Several weeks ago during a compilation process, I noticed that my laptop became very hot under my palms. At first, I did not pay any attention to this, however, when it became uncomfortable to work I started to worry. My first thought was that the laptop got dusted and cannot remove the heat effectively. But then I noticed that I did not hear the fan noise when the load on the CPU increases, and I decided that my cooler is either broken or blocked. I was almost about to start disassembling my laptop, but luckily I decided to check the temperature using Linux utilities. There I found out that, despite I feel the laptop being hot, the sensor [
temp1] showed that the CPU temperature was normal (showing all the time the temperature of 45°C). This looked suspicious, and I checked other sensors measurements and found out that the [
coretemp-isa-0000] sensors showed more correct temperature values, which in addition reacted on load increase. In this article, I want to describe, how I forced my system to react also on the values from these additional sensors and cooled down my laptop.
Currently besides all other activities, I am developing a habit of programming following Test Driven Development (TDD) methodology. This is a perfect time because I continue to explore Rust, a new programming language to me. Moreover, this language encourages you to cultivate this best practice by providing great documentation and well-thought ecosystem.
In our programs, we often face with exceptional situations (e.g., lack of space when you try to write a file, or absence of a resource), and we need to handle them. If you follow the TDD approach, you need to ensure that these exceptional situations are also properly covered in your tests. Id est, you have to develop tests that reproduce these exceptional situations and make sure that your code detect and handle them correctly. In this post, I want to discuss how to test exceptional situations in Rust.
I like to work using an adapted Pomodoro technique, therefore I added a timer widget to my desktop (I use Kubuntu as my operating system). Unfortunately, in Kubuntu by default when the timer ends, there is no sound notification about this event. Moreover, the set of predefined timer intervals does not fit my needs. In this short post, I explain how to make the timer widget more comfortable.
Today, I want to note down my thoughts on closures. Closures are important in Rust, because they are extensively used in iterator adapters paramount in development highly performant programs. However, to my point of view this topic is not well-covered in The Book. This may be a reason why it is considered among the most difficult parts of the language. In this post, I will try to shed more light on it, hopefully making it more clear to Rust learners. Note that I am still a novice to the language, and my understanding may not be fully correct.
When you develop your first binary application using new language, the first issue that you face is how to organize your code so that you can easily extend it in the future. There is a good example in The Book on how to organize your code, parse and process command line arguments by yourself. However, in real world you would use a library to parse command line arguments, which most probably would be the clap library in case of Rust. In this article, I describe my template for creating a CLI (command line interface) application.
In my previous articles (“Clearing Output Data in Jupyter Notebooks using Pre-commit Framework” and “Clearing Output Data in Jupyter Notebooks using a Bash Script Hook”), I described how to clear output data in Jupyter notebooks using the pre-commit framework and the git hook script correspondingly. Both these approaches are usable and could be applied for your project repositories. However, recently I have found the third way how to clear Jupyter notebook output cells that seems to me more clear and easier to implement. In this article, I describe my last findings.
In my previous article, I described why you may need to clear output data in your Jupyter notebooks. As at the time I participated in a pre-sail project for AI Superior, we required a quick solution to achieve this goal. That is why I used Python-based pre-commit framework to create a pipeline to clear output data. However, this approach requires you to install additional Python package into your system, that might not be always possible. Therefore, at the time I decided that I would implement this approach as a pure Bash script. Recently, I have found some spare time and decided to dig deeper into this topic. As a result of my explorations, I developed a git pre-commit hook that clears Jupyter output cells and wrote this article describing it. If you are an adept of ‘show me the code’ and do not want to read the article, you can find the final script here.
In my previous articles (Configuring Python Workspace and Configuring Python Workspace: Poetry), I have described how I use pyenv to create several virtual environments. With the lapse of time, the tools that you install in these environments become outdated and you need a tool to update them. I develop a pyenv plugin that updates all packages in all or particular pyenv environments and in this post I describe how to use it.
De facto, git is a standard version control system now. Not surprisingly that I use it for my projects. Working on a project, I often face with a situation when I have made a number of changes, and I need to describe them in a commit message. Of course, I try following the line when every change results in a new commit, however, on practice, sometime I face with the situation when I need to describe a number of changes in one commit message. If there are a number of changes (or peculiarities), mentioning all of them could be a challenge. Of course, you can open an additional terminal and do diffing, however, it would be great if this information is included in the commit message.
Hugo 0.56.0 introduced one notable feature called “Hugo Modules”. Hugo Modules allow you to add more flexibility to your Hugo project organization. Using this feature, you can import different modules that will implement one or more Hugo component types. For instance, you can use one module that provides layout for your website, and another one to add more shortcodes, etc. Moreover, this feature enables you to mount your own directories or files that are not necessary tracked by Hugo.
For my webpage, I use a modified “Academic” theme that has been recently renamed to Wowchemy. As a part of the rebranding, the author migrated it to use Hugo Modules. I have devoted some time to understand how Hugo Modules work and how to migrate my website to use this feature. This blog post is mostly a memo for myself, however, it may be useful for others as well.