This library was a personal project around formally manipulating regular expressions. The idea is basically as follows:

• Parse the regular expression using a custom parsimonious grammar into an AST. (See regex_gramar.py.)
• Compile the AST into RegularExpression objects using the Brzozowski derivative. (See http://www.drmaciver.com/2016/12/proving-or-refuting-regular-expression-equivalence/ for background and derivative.py).
• Form a graphical representation of the regular expression by taking the derivative with respect to each letter of the alphabet. (In other words, convert it to a DFA. See dfa.py.)
• Convert the graphical representation to a matrix, whose powers can be used to compute probability distributions of strings that match the original regular expression. (See generation.py.)

This allows you to do the following:

• Check if two regular expressions can match the same string, which may be of interest for some problems. (This was the original impetus for the project, checking whether two rules which depend on regular expressions might both apply.) This is possible because the Brzozowski formalism makes negation and intersection of regular expressions easy.
• Produce strings of a given length sampled uniformly at random from the probability distribution of strings matching the regular expression of a given length. Hypothesis has since implemented a strategy that allows generation of strings matching a regular expression that is presumably better than this approach for the purpose of property-based testing. (See https://hypothesis.readthedocs.io/en/latest/data.html#hypothesis.strategies.from_regex)