hexagon VS pytest

Hexagon is a Microservices Toolkit that aims to provide all you need to develop applications that run on Cloud environments.

Ktor is a project that's not primarily focused on application performance but developer performance. It seems to be sth different than what you want to achieve. I don't think a lot frameworks... or any other framework writes its own low level io stuff from scratch, they mostly use https://netty.io/ because there's not too much room for improvement and it's complete, battle tested and so on. I lately came across https://github.com/hexagonkt/hexagon which seems to have a very solid code base based on modules modules modules, is kotlin first and they have an adapter for netty. The usage of the naked http server seems to be as easy as it can be https://hexagonkt.com/port_http_server/port_http_server/ and they are even listed on techempower benchmarks https://github.com/hexagonkt/hexagon/ .

https://github.com/hexagonkt/hexagon A microservices toolkit written in Kotlin.

In this blog post I want to demonstrate how my lab equipment such as a lab power supply or a digital multimeter (DMM) have been integrated into some pytest-based tests. Would love to get your feedback and thoughts! 🚀

Pytest: is a third-party testing framework that supports fixtures, parameterized testing, and easy test discovery while having room to add plugins to extend its functionality.

Next, you need to install a testing framework that will be used for performing unit testing in your project. Several testing frameworks are available depending on the programming language used to create an application. For example, JUnit is commonly used for Java apps, pytest for Python apps, NUnit for .NET apps, Jest for JavaScript apps, and so on. We’ll use the Jest framework for this tutorial since we are using JavaScript.

Yea, read through the pytest docs.

I absolutely agree about fixtures-as-arguments thing. Ward does this a lot better, using default values for the fixture factory. There's a long issue on ideas to implement something like that as a pytest plugin (https://github.com/pytest-dev/pytest/issues/3834), but it seems the resulting plugin relies on something of a hack.

I recommend writing a few tests. py.test makes that quite simple:

Since ITK's inception in 1999, there has been a focus on engineering practices that result in high-quality software. High-quality scientific software is driven by regression testing. The ITK project supported the development of CTest and CDash unit testing and software quality dashboard tools for use with the CMake build system. In the Python programming language, the pytest test driver helps developers write small, readable scripts that ensure their software will continue to work as expected. However, pytest can only test Python scripts by default, and errors in untested computational notebooks are more common than well-tested Python code.