What is the state of serverless computing and Python in 2024? What are some of the new tools and best practices? We are lucky to have Tony Sherman who has a lot of practical experience with serverless programming on the show. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Mailtrap Talk Python Courses Links from the show Tony Sherman on Twitter: twitter.com Tony Sherman: linkedin.com PyCon serverless talk: youtube.com AWS re:Invent talk: youtube.com Powertools for AWS Lambda: docs.powertools.aws.dev Pantsbuild: The ergonomic build system: pantsbuild.org aws-lambda-power-tuning: github.com import-profiler: github.com AWS Fargate: aws.amazon.com Run functions on demand. Scale automatically.: digitalocean.com Vercel: vercel.com Deft: deft.com 37 Signals We stand to save $7m over five years from our cloud exit: world.hey.com The Global Content Delivery Platform That Truly Hops: bunny.net Watch this episode on YouTube: youtube.com --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

We've spoken previously about security and software supply chains and we are back at it this episode. We're diving in again with Charles Coggins. Charles works at a software supply chain company and is on to give us the insiders and defender's perspective on how to keep our Python apps and infrastructure safe. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Mailtrap Talk Python Courses Links from the show Pick a Python Lockfile and Improve Security: blog.phylum.io Bad Beat Poetry: blog.phylum.io PEP 665 – A file format to list Python dependencies for reproducibility of an application: peps.python.org PEP 517 – A build-system independent format for source trees: peps.python.org PEP 518 – Specifying Minimum Build System Requirements for Python Projects: peps.python.org Lockfiles should be committed on all projects: classic.yarnpkg.com An Overview of Software Supply Chain Security: tldrsec.com Typosquatting: docs.phylum.io Common Attack Pattern Enumeration and Classification: capec.mitre.org Dependency Confusion: docs.phylum.io Expired Author Domains: docs.phylum.io Unverifiable Dependency: docs.phylum.io Repo Jacking: Hidden Danger in Broken Links: blog.phylum.io Software Libraries Are Terrifying: medium.com phylum 0.43.0: pypi.org linguist: github.com rich-codex ⚡️📖⚡️: ewels.github.io Phylum Community Discord: discord.gg The dream is dead?: mastodon.social When "Everything" Becomes Too Much: The npm Package Chaos of 2024: socket.dev pip-tools: github.com Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

Do you know what custom GPTs are? They're configurable and shareable chat experiences with a name, logo, custom instructions, conversation starters, access to OpenAI tools, and custom API actions. And, you can build them with Python! Ian Maurer has been doing just that and is here to share his experience building them. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Neo4j Talk Python Courses Links from the show Ian on Twitter: @imaurer Mobile Navigation: openai.com What is a Custom GPT?: imaurer.com Mobile Navigation: openai.com FuzzTypes: Pydantic library for auto-correcting types: github.com pypi-gpt: github.com marvin: github.com instructor: github.com outlines: github.com llamafile: github.com llama-cpp-python: github.com LLM Dataset: llm.datasette.io Plugin directory: llm.datasette.io Data exploration at your fingertips.: visidata.org hottest new programming language is English: twitter.com OpenAI & other LLM API Pricing Calculator: docsbot.ai Vector DB Comparison: vdbs.superlinked.com bpytop: github.com Source Graph: about.sourcegraph.com Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

Interested in data science but you're not quite working in it yet? In software, getting that very first job can truly be the hardest one to land. On this episode, we have Avery Smith from Data Career Jumpstart here to share his advice for getting your first data job. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Posit Talk Python Courses Links from the show Avery Smith: www.linkedin.com Data Career Jumpstart: www.datacareerjumpstart.com Data Nerd Site: datanerd.tech Write C# LINQ queries to query data: learn.microsoft.com A faster way to build and share data apps: streamlit.io Plotly Dash: dash.plotly.com Michael's Keynote: State of Python in 2024: youtube.com Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

Do you have data that you pull from external sources or is generated and appears at your digital doorstep? I bet that data needs processed, filtered, transformed, distributed, and much more. One of the biggest tools to create these data pipelines with Python is Dagster. And we are fortunate to have Pedram Navid on the show this episode. Pedram is the Head of Data Engineering and DevRel at Dagster Labs. And we're talking data pipelines this week at Talk Python. Episode sponsors Talk Python Courses Posit Links from the show Rock Solid Python with Types Course: training.talkpython.fm Pedram on Twitter: twitter.com Pedram on LinkedIn: linkedin.com Ship data pipelines with extraordinary velocity: dagster.io dagster-open-platform: github.com The Dagster Master Plan: dagster.io data load tool (dlt): dlthub.com DataFrames for the new era: pola.rs Apache Arrow: arrow.apache.org DuckDB is a fast in-process analytical database: duckdb.org Ship trusted data products faster: www.getdbt.com Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

Have you ever been wait around for pip to do its thing while installing packages or syncing a virtual environment or through some higher level tool such as pip-tools? Then you'll be very excited to hear about the tool just announced from Astral called uv. It's like pip, but 100x faster. Charlie Marsh from Ruff fame and founder of Astral is here to dive in. Let's go. Episode sponsors Neo4j Talk Python Courses Links from the show Charlie Marsh on Twitter: @charliermarsh Charlie Marsh on Mastodon: @charliermarsh Astral: astral.sh uv: github.com Ruff: github.com Ruff Rules: docs.astral.sh When "Everything" Becomes Too Much: The npm Package Chaos of 2024: socket.dev Talk Python's free Audio AI Course: training.talkpython.fm Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

Have you heard of Quart? It's the fully-async version of Flask created by Philip Jones who is working closely with the Flask team on these parallel projects. The TL;DR; version is that if you want to take advantage of async and await and you're using Flask, you want to give Quart a solid look. We've spoken to Philip previously about Quart. This time around here's here to share his top Quart extensions and libraries you can adopt today. Episode sponsors Posit Talk Python Courses Links from the show Pallets Team on ExTwitter: @PalletsTeam Quart Framework: quart.palletsprojects.com Using Quart Extensions: quart.palletsprojects.com Quart Tasks: quart-tasks.readthedocs.io Quart Minify: github.com Quart Db: github.com Hypercorn: github.com Quart-CORS: github.com Quart-Auth: github.com Quart-Rate: github.com Quart-Schma: github.com Flask-Socket: github.com Quart-SqlAlchemy: github.com Flask-Login: github.com greenback: github.com secure: github.com msgspec: jcristharif.com Server-Sent Events: pgjones.gitlab.io Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

Are you interested in contributing to Django? Then there is an amazing mentorship program that helps Python and Django enthusiasts, because contributes and potentially core developers of Django. It's called Djangonauts and their slogan is "where contributors launch." On this episode, we have Sarah Boyce from the Django team and former Djangonaut and now Djangonaut mentor, Tushar Gupta. Not only is this excellent for the Django community, many of other open source communities would do well to keep an eye on how this creative project is working. Episode sponsors Neo4j Posit Talk Python Courses Links from the show Sarah on Mastodon: @sarahboyce@mastodon.social Sarah on LinkedIn: linkedin.com Tushar on Twitter: @tushar5526 Djangonaut Space on Mastodon: @djangonaut@indieweb.social Djangonaut Space on Twitter: @djangonautspace Djangonaut Space on LinkedIn: linkedin.com Website: djangonaut.space Djangonaut Space Launch Video: youtube.com Sessions: djangonaut.space Djangonaut Space Interest Form: google.com/forms Program: github.com Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

You've built an awesome set of APIs and you have a wide array of devices and clients using them. Then you need to upgrade an end point or change them in a meaningful way. Now what? That's the conversation I dive into over the next hour with Stanislav Zmiev. We're talking about Versioning APIs. Episode sponsors Neo4j Sentry Error Monitoring, Code TALKPYTHON Talk Python Courses Links from the show Stanislav Zmiev: github.com Monite: monite.com Cadwyn: github.com Stripe API Versioning: stripe.com API Versioning NOtes: github.com FastAPI-Versioning: github.com Flask-Rebar: readthedocs.io Django Rest Framework Versioning: django-rest-framework.org pytest-fixture-classes: github.com Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

Building web UIs in Python has always been in interesting proposition. On one end, we have a the full web design story with artisanal HTML and CSS. On another end there are several Python platforms that aim to the bring RAD, rapid app development, style of building with Python. Those can be great, and I've covered a couple of them, but they usually reach a limit on what they can do or how they integrate with the larger web ecosystem. On this episode, we have Samuel Colvin to share his latest exciting project FastUI. With FastUI, you build responsive web applications using React without writing a single line of JavaScript, or touching npm. Yet designers and other tools can focus on React front-ends for a professional SPA like app experience. Episode sponsors bright data Sentry Error Monitoring, Code TALKPYTHON Talk Python Courses Links from the show Samuel on Mastodon: fosstodon.org Samuel on X: x.com FastUI: github.com FastUI Demos: fastui-demo.onrender.com FastAPI: fastapi.tiangolo.com Pydantic: pydantic.dev How Did REST Come To Mean The Opposite of REST Article: htmx.org Tailwind UI: tailwindui.com Dropbase: dropbase.io Anvil: anvil.works Flutter code example: github.com ReactJS code example: github.com Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

So you've created a Python-based open source project and it's started to take off. You're getting contributors, lots of buzz in the podcast space, and more. But you have that day job working on Java. How do you make the transition from popular hobby project to full time job? After all, you are giving away your open source project for free, right? Well, on this episode, I have put together an amazing panel of guests who all have done exactly this: Turned their project into full time work and even companies in some cases. We have Samuel Colvin, Gina Häußge, Sebastián Ramírez, Charlie Marsh, Will McGugan and Eric Holscher on to share their stories. Episode sponsors Basedash Sentry Error Monitoring, Code TALKPYTHON Talk Python Courses Links from the show Will McGugan: @willmcgugan Charlie Marsh: @charliermarsh@hachyderm Sebastián Ramírez: @tiangolo Samuel Colvin: @samuel_colvin Gina on Mastodon: chaos.social/@foosel Eric Holscher: @ericholscher Pydantic: pydantic.dev Astral (makes of Ruff): astral.sh Octoprint: octoprint.org Read the Docs: readthedocs.com FastAPI: fastapi.tiangolo.com Textual (makes of Rich): textualize.io Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

It's an exciting time for the capabilities of Python. We have the Faster CPython initiative going strong, the recent async work, the adoption of typing and on this episode we discuss a new isolation and parallelization capability coming to Python through sub-interpreters. We have Eric Snow who spearheaded the work to get them added to Python 3.12 and is working on the Python API for 3.13 along with Anthony Shaw who has been pushing the boundaries of what you can already do with subinterpreters. Episode sponsors Pybites PDM Sentry Error Monitoring, Code TALKPYTHON Talk Python Courses Links from the show Guests Anthony Shaw: @tonybaloney@fosstodon.org Eric Snow: @ericsnowcurrently@mastodon.social PEP 684 – A Per-Interpreter GIL: peps.python.org PEP 734 – Multiple Interpreters in the Stdlib: peps.python.org Running Python Parallel Applications with Sub Interpreters: fosstodon.org pytest subinterpreters: fosstodon.org Long-Term Vision for a Parallel Python Programming Model?: fosstodon.org Hypercorn Server: github.com msgspec: jcristharif.com Dill package: pypi.org Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

Why is Python so popular? There is plenty of room for debate on this but one solid reason is it's easy to adopt, easy to use, and caters to people who are not quite developers/data scientists but need to do some computing. Do you know where there largest untapped set of that group hang out? Excel. That's why it's super exciting that Python is now going to be built directly into Excel. Just go into a cell and type =PY and you're off writing full Python 3 code that is backed by a lite Anaconda distribution of Python. And we have Dr. Sarah Kaiser here to give us the rundown on Python in Excel. Episode sponsors Posit Pybites PDM Talk Python Courses Links from the show Sarah's website: sckaiser.com Sarah on Mastodon: @crazy4pi314@mathstodon.xyz Get started with Python in Excel: microsoft.com Python in SQL Server: microsoft.com 8 of the Biggest Excel Mistakes of All Time: blog.hurree.co Security and Python in Excel: microsoft.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

When you run your code in the cloud, how much do you know about where it runs? I mean, the hardware it runs on and the data center it runs in? There are just a couple of hyper-scale cloud providers in the world. This episode is a very unique chance to get a deep look inside one of them: Microsoft Azure. Azure is comprised of over 200 physical data centers, each with 100,000s of servers. A look into how code runs on them is fascinating. Our guide for this journey will be Mark Russinovich. Mark is the CTO of Microsoft Azure and a Technical Fellow, Microsoft's senior-most technical position. He's also a bit of a programming hero of mine. Even if you don't host your code in the cloud, I think you'll enjoy this conversation. Let's dive in. Episode sponsors Posit Pybites PDM Talk Python Courses Links from the show Mark Russinovich: @markrussinovich Mark Russinovich on LinkedIn: linkedin.com SysInternals: learn.microsoft.com Zero Day: A Jeff Aiken Novel: amazon.com Inside Azure Datacenters: youtube.com What runs chatgpt?: youtube.com Azure Cobalt ARM chip: servethehome.com Closing talk by Mark at Ignite 2023: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

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. Episode sponsors Talk Python Courses Links from the show Sydney Runkle: linkedin.com Pydantic: pydantic.dev Code Combat: codecombat.com Humanitarian Toolbox: www.htbox.org PyCon 2024: pycon.org Good first issue example: github.com Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

Special crossover episode of Python Bytes to wrap up 2023. Topics include: Michael #1: Hatch v1.8 Brian #2: svcs : A Flexible Service Locator for Python Michael #3: Steering Council 2024 Term Election Results Brian #4: Python protocols. When to use them in your projects to abstract and decoupling ExtrasJoke: Joke: The dream is dead? Episode sponsors Posit Talk Python Courses

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. Episode sponsors Posit Talk Python Courses Links from the show Jim Crist-Harif: jcristharif.com Jim @ GitHub: github.com Jim @ Mastdon: @jcristharif@hachyderm.io msgspec: github.com Projects using msgspec: github.com msgspec on Conda Forge: anaconda.org msgspec on PyPI: pypi.org Litestar web framework: litestar.dev Litestar episode: talkpython.fm Pydantic V2 episode: talkpython.fm JSON parsing with msgspec article: pythonspeed.com msgspec bencharmks: jcristharif.com msgspec vs. pydantic v1 and pydantic v2: github.com Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

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. Episode sponsors Talk Python Courses Links from the show Brett Cannon: @brettcannon@fosstodon.org Syntactic sugar series: snarky.ca Syntactic sugar: wikipedia.org Unravelling attribute access in Python: snarky.ca Unravelling binary arithmetic operations: snarky.ca Unravelling the import statement: snarky.ca record-type: pypi.org Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

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. Episode sponsors Posit Talk Python Courses Links from the show David Qiu: linkedin.com Jupyter AI: jupyter-ai.readthedocs.io Asking about something in your notebook: jupyter-ai.readthedocs.io Generating a new notebook: jupyter-ai.readthedocs.io Learning about local data: jupyter-ai.readthedocs.io Formatting the output: jupyter-ai.readthedocs.io Interpolating in prompts: jupyter-ai.readthedocs.io JupyterCon 2023 Talk: youtube.com PyData Seattle 2023 Talk: youtube.com Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

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. Episode sponsors Posit Python Tutor Talk Python Courses Links from the show Guests Wolf Vollprecht: github.com/wolfv Ruben Arts: github.com/ruben-arts pixi: prefix.dev Prefix: prefix.dev Launching pixi: prefix.dev Conda: docs.conda.io Conda Forge: conda-forge.org NixOS: nixos.org Packaging Con 2023: packaging-con.org Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy