Let’s see how to edit descriptions of Jira issues in Vim or Neovim. We will do this by installing a browser extension that can open text fields in an external editor. We will also cover how to make Jira issues syntax-highlighted in Vim, how to enable spell checking, and how to use snippets to speed up the writing of Jira issues. The approach described in the blog post can be used to edit text fields on other sites as well, such as GitHub or Stack Overflow.
Read More
Category Archives: Software Engineering
When You Import a Python Package and It Is Empty
Recently, I have stumbled upon an apparently strange situation in which a non-empty Python package was empty after it got imported. Let’s take a close look at that issue because it may happen to anyone.
Read More
Accidentally Overwriting Another Local Variable in C and C++
An example of a subtle bug that you can run into in C and C++: accidentally overwriting another local variable. Such an issue can manifest only on certain systems, and can be hard to debug if you have not seen it before. An oldie but goodie.
Read More
Even a Feature That You Do Not Use Can Bite You
Let’s have a look at a simple piece of Python code that I have both accidentally written and seen in code reviews which does an entirely different thing than expected.
On Incomplete HTTP Reads and the Requests Library In Python
The requests library is arguably the mostly widely used HTTP library for Python. However, what I believe most of its users are not aware of is that its current stable version happily accepts responses whose length is less than what is given in the Content-Length header. If you are not careful enough to check this by yourself, you may end up using corrupted data without even noticing. I have witnessed this first-hand, which is the reason for the present blog post. Let’s see why the current requests version does not do this checking (spoiler: it is a feature, not a bug) and how to check this manually in your scripts.
Read More
Implementing multiprocessing.pool.ThreadPool from Python in Rust
In this post, we will implement multiprocessing.pool.ThreadPool from Python in Rust. It represents a thread-oriented version of multiprocessing.Pool, which offers a convenient means of parallelizing the execution of a function across multiple input values by distributing the input data across processes. We will use an existing thread-pool implementation and focus on adjusting its interface to match that of multiprocessing.pool.ThreadPool.
Read More
When auto Seemingly Deduces a Reference in C++
One of the first things that C++ programmers learn about auto is that bare auto never deduces a reference. In the present post, I show you two examples when it seemingly does. The first one involves proxy objects. The second one concerns structured bindings from C++17.
Read More
Ensuring That a Linux Program Is Running at Most Once by Using Abstract Sockets
It is often useful to have a way of ensuring that a program is running at most once (e.g. a system daemon or Cron job). Unfortunately, most commonly used solutions are not without problems. In this post, I show a simple, reliable, Linux-only solution that utilizes Unix domain sockets and the abstract socket namespace. The post includes a sample implementation in the Rust programming language.
Read More
Consuming and Publishing Celery Tasks in C++ via AMQP
Celery is an asynchronous task queue based on distributed message passing. It is written in Python, but the protocol can be implemented in any language. However, there is currently no C++ client that is able to publish (send) and consume (receive) tasks. This is needed when your project is written in a combination of Python and C++, and you would like to process tasks in both of these languages. In the present post, I describe a way of interoperating between Python and C++ workers via the AMQP back-end (RabbitMQ).
Read More
Pros and Cons of Alternative Function Syntax in C++
C++11 introduced an alternative syntax for writing function declarations. Instead of putting the return type before the name of the function (e.g. int func()), the new syntax allows us to write it after the parameters (e.g. auto func() -> int). This leads to a couple of questions: Why was such an alternative syntax added? Is it meant to be a replacement for the original syntax? To help you with these questions, the present blog post tries to summarize the advantages and disadvantages of this newly added syntax.
Read More