$ cat /etc/motd
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The Hub of Heliopolis — notes on technology and my experiments with it.
$ ls -lt posts/
CPython now ships its own sampling profiler, free-threading is going mainstream, and coding agents have started reading profiles. In this post I look at where Python profiling stands today, compare Tachyon, py-spy, Scalene and Austin, and go through what's new in Austin 4.1.
Coding agents are fast becoming the main generators of new source code, but they are also being used for code review, finding and fixing bugs. How can they be used to the best extent to discover and fix performance issues?
In this post I will describe my approach to C unit testing using pytest. In particular, we get to see how to gracefully handle SIGSEGVs and prevent them from stopping the test runner abruptly. Furthermore, we shall try to write tests in a Pythonic way.
I finally had the chance to set some time aside to touch the Linux kernel source, for fun and profit. This is the story of how I implemented a new BPF helper.
The latest version of Austin comes with a heap size option that can be used in increase the accuracy with which invalid samples are detected. In this post I give a brief description of how this works.
I shall reveal to you how I managed to complete the Hacktoberfest 2021 challenge with just a profiler. So read on if you are interested!
Observability into native call stacks requires some compromise. In this post I explain what this actually means for a Python tool like Austin.
In this short post I will try to convince you of how easy it is to find performance issues in your Python code and how you should develop the habit of profiling your code before you ship it.
My adventure with Avaloq started in August 2016 and ended in January 2021. It's time to look back at what has happened during these years.
The latest version of the Austin TUI project makes use of a custom XML resource file to describe and build the actual text-based UI, using curses as back-end. In this post we shall see how one can use the same technology to quickly build reactive TUIs using Python.