Python has a long history, and it has evolved over time. This article describes some agreed modern best practices. Use a Helper to Run Python Tools #Use either pipx or uv to run Python tools on development systems, rather than installing these applications with pip or another method. Both pipx and uv automatically put each application into a separate Python virtual environment. Always follow the i
by Sasha Rush - srush_nlp GPU architectures are critical to machine learning, and seem to be becoming even more important every day. However, you can be an expert in machine learning without ever touching GPU code. It is hard to gain intuition working through abstractions. This notebook is an attempt to teach beginner GPU programming in a completely interactive fashion. Instead of providing text w
FMP Notebooks Python Notebooks for Fundamentals of Music Processing The FMP notebooks offer a collection of educational material closely following the textbook Fundamentals of Music Processing (FMP). This is the starting website, which is opened when calling https://www.audiolabs-erlangen.de/FMP. Besides giving an overview, this website provides information on the license and the main contributors
ndindex¶ A Python library for manipulating indices of ndarrays. ndindex is a library that allows representing and manipulating objects that can be valid indices to numpy arrays, i.e., slices, integers, ellipses, None, integer and boolean arrays, and tuples thereof. The goals of the library are Provide a uniform API to manipulate these objects. Unlike the standard index objects themselves like slic
Lately I’ve been messing around with Python 3.12, discovering new features around typing and pattern matching. Combined with dataclasses, they provide support for a style of programming that I’ve employed in Kotlin and Typescript at work. That style in turn is based on what I’d do in OCaml or Haskell, like modelling data with algebraic data types. However, the more advanced concepts from Haskell —
This blog is adapted from a talk at an MLOps Learners demo day (slides, video). marimo is free and open source, available on GitHub. I worked on vector embeddings during my PhD at Stanford. I used Jupyter daily, because it paired code with visuals in an iterative programming environment. But I realized early on that we needed a Python notebook that was more than just a REPL. I spent a lot of time
We're going to speed up some numpy code by 100x using "unsafe Python." Which is not quite the same as unsafe Rust, but it's a bit similar, and I'm not sure what else to call it... you'll see. It's not something you'd use in most Python code, but it's handy on occasion, and I think it shows "the nature of Python” from an interesting angle. So let's say you use pygame to write a simple game in Pytho
Your code might be perfect and never fail, but unfortunately the outside world is less reliable. Sometimes, other people's programs crash or freeze. Networks go down; printers catch on fire. Your code needs to be prepared for this: every time you read from the network, attempt to acquire an inter-process lock, or send an HTTP request, there are at least three possibilities you need to think about:
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