Python

GitHub offers a way to customize one’s profile by allowing one to create a README in a specific repository, named as your profile, e.g., nfrankel/nfrankel. A couple of years ago, I automated the update of my GitHub profile with up-to-date info: my latest blog posts, my upcoming talks, and the last recorded YouTube talk. I took the time to document how to do it on this blog. At the time, I chose Kotlin scripting because I was proficient enough in Kotlin, but I wanted to learn the scripting

I got plenty of feedback on my post about Calling Rust from Python: Hacker News/r/python/r/rust Many comments mentioned pyo3, and I should use it instead of cooking my own. Thanks to the authors, I checked: in this post, I explain what it is and how I migrated my code. What is pyo3? Rust bindings for Python, including tools for creating native Python extension modules. Running and interacting with Python code from a Rust binary is also supported. — PyO3 user guide Indeed, pyo3

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

Python provides specially-named methods: methods that the runtime interprets in a certain way, but that you need to know about. The documentation is pretty exhaustive about them, but it needs examples for beginners. The goal of this two-part series is to list these methods and provide these examples, so that I can remember them. Part 1Part 2

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