Plurrrr

If you’re doing text or string manipulation in Python, what do you do if your code is too slow? Assuming your algorithm is reasonably efficient, the next step is to try faster alternatives to Python: a compiled extension.

Unfortunately, this is harder than it seems. Some options don’t offer an easy path to optimizations, others are actually slower. To see this limitation in action, we’ll consider some alternatives:

• Pure Python, with the default Python interpreter.
• Cython.
• mypyc.
• Rust.
• Pure Python, with the PyPy interpreter.

We’ll also consider what can be done if these option don’t help.

Reading the thought-provoking "Patterns & Abstractions" post reminded me of a long-held opinion I have about programming language design: we have a tendency to keep adding features to a language until it becomes so big that its sheer size makes it difficult to use reliably. Since most of us spend most of our time programming in one language, it can be difficult to see a common trend amongst languages in general.

Let’s build a container around a Rust webserver and some static files using Nix and Gitlab CI. The process is what you’d expect, but there are a few details that are annoying to puzzle out.