Hey, it’s been a long time! We’re happy to share that Watermill v1.3 is now out! What is Watermill Watermill is an open-source library for building message-driven or event-driven applications the easy way in Go. Our definition of “easy” is as easy as building an HTTP server in Go. With all that, it’s a library, not a framework. So your application is not tied to Watermill forever. Currently, Watermill has over 6k stars on GitHub, has over 50 contributors, and has been used by numerous projects in the last 4 years.
After almost three years since the last stable release, Watermill v1.2 is finally out! If you’re new here, Watermill is our open-source library for building event-driven applications in Go, the easy way. A lot has happened since v1.1. We’ve been running Watermill on production in many projects, using it in new ways and adding features to support new use cases. We also received a lot of feedback and contributions from the community.
Did you have a situation when you lost a ton of time finding a Go library for your need? In theory, you can check lists like Awesome Go or make a choice based on GitHub stars. But Awesome Go contains over 2600 libraries, and popularity is not always the best indicator of library quality. I often thought that it would be great to have a place where I could find just the best and battle-tested libraries I could use in my project.
While writing this blog and leading Go teams for a couple of years, the most common question I heard from beginners was “What framework should I use?”. One of the worst things you can do in Go is follow an approach from other programming languages. Other languages have established, “default” frameworks. Java has Spring, Python has Django and Flask, Ruby has Rails, C# has ASP.NET, Node has Express, and PHP has Symfony and Laravel.
Cohesion is part of the low coupling, high cohesion principle that’s supposed to keep your code maintainable. While low coupling means few dependencies, high cohesion roughly translates to single responsibility. Highly cohesive code (a module or a function) is focused on a single purpose. Low cohesion means it does many unrelated things. I’ve written about coupling in the previous article on anti-patterns. Here are some tips on increasing cohesion in Go applications using the recently released generics.
Hello! Please give Krzysztof a warm welcome in the first guest post on our blog. 🎉 We’ve been working with Krzysztof for the past two years, and we’re excited to share his work here. Miłosz & Robert We all struggle with software architecture diagrams, don’t we? Have you ever wondered why? If you ask yourself that question, why maintenance of up-to-date and detailed software architecture diagrams is so painful, you will come up with a long list of valid answers.
Enums are a crucial part of web applications. Go doesn’t support them out of the box, but there are ways to emulate them. Many obvious solutions are far from ideal. Here are some ideas we use that make enums safer by design. iota Go lets you enumerate things with iota. const ( Guest = iota Member Moderator Admin ) Full source: github.com/ThreeDotsLabs/go-web-app-antipatterns/02-enums/01-iota/role/role.go While Go is explicit, iota seems relatively obscure.
At one point in my career, I was no longer excited about the software I was building. My favorite part of the job were low-level details and complex algorithms. After switching to user-facing applications, they were mostly gone. It seemed programming was about moving data from one place to another using existing libraries and tools. What I’ve learned so far about software wasn’t that useful anymore. Let’s face it: most web applications don’t solve tough technical challenges.
A couple of years ago, I worked in a SaaS company that suffered from probably all possible issues with software development. Code was so complex that adding simples changes could take months. All tasks and the scope of the project were defined by the project manager alone. Developers didn’t understand what problem they were solving. Without an understanding the customer’s expectations, many implemented functionalities were useless. The development team was also not able to propose better solutions.
This post is a direct follow-up to Microservices test architecture where I’ve introduced new kinds of tests to our example project. Wild Workouts uses Google Cloud Build as CI/CD platform. It’s configured in a continuous deployment manner, meaning the changes land on production as soon as the pipeline passes. If you consider our current setup, it’s both brave and naive. We have no tests running there that could save us from obvious mistakes (the not-so-obvious mistakes can rarely be caught by tests, anyway).
© Three Dots Labs Cookies Policy