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. Links from the show Glyph on Mastodon: @[email protected] ShhGit: github.com Encrust: github.com GitHub Security Alerts: github.com CIA Triad: fortinet.com pinpal: github.com XKCD Authorization: xkcd.com Tokenring: github.com AWS Vault: github.com Gimme-AWS-creds: github.com Secrets in GitHub Actions: github.com Python Client for HashiCorp Vault: python-hvac.org Pomodouroboros app: github.com DateType: pypi.org Haveibeenpwned: haveibeenpwned.com PEP 541: peps.python.org Glyph's security talk at PyCon: us.pycon.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 Sponsors PyCharm RedHat Talk Python Training

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 --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy Sponsors PyCharm RedHat 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 --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy Sponsors PyCharm influxdata Talk Python Training

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 --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy Sponsors Sentry Error Monitoring, Code TALKPYTHON influxdata Talk Python Training

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 --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy Sponsors Sentry Error Monitoring, Code TALKPYTHON Talk Python Training