Datatest provides tools for test driven data-wrangling and data validation. It supports both pytest and unittest style testing. I've been working to get datatest ready for a few pre-PyCon updates. This latest release takes many of the "how-to" solutions and brings them into the core package. * Docs - https://datatest.readthedocs.io/ * PyPI - https://pypi.org/project/datatest/ * Devel - https://github.com/shawnbrown/datatest Upgrade an existing installation to 0.9.4: pip install --upgrade datatest What's New in Datatest 0.9.4: * Added Python 3.8 testing and support. * Added new validate methods (moved from how-to recipes into core module): * Added approx() method to require for approximate numeric equality. * Added fuzzy() method to require strings by approximate match. * Added interval() method to require elements within a given interval. * Added set(), subset(), and superset() methods for explicit membership checking. * Added unique() method to require unique elements. * Added order() method to require elements by relative order. * Changed default sequence validation to check elements by index position rather than checking by relative order. * Added fuzzy-matching allowance to allow strings by approximate match. * Added Predicate class to formalize behavior--also provides inverse-matching with the inversion operator (~). * Added new methods to Query class: * Added unwrap() to remove single-element containers and return their unwrapped contents. * Added starmap() to unpack grouped arguments when applying a function to elements. * Fixed improper use of assert statements with appropriate conditional checks and error behavior. * Added requirement class hierarchy (using BaseRequirement). This gives users a cleaner way to implement custom validation behavior and makes the underlying codebase easier to maintain. * Changed name of ProxyGroup to RepeatingContainer. * Changed "How To" examples to use the new validation methods.