See the full show notes for this episode on the website at talkpython.fm/318

#318: Measuring your ML impact with CodeCarbon

Talk Python to Me is a weekly podcast hosted by developer and entrepreneur Michael Kennedy. We dive deep into the popular packages and software developers, data scientists, and incredible hobbyists doing amazing things with Python. If you're new to Python, you'll quickly learn the ins and outs of the community by hearing from the leaders. And if you've been Pythoning for years, you'll learn about your favorite packages and the hot new ones coming out of open source.

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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.



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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 ---

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Follow Michael on Mastodon: mkennedy


#466: Pydantic Performance Tips

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


#465: The AI Revolution Won't Be Monopolized

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


#464: Seeing code flows and generating tests with Kolo

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


#463: Running on Rust: Granian Web Server

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


#318: Measuring your ML impact with CodeCarbon

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