tricorder
jsverify
tricorder | jsverify | |
---|---|---|
5 | 5 | |
50 | 1,666 | |
- | 0.1% | |
5.6 | 1.8 | |
7 months ago | about 3 years ago | |
Rust | JavaScript | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tricorder
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Show HN: A new open-source automation tool as an alternative to Ansible/Salt
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".
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Ask HN: What's your favorite software testing framework and why?
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
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Created a simple tool for task automation in Rust
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!
- Show HN: Automation the KISS way. No YAML involved
jsverify
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The 5 principles of Unit Testing
Libraries like JSVerify or Fast-Check offer essential tools to facilitate property-based testing.
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Ask HN: What's your favorite software testing framework and why?
I tend to use anything that offers property-testing, since tests are much shorter to write and uncover lots more hidden assumptions.
My go-to choices per language are:
- Python: Hypothesis https://hypothesis.readthedocs.io/en/latest (also compatible with PyTest)
- Scala: ScalaCheck https://scalacheck.org (also compatible with ScalaTest)
- Javascript/Typescript: JSVerify https://jsverify.github.io
- Haskell: LazySmallCheck2012 https://github.com/UoYCS-plasma/LazySmallCheck2012/blob/mast...
- When I wrote PHP (over a decade ago) there was no decent property-based test framework, so I cobbled one together https://github.com/Warbo/php-easycheck
All of the above use the same basic setup: tests can make universally-quantified statements (e.g. "for all (x: Int), foo(x) == foo(foo(x))"), then the framework checks that statement for a bunch of different inputs.
Most property-checking frameworks generate data randomly (with more or less sophistication). The Haskell ecosystem is more interesting:
- QuickCheck was one of the first property-testing frameworks, using random genrators.
- SmallCheck came later, which enumerates data instead (e.g. testing a Float might use 0, 1, -1, 2, -2, 0.5, -0.5, etc.). That's cute, but QuickCheck tends to exercise more code paths with each input.
- LazySmallCheck builds up test data on-demand, using Haskell's pervasive laziness. Tests are run with an error as input: if they pass, we're done; if they fail, we're done; if they trigger the error, they're run again with slightly more-defined inputs. For example, if the input is supposed to be a list, we try again with the two forms of list: empty and "cons" (the arguments to cons are both errors, to begin with). This exercises even more code paths for each input.
- LazySmallCheck2012 is a more versatile "update" to LazySmallCheck; in particular, it's able to generate functions.
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Property Based Testing Framework for Node
The usage of hypothesis is very intuitive and simple, and presents the concept of property-based testing perfectly. So I also wanted to find an equivalent alternative in Node. Two of them have high star ratings on Github, JSVerify with 1.6K stars and fast-check with 2.8K stars. So I took some time to study fast-check a little bit and try to get closer to my daily work.
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Machine Readable Specifications at Scale
Systems I've used for this include https://agda.readthedocs.io/en/v2.6.0.1/getting-started/what... https://coq.inria.fr https://www.idris-lang.org and https://isabelle.in.tum.de
An easier alternative is to try disproving the statement, by executing it on thousands of examples and seeing if any fail. That gives us less confidence than a full proof, but can still be better than traditional "there exists" tests. This is called property checking or property-based testing. Systems I've used for this include https://hypothesis.works https://hackage.haskell.org/package/QuickCheck https://scalacheck.org and https://jsverify.github.io
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React to Elm Migration Guide
Using create-react-app, you’ll run npm test which uses Jest internally. If you are dealing with a lot of data on the UI, or using TypeScript, use JSVerify for property tests. For end to end tests, Cypress is a great choice.
What are some alternatives?
z-run - z-run -- scripting library lightweight Go-based tool
greenlight - Clojure integration testing framework
testy - test helpers for more meaningful, readable, and fluent tests
LazySmallCheck2012 - Lazy SmallCheck with functional values and existentials!
ospec - Noiseless testing framework
fast-check - Property based testing framework for JavaScript (like QuickCheck) written in TypeScript
php-easycheck - Mirror of http://chriswarbo.net/git/php-easycheck
hitchstory - Type-safe YAML integration tests. Tests that write your docs. Tests that rewrite themselves.
automate - Native bash script for automate tasks in a multiple servers
datadriven - Data-Driven Testing for Go