Category Programming

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I like having the core logic of our application free of distractions like too many technical “details” like logging or generating metrics. Of course, sometimes it’s hard to avoid it. I found in many projects a situation where we put the logger very deeply inside of the code. At the end of the day, we had the logger almost everywhere. In tests, we had to provide the mocked implementation everywhere as well.

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Sometimes, we may want to use a library but a slightly modified version. It happens very often when we develop the library but test it in the context of an application. Go has a handy mechanism in go modules that can help us with it. To make it work, we have to clone the library somewhere near the target project and run the following command in the application’s folder. go mod edit -replace github.

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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.

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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.

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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.

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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.

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When I started my career as a software developer and published the first production application what I did was staring at logs and look for some fatal errors. It was a monolith application. Every log saying that something’s wrong had to be fixed. ASAP. This approach worked for some time. However, when the scale increased, and I started building microservices, I couldn’t get rid of all of them. Network issues, database failures, and more - it happens all the time.

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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.

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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.

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The varnish is a well-known HTTP accelerator. As the continuation of the GoInPractice series, today I’ll show how you can build a simple (and naive) varnish implementation in Go. Some of the code is reused from Writing a reverse proxy so if you don’t understand something, I recommend taking a look at the blog post. We’ll split our project into a few parts. The first one will be the caching mechanism.