ginkgo
GJSON
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ginkgo
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Writing tests for a Kubernetes Operator
Ginkgo: a testing framework based on the concept of "Behavior Driven Development" (BDD)
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We moved our Cloud operations to a Kubernetes Operator
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.
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Recommendations for Learning Test-Driven Development (TDD) in Go?
A bit off-topic, but i really like the ginkgo BDD framework
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Start test names with “should” (2020)
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.
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ginkgo integration with jira/elasticsearch/webex/slack
If you are using Ginkgo for your e2e, this library might of help.
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Testing frameworks, which to use?
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.
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Testza - A modern test framework with pretty output
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?
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What are your favorite packages to use?
Ginkgo Behavioural test framework
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Air – Live reload when developing with Go
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/
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Half a million lines of Go at The Khan Academy
The BDD testing framework Ginko [1] has some "weird" / unidiomatic patterns, yet it is very popular
https://github.com/onsi/ginkgo
GJSON
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Rob Pike: Gobs of data (2011)
Someone made a benchmark of serialization libraries in go [1], and I was surprised to see gobs is one of the slowest ones, specially for decoding. I suspect part of the reason is that the API doesn't not allow reusing decoders [2]. From my explorations it seems like both JSON [3], message-pack [4] and CBOR [5] are better alternatives.
By the way, in Go there are a like a million JSON encoders because a lot of things in the std library are not really coded for maximum performance but more for easy of usage, it seems. Perhaps this is the right balance for certain things (ex: the http library, see [6]).
There are also a bunch of libraries that allow you to modify a JSON file "in place", without having to fully deserialize into structs (ex: GJSON/SJSON [7] [8]). This sounds very convenient and more efficient that fully de/serializing if we just need to change the data a little.
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1: https://github.com/alecthomas/go_serialization_benchmarks
2: https://github.com/golang/go/issues/29766#issuecomment-45492...
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3: https://github.com/goccy/go-json
4: https://github.com/vmihailenco/msgpack
5: https://github.com/fxamacker/cbor
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6: https://github.com/valyala/fasthttp#faq
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7: https://github.com/tidwall/gjson
8: https://github.com/tidwall/sjson
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Jj: JSON Stream Editor
```
I don't think there is a way to sort an array, though. However, there is an option to have keys sorted. Personally, I don't think there is much annoyance in that. One could just pipe `jj` output to `sort | uniq -c`.
[0]: https://github.com/tidwall/gjson/blob/master/SYNTAX.md
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Library to analyze an arbitrary JSON string
I’m using GJSON, so far so good!
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Mapping json fields in api calls to a struct to store them in a database or cache
If the fields you need are just a small subset of the whole json, maybe https://github.com/tidwall/gjson might be of use to read only those (using jsonpath) without needing to create complete corresponding structs.
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Which CPU to buy based on profiling
Thank you for the reminder, it's never too much of it :) Didn't say it, but the code was pprof-iled many times and i can really say it's well optimized. I use own libraries with on-the-fly equations (sums, avgs, emas, stds, ...) wherever possible and also made custom json parser as json messages are in fixed format, so the parser is about 10x faster than gjson. I optimized it to the point that I avoided using maps, and rather iterate via slice where ever possible.
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Jetro - transform and query JSON format
You are right, for learning purposes this fit my needs, but I can imagine an approach similar to this repo: https://github.com/tidwall/gjson
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Any way to convert unknown/dynamic json to generic object structure
https://github.com/tidwall/gjson is a relatively sensible library if this is something you need to deal with and the structure is actually unknowable.
- Need help with getting the grandchild in nested JSON
- Double down on python or learn Go
- Ad hoc JSON parsing
What are some alternatives?
Testify - A toolkit with common assertions and mocks that plays nicely with the standard library
jsoniter - A high-performance 100% compatible drop-in replacement of "encoding/json"
GoConvey - Go testing in the browser. Integrates with `go test`. Write behavioral tests in Go.
go-json - Fast JSON encoder/decoder compatible with encoding/json for Go
godog - Cucumber for golang
intrinsic
goblin - Minimal and Beautiful Go testing framework
gojson - Automatically generate Go (golang) struct definitions from example JSON
httpexpect - End-to-end HTTP and REST API testing for Go.
hub - A command-line tool that makes git easier to use with GitHub.
gocheck - Rich testing for the Go language
ngrok - Unified ingress for developers