ginkgo VS gopherjs

Ginkgo: a testing framework based on the concept of ‌"Behavior Driven Development" (BDD)

We were also able to leverage Ginkgo's parallel testing runtime to run our integration tests on multiple concurrent processes. This provided multiple benefits: we could run our entire integration test suite in under 10 minutes and also reuse the same suite to load test the operator in a production-like environment. Using these tests, we were able to identify hot spots in the code that needed further optimization and experimented with ways to save API calls to ease the load on our own Kubernetes API server while also staying under various AWS rate limits. It was only after running these tests over and over again that I felt confident enough to deploy the operator to our dev and prod clusters.

A bit off-topic, but i really like the ginkgo BDD framework

You obviously are not familiar with the third circle of golang continuous integration hell that is ginkgo+gomega:

https://onsi.github.io/ginkgo/#adding-specs-to-a-suite

It’s actually worse than that example suggests. Stuff like Expect(“type safety”).ShouldBe(GreaterThan(13)) throws runtime errors.

The semantics of parallel test runs weren’t defined anywhere the last time I checked.

Anyway, you’ll be thinking back fondly to the days of TestShouldReplaceChildrenWhenUpdatingInstance because now you need to write nested function calls like:

Context(“instances”, func …)

Describe(“that are being updated”, …)

Expect(“should replace children”, …)

And to invoke that from the command line, you need to write a regex against whatever undocumented and unprinted string it internally concatenates together to uniquely describe the test.

Also, they dump color codes to stdout without checking that they are writing to a terminal, so there will be line noise all over whatever automated test logs you produce, or if you pipe stdout to a file.

If you are using Ginkgo for your e2e, this library might of help.

https://onsi.github.io/ginkgo/ offers a simple way to create tables with different scenarios useful to generate different test cases based on a file like a yml without to need to develop useless code. Maybe at start seems to be a little verbose but depends how you design the test case.

What are people’s thoughts on testing frameworks? I’ve heard that most devs only use the testing package in the standard library and the testify package for assertions— I assume this is because Go is meant to be lightweight and scalable, and adding external dependencies basically goes against that. But I’ve also seen devs use packages like ginkgo to make tests more structured and readable. What do you guys think?

Ginkgo Behavioural test framework

If you write your tests with Ginkgo [0] its CLI can do this for you. It also has nice facilities to quickly disable a test or portion of a test by pretending an X to the test function name, or to focus a test (only run that test) by prepending an F. It’s pretty nice.

[0]: https://onsi.github.io/ginkgo/

The BDD testing framework Ginko [1] has some "weird" / unidiomatic patterns, yet it is very popular

https://github.com/onsi/ginkgo

IDE: use whatever make you productive. I personally use vscode. VCS: git, as golang communities use github heavily as base for many libraries. AFAIK Linter: use staticcheck for linting as it looks like mostly used linting tool in go, supported by many also. In Vscode it will be recommended once you install go plugin. Libraries/Framework: actually the standard libraries already included many things you need, decent enough for your day-to-day development cycles(e.g. `net/http`). But here are things for extra: - Struct fields validator: validator - Http server lib: chi router , httprouter , fasthttp (for non standard http implementations, but fast) - Web Framework: echo , gin , fiber , beego , etc - Http client lib: most already covered by stdlib(net/http), so you rarely need extra lib for this, but if you really need some are: resty - CLI: cobra - Config: godotenv , viper - DB Drivers: sqlx , postgre , sqlite , mysql - nosql: redis , mongodb , elasticsearch - ORM: gorm , entgo , sqlc(codegen) - JS Transpiler: gopherjs - GUI: fyne - grpc: grpc - logging: zerolog - test: testify , gomock , dockertest - and many others you can find here

Release notes have all the details. For now it is just compatibility with the 1.18 standard library, but generics support is planned.

Why not use https://github.com/gopherjs/gopherjs with jMonkeyEngine as-is?

When I wrote my first project in this year, I don't even planed to used blazor. But my childlike curiosity directed me on that path. I wanted to know, haw hard will be port game from desktop to web browser in .net. And I found out is not that hard. But I have experience with similar tools before. I used gopherjs and emscripten. Thanks to that I know what must to do, to communicate c# with javasrcipt. I made working blazor port pretty fast. Not only server side but webassembly to. Of curs create port for different platform always generate some problems. Most weird problem I have in blazor is how floating point number behave. I received in some cases NaN values. This problem I resolve adding value like 0.0001 in calculation.

If you're already building the backend in go and you don't like the prospect of coding in JavaScript it might be worth trying out https://github.com/gopherjs/gopherjs

Maybe this is were https://github.com/gopherjs/gopherjs will truly shine? Has anyone ever seen Go used for this?

You can also write JS in Go with GopherJS, but if you don't fully understand the underlying JS webdev ecosystem, adding this extra layer of complexity is probably a really bad idea, at least at first.