Performance
Posts about Performance
Poetry is Dead to Me: Why I Switched to uv
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 Poetry 1 back in 2023.
Numpyro: Probabilistic Programming That Doesn’t Waste My Time
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 an entire.
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 to TensorFlow 2.18.
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 walked into the room, eaten.
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++ speed, and a magical.
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.
Stop Using pipx: Why uv Is The Only Python Tool Manager You Need
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.
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 Chrome with fifty tabs open.
Stop Downsampling Your Data: The New Pandas Update is Actually Good
I have a confession to make. For the last five years, I’ve been lying to my stakeholders. Not big lies—just little white lies about data granularity.