Tag golang

gRPC supports authentication. Adding it to your project is simple. All you have to do is configure it with just a few lines of code. One of the authentication types that gRPC supports is SSL/TLS. From the server-side, the code looks like this: creds, err := credentials.NewServerTLSFromFile(certFile, keyFile) if err != nil { // handle the error - no ignore it! } s := grpc.NewServer(grpc.Creds(creds)) The client has to update the code as shown below.

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.

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.

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.

The context package in Go is quite simple and well-known. On the other hand, there are some misunderstandings while using it. Today, I’ll try to explain all the most popular concerns and make more clear when and how use the Context. Let’s start with what the context is. Package context defines the Context type, which carries deadlines, cancellation signals, and other request-scoped values across API boundaries and between processes. ref: https://golang.

Go has plenty of different web frameworks. When you are faced with choosing a framework for the first time, it may turn out to be quite a challenge to choose the best one. This article is intended to help you choose the best one. It is full of personal judgments that you may disagree with. However, I believe you will find it most helpful. Martini The first framework is Martini. Honestly, it shouldn’t be here as it’s been under development since 2017.

In Go, we can refer to variables using value or pointers. Sometimes, it’s hard to answer which approach is more suitable. At the first place, you should learn about general rules. Value semantic should be used every time when copying the value make sense in the logic of your code. For example, every value object should be passed by value. If you have a struct Money then it’s possible (and also make sense) to have, at the same time, multiple 10$ in your code.

Slice is the most important data structure in Go. When it comes to performance, slices are going to beat any other data structure. They are simple but powerful. However, there are some gotchas you have to keep in mind. Today, I’ll explain how slices work to help you prevent some hard to find bugs and write better code. In Go, arrays have a fixed size. The length is part of the array’s type.

In the garbage-collected world, we want to keep the GC overhead as little as possible. One of the things we can do is limiting the number of allocations in our application. How to achieve that? There’s sync.Pool which caches allocated but unused items for later reuse. The Pool can become very useful when you have multiple parallel operations that can share the same piece of memory between them. The real power of it is visible when you have frequent allocations and deallocations of the same data structure.