are

Library for defining and working with abstract regular expressions that support strings/sequences with elements of any symbol type, with an emphasis on supporting scenarios in which it is necessary to work with regular expressions as abstract mathematical objects.

Purpose

This library provides classes that enable concise construction of abstract regular expressions. In the case of this library, the term abstract refers to the fact that the symbols that constitute the abstract strings (i.e., iterable sequences) that satisfy an abstract regular expression can be values or objects of any immutable type. Thus, this library also makes it possible to determine whether an iterable containing zero or more objects satisfies a given abstract regular expression. Any abstract regular expression can also be converted into a nondeterministic finite automaton (as implemented within another package) that accepts exactly those iterables which satisfy that abstract regular expression.

Installation and Usage

This library is available as a package on PyPI:

python -m pip install are

The library can be imported in the usual way:

import are
from are import *

Examples

This library makes it possible to construct abstract regular expressions (represented as instances of the are_ class) that work with a chosen symbol type. In the example below, a regular expression is defined (using the literal operator lit_ and concatenation operator con_) in which symbols are integers. It is then applied to an iterable of integers. This returns the iterable's length (as an integer) if that iterable satisfies the abstract regular expression:

>>> from are import *
>>> a = con(lit(1), con(lit(2), lit(3)))
>>> a([1, 2, 3])
3

If the longest prefix of an iterable that satisfies an abstract regular expression is desired, the full parameter can be set to False:

>>> a([1, 2, 3, 4, 5], full=False)
3

Operators for alternation and repetition of abstract regular expressions are also available:

>>> a = rep(con(lit(1), lit(2)))
>>> a([1, 2, 1, 2, 1, 2])
6
>>> a = alt(rep(lit(2)), rep(lit(3)))
>>> a([2, 2, 2, 2, 2])
5
>>> a([3, 3, 3, 3])
4

The emp_ constructor can be used to create an abstract regular expression that is satisfied by the empty iterable:

>>> a = emp()
>>> a([])
0

The nul_ constructor can be used to create an abstract regular expression that cannot be satisfied:

>>> a = nul()
>>> a([]) is None
True
>>> a([1, 2, 3]) is None
True

An abstract regular expression that has only string symbols can be converted into a regular expression string that is compatible with the built-in re library:

>>> a = alt(lit('x'), rep(lit('y')))
>>> r = a.to_re()
>>> r
'(((x)*)|((y)*))'
>>> import re
>>> r = re.compile(a.to_re())
>>> r.fullmatch('yyy')

An abstract regular expression can also be converted into an NFA representation (as implemented within the PyPI package):

>>> a = con(lit(1), con(lit(2), lit(3)))
>>> a.to_nfa()
nfa({1: nfa({2: nfa({3: nfa()})})})

Development

All installation and development dependencies are fully specified in pyproject.toml. The project.optional-dependencies object is used to specify optional requirements for various development tasks. This makes it possible to specify additional options (such as docs, lint, and so on) when performing installation using pip:

python -m pip install .[docs,lint]

Documentation

The documentation can be generated automatically from the source files using Sphinx:

python -m pip install .[docs]
cd docs
sphinx-apidoc -f -E --templatedir=_templates -o _source .. && make html

Testing and Conventions

All unit tests are executed and their coverage is measured when using pytest (see the pyproject.toml file for configuration details):

python -m pip install .[test]
python -m pytest

The subset of the unit tests included in the module itself can be executed using doctest:

python src/are/are.py -v

Style conventions are enforced using Pylint:

python -m pip install .[lint]
python -m pylint src/are test/test_are.py

Contributions

In order to contribute to the source code, open an issue or submit a pull request on the GitHub page for this library.

Versioning

Beginning with version 0.1.0, the version number format for this library and the changes to the library associated with version number increments conform with Semantic Versioning 2.0.0.

Publishing

This library can be published as a package on PyPI by a package maintainer. First, install the dependencies required for packaging and publishing:

python -m pip install .[publish]

Ensure that the correct version number appears in pyproject.toml, and that any links in this README document to the Read the Docs documentation of this package (or its dependencies) have appropriate version numbers. Also ensure that the Read the Docs project for this library has an automation rule that activates and sets as the default all tagged versions. Create and push a tag for this version (replacing ?.?.? with the version number):

git tag ?.?.?
git push origin ?.?.?

Remove any old build/distribution files. Then, package the source into a distribution archive:

rm -rf build dist src/*.egg-info
python -m build --sdist --wheel .

Finally, upload the package distribution archive to PyPI:

python -m twine upload dist/*