Talk Python To Me

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.

Links from the show

Max on Twitter: @mistercrunch
Promptimize: github.com
Introducing Promptimize ("the blog post"): preset.io
Preset: preset.io
Apache Superset: Modern Data Exploration Platform episode: talkpython.fm
ChatGPT: chat.openai.com
LeMUR: assemblyai.com
Microsoft Security Copilot: blogs.microsoft.com
AutoGPT: github.com
Midjourney: midjourney.com
Midjourney generated pytest tips thumbnail: talkpython.fm
Midjourney generated radio astronomy thumbnail: talkpython.fm
Prompt engineering: learnprompting.org
Michael's ChatGPT result for scraping Talk Python episodes: github.com
Apache Airflow: github.com
Apache Superset: github.com
Tay AI Goes Bad: theverge.com
LangChain: github.com
LangChain Cookbook: github.com
Promptimize Python Examples: github.com
TLDR AI: tldr.tech
AI Tool List: futuretools.io
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm

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Talk Python Training

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.

Links from the show

Koen on Twitter: @mr_le_fox
PySport on Twitter: @PySportOrg
Calling R from Python: medium.com
DuckDB: duckdb.org
PySport Playground: playground.pysport.org
NFLVerse: github.com
NBA Stats: nba.com
Sports Databases: opensource.pysport.org
Data sets: opensource.pysport.org
Visualizations: opensource.pysport.org
I/O: opensource.pysport.org
Models: opensource.pysport.org
Scrapers/APIs: opensource.pysport.org
Fast F1: docs.fastf1.dev
Fast F1 graphics: docs.fastf1.dev
Pysport Intro: pysport.org

New Talk Python Training Apps: talkpython.fm
Michael's blog post about the apps: mkennedy.codes
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm

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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.

Links from the show

Sebastián Ramírez: @tiangolo
Samuel Colvin: @samuel_colvin

FastAPI: fastapi.tiangolo.com
Pydantic: pydantic.dev
Pydantic V2 Pre Release: pydantic.dev
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm

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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.


Links from the show

Ponder: ponder.io
generally intelligent: generallyintelligent.com
Wherobots: wherobots.ai
Neptyne: neptyne.com
Nixtla: nixtla.io
Predibase: predibase.com
Pynecone: pynecone.io
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm

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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.

Links from the show

Jay Miller: @kjaymiller
Mario Munoz: @[email protected]
Ray McLendon: linkedin.com
Nick Muoh: @[email protected]
Sean Tibor: @[email protected]
Chris Williams: @[email protected]

Python Community News: youtube.com
The Birth & Death of JavaScript: destroyallsoftware.com
Talk Python episode with Rivers Cuomo: talkpython.fm
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm

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Talk Python Training

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.

Links from the show

Nathaniel: @[email protected]
[announce] Pybi and Posy: discuss.python.org
PEP 711: peps.python.org
Py2App: readthedocs.io
PyInstaller: pyinstaller.org
py-spy: github.com
Anthropic: anthropic.com
Trio: github.com
Trio on Talk Python: talkpython.fm
Zip Documentary: The Dark History of Zip Files: youtube.com
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm

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What advice would you give someone just getting into Python? What did you learn over time through hard work and a few tears that would have really helped you? It's a fun game to play and we have Jason McDonald on the podcast to give us his take. Enjoy!

Links from the show

Jason C. McDonald: @[email protected]
Dead Simple Python: nostarch.com
Coroutines and Tasks: docs.python.org
Duck Typing: wikipedia.org
Static Duck Typing in Python with Protocols: daan.fyi
PEP 709: peps.python.org
PEP 289: peps.python.org
Python Packaging Strategy Discussion - Part 1: discuss.python.org
Branch-detective: github.com
Hypothesis: readthedocs.io
Pydantic v2 announcement: pydantic.dev
Michael's venv alias: digitaloceanspaces.com
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm

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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.

Links from the show

Sketch: github.com
Lambdapromp: github.com
Python Bytes 320 - Coverage of Sketch: pythonbytes.fm
ChatGPT: chat.openai.com
Midjourney: midjourney.com
Github Copilot: github.com
GitHub Copilot Litigation site: githubcopilotlitigation.com
Attention is All You Need paper: research.google.com
Live Colab Demo: colab.research.google.com
AI Panda from Midjourney: digitaloceanspaces.com
Ray: pypi.org
Apache Arrow: arrow.apache.org

Python Web Apps that Fly with CDNs Course: talkpython.fm
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm

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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.

Links from the show

California Consumer Privacy Act (CCPA): oag.ca.gov
30 Biggest GDPR Fines So Far: tessian.com
Website fined for Google Fonts: theregister.com
Fides on Github: github.com
Fides: ethyca.com
Bunny.net Fonts: fonts.bunny.net
DBT: getdbt.com
eBFP Kernel tools: ebpf.io
nox: nox.thea.codes
rich-click: github.com
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm

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Talk Python Training

In recent years, there has been a lot of experimenting how we work with dependencies and external libraries for our Python code. There is pip, pip-tools, Poetry, pdm, pyenv, pipenv, Hatch and others workflows. We dove into this deeply back on episode 406: Reimagining Python's Packaging Workflows. We're back with Ofek Lev to take a deeper look at Hatch.


Links from the show

Hatch: hatch.pypa.io
Ofek on Twitter: @Ofekmeister
Mamba: github.com
Hatch env management: hatch.pypa.io
Packaging a Python project tutorial: packaging.python.org
Customize project generation: hatch.pypa.io
Textual: textualize.io
Ruff on Talk Python: talkpython.fm
RustUp: rustup.rs
Conda: docs.conda.io
import antigravity: xkcd.com
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm

--- Stay in touch with us ---
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If you're like most people, the simplicity and easy of getting started is a big part of pytest's appeal. But beneath that simplicity, there is a lot of power and depth. We have Brian Okken on this episode to dive into his latest pytest tips and tricks for beginners and power users.

Links from the show

pytest tips and tricks article: pythontest.com
Getting started with pytest Course: training.talkpython.fm
pytest book: pythontest.com
Python Bytes podcast: pythonbytes.fm
Brian on Mastodon: @[email protected]

Hypothesis: readthedocs.io
Hypothesis: Reproducability: readthedocs.io
Get More Done with the DRY Principle: zapier.com
"The Key" Keyboard: stackoverflow.blog
pytest plugins: docs.pytest.org
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm

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