Programs should be written for people to read, and only incidentally for machines to execute - Abelson and Sussman It is one of the most popular questions. You can find on the Internet attempts to answer this question. I’ve had concerns if I’m designing my packages or even the whole project correctly. Today, I’m not 100% sure about that! Some time ago, I had the pleasure to meet Robert Griesemer (one of Go’s authors) in person.

Some time ago, I found a Stack Overflow question. The author had a problem with understanding why the context from the request he’s using is canceled. I remember that I had a similar situation in the past: I used the context from the HTTP request and tried to use it in background operation and return the response to the user before it was finished. This issue comes from not understanding how the context is used in the http.

You can find a lot of articles about Go that describe general aspects of it. Including the content on this blog. Today, I decided to prepare something different. I’ll tell you about one of my tasks and I’ll show you how I resolved it using Go. I thought it’d be useful to show the exec package and to tell a bit about the ssh command and learn AWS EE2 a bit better.

Failures and downtime are part of our day-to-day life. I had a problem with one of the services that started crashing a few times a week. We noticed that it crashes because the memory usage reaches its limits no matter how high the limit is. Debugging memory leaks is hard and time-consuming. As a temporary fix[^Nothing is more permanent than a temporary solution] we decided to restart the application once a day.

Writing linters is simple. I was surprised how it’s easy to write a Go linter. Today, we’ll write a linter that will calculate the cyclomatic complexity of the Go code. What is cyclomatic complexity? Cyclomatic complexity is a software metric used to indicate the complexity of a program. ref The idea is simple - every time we find any control flow statements we increase the complexity by one. I know I oversimplified it a bit but I don’t want to overwhelm you with unnecessary details.

It took a while since I got this book. At the very beginning, I didn’t want to buy it. However, I got so much feedback that this book is so good that I had to check it myself. It is the second Go book in my library. I didn’t write about the first one because I wanted to compare it with another one. I wanted to recommend you only the best.

In the last article, we wrote a few tests for a project to make sure that our refactoring won’t break anything. To understand the project better, we will separate the part of the domain and add a test to it. This will make the test more authentic. There is a problem with the end-to-end (e2e) tests: database under the hood. This attitude is not carefree. Firstly, those tests are rather slow.

When we talk about software design we very often use very generic and abstract words. But, how about the practice? How does it look in a real-world project? Today, you and I will start refactoring a small to-do app for better testability and maintainability. In this article, we will make the application testable. We’ll write black-box tests that will prevent from some bugs and make future refactoring easier and safer.

In this article, I explain how you can detect if the interface you’re using is getting too big and requires splitting into smaller ones. Smaller interfaces help to improve the maintenance and readability of the code. What’s more, it helps with understanding the code. Interfaces in Go are different than those known in Java, c#, PHP etc. In those languages you define interfaces up-front. In other words, at the moment of creating a class you need to know how the class will be used.