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Callable subclass of the tuple type for representing logical operators/connectives based on their truth tables.

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logical

Callable subclass of the tuple type for representing logical operators/connectives based on their truth tables.

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Installation and Usage

This library is available as a package on PyPI:

python -m pip install logical

The library can be imported in the usual ways:

import logical
from logical import *

Examples

Each instance of the logical class (derived from the built-in tuple class) represents a boolean function that accepts n inputs by specifying its output values across all possible inputs. In other words, an instance represents the output column of a truth table for a function (under the assumption that the input vectors to which each output value corresponds are sorted in ascending order). Thus, each instance representing a function that accepts n inputs must have length 2**n.

For example, consider the truth table below for a boolean function f that accepts three inputs:

x y z f (x, y, z)
0 0 0 1
0 0 1 0
0 1 0 1
0 1 1 0
1 0 0 0
1 0 1 1
1 1 0 1
1 1 1 0

Notice that the input vectors (i.e., the left-most three column values in each row) are sorted in ascending order from top to bottom. If we always assume this order for input vectors, the entire function f can be represented using the right-most column. For the example function f defined by the table above, this can be done in the manner illustrated below:

>>> from logical import *
>>> f = logical((1, 0, 1, 0, 0, 1, 1, 0))

It is then possible to apply the instance f defined above to any three-component input vector:

>>> f(0, 1, 1)
0
>>> f(1, 1, 0)
1

It is also possible to create a new logical instance that has a function attribute corresponding to a compiled Python function that has the same behavior as the __call__ method (at least, on valid inputs). This Python function does not check that inputs are of the correct type and format, but has an execution time that is usually at most half of the execution time of the __call__ method:

>>> f = logical((1, 0, 0, 1, 0, 1, 0, 1))
>>> g = f.compiled()
>>> g.function(0, 0, 0)
1
>>> g.function(1, 1, 0)
0

Pre-defined instances are provided for all nullary, unary, and binary boolean functions. These are available both as constants and as attributes of the logical class:

>>> logical.xor_(1, 0)
1
>>> and_(1, 0)
0

The constants nullary, unary, and binary are also defined. Each is a set containing exactly those instances of logical that represent functions having that arity:

>>> unary
{(0, 0), (1, 0), (1, 1), (0, 1)}
>>> len(binary)
16

For convenience, the constant every is defined as the union of nullary, unary, and binary.

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

Alternatively, all unit tests are included in the module itself and can be executed using doctest:

python src/logical/logical.py -v

Style conventions are enforced using Pylint:

python -m pip install .[lint]
python -m pylint src/logical

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

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/*