Performance
Posts about Performance
I Turned on the Python 3.14 JIT in Production (Well, Staging). Here’s the Truth.
Well, I have to admit, I was a bit skeptical about this whole Python JIT thing at first. In my experience, “free performance” usually comes …
Poetry is Dead to Me: Why I Switched to uv
Uv installer: Actually, I should clarify – I held on for as long as I could. Really, I did. I was the guy in the team chat defending Poetry1 back in 2023.
Numpyro: Probabilistic Programming That Doesn’t Waste My Time
NumPy news: I remember the bad old days of probabilistic programming. You’d define a hierarchical model, hit “sample,” and then—I’m not joking—go watch …
TF 2.18 & Keras: Real-World Performance Review
I finally bit the bullet last week. After ignoring the notification icons for two months, I upgraded our main training pipeline Learn about Keras updates.
RNNs Aren’t Dead: Liquid Networks in Keras 3
I distinctly remember the funeral we all held for Recurrent Neural Networks around 2019. The Transformer architecture had just Learn about Keras updates.
Mojo in 2026: Is It Finally Time to Ditch Pure Python?
Actually, I still remember the noise when Mojo first dropped. It was mid-2023, and the promise was wild: Python syntax, C++ Learn about Mojo language.
PyScript in 2026: Why I Finally Stopped Hating Client-Side Python
Actually, I should clarify – I remember sitting in the audience at PyCon 2022 when PyScript was first announced. The demo was Learn about PyScript web.
Stop Using pipx: Why uv Is The Only Python Tool Manager You Need
Uv installer: I have a confession. For about five years, I was the biggest advocate for pipx you’d ever meet. I annoyed my coworkers about it.
Stop Rewriting Your Pandas Code for Spark. Seriously.
I looked at my terminal yesterday and saw the one error message that has haunted my entire career in data engineering. Learn about NumPy news.
NASA Just Paid to Fix NumPy’s Messy Parts. About Time.
I was staring at a flame graph at 11 p. m. last Tuesday, wondering why my seemingly simple data pipeline was eating RAM like Learn about NumPy news.