Flask is one of the most important Python web frameworks and powers a bunch of the internet. David Lord, Flask's lead maintainer is here to give us an update on the state of Flask and Pallets in 2024. If you care about where Flask is and where it's going, you'll definitely want to listen in. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Talk Python Courses Links from the show David on Mastodon: @davidism David on X: @davidism State of Pallets 2024 FlaskCon Talk: youtube.com FlaskCon: flaskcon.com FlaskCon 2024 Talks: youtube.com Pallets Discord: discord.com Pallets Eco: github.com JazzBand: jazzband.co Pallets Github Org: github.com Jinja: github.com Click: github.com Werkzeug: github.com MarkupSafe: github.com ItsDangerous: github.com Quart: github.com pypistats: pypistats.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

If you want to get better at something, often times the path is pretty clear. If you get better at swimming, you go to the pool and practice your strokes and put in time doing the laps. If you want to get better at mountain biking, hit the trails and work on drills focusing on different aspects of riding. You can do the same for programming. Reuven Lerner is back on the podcast to talk about his book Pandas Workout. We dive into strategies for learning Pandas and Python as well as some of his workout exercises. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Scalable Path Talk Python Courses Links from the show Reuven Lerner on Twitter: @reuvenmlerner Pandas Workout Book: manning.com Bamboo Weekly: Solar eclipse: bambooweekly.com Bamboo Weekly: Avocado hand: bambooweekly.com Scaling data science across Python and R: 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

Python is special. It's used by the big tech companies but also by those you would rarely classify as developers. On this episode, we get a look inside how Python is being used at a Children's Hospital to speed and improve patient care. We have Dr. Somak Roy here to share how he's using Python in his day to day job to help kids get well a little bit faster. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Posit Talk Python Courses Links from the show Somak Roy: linkedin.com Cincinnati Children's Hospital: cincinnatichildrens.org CNVkit: Genome-wide copy number: readthedocs.io cnaplotr: github.com hgvs: readthedocs.io openpyxl: readthedocs.io Hera is an Argo Python SDK: github.com insiM: in silico Mutator software for bioinformatics: github.com Bamsurgeon: github.com pysam - An interface for reading and writing SAM files: readthedocs.io Scientists rename human genes to stop Microsoft Excel from misreading them as dates: theverge.com BioPython: biopython.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

Python is one of the most popular languages of the current era. It dominates data science, it an incredible choice for web development, and its many people's first language. But it's not super great on front-end programing, is it? Frameworks like React, Vue and other JavaScript frameworks rule the browser and few other languages even get a chance to play there. But with pyscript, which I've covered several times on this show, we have the possibility of Python on the front end. Yet it's not really a front end framework, just a runtime in the browser. That's why I'm excited to have Ken Kinder on the podcast to talk about his project PuePy, a reactive frontend framework in Python. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Code Comments Talk Python Courses Links from the show Michael's Code in a Castle Course: talkpython.fm/castle Ken Kinder: @bouncing@twit.social PuePy: puepy.dev PuePy Docs: docs.puepy.dev PuePy on Github: github.com pyscript: pyscript.net VueJS: vuejs.org Hello World example: docs.puepy.dev Tutorial: docs.puepy.dev Tutorial running at pyscript.com: pyscript.com Micropython: micropython.org Pyodide: pyodide.org PgQueuer: github.com Writerside: jetbrains.com Michael's PWA pyscript app: github.com Michael's demo of a PWA pyscript app: youtube.com Python iOS Web App with pyscript and offline PWAs video: 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

I've gathered a group of Python experts who have been thinking deeply about where Python is going and who have lived through where it has been. This episode is all about near-term Python trends and things we each believe will be important to focus on as Python continues to grow. Our panelists are Jodie Burchell, Carol Willing, and Paul Everett. Episode sponsors Code Comments Posit Talk Python Courses Links from the show Shiny course at Talk Python: talkpython.fm/shiny Jodie Burchell: @t_redactyl Carol on Mastodon: @willingc@hachyderm.io Paul Everitt: @paulweveritt 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

I have a special episode for you this time around. We're coming to you live from PyCon 2024. I had the chance to sit down with some amazing people from the data science side of things: Jodie Burchell, Maria Jose Molina-Contreras, and Jessica Greene. We cover a whole set of recent topics from a data science perspective. Though we did have to cut the conversation a bit short as they were coming from and go to talks they were all giving but it was still a pretty deep conversation. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Code Comments Talk Python Courses Links from the show Jodie Burchell: @t_redactyl Jessica Greene: linkedin.com Maria Jose Molina-Contreras: linkedin.com Talk Python's free Shiny course: talkpython.fm/shiny 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're using Pydantic and it seems pretty straightforward, right? But could you adopt some simple changes to your code that would make it a lot faster and more efficient? Chances are, you'll find a couple of the tips from Sydney Runkle that will do just that. Join us to talk about Pydantic performance tips here on Talk Python. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Code Comments Talk Python Courses Links from the show Sydney Runkle: linkedin.com Pydantic: pydantic.dev Performance docs: docs.pydantic.dev Union tips: docs.pydantic.dev Sydney's presentation slides: docs.google.com JSON to Pydantic: jsontopydantic.com Samuel talking FastUI: talkpython.fm CodeFlash: codeflash.ai Codspeed: codspeed.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

There hasn't been a boom like the AI boom since the .com days. And it may look like a space destined to be controlled by a couple of tech giants. But Ines Montani thinks open source will play an important role in the future of AI. I hope you join us for this excellent conversation about the future of AI and open source. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Porkbun Talk Python Courses Links from the show Ines Montani on Twitter: @_inesmontani spaCy: spacy.io Prodigy App: prodi.gy Ines' presentation at PyCon Lithuania: youtube.com LM Studio: lmstudio.ai Little Bobby Tables: xkcd.com spaCy and NLP course: talkpython.fm Use my link to get your .app, .dev, or .foo domain for just $1 right now at Porkbun: talkpython.fm/porkbun 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 want to look inside your Django request? How about all of your requests in development and see where they overlap? If that sounds useful, you should check out Kolo. It's a pretty incredible extension for your editor (VS Code at the moment, more editors to come most likely). We have Wilhelm Klopp on to tell us all about it. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Talk Python Courses Links from the show Wil on Twitter: @wilhelmklopp Kolo: kolo.app Kolo's info repo: github.com Kolo Playground: play.kolo.app Generating tests with Kolo: kolo.app 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 web app with Python using Flask, Django, FastAPI, or even Emmett. It works great on your machine. How do you get it out to the world? You'll need a production-ready web server. On this episode, we have Giovanni Barillari to tell us about his relatively-new server named Granian. It promises better performance and much better consistency than many of the more well known ones today. Episode sponsors Neo4j Talk Python Courses Links from the show New spaCy course: talkpython.fm Giovanni: @gi0baro Granian: github.com Emmett: emmett.sh Renoir: 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

This episode dives into some of the most important data science libraries from the Python space with one of its pioneers: Wes McKinney. He's the creator or co-creator of pandas, Apache Arrow, and Ibis projects and an entrepreneur in this space. Episode sponsors Neo4j Mailtrap Talk Python Courses Links from the show Wes' Website: wesmckinney.com Pandas: pandas.pydata.org Apache Arrow: arrow.apache.org Ibis: ibis-project.org Python for Data Analysis - Groupby Summary: wesmckinney.com/book Polars: pola.rs Dask: dask.org Sqlglot: sqlglot.com Pandoc: pandoc.org Quarto: quarto.org Evidence framework: evidence.dev pyscript: pyscript.net duckdb: duckdb.org Jupyterlite: jupyter.org Djangonauts: djangonaut.space 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 use Python in an academic setting? Maybe you run a research lab or teach courses using Python. Maybe you're even a student using Python. Whichever it is, you'll find a ton of great advice in this episode. I talk with Keiland Cooper about how he is using Python at his neuroscience lab at the University of California, Irvine. Episode sponsors Neo4j Posit Talk Python Courses Links from the show Keiland's website: kwcooper.xyz Keiland on Twitter: @kw_cooper Keiland on Mastodon: @kwcooper@fediscience.org Journal of Open Source Software: joss.readthedocs.io Avalanche project: avalanche.continualai.org ContinualAI: continualai.org Executable Books Project: executablebooks.org eLife Journal: elifesciences.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

Do you find yourself or your team building internal apps frequently for your company? Are you familiar with the term "forms over data"? They are super empowering for your org but they can be pretty repetitive and you might find yourself spending more time than you'd like working on them rather than core products and services. I invited Jimmy Chan from Dropbase to tell us about their service who's tagline is "Build internal web apps with just Python." It's a cool service and a fun conversation. Episode sponsors Mailtrap Talk Python Courses Links from the show Build internal web apps with just Python.: dropbase.io Dropbase on Github: github.com Dropbase @ LinkedIn: linkedin.com Dropbase on Twitter: twitter.com Jimmy Chan: linkedin.com Jimmy on Twitter: twitter.com Dropbase Docs: docs.dropbase.io Dropbase: dropbase.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

We all know that tools like ChatGPT have really empowered developers to tackle bigger problems. Are you using TailwindCSS and need a login page? Try asking Chat "What is the HTML for a login page with the login username, password, and button in its own section in the center of the page?" It will literally give you a first pass version of it. But how far can you push this? Fred Tubiermont may have taken it farther than most. He built a functioning SaaS product with paying customers by only using ChatGPT and Python. It's fascinating to hear his story. Episode sponsors Mailtrap Talk Python Courses Links from the show Frederick Tubiermont: linkedin.com The #1 AI Jingle Generator: aijinglemaker.com Fred's YouTube Channel: youtube.com AI Coding Club: aicodingclub.com No Code: saashub.com Prompt Engineering 101 - Crash Course & Tips: youtube.com gpt-engineer: github.com Instant Deployments, Effortless Scale: railway.app Self-hosting with superpowers.: coolify.io The newsletter platform built for growth.: beehiiv.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

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 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'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 Series: How Malicious Python Code Gains Execution: blog.phylum.io 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