hypothesis VS sphinx

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

Sphinx is primarily known as a documentation generator, but it can also be used to create static websites. It excels in generating technical documentation, and its support for multiple output formats, including HTML and PDF, makes it a versatile tool. Sphinx uses reStructuredText for content creation and is highly extensible through plugins.

Sphinx a documentation generator or a tool that translates a set of plain text source files into various output formats, automatically producing cross-references, indices, etc. That is, if you have a directory containing a bunch of reStructuredText or Markdown documents, Sphinx can generate a series of HTML files, a PDF file (via LaTeX), man pages and much more.

Notable mentions to [Sphinx](https://www.sphinx-doc.org/). It's workflow is more tuned to the "book" format rather than the blog, forum or thread format.

Currently trying out Sphinx (https://www.sphinx-doc.org) and the trying to get the autodocgen feature to see what that can do.

So, I've documented my code and now I need a .PDF with this documentation. Is there any easy way to do it? Once I used Sphinx but it generated a not so easy .TeX.

AutoPyTabs allows you to write code examples in your documentation targeting a single version of Python and then generates examples targeting higher Python versions on the fly, presenting them in tabs, using popular tabs extensions. This all comes packaged as a markdown extension, MkDocs plugin and a Sphinx, so it can easily be integrated with your documentation workflow.

Honestly, I think it's just an issue of documentation. For example, if there was an easier way to document @overload functions, that would help (cf. https://github.com/sphinx-doc/sphinx/issues/7787)

We use sphynx for our pipeline documentation for all technical details Classes , packages and functions docstrings using reStructuredText (reST) format

I like Sphinx [0] with the MyST Markdown syntax [1]. There is a related project, Myst NB [2], which enables including Jupyter notebooks in your site. There is also a plugin for blogging [3].

[0]: https://www.sphinx-doc.org

Sphinx is the go-to tool for documentation. It took me a while to understand how to use Sphinx, but I now have a decent workflow with MyST which allows me to write all the docs in markdown. My sphinx-markdown-docs repo shows an example of what I do.