datadriven VS tricorder

Table driven tests are a lot better than a bunch of imperative tests but they rapidly become unwieldy to debug, maintain, and evolve. Their readability often isn’t great.

If you’re using go, check out https://github.com/cockroachdb/datadriven. It takes a little bit of effort to craft a testing dsl, but it is so worth it.

Also, snapshot style testing where the test writes out its expectations and you just inspect it and save it (part of datadriven) is wonderful.

I’ve been using insta in rust lately and it’s some of what I want but not quite datadriven.

I’ve found the datadriven[1] testing approach in go to be quite effective. The idea is that you leverage a standardized file structure to construct a little DSL for testing your code. This allows you to write expressive tests that print the state of the code and then look at it. Rewrite is also very powerful.

This is all inspired by the sqllite logic test framework.

[1]: https://github.com/cockroachdb/datadriven

There is https://pyinfra.com/

As a sidenote, I also made a small experiment a while ago : https://github.com/linkdd/tricorder/

But it's a bit of a chicken-and-egg problem. Without users, I don't know how it should be used, without features I won't get any users. So for now, it's in a state of "I'll address bug reports and feature requests, but I won't actively develop it".

Thank you. Your library seems nice.

Unfortunately, I have to say it... I hate YAML with a passion, k8s, github actions/gitlab ci, ansible, etc... When I'm doing ops jobs, I feel like I'm coding in YAML.

Btw, this hate for YAML birthed https://linkdd.github.io/tricorder/ :P

Another one in the same vein is tricorder, which has one of the coolest websites ever. AFAIK it doesn't do dependencies, though. But it's got a RUST API!