microservice-apis VS hypothesis

The code for the book is freely available on GitHub. Feel free to check out the code, raise issues if something isn’t clear, and contribute new code. It’d be cool if this becomes a reference for Python developers interested in microservices and APIs.

Hi u/Kranke you can see an example of how to implement a fully decoupled service layer in chapter 7 of my book Microservice APIs, which you can download for free from this link. The code for the book is also freely available and you can check it out in this repo. Decoupling is desirable for the reasons explained in this part of the video.

There's not a whole lot of documentation and tutorials on how to use these tools, but I've written something about them in my upcoming book Microservice APIs. To see a practical example on how to use hypothesis-graphql, check out this file from the book's GitHub repository. For an explanation of the code, check out section 12.5.2 of chapter 12 of the book. Note: that section will go away in the next release of the chapter so make sure you check that specific link. You don't need to buy the book to read the section - Manning allows you to read a few fragments for free every day. To learn to generate hypothesis strategies, check out section 12.3 of chapter 12.

Hypothesis for Property-Based Testing: Hypothesis is a Python library facilitating property-based testing. It offers a distinct advantage by generating a wide array of input data based on specified properties or invariants within the code. The perks of Hypothesis include:

But then add tests! Tests for LaTeX equations that had never been executable as code.

https://github.com/HypothesisWorks/hypothesis :

> Hypothesis is a family of testing libraries which let you write tests parametrized by a source of examples. A Hypothesis implementation then generates simple and comprehensible examples that make your tests fail. This simplifies writing your tests and makes them more powerful at the same time, by letting software automate the boring bits and do them to a higher standard than a human would, freeing you to focus on the higher level test logic.

> This sort of testing is often called "property-based testing", and the most widely known implementation of the concept is the Haskell library QuickCheck, but Hypothesis differs significantly from QuickCheck and is designed to fit idiomatically and easily into existing styles of testing that you are used to, with absolutely no familiarity with Haskell or functional programming needed.

pgregory.net/rapid is a modern Go property-based testing library initially inspired by the power and convenience of Python's Hypothesis.

Hypothesis to generate dummy data for test.

To create your own test cases, I recommend you use hypothesis-graphql in combination with hypothesis. hypothesis is a property-based testing library. Property-based testing is an approach to testing in which you make assertions about the result of a test given certain conditions and parameters. For example, if you have a mutation that requires a boolean parameter, you can assert that the client will receive an error if it sends a different type. hypothesis-graphql is a GraphQL testing library that knows how to use hypothesis strategies to generate query documents.

The Hypothesis stateful testing code is somewhat self-contained, since it mostly builds on top of internal APIs that already existed.

We've had a lot of success combining that approach with property-based testing (https://github.com/HypothesisWorks/hypothesis) for the query engine at backtrace: https://engineering.backtrace.io/2020-03-11-how-hard-is-it-t... .

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