integraty | experimental integration testing framework

integraty is a Python library. integraty has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

An experimental integration testing framework, or perhaps building blocks for one. Don't use this unless you are ready for a lot of pain. :). The main goal of this library is to provide just enough tooling to make integration testing a little less painful. Integration testing is normally the domain of shell scripts and tools like awk, sed, grep, cut, etc., etc. However, there are a number of problems with this traditional approach which tend to lead to tests which are difficult to maintain and often are hard to read and follow. Without any doubt gluing commands together with pipes is an extremely powerful mechanism, which makes the shell amazingly flexible and infinitely extensible. But these very same attributes also make it difficult to write very standard looking code, which can be maintained by multiple people over long time intervals. This library aims to build on top of excellent tools already part of Python distribution and additionally makes possible to take advantage of the amazing pytest package. While pytest is actually optional, it is a very solid and mature package which could be used for anything from unit tests to functional and integration tests. This library is actually a combination of a few loosely coupled components. Its aim is to reduce information and transform output from programs in the same way that would typically be done with filtering tools like grep and awk, etc., but instead do it with the Python, while also transforming reduced data into structures which are pleasant to work with. It is no secret that shell's strength is not its rich data structures. Conversely Python excels at data manipulation extraction and transformation. It is fast-becoming the lingua franca of data science, field rich with data and demanding flexibility, expressiveness and maintainability of code. Python is low-boilerplate, and scores highly in the readability test. My hope is to capture these strengths and substitute shell's weaknesses without losing very much of what makes using shell the defacto standard for integration testing on nix systems.