Colvin, creator of Pydantic, to the show. We'll dive into the history of Pydantic and it's many uses and benefits.
Full show notes at https://talkpython.fm/episodes/show/313/automate-your-data-exchange-with-pydantic
How do you build Python applications that can handling literally billions of requests. I has certainly been done to great success with places like YouTube (handling 1M requests / sec) and Instagram as well as internal pricing APIs at places like PayPal and other banks.
While Python can be fast at some operations and slow at others, it's generally not so much about language raw performance as it is about building an architecture for this scale. That's why it's great to have Julian Danjou on the show today. We'll dive into his book "The Hacker's Guide to Scaling Python" as well as some of his performance work he's doing over at Datadog.
Full show notes at https://talkpython.fm/episodes/show/312/python-apps-that-scale-to-billions-of-users
Full show notes at https://pythonbytes.fm/episodes/show/229/has-one-of-your-dependencies-died
These days Git is synonymous with source control itself. Rare are the current debates of whether to use git vs SVN vs some fossil like SourceSafe vs you name it. But do you know how Git works? What about it's internals? I'm sure you've seen a .git folder in your project's root. But to most folks, it's a black box.
In this episode, you'll meet Rob Richardson. He's going pop the lid on that black box as we dive into git internals and the .git folder, among other things source control.
Full show notes at https://talkpython.fm/episodes/show/311/get-inside-the-.git-folder
Full show notes over at https://pythonbytes.fm/episodes/show/228/supreme-court-sides-descides-api-copyright-battle
The tables have turned and this time I'm the guest and you all are the hosts. I get a ton of questions over email and twitter asking me about my thoughts on various trends, tools, and behind the scenes questions around Talk Python. So I've enlisted two listeners who are up for hosting a conversation and taking questions from you all.
Thank you to Patrik Hlobil and Kim van Wyk who guest host this episode where I answer a bunch of audience questions in this ask my anything.
Check it out at https://talkpython.fm/episodes/show/310/ama-ask-me-anything-with-michael
Full show notes at https://pythonbytes.fm/episodes/show/227/no-more-awaiting-async-comes-to-sqlalchemy
Machine learning and data science are full of best practices and important workflows. Can we extrapolate these to our broader lives? Eugene Yan and I give it a shot on this slightly more philosophical episode of Talk Python To Me.
The seven lessons:
- Data cleaning: Assess what you consume
- Low vs. high signal data: Seek to disconfirm and update
- Explore-Exploit: Balance for greater long-term reward
- Transfer Learning: Books and papers are cheat codes
- Iterations: Find reps you can tolerate, and iterate fast
- Overfitting: Focus on intuition and keep learning
- Ensembling: Diversity is strength
Full show notes at https://talkpython.fm/episodes/show/309/what-ml-can-teach-us-about-life-7-lessons
Full show notes at https://pythonbytes.fm/episodes/show/226/teaching-python-podcast-on-the-podcast
Docker is one of the core elements of developing Python applications in consistent ways as well as running them across different hardware universally. On this episode, you'll meet Peter McKee from Docker. He's here to catch us up on what's happening in the Docker universe for Python developers.
Full details at https://talkpython.fm/episodes/show/308/docker-for-python-developers-2021-edition
Python has changed a lot since its inception 30 years ago. On this episode, you'll meet Paul Everitt and Barry Warsaw. They have both been involved with Python since the very first Python conference (called SPAM1 even). We discuss how it's changed but also how so many of the pressures and ideas from the very early days are still playing out in 2021. I'm sure you'll enjoy all the stories and reminiscing.
Full show notes at https://talkpython.fm/episodes/show/307/python-from-1994-to-2021-my-how-youve-grown
When we talk about scaling software threading and async get all the buzz. And while they are powerful, using asynchronous queues can often be much more effective. You might think this means creating a Celery server, maybe running RabbitMQ or Redis as well.
What if you wanted this async ability and many more message exchange patterns like pub/sub. But you wanted to do zero of that server work? Then you should check out ZeroMQ.
ZeroMQ is to queuing what Flask is to web apps. A powerful and simple framework for you to build just what you need. You're almost certain to learn some new networking patterns and capabilities in this episode with our guest Min Ragan-Kelley to discuss using ZeroMQ from Python as well as how ZeroMQ is central to the internals of Jupyter Notebooks.
Check it out https://talkpython.fm/episodes/show/306/scaling-python-and-jupyter-with-zeromq
Full show notes at https://pythonbytes.fm/episodes/show/223/beware-a-ninja-is-shadowing-sebstastian-from-fastapi
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
Full show notes at https://pythonbytes.fm/episodes/show/222/autocomplete-with-type-annotations-for-aws-and-boto3
The relatively recent introduction of async and await as keywords in Python have spawned a whole area of high performance, highly scalable frameworks and supporting libraries. One such library that has great async building blocks is Omnilib.
On this episode, you'll meet John Reese. John is the creator of Omnilib, which includes packages such as aioitertools, aiomultiprocess, and aiosqlite. Join us as we async all the things.
Full show notes at https://talkpython.fm/episodes/show/304/asyncio-all-the-things-with-omnilib
Full show notes at https://pythonbytes.fm/episodes/show/221/pattern-matching-and-accepting-change-in-python-with-brett-cannon
If you are involved in science or use computational tools in your work, you should be using code to solve your problem. On this episode, we have Dr. Becky Smethurst who's an astrophysicist at Oxford University. She uses Python to explore galaxies and black holes.
Learn how she's using Python to make new discoveries at the cutting edge of research and dive into a couple of her YouTube videos aimed at spreading scientific truth in an entertaining wrapper.
Full show notes at https://talkpython.fm/episodes/show/303/python-for-astronomy-with-dr.-becky
Full show notes at https://pythonbytes.fm/episodes/show/220/what-why-and-where-of-friendly-errors-in-python
I'm sure you're familiar with data science. But what about data engineering? Are these the same or how are they related?
Data engineering is dedicated to overcoming data-processing bottlenecks, data cleanup, data flow and data-handling problems for applications that utilize lots of data.
On this episode, we welcome back Tobias Macey to give us the 30,000 ft view of the data engineering landscape in 2021.
Full show notes at https://talkpython.fm/episodes/show/302/the-data-engineering-landscape-in-2021
Full show notes at https://pythonbytes.fm/episodes/show/219/htmx-dynamic-and-live-html-without-javascript
Have you been learning Django and now want to get your site online? Not sure the best way to host it or the trade offs between the various options? Maybe you want to make sure your Django site is secure. On this episode, I'm joined by two Django experts Will Vincent and Carlton Gibson to talk about deploying and running Django in production along with recent updates in Django 3.2 and beyond.
Full show notes at https://talkpython.fm/episodes/show/301/deploying-and-running-django-web-apps-in-2021
Full show notes at https://pythonbytes.fm/episodes/show/218/keyboards-for-developers-python-and-some-history
You've heard that software developers and startups go hand-in-hand. But what about data scientists? Of course they! But how do you turn your data science skill set into a data science business skill set? What are some of the areas ripe for launching such a business into?
On this episode, I welcome back 4 prior guests who have all walked their own version of this path and are currently running successful Python-based Data Science startups:
- Ines Montani from Explosion AI
- Matthew Rocklin from Coiled
- Jonathon Morgan from Yonder AI
- William Stein from Cocalc
Full show notes at https://talkpython.fm/episodes/show/300/building-a-data-science-startup-panel
In this episode, we'll be discussing two powerful tools for data reporting and exploration: Datasette and Dogsheep.
Datasette helps people take data of any shape or size, analyze and explore it, and publish it as an interactive website and accompanying API.
Dogsheep is a collection of tools for personal analytics using SQLite and Datasette. Imagine a unified search engine for everything personal in your life such as twitter, photos, google docs, todoist, goodreads, and more, all in once place and outside of cloud companies.
On this episode we talk with Simon Willison who created both of these projects. He's also one of the co-creators of Django and we'll discuss some early Django history!
Check it out at https://talkpython.fm/episodes/show/299/personal-search-engine-with-datasette-and-dogsheep
Are you building or running an internal machine learning team? How about looking for a new ML position? On this episode, I talk with Chip Huyen from Snorkel AI about building ML teams, finding ML positions, and teach ML at Stanford.
Full show notes at https://talkpython.fm/episodes/show/298/building-ml-teams-and-finding-ml-jobs
Full show notes at https://pythonbytes.fm/episodes/show/215/a-visual-introduction-to-numpy
2020 will be one for the history books, won't it? I've put together a great group to look back on 2020 - from the Python perspective.
Join me along with Cecil Phillip, Ines Montani, Jay Miller, Paul Everitt, Reuven Lerner, Matt Harrison, and Brian Okken for a light-hearted and fun look back on the major Python events of 2020.
Full show notes at https://talkpython.fm/episodes/show/297/python-year-in-review-2020-edition
Full show notes at https://pythonbytes.fm/episodes/show/214/python-year-in-review-2020-edition
Geography is the study of places and the relationships between people and their environments. Often we think of maps, but maps are static. GIS gets interesting when you realize that we're studying and visualizing data flowing through these locations and communities.
In this episode, you'll meet Silas Toms. He's an author of several Python GIS books and the host of The Mappist Hour podcast. Are you ready to dive into GIS with Python?
Full show notes at https://talkpython.fm/episodes/show/295/gis-python
Full show notes at https://pythonbytes.fm/episodes/show/212/sqlite-as-a-file-format-like-docx
Full show notes at https://pythonbytes.fm/episodes/show/211/will-a-black-hole-devour-this-episode
When we think about accounts and security, we often think about identity (logging in and proving who you are). But for many applications, especially internal apps at large organizations, that's just step one. The next step is what can you do and what can you not do.
In this episode, you'll learn about a new library called oso. It's a declarative way to create policy code that maps to your mental model for who is allowed to do what in your system. We have two guests, Graham Neray and Sam Scott from the oso project to tell us all about it.
See the full show details at https://talkpython.fm/episodes/show/294/oso-authorizes-python
Full show notes at https://pythonbytes.fm/episodes/show/210/analyzing-kickstarter-campaigns-with-python
As software developers, we live in a world of uncertainty and flux. Do you need to build a new web app? Well maybe using Django makes the most sense if you've been doing it for a long time. There is Flask, but it's more mix and match being a microframework. But you've also heard that async and await are game changers and FastAPI might be the right choice.
Whatever it is you're building, there is constant pressure to stay on top of a moving target. Learning is not something you do in school then get a job as a developer. No, it a constant and critical part of your career. That's why we all need to be good, very good, at it.
Matt Harrison is back on Talk Python to talk to us about some tips, tricks, and even science about learning as software developers.
Full show notes at https://talkpython.fm/episodes/show/293/learning-how-to-learn-as-a-developer
Full show notes at https://pythonbytes.fm/episodes/show/209/jiting-python-with-.net-no-irons-in-sight
So you're excited about that next app you're about to build. You can visualize the APIs with the smooth scalability taking to the mobile apps. You can see how, finally, this time, you'll get deployment right and it'll be pure continuous delivery out of GitHub with zero downtime.
What you're probably not dreaming about is writing yet another password reset form and integrating mail capabilities just for this purpose. Or how you'll securely store user accounts the right way this time.
Don't worry, we got you covered. Our guests, Christos Matskas and John Patrick Dandison are here to cover a bunch of different libraries and techniques we can use for adding identity to our Python applications.
Full show notes at https://talkpython.fm/episodes/show/292/pythonic-identity-auth-in-python-ecosystem
Do you have a scientific system that needs optimization or solving? Our guest, on this episode, Clark Petri is here to tell us all about pyomo. This is a library that can solve all sorts of cool problems, linear programming, nonlinear equations, and many other things you can throw at it.
We're gonna solve a really fun diet problem: What is the most nutritious meal that you can eat for the least amount of money? The answer might surprise you a little bit! It's going to be a lot of fun. So listen in to hear about how Clark has used pyomo to do his work and how you might use it in yours.
Full show notes at https://talkpython.fm/episodes/show/291/operational-resilience-with-pyomo
Full show notes at https://pythonbytes.fm/episodes/show/207/fastapi-as-a-web-platform-not-just-apis
Are you a data scientist looking to branch out on your own and start something new? Maybe you're just looking for a way to work with those exciting libraries that aren't yet in play at the day job. Rather than putting everything on the line, quitting your job, and hoping things work out, maybe you should start with a side-hustle.
On this episode, you'll meet Keith McCormick, a data scientist who has many irons in the fire and he's here to tell us about different types of side hustles and why you may want to try or avoid one.
Full show notes at https://talkpython.fm/episodes/show/290/side-hustles-for-data-scientists
When I saw the headline "Machine learning algorithm confirms 50 new exoplanets in historic first" I knew the Python angle of this story had to be told! And that's how this episode was born. Join David Armstrong and Jev Gamper as they tell us how they use Python and machine learning to discover not 1, but 50 new exoplanets in pre-existing Keplar satellite data.
Full show notes at https://talkpython.fm/episodes/show/289/disovering-exoplanets-with-python
Full show notes at https://pythonbytes.fm/episodes/show/206/python-dropping-old-operating-systems-is-normal
Excel is one of the most used and most empowering piece of software out there. But that doesn't make it a good fit for every data processing need. And when you outgrow Excel, a really good option for a next step is Python and the data science tech stack: Pandas, Jupyter, and friends.
Chris Moffitt is back on Talk Python to give us concrete tips and tricks for moving from Excel to Python!
Full show notes at https://talkpython.fm/episodes/show/288/10-tips-to-move-from-excel-to-python
Full show notes at https://pythonbytes.fm/episodes/show/205/this-is-going-to-be-a-little-bit-awkward
Full show notes at https://pythonbytes.fm/episodes/show/204/take-the-psf-survey-and-will-carlton-drop-by
We know our unit tests should be relatively independent from other parts of the system. For example, running a test shouldn't generally call a credit card possessing API and talk to a database when your goal is just to test the argument validation.
And yet, your method does all three of those and more. What do you do? Some languages use elaborate dependency passing frameworks that go under the banner of inversion of control (IoC) and dependency injections (DI). In Python, the most common fix is to temporarily redefine what those two functions do using patching and mocking.
On this episode, we welcome back Anna-Lena Pokes to talk us through the whole spectrum of test doubles, dummies, mocks, and more.
Full show notes at https://talkpython.fm/episodes/show/287/testing-without-dependencies-mocking-in-python
Full show notes at https://pythonbytes.fm/episodes/show/203/scripting-a-masterpiece-for-python-web-automation
NASA's Jet Propulsion Laboratory (JPL)'s primary function is the construction and operation of planetary robotic spacecraft, though it also conducts Earth-orbit and astronomy missions. It is also responsible for operating NASA's Deep Space Network.
On this episode, you'll meet Chris Mattman. He's the Division Manager for the Artificial Intelligence, Analytics and Innovation at NASA JPL and he's JPL's first Principal Scientist in the area of Data Science. We cover a wide range of topics, and dive into how Python and open-source are growing in the space exploration field. And he answers the question of whether he thinks we'll have Python running on robots and rovers in space.
Full show notes at https://talkpython.fm/episodes/show/286/python-and-ml-at-nasa-jet-propulsion-laboratory-jpl
If you're into data science, you've probably heard about Dask. It's a package that feels like familiar APIs such as Numpy, Pandas, and Scikit-Learn. Yet it can scale that computation across CPU cores on your local machine all the way to distributed grid-based computing in large clusters.
While powerful, this may take some serious setup to execute in its full glory. That's why Matthew Rocklin has teamed up with Hugo Bowne-Anderson and others to launch a business to help Python loving data scientists run Dask workloads in the cloud. And they are here to tell us about they open-source foundation business.
And they must be on to something, between recording and releasing this episode, they raised $5M in VC funding.
Get the full story at https://talkpython.fm/episodes/show/285/dask-as-a-platform-service-with-coiled
As Python 3 has eclipsed the old constrains of Python 2 and web frameworks that adopted them, we have seen a big jump in new frameworks appearing on the scene taking full advantage of things like type hints, async and await, and more.
No framework has done this more successfully than FastAPI recently. That's why we are here with the creator of FastAPI, Sebastián Ramírez to dive into this exciting new Python web framework.
Full show notes at https://talkpython.fm/episodes/show/284/modern-and-fast-apis-with-fastapi
Full show notes at https://pythonbytes.fm/episodes/show/201/understand-git-by-rebuilding-it-in-python
Full show notes at https://pythonbytes.fm/episodes/show/200/no-dog-piling-please-it-s-episode-200
Web scraping is pulling the HTML of a website down and parsing useful data out of it. The use-cases for this type of functionality are endless. Have a bunch of data on governmental sites that are only listed online in HTML without a download? There's an API for that! Do you want to keep abreast of what your competitors are featuring on their site? There's an API for that. Need alerts for changes on a website, for example enrollment is now open at your college and you want to be first to get in and avoid the 8am Monday morning course slot? There's an API for that.
That API is screen scraping and Attila Tóth from ScrapingHub is here to tell us all about it.
Full show notes at https://talkpython.fm/episodes/show/283/web-scraping-the-2020-edition
Git hook scripts are useful for identifying simple issues before committing your code. Hooks run on every commit to automatically point out issues in code such as trailing whitespace and debug statements. By pointing these issues out before code review, this allows a code reviewer to focus on the architecture of a change while not wasting time with trivial style nitpicks.
As we created more libraries and projects we recognized that sharing our pre-commit hooks across projects is painful. That's why I'm happy to welcome Anthony Sottile to the show to discuss pre-commit, a framework for managing and maintaining multi-language pre-commit hooks.
Full show notes at https://talkpython.fm/episodes/show/282/pre-commit-framework
Full show notes at https://pythonbytes.fm/episodes/show/199/big-news-for-a-very-small-python-runtime
Full show notes at https://pythonbytes.fm/episodes/show/198/there-s-a-beaver-in-your-database-and-anna-lena-drops-by
I love to bring you stories of Python being used in amazing places outside the traditional tech silos of pure web development and data science.
On this episode, you'll meet Robert "Kane" Replogle, who works on the simulation and test software at Richard Childress Racing. The NASCAR team that just finished #1 and 2 in at the Texas Motor Speedway.
You'll hear how Python is allowing them to model car behavior, air flow, and more much faster than others using outdated tools.
https://talkpython.fm/episodes/show/281/python-in-car-racing
If there has ever been a time in history that journalism is needed to shine a light on what's happening in the world, it's now. Would it surprise you to hear that Python and machine learning are playing an increasingly important role in discovering and bringing us the news? On this episode, you'll meet Carolyn Stansky, a journalist and developer who's been researching this intersection.
Full show notes at https://talkpython.fm/episodes/show/280/python-and-ai-in-journalism
Full show notes at https://pythonbytes.fm/episodes/show/197/structured-concurrency-in-python
Python is quick and easy to learn. And yet, there is a massive gap between knowing the common aspects of the language (loops, variables, functions, and so on) and how to write a well-factored application using modern tools and libraries. That's where learning Python is a never-ending journey.
Sebastian Witowski is here to give us his take on a modern Python developer's toolkit. There are a bunch of great tips in store for us.
Full show notes at https://talkpython.fm/episodes/show/279/modern-python-developers-toolkit
If there is one message I've been pushing across all of the Talk Python episodes, it's that programming is a super power. Rather than all of us abandoning what we're interested in and becoming CS majors, we can take our passion or expertise and 10x it with a little programming skill.
In that case, we should be teaching kids fluency in programming at a younger age. And yet, almost every platform or example meant to do so pulls its punches. We'll teach kids programming concepts but not code itself. That's a bridge too far.
But it's not! That's why I'm excited about Code Combat. It's an online coding platform that uses real Python syntax to guide your hero, visually, through a dungeon full of challenges. Yet the editor and customzied error messages mean this is approachable for kids before they can even type reliably.
On this episode, we'll meet Nick Winter, one of the cofounders of Code Combat. There's a lot of philophy behind the tool and technology to make it kid-friend and real Python at the same time.
Oh, and it's running Python in the browser.
Full episode page at https://talkpython.fm/episodes/show/278/teach-kids-python-with-real-programming-and-fun-games-at-code-combat
Full show notes at https://pythonbytes.fm/episodes/show/195/runtime-type-checking-for-python-type-hints
Full show notes at https://pythonbytes.fm/episodes/show/194/events-and-callbacks-in-the-python-language
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
Full show notes at https://pythonbytes.fm/episodes/show/193/break-out-the-django-testing-toolbox
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 second GeekOut episode. Last time we geeked out about the real science and progress around a moon base. This time it's why is there life on Earth, where could it be or have been in the solar system, and beyond.
In case you didn't catch the first GeekOut, episode 253, this one is more of a general science and tech episode. I love digging into the deep internals of all the tools of the Python space, but given all that is going on in the world, I thought it'd be fun to take a step back and just enjoy some fun geekery and give you all something to just sit back and let your mind dream.
Full show notes at https://talkpython.fm/episodes/show/276/geekout-life-in-the-solar-system-and-beyond
Full show notes at https://pythonbytes.fm/episodes/show/192/calculations-by-hand-but-in-the-compter-with-handcalcs
Do you obsess about writing your code just the right way before you get started? Maybe you have some ugly code on your hands and you need to make it better. Either way, refactoring could be your ticket to happier days! On this episode, we'll talk through a powerful example of iteratively refactoring some code until we eventually turn our ugly duckly into a Pythonic beauty.
Conor Hoekstra is our guest on this episode to talk us through refactoring some web scraping code.
Full show notes at https://talkpython.fm/275
Do you write data science code? Do you struggle loading large amounts of data or wonder what parts of your code use the maximum amount of memory? Maybe you just want to require smaller compute resources (servers, RAM, and so on).
If so, this episode is for you. We have Itamar Turner-Trauring, creator of the Python data science memory profiler FIL here to talk memory usage and data science.
Full show notes at https://talkpython.fm/episodes/show/274/profiling-data-science-code-with-fil
Full show notes at https://pythonbytes.fm/episodes/show/191/live-from-the-manning-python-conference
Everyone in the Python space is familiar with Notebooks these days. One of the original notebook environments was SageMath. Created by William Stein, and collaborators, it began as an open-source, Python-based, computational environment focused on mathematicians.
It has since grown into a full-blown company and has become a proper collaborative environment for things like Jupyter notebooks, Linux-backed Bash shells, and much more. Think Google Docs but across all these facets of development in your browser.
We welcome back William Stein to give us an update on his journey from professor to entrepreneur building CoCalc along the way.
Full show notes at https://talkpython.fm/episodes/show/273/cocalc-a-fully-colloborative-notebook-development-environment
Full show notes at https://pythonbytes.fm/episodes/show/190/you-will-now-be-notified-if-the-python-zipper-is-broken
Python is one of the primary languages for IoT devices. With runtimes such as CircuitPython and MicroPython, they are ideal for the really small IoT chips.
Maybe you've heard of the Circuit Playground Express, BBC micro:bit, or the fancy Adafruit CLUE. They aren't too expensive (ranging from $25 to $50 each). But for large groups such as classrooms, this can be a lot of money. Moreover, getting your hands on these devices can sometimes be tricky as well.
With an extension for VS Code called Device simulator express, you can have instant access to all three (virtually of course). This cool extension adds a visual emulator as well as the native interactions such as buttons and temperature sensors.
Get your IoT on without a real device using VS code today.
Full show notes at https://talkpython.fm/episodes/show/272/no-iot-things-in-hand-simulate-them-with-device-simulator-express
Full show notes at https://pythonbytes.fm/episodes/show/189/what-does-str.strip-do-are-you-sure
Time is a simple thing, right? And working with it in Python is great. You just import datetime and then (somewhat oddly) use the datetime class from that module.
Oh except, there are times with timezones, and times without. And why is there a total_seconds() but not total_minutes(), hours() or days() on timedelta? How about computing the number of weeks?
What if you wanted to iterate over the next 22 workdays, skipping weekends?
Ok, we'd better talk about time in Python! Good thing Paul Ganssle is here. He's a core developer who controls time in CPython.
Full show notes at https://talkpython.fm/episodes/show/271/unlock-the-mysteries-of-time-pythons-datetime-that-is
Full show notes at https://pythonbytes.fm/episodes/show/188/will-the-be-a-switch-in-python-the-language
Full show notes at https://pythonbytes.fm/episodes/show/187/ready-to-find-out-if-you-re-git-famous
On this episode, we are going to weave a thread through three different areas of Python programming that at first seem unlikely to have much in common. Yet, the core will be the same throughout. I think this is a cool lesson to learn as you get deeper into programming and a great story to highlight it.
We are going to meet Ravin Kumar who wrote Python code and data science tooling for oil rig tool manufacturer, a rocket company, and a hip multilocation restaurant chain.
Full show notes at https://talkpython.fm/episodes/show/270/python-in-supply-chains-oil-rigs-rockets-and-lettuce
Are you using interactive notebooks for your data exploration or day-to-day programming? What environment do you use? Was it Jupyter and now you've made the move to JupyterLab? That's a great choice. But did you know there are more environments out there to choose from and compare? Have you heard of Callisto or Iodide? How about CoCalc or PolyNote? That's just the tip of the iceberg!
That's why I'm happy to have Sam Lau and Philip Guo here to share their research comparing and categorizing over 60 notebook environments.
Full show notes at https://talkpython.fm/episodes/show/268/analyzing-dozens-of-notebook-environments
Do you write tests for your code? You probably should. And most of the time, pytest is the industry standard these days. But pytest can be much more than what you get from just installing it as a tool.
There are many amazing plugins that improve pytest in many aspects. That's why I invited Brian Okken to the show to tell us about his favorites. Listen in and your Python testing will be faster, stronger, and more beautiful!
Full show notes at https://talkpython.fm/episodes/show/267/15-amazing-pytest-plugins
Refactoring your code is a fundamental step on the path to professional and maintainable software. We rarely have the perfect picture of what we need to build when we start writing code and attempts to over plan and overdesign software often lead to analysis paralysis rather than ideal outcomes.
Join me as I discuss refactoring with Brendan Maginnis and Nick Thapen as well as their tool, Sourcery, to automate refactoring in the popular Python editors.
Full show notes at https://talkpython.fm/episodes/show/266/refactoring-your-code-like-magic-with-sourcery
Full show notes at https://pythonbytes.fm/episodes/show/183/need-a-beautiful-database-editor-look-to-the-bees
The debate about whether Python is fast or slow is never-ending. It depends on what you're optimizing for: Server CPU consumption? Developer time? Maintainability? There are many factors. But if we keep our eye on pure computational speed in the Python layer, then yes, Python is slow.
In this episode, we invite Anthony Shaw back on the show. He's here to dig into the reasons Python is computationally slower than many of its peer languages and technologies such as C++ and JavaScript.
See the full show notes at https://talkpython.fm/episodes/show/265/why-is-python-slow
Full show notes at details at https://pythonbytes.fm/episodes/show/181/it-s-time-to-interrogate-your-python-code
Are you a web developer who uses Flask? It has become the most popular Python web framework. Even if you have used it for years, I bet we cover at least one thing that will surprise you and make your Flask code better.
Join me as I speak with Miguel Grinberg about his top 10 list for tips and tricks in the Flask world. They're great!
Full show notes at https://talkpython.fm/episodes/show/264/10-tips-every-flask-developer-should-know
Full show notes at https://pythonbytes.fm/episodes/show/180/transactional-file-io-with-python-and-safer
As developers and technologists, it's easy to think that powerful and unique ideas will percolate to the top. If we build something amazing, enthusiastic users will find and share our creations.
Sometimes this happens. But more often, success is an iceberg, on so many levels. We are going to look at one of those icebergs on this episode. Join me and Cristian Medina as we discuss SEO, search engine optimization, for developers. Some of your search ranking is out of your control, but as you will see, there are many tools in the developer's toolbox that will directly affect your search rank. Let's dive in!
https://talkpython.fm/episodes/show/263/seo-for-developers
Full show notes at https://pythonbytes.fm/episodes/show/179/guido-van-rossum-drops-in-on-python-bytes
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
Traditionally, when we have depended upon software to make a decision with real-world implications, that software was deterministic. It had some inputs, a few if statements, and we could point to the exact line of code where the decision was made. And the same inputs lead to the same decisions.
Nowadays, with the rise of machine learning and neural networks, this is much more blurry. How did the model decide? Has the model and inputs drifted apart, so the decisions are outside what it was designed for?
These are just some of the questions discussed with our guest, Andrew Clark, on this episode of Talk Python To Me.
Full show notes at https://talkpython.fm/episodes/show/261/monitoring-and-auditing-machine-learning
Full show notes at https://pythonbytes.fm/episodes/show/178/build-a-pypi-package-from-a-jupyter-notebook
If you work on the data science or data visualization side of Python, you may have come to it from a scripting side of things. Writing just a little Python, using its magical libraries, with little structure or formalism to build a powerful analysis tool that runs in the terminal or maybe a jupyter notebook.
What if you could take that same code, sprinkle in just a bit of a simple API, and turn it into a fast and dynamic single page application allowing your users to dive into the visualizations on the web?
Well, that's basically what the folks over at Streamlit created! We'll dive into it with one of the creators, Adrien Treuille.
Full show notes over at https://talkpython.fm/episodes/show/260/from-basic-script-to-interactive-data-sci-app-with-streamlit
Full show notes at https://pythonbytes.fm/episodes/show/177/coding-is-90-google-searching-or-is-it
Did you come to Python from the academic side of the world? Maybe got into working with code for research or lab work and found you liked coding more than your first field of study. Whatever the reason, many people make the transition from the academic world over to tech and industry.
On this episode, you'll meet three women who have made this transition, and you'll hear their stories. I'm excited to speak with Jennifer Stark, Kaylea Haynes, and Eslene Bikoumou about their journey to the tech field.
Check out the episode at https://talkpython.fm/episodes/show/259/from-academia-to-tech-industry-and-python
Full show notes at https://pythonbytes.fm/episodes/show/176/how-python-implements-super-long-integers
If you are listening to this episode when it came out, April 4th, 2020, there's a good chance you are listening at home, or on a walk. But it's probably not while commuting to an office as much of the world is practicing social distancing and working from home. Maybe this is a new experience, brought upon quickly by the global lockdowns, or maybe it's something you've been doing for awhile.
Either way, being effective while working remotely, away from the office, is an increasingly valuable skill that most of us in the tech industry have to quickly embrace.
On this episode, I'll exchange stories about working from home with Jayson Phillips. He's been writing code and managing a team from his home office for years and has brought a ton of great tips to share with us all.
https://talkpython.fm/episodes/show/258/thriving-in-a-remote-developer-environment
Full show notes at https://pythonbytes.fm/episodes/show/175/python-string-theory-with-superstring.py
With radio astronomy, we can look across many light-years of distance and see incredible details such as the chemical makeup of a given region. Kevin Vinsen and Rodrigo Tobar from ICRAR are using the world's fastest supercomputer along with some sweet Python to process the equivalent of 1,600 hours of standard-definition YouTube video per second.
Full show notes at https://talkpython.fm/episodes/show/257/exploring-the-galaxy-with-the-fastest-supercomputer-python-and-radio-astronomy
Full show notes at https://pythonbytes.fm/episodes/show/174/happy-developers-use-python-3
Have you come across a GitHub repo with a Jupyter notebook that has a "Run in Binder" button? It seems magical. How does it know what dependencies and external libraries you might need? Where does it run anyway?
Like all technology, it's not magic. It's the result of hard work by the people behind mybinder.org. On this episode, you'll meet Tim Head, who has been working to bring Binder to us all. Take a look inside mybinder.org, how it works, and the history of the project.
Check out the episode at https://talkpython.fm/episodes/show/256/click-to-run-your-notebook-with-binder
Full show notes at https://pythonbytes.fm/episodes/show/173/you-test-deserves-a-fluent-flavor
Modern cars have become mobile computer systems with many small computers running millions of lines of code. On this episode, we plug a little Python into those data streams.
You'll meet Shea Newton, who is a Python developer who has worked on autonomous cars and is currently at ActiveState.
Full show notes at https://talkpython.fm/episodes/show/255/talking-to-cars-with-python
Full show notes at https://pythonbytes.fm/episodes/show/172/floating-high-above-the-web-with-helium
How do you go from poking around at Python code to actually solving real problems, the right way?
There are many paths. The longest one probably is to get a 4-year CS degree. Maybe faster, but pricy as well, is a solid in-person developer bootcamp.
Have you considered reaching out to the community to find a mentor? Many Python meetups have project nights where folks who could help will be attending. If you're up for giving back, maybe you could become a mentor too.
That's what this episode is about. We'll hear from two former guests of Talk Python, Rusti Gregory and Doug Farrell. They teamed up and are back to share their mentorship story!
Full show notes at https://talkpython.fm/episodes/show/254/a-python-mentorship-story
Full show notes at https://pythonbytes.fm/episodes/show/171/chilled-out-python-decorators-with-pep-614
This episode is a unique one. On this episode, I've invited Richard Campbell and developer and podcaster who also dives deep into science and tech topics. We are going to dig into his geekout series and spend some time talking realistically about moonbases and space travel.
I think you're really going to enjoy the conversation. But I would love to hear, either way, if you like this minor diversion from pure Python topics (although we do talk some Python and programming). We can do more like this in the future if you all enjoy listening to these as much as I enjoyed making them.
Full show notes at https://talkpython.fm/episodes/show/253/moon-base-geekout
Full show notes at https://pythonbytes.fm/episodes/show/170/visualize-this-visualizing-python-s-visualization-ecosystem
Did you come into Python from a computational science side of things? Were you just looking for something better than Excel or Matlab and got pulled in by all the Python has to offer?
That's great! But following that path often means some of the more formal practices from software development weren't part of the journey.
On this episode, you'll meet Martin Héroux, who does data science in the context of academic research. He's here to share his best practices and lessons for data scientists of all sorts.
Full show notes at https://talkpython.fm/episodes/show/252/what-scientific-computing-can-learn-from-cs
Full show notes at https://pythonbytes.fm/episodes/show/169/jupyter-notebooks-natively-on-your-ipad
What does it take to build a Python library that will be used by a large number of developers? This happens all the in open source. Projects take off and become wildly successful.
What if you could sit down with developers using your library and see how they take to it? Well, over on the Azure team, Kate Olszewska and Johan Stenberg do incredible user testing for Azure's Python SDK.
Just to give you a taste, imagine a room with a computer, a couple of developers unfamiliar with the API, a one-way mirror, and lots of feedback.
See the show at https://talkpython.fm/episodes/show/251/building-and-ux-testing-azure-s-python-sdk
Full show notes at https://pythonbytes.fm/episodes/show/168/race-your-donkey-car-with-python
As the popularity of Python grows, we see it popping up in all sorts of interesting places and projects. On this episode, you'll meet C.K. Sample and Nathan Papapietro from HyperGiant. They are using Python and AI to develop the EOS Bioreactor.
This is a fridge sized box containing water and algae which sequesters a huge amount of C02, as much as 400x as much as an acre of trees.
Let's dive into how they are using Python for this cutting-edge project.
Full show notes at https://talkpython.fm/episodes/show/250/capture-over-400x-c02-as-trees-with-ai-and-python
Full show notes at https://pythonbytes.fm/episodes/show/167/cheating-at-kaggle-and-uwsgi-in-prod
Are you learning or helping someone else learn Python, why not make a game out of it? TwilioQuest is a game that doesn't treat you with kid-gloves while teaching you Python. Using your editor of choice, write code on your machine, and still play the game to solve Python challenges.
In this episode, you'll meet Kevin Whinnery and Ryan Kubik from Twilio, who created TwiloQuest. They are here to tell us all about it.
Full details at https://talkpython.fm/episodes/show/249/capture-the-staff-of-pythonic-knowledge-in-twilioquest
Full show notes at https://pythonbytes.fm/episodes/show/166/misunderstanding-software-clocks-and-time
The most critical issue of our time is climate change. Yet, when you think about our carbon impact in the software industry, what comes to mind? Business travel? Commuting to the office so you don't miss filing that TPS report? Yeah, those are bad. But data centers, servers, and our apps consume a substantial portion of the total energy used by modern humans.
In this episode, you'll meet Chris Adams. He has been advocating for a greener software environment and has concrete advice to make your Python program more climate-friendly.
The good news is, generally speaking, what we need to do to make our code easier on the planet is the same things we do to make our code faster!
Full show notes at https://talkpython.fm/episodes/show/248/climate-change-and-your-python-code
Full show notes at https://pythonbytes.fm/episodes/show/165/ranges-as-dictionary-keys-oh-my
Do you run an open-source project? Does it seem like you never have enough time to support it? Have you considered starting one but are unsure you can commit to it? It's a real challenge.
On this episode, we welcome back Philip Guo, who has been a solo maintainer of the very popular PythonTutor.com project for over 10 years. He has some non-traditional advice to keep your sanity and keep your project going while holding down a busy full-time job.
Full show notes at https://talkpython.fm/episodes/show/247/solo-maintainer-of-open-source-in-academia
Full show notes at https://pythonbytes.fm/episodes/show/164/use-type-hints-to-build-your-next-cli-app
When you can call yourself a professional developer? Sure, getting paid to write code is probably part of the formula. But when is your skillset up to that level?
Many folks in the industry suffer from imposter syndrome and other types of uncertainty. Yet, there are real techniques and skills you should know before you meet this bar.
Dane Hillard is here to share his take on the practices of the Python pro. We'll discuss concrete steps and abstract design concepts to help your code make the jump to pro level.
Full show notes at https://talkpython.fm/episodes/show/246/practices-of-the-python-pro
Full show notes at https://pythonbytes.fm/episodes/show/163/meditations-on-the-zen-of-python
Full show notes at https://pythonbytes.fm/episodes/show/162/retrofitting-async-and-await-into-django
Python is growing incredibly quickly and has found its place in many facets of the developer and computational space. But one area that is still shaky and uncertain is packaging and shipping software to users.
I'm not talking about building reusable libraries and hosting them on PyPI. I'm talking about shipping executable software to non-developers.
Take a moment to stop and think about what ways you would send an end-user a program built with Python that they can simply run. It's a bit of a mixed bag, isn't it?
On this episode, we welcome back Cristian Medina to run through the state if Python packaging.
Full show notes at https://talkpython.fm/episodes/show/245/python-packaging-landscape-in-2020
We've come to the end of 2019. Python 2 has just a handful of days before it goes unsupported. And I've met up with Dan Bader from RealPython.com to look back at the year of Python articles on his website. We dive into the details behind 10 of his most important articles from the past year.
Full show notes at https://talkpython.fm/episodes/show/244/top-10-real-python-articles-of-2019
Full show notes at https://pythonbytes.fm/episodes/show/161/sloppy-python-can-mean-fast-answers
We all love the Python language. But it's the 200,000+ packages that actually make Python incredibly useful and productive. But installing these libraries and sometimes even Python itself can vary across platforms. In particular, Windows has had a hard time. Many of the library authors don't use Windows and so don't test their packages on that platform. Tutorial authors often start their tutorial steps by activating a virtual environment with $ source venv/bin/activate. This, of course, doesn't work on Windows. Yet, over 50% of all developers programming in Python do so on Windows.
In this episode, you'll meet Steve Dower. He works at Microsoft and is a Python core developer. He has a bunch of stats for us. But he also has tons of good news on how Python on Windows is getting much better.
Full show notes at https://talkpython.fm/episodes/show/243/python-on-windows-is-ok-actually
Full show notes at https://pythonbytes.fm/episodes/show/160/your-json-shall-be-streamed
Online education has certainly gone mainstream. Developers and companies have finally gotten comfortable taking online courses. Sometimes these are recorded, self-paced courses like we have at Talk Python Training. Other times, they are more like live events in webcast format.
In this episode, you'll meet two guys who are taking the interactivity of online learning up a notch. Brian Clark and Cecil Philip run a weekly event on Twitch where they are live-streaming an interactive Python course. They take questions from 100's of students and dig into the diversions more mainstream online learning simply cannot.
Full show notes at https://talkpython.fm/episodes/show/242/your-education-will-be-live-streamed
Open source has permeated much of the software industry. What about health care? This highly regulated and important industry might seem to be the domain of huge specialized software companies.
On this episode, Fred Kingham is here to introduce us to a project called OPAL. It was born out of NHS Hack Days in the UK and is a full-stack web framework for building health care applications. It's based on Django and has a ton of interesting features as a framework in general.
Full show notes at https://talkpython.fm/episodes/show/241/opal-full-stack-health-care-apps
Full show notes at https://pythonbytes.fm/episodes/show/159/brian-s-pr-is-merged-the-src-will-flow
You might use Python every day. But how much do you know about what happens under the covers, down at the C level? When you type something like variable = [], what are the byte-codes that accomplish this? How about the class backing the list itself?
All of these details live at the C-layer of CPython. On this episode, you'll meet Anthony Shaw. He and I take a guided tour of the CPython source code. After this, you won't have to guess what's happening. You can git-clone the CPython source code and see for yourself.
Full show notes at https://talkpython.fm/episodes/show/240/a-guided-tour-of-the-cpython-source-code
Full show notes at https://pythonbytes.fm/episodes/show/158/there-s-a-bounty-on-your-open-source-bugs
In this episode, we'll dive into one of the foundations of modern data science, Bayesian algorithms, and thinking. Join me along with guest Max Sklar as we look at the algorithmic side of data science.
Full show notes at https://talkpython.fm/episodes/show/239/bayesian-foundations
Collaborative data science has a few challenges. First of all, those who you are collaborating with might not be savvy enough in the computer science techniques (for example, git and source control or docker and Linux). Second, seeing the work and changes others have made is a challenge too.
That's why Dean Kleissas and his cofounders created Gigantum. It's a platform that runs either locally or in the cloud, spins up data science environments into docker containers seamlessly, and sync collaborative updates from machine to machine.
Full show notes at https://talkpython.fm/episodes/show/238/collaborative-data-science-with-gigantum
Let's start with a philosophical question: Are you human? Are you sure? We could begin to answer the question physically. Are you made up of cells that would typically be considered as belonging to the human body?
It turns out we have many ecosystems within us. Understanding them is important to our own wellbeing. In this episode, you'll meet Sebastian Proost, who is using Python to study bacteria in our world.
Full show notes at https://talkpython.fm/episodes/show/237/a-gut-feeling-about-python
Do you do data science? Imagine you work with over 200 data scientists. Many of whom have diverse backgrounds or have come from non-CS backgrounds. Some of them want to use Python. Others are keen to work with R.
Your job is to level the playing field across these experts through technical education and build libraries and tooling that are useful both in Python and R.
It sounds like a fun challenge, doesn't it? That's what Ethan Swan and Bradley Boehmke are up to. And they are here to give us a look inside their world!
Full show notes at https://talkpython.fm/episodes/show/236/scaling-data-science-across-python-and-r
Full show notes at https://pythonbytes.fm/episodes/show/154/code-frozen-in-carbon-on-display-for-all
Do you dream of a day when you can write Python in the browser rather than JavaScript? This is no pipe dream! There are several ways to write Python that runs in the browser already.
One of the leaders here is Skulpt. It's not just an experiment but real, powerful web applications with rich client-side code, Python code, are out in the wild and built with Skulpt.
We dig into it with Meredydd Luff and Albert-Jan Nijburg on this episode.
Full show notes at https://talkpython.fm/episodes/show/235/python-in-your-browser-with-skulpt
Full show notes at https://pythonbytes.fm/episodes/show/153/auto-format-my-python-please
Have you heard of awesome lists? They are well, pretty awesome! Gathering up the most loved libraries and packages for a given topic.
While most lists cover awesome developer tools and libraries, we don't have many examples of awesome applications both for use and for examples to draw from.
That's why Mahmoud Hashemi decided to create Awesome Python Applications, and you're about to dive headfirst into them!
Full show notes at https://talkpython.fm/episodes/show/234/awesome-python-applications
Full show notes at https://pythonbytes.fm/episodes/show/152/you-have-35-million-lines-of-python-2-now-what
Folks, it's not like the old days where there were just a couple of web frameworks for building apps with Python. These days there are many. One of those frameworks is the Masonite web framework created by Joseph Mancuso. Joseph is here today to tell us all about Masonite, what makes it special, it's core value proposition for web developers and much more.
Full show notes at https://talkpython.fm/episodes/show/233/the-masonite-python-web-framework
Full show notes at https://pythonbytes.fm/episodes/show/151/certified-it-works-on-my-machine
Full show notes at https://pythonbytes.fm/episodes/show/150/winning-the-python-software-interview
When you think about the types of jobs you get as a Python developer, you probably weight the differences between data science and web development.
But did you consider programming robots in Python? And not just toys, but serious, productive machines. It turns out there is a gap in the industry where we could use more Python developers in robotics.
That's why I'm happy to have Ricardo Tellez here to give us an overview of the software development side of robotics programming with Python.
Full show notes at https://talkpython.fm/episodes/show/232/become-a-robot-developer-with-python
Full show notes at https://pythonbytes.fm/episodes/show/149/python-s-small-object-allocator-and-other-memory-features
Have you ever wanted to get into consulting? Maybe you're seeking the freedom to work on whatever project you'd like or gain more control of your time.
Many folks see consulting and freelancing as the next step in their career. But what do they need to put in place first? What challenges might come their way they won't see coming?
Join me as I speak with Reuven Lerner and Casey Kinsen, two successful software freelances about their journey and their advice.
Check out the full show notes at https://talkpython.fm/episodes/show/231/advice-for-freelancing-with-python
Full show notes at https://pythonbytes.fm/episodes/show/148/the-asgi-revolution-is-upon-us
You've often heard me talk about Python as a superpower. It can amplify whatever you're interested in or what you have specialized in for your career.
This episode is an amazing example of this. You'll meet Cornelis van Lit. He is a scholar of medieval Islamic philosophy and woks at Utrecht University in the Netherlands. What he is doing with Python is pretty amazing.
Even if you aren't interested in digital humanities and that type of research, the example set by Cornelis is a blueprint for bringing Python into your world and for those around you. I think you'll enjoy this conversion.
Full show notes at https://talkpython.fm/episodes/show/230/python-in-digital-humanities-research
On this episode, we dive into Python for lawyers and a special tool for conducting legal interviews. Imagine you have to collect details for 20,000 participants in a class-action lawsuit. docassemble, a sweet Python web app, can do it for you with easy.
Now, you may be thinking, I'm not a lawyer so this isn't for me. Hang on for a sec. docassemble is actually a general-purpose tool. If you've ever done anything with a site like survey monkey or Google forms, you could do something more advanced with docassemble.
Join me as I talk with Jonathan Pyle, creator and maintainer of docassemble.
Full show notes at https://talkpython.fm/episodes/show/229/building-advanced-pythonic-interviews-with-docassemble
Full show notes at https://pythonbytes.fm/episodes/show/146/slay-the-dragon-learn-the-python
What's it's like building a startup with Python and going through a tech accelerator? You're about to find out. On this episode, you'll meet Elissa Shevinsky from Faster Than Light. They are building a static code analysis as a service business for Python and other code bases. We touch on a bunch of fun topics including static code analysis, entrepreneurship, and tech accelerators.
Full show notes at https://talkpython.fm/episodes/show/228/hunting-bugs-and-tech-startups-with-python
Did you come to software development outside of traditional computer science? This is common, and even how I got into programming myself. I think it's especially true for data science and scientific computing. That's why I'm thrilled to bring you an episode with Daniel Chen about maintainable data science tips and techniques.
Full show notes at https://talkpython.fm/episodes/show/227/maintainable-data-science-tips-for-non-developers
If you're a data scientist, how do you deliver your analysis and your models to the people who need them? A really good option is to serve them over Flask as an API. But there are some special considerations you might keep in mind. How should you structure this API? What type of project structures work best for data science and Flask web apps? That and much more on this episode of Talk Python To Me with guest AJ Pryor.
Full show notes at https://talkpython.fm/episodes/show/226/building-flask-apis-for-data-scientists
Full show notes at https://pythonbytes.fm/episodes/show/144/are-you-mocking-me-it-won-t-work
Full show notes at https://pythonbytes.fm/episodes/show/143/spike-the-robot-powered-by-python
Have you heard that Python is not good for writing concurrent asynchronous code? This is generally a misconception. But there is one class of parallel computing that Python is not good at: CPU bound work running the Python layer.
What's the main problem? It's Python's GIL or Global Interpreter Lock of course. Yet, the fix for this restriction may have been hiding inside CPython since version 1.5: subinterpreters.
Join me to talk about PEP 554 with core developer Eric Snow.
Full show notes at https://talkpython.fm/episodes/show/225/can-subinterpreters-free-us-from-python-s-gil
Full show notes at https://pythonbytes.fm/episodes/show/142/there-s-a-bandit-in-the-python-space
Back in May of 2018, Bob Belderbos, Julian Sequeira, and I started on what would be a 9-month project. We wanted to create a dedicated, 100 days of code course specifically for Python web developers. Much of what we created for that course, we had prior experience with. But much of it was also new to us.
On this episode, we teamed up to distill the lessons, tips, and tools we found interesting on that journey into a quick list of cool tips and techniques. We hope you find some of them new and useful!
Full show notes at https://talkpython.fm/episodes/show/224/12-lessons-from-100-days-of-web
Do you have data you want to visualize and share? It's easy enough to make a static graph of it. But what if you want to zoom in and highlight different sections? What if you need to rerun your ML model on selected data? Then you might want to consider working with Bokeh. It does this and much more. Join me on this episode where you'll meet Bryan Van de Ven who heads up the Bokeh project.
Full show notes at https://talkpython.fm/episodes/show/222/interactive-graphs-with-bokeh-and-python
Full show notes at https://pythonbytes.fm/episodes/show/141/debugging-with-f-strings-coming-in-python-3.8
Do you have data you want to visualize and share? It's easy enough to make a static graph of it. But what if you want to zoom in and highlight different sections? What if you need to rerun your ML model on selected data? Then you might want to consider working with Bokeh. It does this and much more. Join me on this episode where you'll meet Bryan Van de Ven who heads up the Bokeh project.
Full show notes at https://talkpython.fm/episodes/show/222/interactive-graphs-with-bokeh-and-python
Full show notes at https://pythonbytes.fm/episodes/show/140/becoming-a-10x-developer-sorta
How do we get kids excited about programming? Make programming tangible with embedded devices. Did you know that after kids learned to code with the BBC micro:bit, 90% of kids "thought coding was for everyone" and 86% said it made CS topics more interesting?
One person doing great work in this space is Nina Zakharenko. She's here to tell us all about her projects with CircuitPython.
Full show notes at https://talkpython.fm/episodes/show/221/empowering-developers-by-embedding-python
On this episode, you'll meet Francesca Lazzeri and hear story how she went from Research Fellow in Economics at Harvard Business School to working on the AI and data science stack on the Azure team.
Full show notes at https://talkpython.fm/episodes/show/220/machine-learning-in-the-cloud-with-azure-ml
Full show notes at https://pythonbytes.fm/episodes/show/138/will-pyoxidizer-weld-shut-one-of-python-s-major-gaps
In the US, we have a very interesting civil option that is quite new: The United States Digital Service. This service was created by President Obama to fix broken government software systems such as the rocky start of the healthcare system.
Developers and designers can serve in this service for as little as 3 months or as long as 4 years and they pay roughly market rates.
It's an interesting model indeed! I'm excited to have David Holmes from the US Digital Service to talk about their projects and how they are using Python to make the government work for the people.
Full show notes at https://talkpython.fm/episodes/show/219/take-a-python-tour-of-duty-at-the-united-states-digital-service
Full show notes at https://pythonbytes.fm/episodes/show/137/advanced-python-testing-and-big-time-diffs
Full show notes at https://pythonbytes.fm/episodes/show/136/a-python-kernel-rather-than-cleaning-the-batteries
Do you have stateless code that needs to run in the cloud? The clear answer years ago was to create and HTTP, or even, gasp! A SOAP service before then. While HTTP services are still very important, some of this code can move entirely away from the framework that runs it with serverless programming and hosted functions.
On this episode, I meet up with Asavari Tayal to discuss serverless programming in the cloud.
Full show note at https://talkpython.fm/episodes/show/218/serverless-python-functions-in-azure
On this episode, I meet up with Rong Lu and Katherine Kampf from Microsoft while I was at BUILD this year. We cover a bunch of topics around data science and talk about two opposing styles of data science development and related tooling: Notebooks vs Python code files and editors.
The conversation was a lot of fun and I'm looking forward to sharing it with you all.
Full show notes at https://talkpython.fm/episodes/show/217/notebooks-vs-data-science-enabled-scripts
Full show notes at https://pythonbytes.fm/episodes/show/135/macos-deprecates-python-2-will-stop-shipping-it-eventually
One of the questions I often ask at the end of the show is "When you write some Python code, what editor do you use?" Increasingly the most common answer is Visual Studio Code. Despite it's Windows only namesake, Visual Studio Code is cross-platform and has been gaining a lot of traction.
I was at the Microsoft BUILD conference immediately after PyCon this May. There I got the chance to sit down with Dan Taylor from the VS Code team to discuss what they have been up to with VS Code and Python.
Full show notes at https://talkpython.fm/episodes/show/216/digging-into-visual-studio-code
Full show notes at https://pythonbytes.fm/episodes/show/134/python-proves-mercury-is-the-closest-planet-to-earth
How do you stay up on your Python skills. Many of us are self-starters and good at learning on our own or online with the video courses like the ones we have over at Talk Python. But sometimes, having everyone on your team go from zero to ready to work on a project is the best path. And that usually means in-person training.
This is something I did and enjoyed for many years. Our guest on this episode is Reuven Learner who does independent Python training. He's here to tell us how to make the most out of in-person training for your team and how you might get started in this side of software development yourself.
Full show notes at https://talkpython.fm/episodes/show/210/making-the-most-out-of-in-person-training
We all got a bit of a shock to the system when Guido van Rossum decided to step down as the leader and top decider of the Python language and CPython runtime. This happened due to many factors but was precipitated by the so-called walrus operator (PEP 572).
It's been about 9 months since then, the Python community has responded and things are back on track. I'm excited to welcome Brett Cannon to this episode to give us an update on where we are and how we got here. He's a frequent guest and Python core contributor and has the inside view of what happened.
Full show notes at https://talkpython.fm/episodes/show/209/inside-python-s-new-governance-model
Have you ever wondered about the software stack powering Talk Python, the training website, mobile apps, video and audio delivery, and more? While at first glance it might seem pretty simple, there's quite a bit going on. We have our own custom search engines. We deliver 15-20 TB of data per month. Our course video streams from 8 locations throughout the world. Our database server is sending about 12 MBit of traffic / sec with no media in the mix. And it's all powered with Python.
This week is a bit of a role swap. Dan Bader from Real Python is here to interview me about the Talk Python tech stack. But we also get a chance to compare my tech stack with Real Python's, a site which is becoming quite an important one for developers.
Full show notes at https://talkpython.fm/episodes/show/215/the-software-powering-talk-python-courses-and-podcast
Full show notes at https://pythonbytes.fm/episodes/show/133/github-sponsors-the-model-open-source-has-been-waiting-for
Python 3.8 is coming soon. It's scheduled for release at the end of October 2019 and you can already download test versions today. Given that Python ships on an 18-month cycle, it's time to talk about what's coming for us Python developers in the fall.
On this episode, I meet up with Łukasz Langa and Anthony Shaw to chat about the highlights of this upcoming version of Python.
Also, quick show note, we recorded this on-location in Cleveland at PyCon 2019. There may be a small amount of background noise, but I think you'll barely notice.
Full show notes at https://talkpython.fm/episodes/show/214/dive-into-cpython-3.8-and-beyond
On the last episode, we explored Pyodide. A project whose goal is to bring the CPython scientific stack to the browser via WebAssembly.
This time, I meet up with Brett Cannon, one of the more well-known and prolific core developers, to explore what role WebAssembly has for CPython in general and what opportunities exist for Python and WebAssembly at the moment.
Full show notes at https://talkpython.fm/episodes/show/213/webassembly-and-cpython
Full show notes at https://pythonbytes.fm/episodes/show/131/python-3-has-issues-over-on-github
It's been said that JavaScript is the assembly language of the web. But should you be should be required to write code in assembly language or JavaScript?
Most platforms have a dizzying array of options for programming them. But not the frontend web world. But that tide may be turning and WebAssembly could be the key to making it happen.
With WebAssembly, we have a new compilation target for web browsers. And Michael Droettboom from Mozilla and team have decided to help bring the Python scientific stack to the frontend world with Pyodide.
Full show notes at https://talkpython.fm/episodes/show/212/python-in-web-assembly-with-pyiodide
Many of you studied computer science at a University to get into programming and your careers. But I bet most of you came through some self-study or some sort of back door into the industry. I count myself among that crowd.
This is one of the true bright spots of our industry. That we can earn our way in without necessarily getting college degrees. But sometimes that academic formalism would come in handy. That's where David Kopec's book comes in super handy. It's an approachable and quick into to CS and that's our topic on this episode.
Full show notes at https://talkpython.fm/episodes/show/211/classic-cs-problems-in-python
Full show notes at https://pythonbytes.fm/episodes/show/129/maintaining-a-python-project-when-it-s-not-your-job
Full show notes at https://pythonbytes.fm/episodes/show/128/will-the-gil-be-obscure-with-pep-554
Are you going to PyCon (or a similar conference)? Join me and Kenneth Retiz as we discuss how to make the most of PyCon and what makes it special for each of us.
We also cover a buffet of other topics: packaging, pipenv, developing Python on Windows, async and await and more.
Full show notes at https://talkpython.fm/episodes/show/208/packaging-making-the-most-of-pycon-and-more
Full show notes at https://pythonbytes.fm/episodes/show/126/webassembly-comes-to-python
What if you could write standard numpy and pandas code but have it run on a distributed computing grid for incredible parallel processing right from Python? How about just splitting it across multiprocessing to escape the limitations of the GIL on your local machine? That's what Dask was built to do.
On this episode, you'll meet Matthew Rocklin to talk about its origins, use-cases, and a whole bunch of other interesting topics.
Full show notes at https://talkpython.fm/episodes/show/207/parallelizing-computation-with-dask
Full show notes at https://pythonbytes.fm/episodes/show/125/will-you-conquer-the-deadlock-empire
Let's talk about running Django in production. On this episode, you'll meet Michael Herman who used to work on realpython.com and today is running testdriven.io. We also cover some of the tradeoffs of a set of microservices and a monolith and a round trip journey between them.
Full show notes at https://talkpython.fm/episodes/show/206/running-django-in-production
Full show notes at https://pythonbytes.fm/episodes/show/124/this-is-not-the-none-you-re-looking-for
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
Remember back in math class when you would take a test? It wasn't enough to just write down the answer. What's the limit of this infinite summation? pi/2 Yes, but how did you get that number.
Some problems in programming are like this. We want to keep track of the computations done and only add more steps to the results. That's basically the entire premise of functional programming.
On this episode, you'll meet Christopher Ariza who created a project called StaticFrame. Think Pandas and NumPy, but it never changes computation it's already performed.
Full show notes at https://talkpython.fm/episodes/show/204/staticframe-like-pandas-but-safer
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
One core question around open source is how do you fund it? Well, there is always that PayPal donate button. But that's been a tremendous failure for many projects. Often the go-to answer is consulting.
But what if you don't want to trade time for money? You could take things up a notch and change the equation, exchanging value for money. That's what Ines Montani and her co-founder did when they started Explosion.ai with SpaCY as the foundation.
Listen to her story about building a sustainable software business on open source and Python.
Full show notes at https://talkpython.fm/episodes/show/202/building-a-software-business
Full show notes at https://pythonbytes.fm/episodes/show/120/aws-mongodb-and-the-economic-realities-of-open-source-and-more
The Nobel prize in economics recently went to Paul Romer, a convert from proprietary software like Matlab over to Python and the SciPy stack. Paul said, “The more I learn about proprietary software, the more I worry that objective truth might perish from the earth.”
That's quite the statement. But what if your organization is deeply committed to proprietary software such as Matlab? Don't despair because Peter Kazarinoff, a professor at Portland Community College is here to share his experience converting his courses over to Python and JupyterHub.
Full show notes at https://talkpython.fm/episodes/show/201/choosing-jupyterhub-and-python-over-matlab
Full show notes at https://pythonbytes.fm/episodes/show/119/assorted-files-as-django-orm-backends-with-alkali
Do you know or maybe work with people who abuse Excel? Is it their hammer to pound all the computational problems that get in their way? Well, join me to chat about this opportunity to bring Python deeper into their lives. You'll meet Chris Moffitt who runs Practical Business Python. He works with lots of folks who could make better use of Python to solve their business problems and he has a ton of material on his website. It's time to escape Excel hell with Python and Pandas.
Full show notes at https://talkpython.fm/episodes/show/200/escaping-excel-hell-with-python-and-pandas
Do your applications call a lot of APIs? Maybe you have a bunch of microservices driving your app. You probably don't have the crazy combinatorial explosion that Zapier does for connecting APIs! They have millions of users automating things with 1,000s of APIs. It's pretty crazy. And they are doing it all with Python. Join me and Bryan Helmig, the CTO and co-founder of Zapier as we discuss how they pull this off with Python.
Full show notes at https://talkpython.fm/episodes/show/199/automate-all-the-things-with-python-at-zapier
It's time to catch up with the Anaconda crew and see what's new in the Anaconda distribution. This edition of Python was created to solve some of the stickier problems of deployment, especially in the data science space. Their usage gives them deep insight into how Python is being used in the enterprise space as well. Which turns out to be a very interesting part of the conversation.
Full show notes at https://talkpython.fm/episodes/show/198/catching-up-with-the-anaconda-distribution
A recent twitter poll went around the web and it asked, what percentage of the Python standard library do you think you know? Someone copied me on it, maybe expecting some really high percentage answer. In reality, what I did answer and my rough estimate is that it's probably around 50%.
This episode with Alessandro Molina definitely helped confirm that experience for me. He just published a book entitled "Modern Python Standard Library Cookbook" and it's full of these great little corners of the standard library that you might not have bumped into but you'll be super glad to hear about on this episode!
Full show notes at https://talkpython.fm/197
If you are doing any sort of data exploration, you've likely heard about Jupyter notebooks. In fact, there are quite a few options for running and hosting your Jupyter notebooks. You may have heard me rave about PyCharm as an editor too. Well, on this episode, you'll meet Adam Hood from the Datalore team at JetBrains. That's a new project that tries to bring some of the power of PyCharm to notebooks and more.
Full show notes at https://talkpython.fm/196
When you think of learning Python, what type of developer or technologist comes to mind? Is it someone looking to get their first job or maybe moving from .NET to Python and looking for a shift in their careers?
While these are common moves, you may be surprised how many folks within a tech company learn new languages like Python to stay within that company. On this episode, you'll meet Ron Hayden. He founded the Software University internal training program at Apple and is now doing his own independent training around Python.
I think you'll find his story an interesting element in the mosaic of Python.
Full show notes at https://talkpython.fm/195
How do you learn programming when you're working in a vacuum? Sure there are resources on the internet, but sometimes just bouncing ideas of others in person makes a huge difference. Join me along with Rusti Gregory as we discuss how he is learning and teaching Python in a small town in Vermont.
Full show notes at https://talkpython.fm/194
This year, 2018, is the year that the number of data scientists doing Python equals the number of web developers doing Python. That's why I've invited Jonathon Morgan to join me to count down the top 10 stories in the data science space.
You'll find many accessible and interesting stories mixed in with a bunch of laughs. We hope you enjoyed it as much as we did.
Full show notes at https://talkpython.fm/193
It's been a fantastic year for Python. Literally, every year is better than the last with so much growth and excitement in the Python space. That's why I've asked two of my knowledgeable Python friends, Dan Bader and Brian Okken, to help pick the top 10 stories from the Python community for 2018.
Just us on this episode of Talk Python To Me to count them down.
Full show notes at https://talkpython.fm/192
When you think about Microsoft, do you think about Python? Maybe not, but you probably should. They have been doing an incredible amount of work to improve Python for folks on Windows as well as the broader community. You can think of the wild growth of Visual Studio code. But did you know that 5 core developers work there and the majority of Python development happens on Windows?
Join me along with Steve Dower (a core dev working at Microsoft), who just published an amazing retrospective of Python at Microsoft entitled: Python at Microsoft: flying under the radar.
Full show notes at https://talkpython.fm/191
You'll find this episode to be part discussion on how to teach and learn Django as well as why learning web development can be hard and part meta where Will Vincent and I discuss the business of creating content and teaching around Python.
Full show notes at https://talkpython.fm/episodes/show/190/teaching-django
Have you ever wondered what a developer advocate (sometimes called a dev evangelist) does? You know these folks. They are often seen at conferences working at some high-end tech company's booth or traveling from conference to conference speaking on their specialty.
Who are these folks, how did they get this job, and what is it really like to do it day to day? Join me along with Cecil Phillip from Microsoft, Matt Makai from Twilio, and Paul Everett from JetBrains to dig into what it means to be a developer advocate and how they each became one for such cool tech companies.
Full show notes at https://talkpython.fm/episodes/show/189/war-stories-of-the-developer-evangelists
Full show notes at https://pythonbytes.fm/episodes/show/106/fluent-query-apis-on-python-collections
What do most web servers do most of the time? They wait. They wait on external systems while processing a request.
Think about a standard web request to an ecommerce site where you are logged in. You send it a session cookie and a URL. It pulls a bunch of items from a database, a Redis cache, and an external API.
Virtually all this time is spent waiting. That is exactly what asyncio is built for. But to take advantage of it in Python web frameworks, the framework itself has to support async methods.
That's what Sanic was built to do. On this episode, you'll meet Adam Hopkins who is leading the Sanic project.
Full show notes at https://talkpython.fm/episodes/show/188/async-for-the-pythonic-web-with-sanic
Full show notes at https://pythonbytes.fm/episodes/show/105/colorizing-and-restoring-old-images-with-deep-learning
The key to making anything a habit, including learning to program, is to make it fun. That's exactly what Anna-Lena Popkes did with her 100 days of code challenge. She created a magical universe where Python-derived creatures and castles live.
Join us on this episode as we explore some of the Python concepts she encountered on her journey as well as how she made her way to Microsoft Research in the UK where she is doing an AI Residency.
Full show notes at https://talkpython.fm/episodes/show/186/100-days-of-python-in-a-magical-universe
How can we make learning Python and teaching Python more real for students, especially younger students? The BBC in the UK had a great idea. Make it more physically real with actual devices. That's where Nicholas Tollervey got involved. He helped bring the BBC Micro:bit and Python to millions of kids in the UK.
Full show notes at https://talkpython.fm/184
Full show notes at https://talkpython.fm/episodes/show/183/qt-for-python
Python is taking over much of the development world as it quickly is becoming one of the, or simply the most widely used programming languages. But that does not mean that Python is without its weaknesses. In my mind, there are three such weaknesses: #1 GUIs applications, #2 Native, general purpose mobile apps (iOS and Android), #3 deployment as a single binary or set of binary and resource files.
This episode is primarily about #1, the GUI frameworks. One of the best such frameworks looking to make Python a better language for desktop applications is Qt, namely Qt for Python. This week you'll meet Cristián Maureira-Fredes from to tell us all about this revitalization of the Qt and Python space.
But you will also learn that they have aspirations to make Qt for Python and option for mobile app development and to solve the deployment problem as well.
That hits all three of the weak spots and we can only be rooting for them to solve them!
Join me and Doug Farrell as we discuss his career and what he's up to at Shutterfly. You'll learn about the Python stack he's using to work with, not just with bits and bytes, but physical devices on a production line for creating all sorts of picturesque items. You'll also hear how both he and I feel it's a great time to be a developer, even if you're on the older side of 30 or 40 or beyond.
Full show notes at https://talkpython.fm/episodes/show/182/picture-python-at-shutterfly
Full show notes at https://pythonbytes.fm/episodes/show/99/parse-the-regex-antidote-in-python
Listeners often tell me one of the really valuable aspects of this podcast is the packages and libraries that they learn about and start using in their projects from guests and myself. On this episode, I've invited Brian Okken (my co-host over on Python Bytes) to take this to 11. We are going to cover the top 30 Python packages from the past year (metric to be determined later in the show).
Full show notes at https://talkpython.fm/episodes/show/181/30-amazing-python-projects
Full show notes at https://pythonbytes.fm/episodes/show/98/python-electron-as-a-python-gui
The Python core developers recently released Python 3.7 and are now busy planning what's coming in 3.8. That makes right now a great time to dig into what was included in Python 3.7 and what's on deck for the next great release of CPython. This week we have Anthony Shaw back on the podcast to tell us all about it.
Full show notes at https://talkpython.fm/episodes/show/180/what-s-new-in-python-3.7-and-beyond
The Python Language Summit is a yearly gathering of around 40 or 50 developers from CPython, other Python implementations, and related projects. It is held on the first day of PyCon. Many of the decisions driving Python forward are made at this summit. On this episode you'll meet Mariatta Wijaya, Łukasz Langa and Brett Cannon, three well-known core devs to walk us through the major topics of this year's summit.
Full show notes at https://talkpython.fm/episodes/show/179/python-language-summit-2018
You know you should be testing your code right? How do you know whether it's well tested? Are you testing the right things? If you're not using code coverage, chances are is you're guessing.
But you don't need to guess. Just grab coverage.py maintained by our guest this week, Ned Batchelder.
Full show notes at https://talkpython.fm/episodes/show/178/coverage.py
Flask is now 8 years old and until recently had gone along pretty steady state. It had been hanging around at version 0.11 and 0.12 for some time. After a year-long effort, the web framework has now been updated to Flask 1.0.
David Lord is here to share the big news with. He's the maintainer of Flask and we dive into the new features as well as the future directions of Flask with him.
Full show notes at https://talkpython.fm/episodes/show/177/flask-goes-1.0
The Python landscape is changing pretty dramatically. Python's rapid growth over the past 5 years means it doesn't look the same as the early days. On this episode, we take a deep look inside the state of the Python ecosystem with Ewa Jodlowska and Dmitry Filippov. They lead the PSF and JetBrains Python survey. And they are here to dig into the results.
Full show notes at https://talkpython.fm/episodes/show/176/the-python-community-by-the-numbers
Full show notes at https://pythonbytes.fm/episodes/show/94/why-don-t-you-like-notebooks
Full show notes at https://pythonbytes.fm/episodes/show/93/looking-like-there-will-be-a-pyblazor
The discipline of network engineering is quickly moving towards a world where it's as much programming and automation as it is packets and ports. Join me and Hank Preston to discuss what parts of Python are important for network engineers to learn.
Full show notes at https://talkpython.fm/episodes/show/175/teaching-python-to-network-engineers
Full show notes at https://pythonbytes.fm/episodes/show/92/will-your-python-be-compiled
Not everyone comes to software development and Python through 4-year computer science programs at universities. This episode highlights one alternative journey into Python.
Over the course of two episodes, you will meet people who started in other industries and now make Python part of their daily experience. Some of them have used programming to power-up their specialization. Others decided they'd rather be doing programming fulltime and made that switch.
This is part 2 of this two-part series. Our guests this time are Giuseppe Cunsolo, Brian Skinn, and Teresa Borcuch.
Full show notes at https://talkpython.fm/episodes/show/174/coming-into-python-from-another-industry-part-2
Not everyone comes to software development and Python through 4-year computer science programs at universities. This episode highlights one alternative journey into Python.
Over the course of two episodes, you will meet people who started in other industries and now make Python part of their daily experience. Some of them have used programming to power-up their specialization. Others decided they'd rather be doing programming fulltime and made that switch.
This is part 1 of this two-part series. Our guests this time are Derrick Chambers, Jim Taysom, Arash Soheili, and Rob Ward.
Full show notes at https://talkpython.fm/episodes/show/173/coming-into-python-from-another-industry-part-1
Full show notes at https://pythonbytes.fm/episodes/show/89/a-tenasious-episode-that-won-t-give-up
Quick, name some ways to make your Python code faster. Did you think PyPy, the JIT-compiled version of Python? Maybe some async and await parallelism? How about Cython where you write in Python-esc language that compiles to machine instructions?
I'm here to add a new one to your vocabulary. Nuitka. Nuitka is like Cython in that your Python code is compiled into true machine instructions rather than interpreted. But unlike Cython, you can take standard Python 3 without changing the syntax at all and compile it.
And Kay Hayen is here to take us on the journey of Nuitka, a project he created and has been overseeing for some time.
Full show notes at https://talkpython.fm/episodes/show/172/nuitka-a-full-python-compiler
Jupyter notebooks have transformed the way many developers and data scientists do their jobs. They offer a platform to not just explore but to explain data and computation.
But how are they really being used? Adam Rule is here to describe his research (and Ph.D. dissertation) which analyzed over 1M Juypter notebooks found in the wild.
Full show notes at https://talkpython.fm/episodes/show/171/1m-jupyter-notebooks-analyzed
Full show notes at https://pythonbytes.fm/episodes/show/88/python-has-brought-computer-programming-to-a-vast-new-audience
This past week we have had a passing of the reigns for Python leadership. Guido van Rossum who created and has been shepherding the language for 30 years has stepped down from decision making around the Python language.
Join Carol Willing and Brett Cannon both long time core developers and Python leaders along with my co-host at Python Bytes Brian Okken as we discuss that the future holds for Python and how this change will affect how Python is created and evolves.
Full show notes at https://talkpython.fm/episodes/show/170/guido-van-rossum-steps-down
Full show notes available at https://pythonbytes.fm/episodes/show/87/guido-van-rossum-setps-down
Corey Schafer has been building his YouTube channel of tutorials for many years. He recently made the big shift into making this hobby project his full time job. You'll hear about how Corey made that transition, what it takes to "go pro", and even a little bit about the similarities with my work with Talk Python and his project.
Full show notes at https://talkpython.fm/episodes/show/169/becoming-a-python-content-creator
Full show notes at https://pythonbytes.fm/episodes/show/86/make-your-nosql-async-and-await-able-with-umongo
Do you write Python software that uses the network, opens files, or accepts user input? Of course you do! That's what almost all software does. But these actions can let bad actors exploit mistakes and oversights we've made to compromise our systems.
Python is safer than some languages, but there are plenty of issues to be careful about. That's why Anthon Shaw and Anthony Langsworth are joining me to discuss Python security.
Full show notes at https://talkpython.fm/episodes/show/168/10-python-security-holes-and-how-to-plug-them
Full show notes at https://pythonbytes.fm/episodes/show/85/visually-debugging-your-jupyter-notebook
Ever since Python 3.5 was released, we've had a really powerful way to write I/O bound async code using the async and await keywords. On this episode, you'll Nathaniel Smith who wrote the Trio async framework that significantly simplifies complex coordinating operations using async and await. Full show notes at https://talkpython.fm/episodes/show/167/simplifying-python-s-async-with-trio
Full show notes at https://pythonbytes.fm/episodes/show/84/vibora-web-framework-it-s-fast-async-and-means-viper
Full show notes at https://pythonbytes.fm/episodes/show/82/let-s-make-a-clear-python-3-statement
We have evolved from, "It builds, ship it!" to continuous integration where every check-in is automatically verified by something like Travis CI. Taking that further, some people are using continuous delivery. This means, once a check-in is validated by the CI system, it's deployed -- automatically.
There are many moving parts in these processes. On this episode, you'll meet Cris Medina who has put together a world class CI/CD system. And he's here to share how he did it and what tools and libraries are involved.
Full show notes at https://talkpython.fm/episodes/show/166/continuous-deliver-with-python
The blockchain and cryptocurrencies are some of the most disruptive technologies of the decade. On this episode, you'll meet Stuart Farmer who is building a suite of developer tools that speed up the process of creating new and custom blockchains and apps.
Full show notes at https://talkpython.fm/episodes/show/165/python-and-the-blockchain
Full show notes at https://pythonbytes.fm/episodes/show/81/making-your-c-library-callable-from-python-by-wrapping-it-with-cython
The brain is truly one of the final frontiers of human exploration. Understanding how brains work has vast consequences for human health and computation. Imagine how computers might change if we actually understood how thinking and even consciousness worked.
On this episode, you'll meet Justin Kiggins and Corinne Teeter who are research scientists using Python for their daily work at the Paul Allen Brain Institute. They are joined by Nicholas Cain who is a software developer supporting scientists there using Python as well.
Even if you aren't interested in brain science directly, I encourage you to listen to the entire interview. It's really fascinating.
Full show notes at https://talkpython.fm/episodes/show/164/python-in-brain-research-at-the-paul-allen-institute
Full show notes at https://pythonbytes.fm/episodes/show/80/dan-bader-drops-by-and-we-found-30-new-python-projects
Learn how Python is being used in research to understand the inner workings of the Earth. This week, you'll meet Lindsey Heagy, a PhD student in geophysics at the University of British Columbia. She shares how she is using Python to solve these computational problems along with an amazing framework for viewing scientific writing itself through the lens of Python and open source.
Full show notes at https://talkpython.fm/episodes/show/163/python-in-geoscience
Full show notes at https://pythonbytes.fm/episodes/show/79/15-tips-to-enhance-your-github-flow
You often hear about architecture in software. This could be things like microservices, 3-tier apps, or even the dreaded client-server mainframe app. But this episode, we're turning this on its head: It's software in architecture and real-world construction projects with Mark Mendez.
Full show notes at https://talkpython.fm/episodes/show/162/python-in-building-and-architecture
Full show notes at https://talkpython.fm/episodes/show/161/django-2.0
Django has reached a major milestone with its 2.0 release. This puts legacy Python (that is Python 2) fully in the rear-view mirror and brings some nice new features to the framework.
Join me with Daniel Roy Greenfeld to discuss what new best practices we should adopt and which ones are still entirely relevant.
What is the fastest, most scalable web platform? Is it Pyramid running on top of MongoDB with a Redis cache? Maybe Flask and Postgres as a service? Some funky Go API framework?
No. It's static files. But today that does not mean you write a bunch of HTML. With static site frameworks like Lektor and Pelican, you can use data to drive the creation of static sites and then host those wherever makes the most sense for you.
On this episode, you'll meet Joseph Nix who works on Lektor, a Python based static site generator.
Full show notes at https://talkpython.fm/episodes/show/160/lektor-beautiful-websites-out-of-flat-files
Full show notes at https://pythonbytes.fm/episodes/show/75/pypi.org-officially-launches
Python is often described as a "batteries included" language and ecosystem. In fact, that's been taken so far that there is even a delightful Easter egg in the Python REPL. Just type "import antigravity" to see what I mean.
Where do these powerful packages come from? Well, the Python Package Index or PyPI.
On this episode, you will meet Nicole Harris, Ernest Durbin III, and Dustin Ingram. They were part of the team that has just launched the new version of PyPI over at pypi.org.
Not only have they given us a great new website around packaging in Python. They have laid the foundation for innovation in this space for years to come.
Full show notes at https://talkpython.fm/episodes/show/159/inside-the-new-pypi-launch
You've surely heard of quantum computing and quantum computers. They are based on the (often) non-intuitive nature of very small particles described by quantum mechanics. So how do they work and what will they mean for us as a society and as developers?
Luckily, I have Hannah Sim, a Ph.D. student from Harvard working on quantum algorithms here to give us the full story.
Full show notes at https://talkpython.fm/158
Full show notes at https://pythonbytes.fm/episodes/show/74/contributing-to-open-source-effectively
Full show notes at https://pythonbytes.fm/episodes/show/73/this-podcast-comes-in-any-color-you-want-as-long-as-it-s-black
One of the hottest areas of growth for Python is in the scientific and data science communities. But if that work is done in an academic or research setting, it can be very hard to get proper credit for it. You have to write full on peer reviewed articles.
That's where Arfon Smith and JOSS or The Journal of Open Source Software come in. Here developer-scientists and other research-oriented folks can submit their software as a brief paper.
Join us on this episode to learn all about that and Arfon's work with some of the most cutting-edge projects in Astronomy at the Space Telescope Science Institute.
Full show notes at https://talkpython.fm/episodes/show/157/the-journal-of-open-source-software
Full show notes at https://pythonbytes.fm/episodes/show/72/new-versioning-episode-0.0.7.2-with-72-releases
Full show notes at https://pythonbytes.fm/episodes/show/71/we-can-migrate-to-python-3-careful-please
Learning about programming libraries and languages is useful and interesting. But sometimes knowing WHY certain decisions were made or the history leading up to some change or package being created gives you a deeper understanding.
That's what this episode is all about. You'll meet Mike Driscoll who runs PyDev of the Week. He also just published a very relevant book: Python Interviews: Discussions with Python Experts.
Full show notes at https://talkpython.fm/episodes/show/156/python-history-and-perspectives
Full show notes at https://pythonbytes.fm/episodes/show/70/have-you-seen-my-log-it-s-cute
Full show notes at https://pythonbytes.fm/episodes/show/69/digging-into-stackoverflow-s-2018-survey-results
Full show notes at https://talkpython.fm/episodes/show/155/practical-steps-for-moving-to-python-3
Since 2008 there has been this tension in Python where the much of the effort to improve Python has been on Python 3 whereas many developers were left stuck on Python 2 primarily because important packages were not yet Python 3 capable.
We've moved into a new era where most packages anyone uses is fully Python 3 enabled and many are Python 3 only (the latest Django framework for example). There are many carrots and a number of heavy sticks encouraging us all to move to Python 3.
But what if you have a large code base that needs to be migrated? What are the concrete steps and the gotchas in this whole process?
This week, we welcome back Anthony Shaw to show. He just published a new course on migrating Python 2 code and he's here to share his tips.
Python is often used in big-data situations. One of the more personal sources of large data sets is our own genetic code. Of course, as Python grows stronger in data science, it's finding its place in biology and genetics.
In this episode, you'll meet Ian Maurer. He's working to help make cancer a think of the past. We'll dig into how Python is part of that journey.
Full show notes at https://talkpython.fm/episodes/show/154/python-in-biology-and-genomics
If you have spent some time in the Python community, you have probably heard the term PEP which stands for Python Enhancement Proposal. In fact, the very first one was created in June 2000 which defines the PEP process.
Our guest this week, Nick Coghlan, was a co-author on that PEP and many more.
We will discuss PEPs and how Python officially evolves but there are many other forces and influences on Python more broadly.
Full show notes at https://talkpython.fm/episodes/show/153/how-python-evolves
Full show notes at https://pythonbytes.fm/episodes/show/67/result-of-moving-python-to-github
Full show notes at https://talkpython.fm/episodes/show/151/gradual-typing-of-production-applications
I hope you using Python 3 these days. One of its powerful new features is type annotations. This lets you build and maintain large-scale Python projects with much more ease and confidence.
This episode you'll meet Łukasz Langa who has help migrate some very large Python projects. We'll discuss how Python uses the concept of gradual typing to slowly expand the sections of your code that are type checked.
Full show notes at https://pythonbytes.fm/episodes/show/66/wait-nosql-with-acid-and-transactions
Have you heard about ASTs? Maybe that was in the context of compilers or parsers? They are an powerful data structure that we all use but often indirectly. They are just an, well, abstract idea to most of us.
This week, you'll meet Emily Morehouse. She is here to make this abstract concept much more concrete and discuss places where the AST can help us write and maintain better code.
Full show notes at https://talkpython.fm/episodes/show/152/understanding-and-using-python-s-ast
Full show notes at https://pythonbytes.fm/episodes/show/65/speed-of-your-import-statements-affecting-performance
Full show notes at https://pythonbytes.fm/episodes/show/64/the-gui-phoenix-rises-with-wxpython
Full show notes at https://talkpython.fm/episodes/show/150/technical-lessons-learned-from-pythonic-refactoring
Does your code smell? Have a weird fragrance? It turns out code smells are a real thing and an amazing conceptualization of suboptimal design. This week you'll meet Yenny Cheung who has some practical and real-world advice on using refactoring in Python to improve your code and wash away those code smells.
Full show notes at https://talkpython.fm/149
Are you considering getting into web programming? Choosing a web framework (like Pyramid, Flask, or Django) can be daunting. It would be great to see them all build out the same application and compare the results side-by-side.
That's why when I heard what Nick Hunt-Walker was up to, I had to have him on the podcast. He and I will chat about 4 web frameworks, compared. He built a data-driven web app with Flask, Tornado, Pyramid and Django and then put it all together in a presentation. We are going to dive into that.
Full show notes at https://talkpython.fm/episodes/show/148/python-book-authors-panel-discussion
Are you a fan of developer and technical books? Ever wonder what went into the writing of your favorite Python book? This week we peek inside the world of book authorship with a panel of renowned developer-focused authors.
You'll meet Katharine Jarmul, Bruce Eckel, Luciano Ramalho, Dan Bader, and Brian Okken.
Full show notes at https://pythonbytes.fm/episodes/show/62/wooey-and-gooey-are-simple-python-guis
Full show notes at https://talkpython.fm/147
There has been a bunch of new Python web frameworks coming out in the past few years. Generally, these have been focused solely on Python 3 and have tried to leverage Python's new async and await features.
However, generally these frameworks have come with their own new APIs. They may be amazing but it's something new to learn and a barrier to migrating over to them.
That's why when I learned about Quart from Philip Jones, I was excited. It's an async-enabled web framework that attempts to be 100% compatible with Flask, including the extensions.
Full show notes at https://pythonbytes.fm/episodes/show/60/don-t-dismiss-sqlite-as-just-a-starter-db
https://talkpython.fm/episodes/show/146/building-alexa-skills-with-python-and-flask
Voice assistants and voice interfaces are quickly becoming the new, hot way to interact with computers. Two of the notable ones are amazon echo devices and google home devices.
Wouldn't it be great if we could program these with Python? Even better if we could use well-known APIs such as Flask.
This week you'll meet Eric Chou, Dave Voutila, and Cam Sweeney who discuss their frameworks and apps they've created around Amazon and Google's devices.
Full show notes at https://pythonbytes.fm/episodes/show/59/instagram-disregards-python-s-gc-again
It's been an amazing year for Python. We've seen its meteoric growth continue to become the most popular, major programming language. We've seen significant grants and funding come in for open source. And this just might be the year that the Python 2 or Python 3 question was finally settled.
Join Brian Okken, my co-host from our Python Bytes podcast, and me as we look back at many of the major milestones for Python in 2017.
Full show notes at https://talkpython.fm/episodes/show/145/2017-python-year-in-review
We all know Python is becoming increasingly important in both science and machine learning. This week we journey to the very forefront of Physics.
You will meet Michela Paganini, Michael Kagan, and Matthew Feickert. They all work at the Large Hadron Collider and are using Python and machine learning to help make the next major discovery in Physics.
Full show notes at https://talkpython.fm/episodes/show/144/machine-learning-at-the-large-hadron-collider
Full show notes at https://pythonbytes.fm/episodes/show/57/our-take-on-excel-and-python
Full show notes at https://talkpython.fm/episodes/show/143/tuning-python-web-app-performance
Do you run a web application or web service? You probably do a couple of things to optimize the performance of your site. Make sure the database response quickly and more. But did you know a well of performance improvements live in your web servers themselves?
Join Ben Cane and me to discuss how to optimize your Python web app as well as uWSGI and Nginx.
Full show notes at https://pythonbytes.fm/episodes/show/56/the-pendulum-of-time-swings-beautifully-in-pypi
Is there some task you find yourself performing frequently, repetitively on the web? With Python and modern tooling, virtual every website has become easily scriptable.
I'm not talking about web scraping. I'm referring to Selenium which is a headless Python front-end to the full version of the Chrome browser.
Join me and Tim Grossman as we talk about Selenium and how to automate the web. You'll learn about his project InstaPy which is a full Python package for almost any automation involving Instagram.
Full show notes at https://talkpython.fm/episodes/show/142/automating-the-web-with-selenium-and-instapy
How many Python developers do you know that learned Python quickly but then plateaued pretty quickly as well. Maybe this is someone you worked with or maybe it's even you. Python's clean and simple syntax can mean it's easy to learn but hard to master.
After all, maybe it was learned it in a week. What else is there?
Plenty. And Dan Bader is here to share his very popular Python tricks with us. You'll learn to look deeper for more than just how but why and when of many Python's more subtle features.
Full show notes at https://talkpython.fm/episodes/show/141/python-tricks
Full show notes at https://talkpython.fm/140
How do you learn libraries or parts of Python itself that you don't have actual work projects involving them? Whether that's SQLAlchemy, Slack bots, or map APIs, actually building projects (small and large) with them is really the only way to gain true competency.
You might try a 100 days of Python code challenges.
This week you'll meet Bob Belderbos and Julian Sequeira who created PyBites. The have done a few 100 days of code challenges and are here to share their experience and some concrete examples.
Full show notes at https://talkpython.fm/139
Data science is one of the fastest growing segments of software development. It takes a slightly different set of skills than your average full-stack development job. This means there's a big opportunity to get into data science. But how do you get into the industry?
That's what Hugo Bowne-Anderson is here to tell us all about.
Full show notes at https://pythonbytes.fm/episodes/show/52/call-your-apis-with-uplink-and-test-them-in-the-tavern
Full show notes at https://talkpython.fm/episodes/show/138/anvil-all-web-all-python
Have you noticed that web development is kind of hard? If you've been doing it for a long time, this is easy to forget. It probably sounds easy enough to
Pick a server side framework (Pyramid or Django?) Create a new project (pcreate, cookiecutter, manage.py, …) Install some client side dependencies with NPM Install some server side dependencies with pip Create a database (and maybe even a server install)! Connect the app to the db (securely) Pick a front-end framework (Bootstrap or Foundation?) Integrate it Whoa: Now you write code Ugh, time to deploy
Oh wait, that doesn't sound so easy.
What if the web was easy as old school VB 6 with drag-drop and double-click for event handlers, but with Python of course.
With Anvil, you'll see it really is that quick to get started! Meet Meredydd Luff to tell us all about it.
Full show notes at https://pythonbytes.fm/episodes/show/51/how-to-make-your-code-80-times-faster
Design has become a critical element in software. Back in the 90's, it was fine to produce or sell "battleship grey" apps that worked by did not do much to delight. Today, design is table stakes. And knowing how to design applications yourself and work with designers is a key still.
This episode, you'll meet James Stone who staddles that gap between developers and designers (he's both). He has a bunch of tips for improving your design skills as well as working with designers.
Full show notes at https://talkpython.fm/episodes/show/137/design-concepts-and-tips-for-developers
Full show notes at https://talkpython.fm/136
Do run any code that listens on an open port on the internet? This could be a website, a RESTful web service, or (gasp) even a database endpoint.
Troy Hunt, a renowned security expert likes to say that your doing "free pen. testing for that product right there".
Join Troy and me on this episode of Talk Python To Me. We discuss lessons learned from running the vulnerability monitoring website Have I been pwned? As well as other lessons for developers to keep your code safe while providing public services.
Full show notes at https://pythonbytes.fm/episodes/show/50/bundling-shipping-and-protecting-python-applications
We all have smartphones these days. And we take them with us everywhere we go. How much could you infer about a person (their stage in life, their driving style, their work / life balance) based on just a phone's motion and GPS data?
With the right mix of analytics and machine learning, turns out you can learn a lot about a person. Are they a dog-owning workaholic? Or an early rising parent of young children?
This week you'll meet Vincent Spruyt. He is the chief data scientist at Sentiance. A company building an SDK to answer these exact questions. You'll learn how they are using Python to make this happen and how they think this data could be used for the great good.
Full show notes at https://talkpython.fm/episodes/show/135/capturing-human-moments-with-ai-and-python
Full show notes at https://pythonbytes.fm/episodes/show/49/your-technical-skills-are-obsolete-now-what
Full show notes at https://pythonbytes.fm/episodes/show/48/garabage-collection-and-memory-management-in-python
What is the biggest challenge facing human civilization right now? Fake news, poverty, hunger? Yes, all of those are huge problems right now. Well, if climate change kicks in, you can bet it will amplify these problems and more. That's why it's critical that we get answers and fundamental models to help understand where we are, where we are going, and how we can improve things.
On this episode, you'll meet Dr. Damien Irving. He's a climate science researcher using Python to understand what the climate models are telling us.
Full show notes at https://talkpython.fm/episodes/show/134/python-in-climate-science
https://talkpython.fm/episodes/show/133/productivity-for-developers
This episode is all about developer productivity. From continuous learning, to git source control tips, to tools and books for developers, Jay Miller from the Productivity in Tech podcast is here to share his experiences.
Full show notes at https://pythonbytes.fm/episodes/show/46/spicy-lecture-notes-and-unicorn-console-spinners
Full show notes at https://talkpython.fm/132
Are you new to open source? Maybe been using it for a long time and never got around to contributing to it? Wondering how to get started?
In this episode, you'll meet Anthony Shaw, Dan Bader, and Ronald Maravanyika. All of these guys have been successful open source developers. I speak with them about how to find a welcoming project and what you need to know to get started.
We also cover what open source project maintainers can do to help attract new and experienced contributors.
Full show notes at https://pythonbytes.fm/episodes/show/45/a-really-small-web-api-and-os-level-machine-learning
Data science has been one of the major driving forces behind the explosion of Python in recent years. It's now used for AI research, controls some of the most powerful telescopes in the world, tracks crop growth and prediction and so much more.
But with all this growth, there is an explosion of data science and machine learning libraries. That's why I invited Pete Garcin onto the show. He's going to share his top 10 machine learning libraries. After this episode, you should be able to pick the right one for the job.
Full show notes at https://talkpython.fm/episodes/show/131/top-10-machine-learning-libraries
Full show notes at https://talkpython.fm/130
One of the hallmarks of successful developers is continuous learning. The best developers I know don't just keep learning, it's one of the things that drives them. That's why I'm excited to bring you this episode on 10 books Python developers should read.
You'll meet Timo Koola who is an avid reader and self-learner in the Python space. He's found 10 books from his experience that have had huge affects on him and we'll discuss them next.
Full show page at https://talkpython.fm/129
Full featured web frameworks such as Django are great. But sometimes, living closer to the network layer is just the thing you need.
This week you'll meet Kurt Griffiths and John Vrbanac who work on the Falcon web framework. It's a bare-metal Python web API framework for building very fast app backends and microservices.
How bare metal? Well, other frameworks like the Hug REST framework even build upon Falcon.
When you think of networks, you probably think of physic things: Routers, switches, firewalls, and more. But increasingly, network engineers are managing massive networks that are better managed with software than via admin applications.
On this episode, you'll meet David Barroso who created NAPALM: A vendor neutral, cross-platform open source project that provides a unified API to network devices.
Full show notes at https://talkpython.fm/128
To make software useful, honestly, to even make it real, you have to ship it. Building a web app? Then deploy that next version. Building a toolset for data scientists? Send them that application. Managed to get a cool GUI going in Python with Togo or PySide? Time to have your users start downloading it.
Python is an amazing ecosystem. But one of the frailer parts of it has been shipping and deploying software - especially to end users. This episode, you'll meet Glyph.
Join us as we discuss where we are and where we are going for shipping Python code.
Full show notes at https://talkpython.fm/127
Containers are revolutionizing the way we deploy and manage applications. These containers allow us to build, develop, test, and even deploy on the exact same system. We can build layered systems that fill in our dependencies. They even can play a crucial role in zero-downtime upgrades.
This is great, until you end up with 5 different types of containers, each of them scaled out, and you need to get them to work together, discover each other and upgrade together. That's where Kubernetes comes it.
Today you'll meet Kelsey Hightower, a developer advocate on Google's cloud platform.
Full show notes at https://talkpython.fm/episodes/show/126/kubernetes-for-pythonistas
APIs were once the new and enabling thing in technology. Today they are table-stakes. And getting them right is important. Today we'll talk about one of the most popular and mature API frameworks in Django REST Framework. You'll meet the creator, Tom Christie and talk about the framework, API design, and even his successful take on funding open source projects.
But Tom is not done here. He's also creating the next generation API framework that fully embraces Python 3's features called API Star.
Full show notes at https://talkpython.fm/episodes/show/125/django-rest-framework-and-a-new-api-star-is-born
We all know that Python is a major player in the application of Machine Learning and AI. That often involves grabbing Keras or TensorFlow and applying it to a problem. But what about AI research? When you're actually trying to create something that has yet to be created? How do researchers use Python here?
Today you'll meet Alex Lavin, a Python developer and research scientist at Vicarious where they are trying to develop artificial general intelligence for robots.
Full show notes at https://talkpython.fm/124
What if you could take the experience and insight from 100 job interviews and use them to find just the right job. You'd be able to weed out the bad places that are not the right fit. You'd see that low-ball offer coming a mile away and move right along.
But, no one could really do 100 consecutive interviews, right? That'd be a full-time job in and of itself!
You'll meet Susan Tan who did just that.
Full show notes at https://talkpython.fm/123
The past few years have seen an explosion of IoT devices. Many of these are for the so-called smart home. Their true potential lies in the ability to coordinate and automate them as a group.
How can you garage, wifi, chromecast, and window shades work together automatically? Chances are these are all from different manufacturers with different protocols and apps. That's why you need something like Home Assistant. This Python based app brings over 740 devices together and allows you to automate them as a whole.
Today you'll meet Paulus Schoutsen who created Home Assistant.
Full notes at https://talkpython.fm/122
Do you have big, monolithic web applications or services that are hard to manage, hard to change, and hard to scale? Maybe breaking them into microservices would give you many more options to evolve and grow that app.
This week, we meet up again with Miguel Grinberg to discuss the trades offs and advantages of microservices.
Full show notes at https://talkpython.fm/121
Full show notes at https://talkpython.fm/episodes/show/116/10-top-talks-of-pycon-2017-reviewed
Whether you got to attend PyCon, there were just too many good talks to attend them all. Luckily our friends at the PSF were on top of publishing the videos online for the whole world to watch for free.
On this episode, we'll meet up with Brett Slatkin and replay his path through PyCon. We touch on his top 10 sessions from PyCon 2017.
Full show notes at https://talkpython.fm/episodes/show/108/micropython-and-open-source-hardware-at-adafruit
Want to learn how to build an Iron-man like arc reactor accessory or maybe a solar charging backpack? What if you could program these devices with Python?
We'll be talking about a project and company making this possible. This week you'll meet Tony DiCola who works at Adafruit. A company making hardware programming accessible. We will also talk about micropython which lets you program these cool devices in Python!
Full show notes at https://talkpython.fm/episodes/show/79/beeware-python-tools
Could you write me a Python app for the wide range of platforms out there? Oh, wait, I want them to be native GUI applications. And I need them on mobile (Android, iOS, tvOS, and watchOS) as well as major desktop apps. I also need them to appear indistinguishable from native apps (be a .app on macOS, .exe on Windows, etc).
What technology would you use for this? This week I'll introduce you to a wide set of small, focused and powerful tools that make all of this, and more, possible. We're speaking with Russell Keith-Magee, founder of the Beeware project.
Full show notes at https://talkpython.fm/episodes/show/78/how-i-built-an-entire-game-and-toolchain-100-in-python
What kind of applications can you build with python? You hear me featuring many people on this show that build websites, web services, or some data science driven application. Of course, all of those are wonderful but I know many of you have dreamed of building a game.
This episode I'm interviewing Joseph Cherlin. He created the game Epikos and the entire tool chain entirely in Python. He has a great story about how he came across Python, why he decided to use it in his game, and advice he has for anyone out there taking on a large project like this.
We catch up with David Stewart and meet Suresh Srinivas, and Sergey Maidanov from Intel. We talk about how they are working at the silicon level to make even Python 2 run faster and touch on dedicated AI chips that go beyond just what is possible with GPU-computation.
Full show notes at https://talkpython.fm/episodes/show/113/dedicated-ai-chips-and-running-old-python-faster-at-intel
Full show notes at https://talkpython.fm/episodes/show/119/python-in-engineering
Think about how you learn most technical or detail-oriented subjects?
You start at the bottom, lowest level and you create building blocks and work your way into the actual thing you care about. This happens in engineering, in math, and even in programming.
Our guest this week, Dr. Allen Downey, believes that computation and programming can help us turn this inside-out way of teaching right-side out again.
Join Allen and me as we discuss programming as a way of thinking and physical modeling and engineering in Python.
Full show notes at https://pythonbytes.fm/episodes/show/29/responsive-bar-charts-with-bokeh-flask-and-python-3
This week we'll enter the world of stock markets, trades, hedge funds and more. You'll meet Yves Hilpisch who runs The Python Quants where Python, open-source, education, and finance intersect.
Full show notes at https://talkpython.fm/120
Let's consider the progression we've been on over the past 15 or so years.
We've gone from software and operating systems that we manage running on hardware that we own (and babysit), to virtual machines on our hardware, to IaaS in the cloud and PaaS in the cloud. Then onward to containers, usually docker, running on someone else's systems in the cloud, and maybe even microservices which are conglomerates of these containers working together managed by Kubernetes.
Where do we go from there? I can't tell you the final destination, but I believe we've reached a leaf node in this hierarchy with our topic today.
On this, episode 118 of Talk Python To Me, with Ryan Scott Brown, we are going to explore serverless computing. It's an interesting paradigm shift and I hope you enjoy this conversation.
https://talkpython.fm/episodes/show/118/serverless-software
One of the nice things about the Python language is it's at least 3 programming paradigms in one: There's the procedural style, object-oriented style, and functional style.
This week you'll meet Evan Hubinger who is taking Python's functional programming style and turning it to 11. We're talking about Coconut. A full functional programming language that is a proper superset of Python itself.
https://talkpython.fm/117
When you think of popular Python packages, what comes to mind? There's a good chance that this week's guest, Kenneth Reitz, wrote that package you just thought of. He's the author of so of Python's most popular libraries, including Requests, Records, Maya, and pipenv just to name a few.
I got a chance to catch up with Kenneth at PyCon 2017 this year. Here's the story.
https://talkpython.fm/episodes/show/115/python-for-humans-projects
As most of you know, learning to program opens doors. It takes every day people and turns them into creators. Once you know programming, and Python, you've passed through a door to a place with much more opportunity.
Now, consider the impact this could have if you grew up in an environment with less opportunity? With fewer people, you knew leading the way into software careers.
Today you'll meet Sean Valentine and Landon Miller helping to run an amazing project and Mohammed Abdulla and Malik Poole who graduated from this project. It's called The Hidden Genius Project and it helps young black men become developers and entrepreneurs.
https://talkpython.fm/114
Full show notes at https://pythonbytes.fm/episodes/show/27/the-pycon-2017-recap-and-functional-python
Full show notes at https://pythonbytes.fm/episodes/show/26/how-have-you-automated-your-life-or-cli-with-python
I've always thought that if I retired, I'd more or less do what I had been doing as my job - except without the meetings and reports. That is, write interesting and fulfilling software.
In this episode of Talk Python To Me, we are back together with Philip Guo to discuss his research project aimed to improve the learning to code experience for older adults (those 60 - 85 years old).
https://talkpython.fm/episodes/show/112/geeking-out-in-the-golden-years
Time for some Pythonic job and career advice with Matt Harrison. Listen in as we discuss how most developer jobs never make it to full job listings and how you can get in on them. We also discuss his books and his avalanche research with the Pandas library.
Full details at https://talkpython.fm/episodes/show/111/pythonic-career-advice-and-more
Full show notes at https://pythonbytes.fm/episodes/show/24/i-have-a-local-pypi-server-and-so-do-you
Full show notes at https://talkpython.fm/episodes/show/110/data-democratization-with-redash
Are you asked to generate reports from your company's data? Has someone suggested that you buy / deploy massive BI software that expensive, closed source, and generally underwhelming?
Well it's Redash and Python to the rescue. Today you'll meet Arik Fraimovich, the creator of Redash, whose goal is to make your company data driven by connecting to any data source, easily visualizing your data.
Not only is it a cool open source project, it's an example of someone taking a successful open source project and building a business on top of it.
Full show notes at https://talkpython.fm/109
Database design and decisions use to be fairly straightforward. Pick your relational database engine, map out the general entities, apply the third-normal-form (3NF) to them and you're basically done.
With the Cambrian explosion of database options and variations created from 2009 to present, it gets much harder to even choose the database much less follow the well-worn path of 3NF.
On this episode, you'll meet Rick Copeland, a fellow MongoDB Master and author of the book MongoDB Applied Design Patterns. We will discuss modeling data using documents in a document database such as MongoDB and some techniques that particular apply to MongoDB's implementation.
You have heard me go on and on about how Python 3.5's async and await changes the game for asynchronous programming in Python. But what exactly does that mean? How does it work in APIs? Internally?
Today I'm here with David Beazley who has been deeply exploring this space with his project Curio.
Full notes at https://talkpython.fm/107
Full show notes at https://pythonbytes.fm/episodes/show/21/python-has-a-new-star-framework-for-restful-apis
Al Sweigart is back on Talk Python. This time we're inventing our own computer games.
Has anyone ever asked you for a resource to get started learning programming, learning Python? One excellent option is Al's book, just updated, called Invent Your own Computer Games with Python. That's what we're digging into right now.
https://talkpython.fm/episodes/show/106/invent-your-own-computer-games-with-python
Full details at https://pythonbytes.fm/episodes/show/20/finding-similar-but-not-identical-images-in-128-bits-via-python
There are many reasons it's a great time to be a developer. One of them is because there are so many choices around data access and databases. So this week we take tour with our guest Jim Fulton of some databases you may not have heard of or given a try.
You'll hear about the pure Python database ZODB. There's Zero DB, an end-to-end encrypted database in which the database server knows nothing about the data it is storing, and NewtDb spanning the world of ZODB and JSON friendly Postgres.
Show notes and links at https://talkpython.fm/episodes/show/105/a-pythonic-database-tour
Show notes and links at https://pythonbytes.fm/episodes/show/19/put-your-python-dictionaries-in-a-box-and-apparently-python-is-really-wanted
Game theory is the study competing interests, be it individual actors within an economy or healthy vs. cancer cells within a body.
Our guests this week, Vince Knight, Marc Harper, and Owen Campbell, are here to discuss their python project built to study and simulate one of the central problems in Game Theory: The prisoners' dilemma.
https://talkpython.fm/episodes/show/104/game-theory-in-python
Full show notes at https://pythonbytes.fm/episodes/show/18/python-3-has-some-amazing-types-and-you-can-now-constructively-insult-your-shell
This episode we have an optimization 2fer.
We begin looking at optimizing a subset of Python code for machine learning using the LLVM compiler with a project called PyLLVM which takes plain python code, compiles it to optimized machine instructions and distributes it across a cluster.
In the second half, we look at a fabulous new way to work with MongoDB for Python writing data scientists. The project is called bson-numpy and provides a direct connection between MongoDB and NumPy and is 10x faster than standard pymongo.
https://talkpython.fm/episodes/show/103/compiling-python-through-pyllvm-and-mongodb-for-data-scientists
How do you build reliable software with fewer bugs? Yes, unit testing is part of that. But did you know that code reviews often play a key role in this process and come with many benefits on top of just bug detection.
https://talkpython.fm/episodes/show/102/effective-code-reviews
You know the two questions I asked at the end of each episode?
What's your favorite editor for writing Python code and what less-well-known PyPI package do you recommend?
Well this time, we are making a whole episode out of "What's your favorite editor". You'll meet Don Jayamanne who created the wildly popular and open source Python add-in for Visual Studio Code. That's not the Windows-only Visual Studio, but Microsoft's free cross-platform editor.
https://talkpython.fm/episodes/show/101/adding-a-full-featured-python-environment-to-visual-studio-code
Welcome to a very special episode. This is the 100th episode of Talk Python To Me. It's the perfect chance to take a moment and look at where we have come from, and where we are going. Not just with regard to the podcast but for Python in general.
And who better to do this than Python's inventor himself. Guido van Rossum. In this episode, we discuss how Guido got into programming, where Python came from and why, and Python's bright future with Python 3.
https://talkpython.fm/episodes/show/100/python-past-present-and-future-with-guido-van-rossum
Full details: https://pythonbytes.fm/episodes/show/14/lots-of-python-style-and-python-3000-is-3000-days-old
One of the areas where Python truly shines is on the web. Many well known websites like YouTube, Pintrest, and Spotify are powered by Python. In the mid 2000's, a number of powerful and popular frameworks were created such as Django, Flask, and Pyramid.
It may feel like the choices of web frameworks and innovation in that space if baked and done. But we are actually seeing an explosion of new frameworks for new web paradigms.
In this episode, you'll meet Martijn Faassen who created Morepath. A relatively new web framework built to be a first class citizen of this JavaScript, client-side web paradigm popular in many web apps today.
https://talkpython.fm/episodes/show/99/morepath-super-powered-python-web-framework
One of the major areas of innovation in Python 3 is advances in async and concurrent programming. Yet, when working with any of the major web frameworks: django, flask, or pyramid, this is basically no concurrent option. That's why Andrew Godwin decided to tackle the issue on the django side with django channels.
https://talkpython.fm/episodes/show/98/adding-concurrency-to-django-with-django-channels
This is Python Bytes, Python headlines and news deliver directly to your earbuds: episode 12, recorded on February 6th, 2017. In this episode we discuss expanding your Python mental model and serving millions of requests per second with Python.
https://pythonbytes.fm/episodes/show/12/expanding-your-python-mental-model-and-serving-millions-of-requests-per-second-with-python
Become a friend There's a whole spectrum of Python web frameworks. On one end we have the micro-frameworks like bottle, flask, and do some degree Pyramid. On the other things like Django and even CMSes like Wagtail (built on Django) in the far end.
While this is often positioned as an either / or choice, this week you'll meet Ian Dennis Miller, the creator of Flask-Django. An extension to Flask which brings many of the good things from Django to Flask's simple and small API.
https://talkpython.fm/episodes/show/97/flask-django-style-with-flask-diamond
https://talkpython.fm/episodes/show/96/exploring-awesome-python
Python is said to be a language that comes with "batteries included". That has many meanings depending on the level you're focusing on. At the lowest, it's a very rich and expressive language. Most commonly it means Python has a powerful and comprehensive standard library (itertools and elementtree anyone?).
But more holistically, most of the batteries are external, interchangeable ones, from PyPI. Right now, http://pypi.io has 97,326 packages listed on it. That's fantastic. However, it does lead to a discoverability problem. What options do I have for admin backends on web apps, cryptography, raw socket programming, and so on?
This week, Matt Makai is back with me (remember him from episode 26 last year?). We're talking about Awesome Python. A website and open source project attempting to categorize and somewhat rank these options.
This is Python Bytes, Python headlines and news deliver directly to your earbuds: episode 10, recorded on Monday, January 23rd, 2016.
https://pythonbytes.fm/episodes/show/10/dismissing-python-s-garbage-collection-pypi-name-reservations-and-hackers-exfiltrate-us-government-data-to-save-itself
Google runs millions of lines of Python code. The front-end server that drives youtube.com and YouTube’s APIs is primarily written in Python, and it serves millions of requests per second!
On this episode you'll meet Dylan Trotter who is working increase performance and concurrency on these servers powering YouTube. He just launched Grumpy: A Python implementation based on Go, the highly concurrent language from Google.
https://talkpython.fm/episodes/show/95/grumpy-running-python-on-go
This is Python Bytes, Python headlines and news deliver directly to your earbuds: episode 9, recorded on Tuesday, January 17th. In this episode we discuss walking with async coroutines, diving deep into requests, and a universe of options (for AIs).
https://pythonbytes.fm/episodes/show/9/walking-with-async-coroutines-diving-deep-into-requests-and-a-universe-of-options-for-ais
Have you ever had trouble installing a package you wanted to use in your Python app? Likely it contained some odd dependency, required a compilation step, maybe even using an uncommon compiler like Fortran. Did you try it on Windows? How many times have you seen "Cannot find vcvarsall.bat" before you had to take a walk?
If this sounds familiar, you might want to check conda the package manager, Anaconda, the distribution, conda forge, and conda build. They dramatically lower the bar for installing packages on all the platforms.
This week you'll meet Phil Elson, Kale Franz, and Michael Sarahan who all work on various parts of this ecosystem.
https://talkpython.fm/episodes/show/94/guarenteed-packages-via-conda-and-conda-forge
This is Python Bytes, Python headlines and news deliver directly to your earbuds: episode 8, recorded on January 10th, 2017. In this episode we discuss Python is Grumpy, avoiding burnout, Postman for API testing and more.
https://pythonbytes.fm/episodes/show/8/python-gets-grumpy-avoiding-burnout-postman-for-api-testing-and-more
This is Python Bytes, Python headlines and news deliver directly to your earbuds: episode 7, recorded on Wednesday, January 4th.
In this episode we discuss Python 3.6 being release, a blazing Python web framework called Sanic, how we are failing our open source infrastructure, and more.
https://pythonbytes.fm/episodes/show/7/python-3.6-is-out-sanic-is-a-blazing-web-framework-and-are-failing-our-open-source-infrastructure
You often hear that we need to teach computer science as a foundational skill. Why? Well I'm not sure many of the leaders pushing this forward have great answers other than jobs!
But it is fundamentally important that we do teach programming as a core skill. The reason is whatever you specialty, be that biology, psychology, or geosurveys, basic programming will supercharge that skill.
That's why I'm excited to introduce you to Software Carpentry and Jonah Duckles. They are bringing these skills and more to scientists and educators throughout the globe.
https://talkpython.fm/episodes/show/93/spreading-python-through-the-sciences-with-software-carpentry
It's been an amazing year for Python and Data Science. It's time to look back at the major headlines and take stock in what we've done as a community.
I've teamed up with the Partially Derivative podcast and we're running down the top 10 data science stories of 2016 in this joint episode.
https://talkpython.fm/episodes/show/91/top-10-data-science-stories-of-2016
Do you have a dirty, messy data problem? Whether you work as a software developer or as a data scientist, you've surely run across data that was malformed, incomplete, or maybe even wrong. Don't let messy data wreck your apps or generate wrong results.
What should you do? Listen to this episode of Talk Python To Me with Katharine Jarmul about the book she co-authored called Data Wrangling with Python and her PyCon UK presentation entitled How to Automate your Data Cleanup with Python.
https://talkpython.fm/episodes/show/90/data-wrangling-with-python
This special episode is hosted by Jonathon Morgan.
He went to the White House (the White House!) to interview DJ Patil, the Chief Data Scientist of the United States. DJ talked with Jonathon about the relationship between government and Silicon Valley, the White House’s leadership on data ethics, and why the first US Chief Data Scientist was actually George Washington. This was a really special experience, and we were honored at the invitation. Huge thanks to DJ and the White House for making this possible.
https://talkpython.fm/episodes/show/89/a-conversation-with-the-chief-data-scientist-of-the-united-states
In this episode we discuss why Python 3.6 is going to be awesome, kite: your friendly co-developing AI, and more!
https://pythonbytes.fm/episodes/show/6/python-3.6-is-going-to-be-awesome-kite-your-friendly-co-developing-ai
Django is a very popular Python web framework. One reason is you have many building blocks to drop in for large sections of your application. Need a full-on admin table editor backend? That's a few lines of code and boom you have a basic table editor.
This applies to many people. But those of us, myself included, who appreciate lightweight frameworks where we choose just what is included and piece together our web apps from best-of-breed components find this a turn off.
This week you'll meet Julia Elman and Mark Lavin, authors of Lightweight Django who are here to dispel the myth that Django apps have to be built out of large building blocks.
https://talkpython.fm/episodes/show/88/lightweight-django
This is Python Bytes, Python headlines and news deliver directly to your earbuds: episode 5, recorded on December 5, 2016. In this episode we discuss Legacy Python vs Python and why words matter and Request's 5 Whys retrospective.
https://pythonbytes.fm/episodes/show/5/legacy-python-vs-python-and-why-words-matter-and-request-s-5-whys-retrospective
This is Python Bytes, Python headlines and news deliver directly to your earbuds: episode 4: recorded on November 28, 2016. In this episode we cover the case for Python 3, asyncio, pyston, pydoc.io, and q.
https://pythonbytes.fm/episodes/show/4/python-3-is-just-fine-for-beginners-thank-you-q-is-awesome-for-debugging-and-more
If you could have any API you want for accessing data from Python, what would it look like? What would make it Pythonic? This week you'll hear about Pony ORM: Pony is a Python ORM with beautiful query syntax that lets you write your database queries using Python generators and lambdas.
https://talkpython.fm/episodes/show/87/ponyorm-the-most-pythonic-orm-yet
If you run into a problem with some API or Python code what do you do to solve it? I personally through a few keywords into google, sometimes even before checking the full docs.
Why does this work? Because invariably an excellent conversation and answer from StackOverflow comes back with just what I need.
This week you'll meet Martijn Pieters. One of the top Python contributors at StackOverflow with over 16,500 questions answered and a reputation of over 500,000.
https://talkpython.fm/episodes/show/86/python-at-stackoverflow
Welcome to Python Bytes. Python headlines delivered directly to your earbuds. In this episode we cover the new features in Python 3.6, text processing with Pynini, Python is 2nd most popular language on GitHub and more.
https://pythonbytes.fm/episodes/show/3/python-3.6-is-coming-and-it-s-awesome-plus-superior-text-processing-with-pynini
Do you have horribly convoluted things that need parsing? Obviously you'll learn a bunch of tips and tricks from this episode. But you'll see that advanced parsing is a gateway to many interesting computer science techniques.
Listen in as I speak with Erik Rose about his journey to parse weird things at Mozilla.
https://talkpython.fm/episodes/show/85/parsing-horrible-things-with-python
When was the last time you used a 3rd party package in Python? Have you recently pip installed SQLAlchemy? Maybe looked up the documentation on a package you found on PyPI?
The two core pieces of infrastructure involved are both freely available and open source: pip and PyPI as well as ReadTheDocs.
How are these funded? How well are they funded? It turns out that we are not doing a good job sustaining the underlying infrastructure in the Python ecosystem.
This week you'll meet four panelists for a discussion on the problem and its solutions.
https://talkpython.fm/episodes/show/84/are-we-failing-to-fund-python-s-core-infrastructure
Welcome to Python Bytes. Python headlines delivered directly to your earbuds. In this second episode we cover a couple of key python package releases, pycon, awesome python, python developer job prospects, and more!
https://pythonbytes.fm/episodes/show/2/pycon-awesome-python-python-developer-job-prospects-and-more
Welcome to Python Bytes. Python headlines delivered directly to your earbuds. In this first episode we cover PyData videos, safety-db project, and more!
https://pythonbytes.fm/episodes/show/1/intro-to-the-show-and-pip-9-is-out
Have you ever searched for a Python educational video? Maybe how to get started with Pyramid, or running queries with SQLAlchemy's ORM layer?
There is a good chance you've run across PyVideo.org. This amazing site catalogs over 5,000 Python videos from most of the recent Python conferences among other places. Browse by speaker, topic, event and more.
This week you'll meet Paul Logston who has taken over leadership of the project when it was in danger of going dormant.
https://talkpython.fm/episodes/show/83/python-videos-on-demand-at-pyvideo
Algorithms underpin almost everything we do in programming and in problem solving in general. Yet, many of us have partial or incomplete knowledge of the most important and common ones. In this episode, you'll meet Adit Bhargava, the author of the light and playful Grokking Algorithms: An illustrated guide book.
If you struggled to understand and learn the key algorithms, this episode is for you.
https://talkpython.fm/episodes/show/82/grokking-algorithms-in-python
The advances in Astronomy over the past century are both evidence of and confirmation of the highest heights of human ingenuity. We have learned by studying the frequency of light that the universe is expanding. By observing the orbit of Mercury that Einstein's theory of general relativity is correct.
It probably won't surprise you to learn that Python and data science play a central role in modern day Astronomy. This week you'll meet Jake VanderPlas, an astrophysicist and data scientist from University of Washington. Join Jake and me while we discuss the state of Python in Astronomy.
https://talkpython.fm/episodes/show/81/python-and-machine-learning-in-astronomy
What kind of applications can you build with python? You hear me featuring many people on this show that build websites, web services, or some data science driven application. Of course, all of those are wonderful but I know many of you have dreamed of building a game.
This episode I'm interviewing Joseph Cherlin. He created the game Epikos and the entire tool chain entirely in Python. He has a great story about how he came across Python, why he decided to use it in his game, and advice he has for anyone out there taking on a large project like this.
https://talkpython.fm/episodes/show/78/how-i-built-an-entire-game-and-toolchain-100-in-python
NoSQL and document dbs like MongoDB have made building fast scalable software that is easy to evolve and maintain much easier for a broad class of applications. Embeddable, file-based databases like SQLite have made "shipping" an application requiring a database a no brainer. The database just runs in process so there is no setup or maintenance.
Yet, when you try to intersect these two excellent capabilities, you'll find the options very limited. There just aren't many embeddable document databases. If you're a Python developer, and you want a native Python solution, the options are much slimmer still.
That's why I'm excited to introduce you to Markus Siemens and TinyDb. This is a 100% pure python, embeddable, pip-installable document DB for Python.
https://talkpython.fm/episodes/show/80/tinydb-a-tiny-document-db-written-in-python
Could you write me a Python app for the wide range of platforms out there? Oh, wait, I want them to be native GUI applications. And I need them on mobile (Android, iOS, tvOS, and watchOS) as well as major desktop apps. I also need them to appear indistinguishable from native apps (be a .app on macOS, .exe on Windows, etc).
What technology would you use for this? This week I'll introduce you to a wide set of small, focused and powerful tools that make all of this, and more, possible. We're speaking with Russell Keith-Magee, founder of the Beeware project.
https://talkpython.fm/episodes/show/79/beeware-python-tools
Many of you write to me and tell me how you appreciate the way my guests and I highlight a particular Python package at the end of each episode. Well if you enjoy that little segment, you're going to love this episode.
This week you'll meet Caleb Hattingh who wrote a great book called 20 Python Libraries You Aren't Using (But Should). He and I spend an hour digging into all the very powerful and interesting packages that you probably haven't heard of but will be super excited to use after you learn about them.
https://talkpython.fm/episodes/show/77/20-python-libraries-you-aren-t-using-but-should
Even with solar panels on your roof, it’s possible that your home is still being powered by fossil fuels. Climate innovator and Python developer Anna Schneider is trying to change that. At her company WattTime, consumers can source the cleanest energy available on the grid.
In this episode of Talk Python To Me, I talk to Anna about how Python powers WattTime, some popular open-source projects focused on renewable energy, and a few other Python based renewable energy startups.
https://talkpython.fm/episodes/show/76/renewable-python
Do you like to play games or solve puzzles? Chances are pretty good that you do. After all, what is programming and software development but one really elaborate puzzle?
On this episode of Talk Python To Me, you meet someone who pushed this idea of programming as a game to its logical conclusion. Alexander Liabakh is the creator of CheckIO and Empire of Code. CheckIO is a programming adventure game where you solve puzzles and share them with fellow players. Empire of Code is a tower defense game where part of the strategy is to actually program AI in Python.
https://talkpython.fm/episodes/show/75/pythonic-games-at-checkio
Have you heard of IronPython and Jython? These two alternate implementations of Python were created by Jim hugunin. They run on top of the .NET and JVM runtimes. On this episode going to look at the story of IronPython. It's been around for many years. Although the last few years, it's been somewhat stagnant.
That's why I am thrilled to introduce you to Alex Earl, who along with Benedikt Eggers, has become the maintainer of the IronPython project. It's great to see IronPython getting the attention it deserves. We'll talk about IronPython past, present, future on this episode of Talk Python To Me.
https://talkpython.fm/episodes/show/74/past-present-and-future-of-ironpython
In this episode we catch up with David Crook, a developer evangelist at Microsoft. He is a co-organizer for the Fort Lauderdale Machine Learning User Group and is involved in many more user groups and meetups. You hear about some really cool projects where they are using Python and TensorFlow to work on simple things like growing more food to help feed the world.
https://talkpython.fm/episodes/show/73/machine-learning-at-the-new-microsoft
https://talkpython.fm/episodes/show/72/fashion-driven-open-source-software-at-zalando
What happens when you take a tech-driven online fashion company that is experiencing explosive growth and infuse it with a deep open-source mission? You'll find out on this episode of Talk Python To Me.
We'll meet Lauri Apple and Rafael Caricio from Zalando where developers there have published almost 200 open source projects on Github.
https://talkpython.fm/episodes/show/71/soft-skills-the-software-developer-s-life-manual
Writing good, clean code and having a deep working knowledge of Python is critical to your success as a Python developer. But if you look at those who have truly excelled in their career, it's often because they bring something in addition to coding skills.
We all want to be the most successful and satisfied version of ourselves. But that's much easier said than done.
That's why I'm excited to introduce you to John Sonmez. He's had a brilliantly successful career as a developer and he wrote a book to help all of us do the same. It's called Soft Skills: The software developer's life manual and it's packed full of concrete, practical steps you can take to stand out in the tech industry.
Some of the best songs are cover songs of popular music. If you're a musician who wants to create a cover song and actually sell it, you'll be diving deep into complex agreements and legal agreements with record labels. Sounds like no fun to me.
But this is where Python comes to the rescue! The guys and girls over at Loudr are using Python to create a service for creating, selling, and distributing cover songs. This week you'll meet one of the co-founders, Josh Whelchel. He's here to tell us all the cool ways Python makes this possible, including a touch of machine learning!
https://talkpython.fm/episodes/show/70/pythonic-cover-songs-at-loudr
Do you have a blog? How many articles have you written for it? Do you find it hard to keep writing or hard to get started doing technical writing? We might be able to help you out with that this week.
You're probably aware that blogging is one of the key ways to establish yourself as a thought-leader in the industry. You'll make more connections, open more opportunities, and likely find your work more rewarding if you share your experiences and expertise through blogging.
But it can be challenging to keep writing or find time for writing. That's why I asked A. Jesse Jiryu Davis from MongoDB to share his thoughts on writing an excellent programming blog.
https://talkpython.fm/episodes/show/69/write-an-excellent-programming-blog
https://talkpython.fm/episodes/show/68/crossing-the-streams-with-podcast.-init
Have you listened to the other major Python podcast hosted by Tobias Macey and Chris Patti? It's called podcast.__init__ and, like this show, they have some excellent stories from the Python ecosystem on there weekly. So recently some listeners from both shows suggested the unimaginable: That we 'cross the streams'...
We, despite Egon's warning, are going to do it anyway. Recall in the movie ghost busters they defeat Gozer by doing just that.
This time when we cross the streams the result is less dramatic, but something awesome comes out the other side too! A fun podcast episode.
Does a computer see in color or black and white? It's time to find out on this episode of Talk Python to Me. Join Adrian Rosebrock as we talk about PyImageSearch, OpenCV, and building computer vision systems with Python and OpenCV.
This show is part theory, part history, part programming technicals and all coolness. Hope you enjoy it as much as we did!
Let's talk about your unit testing strategy. How do you select the tests you write or do you even write tests? Typically, when you write a test you have to think of what you are testing and the exact set of inputs and outcomes you're looking for. And there are strategies for this. Try to hit the boundary conditions, the most common use-cases, seek out error handling and so on.
We all do this to varying degrees of success. But we if we didn't have to do this. What if there was some kind of way to express the relationship between inputs and outputs but your tests could explore the problem space themselves?
Well, there is a way and it's called property-based testing. This week you'll learn about Hypothesis, the most popular property based testing system created by David MacIver.
https://talkpython.fm/episodes/show/67/property-based-testing-with-hypothesis
Python is a wonderful programming language that is often underestimated because it's so clear and simple. Oftentimes people mistake this simplicity for being too simple for real-programs. After all, you didn't even struggle to get your program to link against an incompatible static library or battle a DLL version mismatch in your Python app today did you?
Usually we find this simple and clear programming language to be powerful and fast. But what happens when it's not fast enough? Do you have to stop and rewrite it in C, C#, or Java?
Well before you do something drastic, Mike Mueller is here to teach us the techniques and steps to determine why our Python programs might be slow and give us some tips to make them faster.
https://talkpython.fm/episodes/show/66/faster-python-programs-measure-don-t-guess
Long gone are the days of the web acting as just linked documents and glorified brochures. Web apps of today are just that, rich interactive applications. But unlike desktop apps of old, these are apps with 100,000's or even millions of concurrent users.
We expect that these apps will instantly reflect changes to the data, potentially made by any of the users connected to the system while we are using them.
This has put a strain on the web servers, databases, and architecture of our web apps. Technology has responded by delivering amazing real-time capabilities with things like websockets and SignalR at the client layer and event driven systems on the web servers. But what about the database? Could it be events all the way down?
That was the goal of RethinkDB's cofounders when they pitched it to YCombinator.
https://talkpython.fm/episodes/show/65/jump-on-the-real-time-web-with-rethinkdb
What is the most powerful part of the Python ecosystem? Well, the ability to say "pip install magic_library" has to be right near the top. But do you what powers the Python Package Index and the people behind it? Did you know it does over 300 TB traffic each month these days?
Just me as we chat with Donald Stufft to look inside Python's package infrastructure.
https://talkpython.fm/episodes/show/64/inside-the-python-package-index
https://talkpython.fm/episodes/show/62/san-diego-technology-immersion-group-learns-python
What's it like to learn Python? Yes, some of you may have just picked up the language while others have lived and breathed it for years. Either way, you may have some hindsight bias towards the experience. What was hard? What were your expectations? What delighted you?
Consider this episode your time-capsule to explore just this experience, 10 months in the making. It starts on July 22, 2015 with a unique user group / meetup called San Diego Technology Immersion Group or SDTIG for short. This group spends 6-8 months deep diving together into a topic rather than hearing a different 1 hour topic per month. We'll follow the organizers and students before many of them learn a line of Python all the way to the end 8 months later after they've studied the language, web, and data science frameworks.
https://talkpython.fm/episodes/show/61/free-software-free-people
How often do you read some news headline about free speech denied and human rights being suppressed and think that sucks but there is nothing I can do about it from my distant perspective. I guess you could vote slightly differently in the next election and maybe, just maybe, it will have a small impact in 4 years time.
If you're a technologist or developer, you have way more power than you realize. Still the challenge is could you use your skills to make a difference? Maybe you could remove a layer surveillance or add a layer of anonymity for the affected people.
If the answer is yes, and it probably is, then the question becomes would you do and even should you act? This week on Talk Python To Me you'll meet Pete Fein who spent two years of his life helping others using his technical skills. His story is both inspiring and amazing. It will show you what can be done to help people in need.
You've heard me talk previously about scaling Python and Python performance on this show. But on this episode I'm bringing you a very interesting project pushing the upper bound of Python performance for a certain class of applications.
You'll meet Braxton McKee from Ufora. They have developed an entirely new Python runtime that is focused on horizontally scaling Python applications across 1000's of CPU cores and even GPUs. They describe it as "compiled, automatically parallel python for data science".
https://talkpython.fm/episodes/show/60/scaling-python-to-1000-s-of-cores-with-ufora
What do you do when you are a high caliber mathematician or scientist and you want share your algorithms and code? This sounds like a job for github, but the problem is often this work is done on proprietary platforms such as Magma, Matlab, Mathematica or others.
Not only can you not share your licenses for say, Matlab, but there are often proprietary separate libraries and tools for specialized work. These are expensive products. One example from my distant past was using the Wavelet toolbox on Matlab. Matlab is 2,000 euros and the wavelet library is another 1,000 euros! So to share my code, you must have both licenses for yourself. This is a problem.
Well, if you're William Stein you take this problem and turn it into an opportunity to build an open source competitor to Matlab and related platforms. This episode is all about SageMath, an open source, feature rich option for scientists and mathematicians built by over 500 contributors and consisting of over 500k lines of Python and Cython code.
https://talkpython.fm/episodes/show/59/sagemath-open-source-is-ready-to-compete-in-the-classroom
What do you focus on once you've learned the core concepts of the Python programming language and ecosystem?
Obviously, knowing a few fundamental packages in your space is critical. If you're a web developer, you should probably know flask or pyramid, and sqlalchemy really well. If you're a data scientist, import pandas, numpy, matplotlib need to be something you type often and intuitively.
But then what? Well I have a few topics for you! This week you'll meet Mark Summerfield, prolific author of many Python books. We spend time digging into the ideas behind his book Python in Practice: Create Better Programs Using Concurrency, Libraries, and Patterns.
What I really like about these topics is that they have a "long shelf life". You find them relevant over time even as frameworks come and go.
https://talkpython.fm/episodes/show/58/create-better-python-programs-with-concurrency-libraries-and-patterns
When you think about the performance of your software, there is nothing more low level and fundamental than how your code executes on the CPU itself. Many of us study and try to understand how to maximize performance at this low level. But few are in a position to define what happens at this level.
That's why I'm thrilled to share the work that Intel, the largest PC chip manufacture, is doing specifically to make Python faster and to make their chips execute Python even better.
This week you'll meet David Stewart, manager in the Intel Data Center Software Technology group at Intel. We'll discuss the wide variety of work Intel is doing in open source and Python.
https://talkpython.fm/episodes/show/57/python-performance-from-the-inside-out-at-intel
You likely know that Python is one of the fastest growing languages for data science.
This is a discipline that combines the scientific inquiry of hypotheses and tests, the mathematical intuition of probability and statistics, the AI foundations of machine learning, a fluency in big data processing, and the Python language itself. That is a very broad set of skills we need to be good data scientists and yet each one is deep and often hard to understand.
That's why I'm excited to speak with Joel Grus, a data scientist from Seattle. He wrote a book to help us all understand what's actually happening when we employ libraries such as scikit-learn or numpy. It's called Data Science from Scratch and that's the topic of this week's episode.
https://talkpython.fm/episodes/show/56/data-science-from-scratch
https://talkpython.fm/episodes/show/54/enterprise-software-with-python
How often have people asked what language / technology you work in and when you answered Python they got a little confused and asked, what can you actually build with Python? What type of apps? The implication being Python is just a notch above Bash scripts. That real things aren't built with Python but rather Java, C#, Objective-C and so on.
Mahmoud Hashemi and I might be able to help you put some real evidence and experience behind your response. On episode 54 of Talk Python To Me, I talk with Mahmoud about his new online course he wrote for O'Reilly entitled Enterprise Software in Python. You'll hear many real-world examples from his experience inside PayPal and more.