Back in 2023, we made a thing for running async code from sync code. I’m happy to announce that it is now available on PyPI as asyncio-thread-runner.

   Last time, we built a hybrid concurrent.futures executor using inheritance. Today, we’re building it again (twice ) using composition and functions only, to figure out which way is better and why. Consider this a worked example.

   in which we build a hybrid concurrent.futures executor that runs I O bound tasks on all available CPUs, thus evading the limitations imposed by the dreaded global interpreter lock on the humble ThreadPoolExecutor.

   Today we’re implementing a least recently used cache with priorities and expiry, using only the Python standard library. This is a bIG TEch CoDINg InTerVIEW problem, so we’ll work hard to stay away from the correctâ data structures, but we’ll end up with a decent solution anyway

   Having trouble figuring out when to use classes? In this article, we look at another heuristic for using classes in Python, with examples from real-world code, and some things to keep in mind.

   So, you’re doing some sync stuff. But you also need to do some async stuff, without making everything async. Hint: asyncio.Runner will get you at least part of the way there.

   Do you feel you’re fighting your tools? Do you feel you’re relying too much on autocomplete and inline documentation? tl;dr: Most good documentation won’t show up in your IDE - rather, it is about how to use the library, and the problem the library is solving.

   Java is notoriously verbose, especially when used in a serious Enterprise Projectâ ...so naturally, I made linesieve, a Python text munging tool to split output into sections and match sub split with the full power of Python’s re module.

   So, you’re doing some async stuff, repeatedly, hundreds of thousands of times. How do you not do it all at once? Hint: asyncio.Semaphore is not always the best way, despite what Stack Overflow may tell you ;)

   in which you’ll find out what while constructing a mapping found unhashable key PyYAML errors mean, why do they happen, and what you can do about it.

   in which you’ll learn how to cache a lot of methods in Python, even for objects created by someone else. Did you know that, contrary to popular belief, Python programmers can have a little monkey patching as a treat?

   reader, my Python feed reader library, is 5 years old; since this is a special occasion, I thought I’d share a few thoughts on the journey so far.

   in which we check if your password has been compromised in many inconvenient ways, in a tale of destruction, obsession, and self-discovery.

   in which we look at one or two ways to make life easier when working with Python regular expressions.

   in which you’ll find out what could not determine a constructor for the tag PyYAML errors mean, why do they happen, and what you can do about it.

   in which we use PyYAML to safely read and write YAML with any tags, in a way that’s as straightforward as interacting with built-in types.

   This is the fourth article in a series about writing my own SQL query builder. Today, we’ll rewrite it from scratch, explore API design, learn when to be lazy, and look at worse and better ways of doing things - all in 150 lines of Python

   namedtuple has been around since forever, and over time, its convenience saw it used far outside its originally intended purpose. With dataclasses now covering part of those use cases, what should one use named tuples for? In this article, I address this question, and give a few examples from real...

   This is the third article in a series about writing an SQL query builder in 150 lines of Python. Here, I talk about why I decided to write my own, the alternatives I considered, why I didn’t use an existing library, and how I knew it wouldn’t become a maintenance burden.

   In this article, we look at a few real-world examples where functions taking the same arguments don’t necessarily make a class, as counter-examples to a heuristic for using classes in Python.

   PEP 661 proposes adding a utility for defining sentinel values in the Python standard library. In this article, you’ll get a PEP 661 summary, learn what sentinel objects are (with real-world examples), how to use them with type hints, and a bit about why PEPs exist in the first place.

   In this article, we look at a heuristic for using classes in Python, with examples from real-world code, and some things to keep in mind.

   This is the second article in a series about writing an SQL query builder in 150 lines of Python, why I wrote it, how I thought about it, and the decisions I had to make. In this article, I talk about why I needed a query builder in the first place, with examples derived from real use cases I had...

   In this series, we examine an SQL query builder I wrote in 150 lines of Python, why I wrote it, how I thought about it, and the decisions I had to make. This article is a sneak peek of the series and the code.

   in which we look at an interesting alternative to Makefiles with .PHONY-only targets, and why I think it’s cool.

   In this article, you’ll find out what Python hashlib object supporting the buffer API required TypeErrors mean, why do they happen, and what you can do about it.

   On your Python learning journey, you may have heard that a great way to get better is to read code written by other people. That’s true, but finding good code to study is not easy, mostly because the design philosophy and the reasoning behind the code are rarely documented. The Python standard...

   in which we talk about the many ways of using Python dataclasses without type annotations (or even variable annotations ), and what this says about Python.

   In this article, you’ll learn how to calculate deterministic hashes for arbitrary Python data objects, stable across interpreter versions and implementations.

   Are you having trouble making the modules work together in a larger project? Have you tried looking at popular projects as models, but were put off by their size and scope, or found it hard to see why they did the things they did? Resources about this do exist, but they’re scattered all over, and...

   in which we optimize our Advent of Code 2020 day 17 (Conway Cubes) solution, focusing on profiling and optimizing existing code, in a way that helps you translate those skills to your regular, non-puzzle coding. With a touch of code generation and some help from PyPy, we end up with a 65x...

   in which we solve the day 17 problem from Advent of Code 2020, Conway Cubes, in a generic way, focusing on testing, refactoring, and idiomatic Python, in a way that helps you translate those skills to your regular, non-puzzle coding.