Nicolas Fränkel

Let’s continue our exploration of Python’s magic methods in this second part of the series. This part will focus on numbers and containers, i.e., collections. You can read the first part here. Container-related methods Python provides the usual containers, e.g., lists, sets, and dictionaries. You can use the following methods when you want to implement your own. Common methods Containers have a size. Python defines two methods to implement to return the number of items in a con

Java was the first language I used professionally and is the scale by which I measure other languages I learned afterward. It’s an OOP statically-typed language. Hence, Python feels a bit weird because of its dynamic typing approach. For example, Object offers methods equals(), hashCode(), and toString(). Because all other classes inherit from Object, directly or indirectly, all objects have these methods by definition. Conversely, Python was not initially built on OOP principles and is

I recently watched GOTO conferences' talk Calling Functions Across Languages by Richard Feldman. I’m afraid I have to disagree with using the term 'language' in this context. It’s a no-brainer to call Java from Kotlin or Scala or to call Java from Kotlin. Hence, in the rest, I’ll use 'stack'. In the talk, the speaker cites two main reasons to go on this road: Gradual migration from one stack to the otherUsing a library that has no equivalent in one’s stack under the ass

As a web architect, one of the many issues is asset management. And the most significant issue in assets is images. A naive approach would be to set an image and let the browser resize the image via CSS: img { height: 100%; width: 100%; object-fit: contain; } However, it means that you download the original image. It entails two problems: the size of the original image and the suboptimal browser-based resizing. This post will cover two alternatives: traditional and brand-new s

My demo, Evolving your APIs, features a custom Apache APISIX plugin. I believe that the process of creating a custom plugin is relatively well-documented. However, I wanted to check the parameters of the _M.access(conf, ctx) function, especially the ctx one. The documentation states: The ctx parameter caches data information related to the request. You can use core.log.warn(core.json.encode(ctx, true)) to output it to error.log for viewing. Unfortunately, core.log ultimately depends on

The JVM is an excellent platform for monkey-patching. Monkey patching is a technique used to dynamically update the behavior of a piece of code at run-time. A monkey patch (also spelled monkey-patch, MonkeyPatch) is a way to extend or modify the runtime code of dynamic languages (e.g. Smalltalk, JavaScript, Objective-C, Ruby, Perl, Python, Groovy, etc.) without altering the original source code. — Wikipedia I want to demo several approaches for monkey-patching in Java in this post

Regular readers of this blog know that I started it a long time ago, namely in April 2008. I soon found my cruising speed: a post a week. It requires time and discipline, but I achieved this goal during all those years. However, while I still have enough of both, I start to miss good post ideas. There are several reasons for this. I’ve always told that working on real-world projects is a vast source of ideas. Moving to Developer Advocacy, I’ve widened the list of topics I’m fa

One of my current talks focuses on Observability in general and Distributed Tracing in particular, with an OpenTelemetry implementation. In the demo, I show how you can see the traces of a simple distributed system consisting of: the Apache APISIX API Gateway, a Kotlin app with Spring Boot, a Python app with Flask, and a Rust app with Axum. Earlier this year, I spoke and attended the Observability room at FOSDEM. One of the talks demoed the Grafana stack: Mimir for metrics, Tempo for traces, and

One of the components of my OpenTelemetry demo is a Rust application built with the Axum web framework. In its description, axum mentions: axum doesn’t have its own middleware system but instead uses tower::Service. This means axum gets timeouts, tracing, compression, authorization, and more, for free. It also enables you to share middleware with applications written using hyper or tonic. — axum README So far, I was happy to let this cryptic explanation lurk in the corner of