symbolism 0.2.3

Extensible combinator library for building symbolic expressions that can be evaluated at a later time.

Extensible combinator library for building symbolic Python expressions that are compatible with serialization and can be evaluated at a later time.

Purpose

In many scenarios that require some form of lazy evaluation, it is sufficient to employ lambda expressions, generators/iterables, or abstract syntax trees (via the ast and/or inspect modules). However, there are certain cases where none of these are an option (for example, employing lambda expressions precludes serialization and employing the ast or inspect modules usually involves introducing boilerplate that expands the solution beyond one line of code). The purpose of this library is to fill those gaps and make it possible to write concise symbolic expressions that are embedded directly in the concrete syntax of the language.

Package Installation and Usage

The package is available on PyPI:

python -m pip install symbolism

The library can be imported in the usual ways:

import symbolism
from symbolism import *

Examples

The library makes it possible to construct symbolic Python expressions (as instances of the symbol class) that can be evaluated at a later time. A symbolic expression involving addition of integers is created in the example below:

>>> from symbolism import *
>>> addition = symbol(lambda x, y: x + y)
>>> summation = addition(symbol(1), symbol(2))

The expression above can be evaluated at a later time:

>>> summation.evaluate()
3

Symbol instances are compatible with all built-in infix and prefix operators. When an operator is applied to one or more symbol instances, a new symbol instance is created:

>>> summation = symbol(1) + symbol(2)
>>> summation.evaluate()
3

Pre-defined constants are also provided for all built-in operators:

>>> conjunction = and_(symbol(True), symbol(False))
>>> conjunction.evaluate()
False

Documentation

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

cd docs
python -m pip install -r requirements.txt
sphinx-apidoc -f -E --templatedir=_templates -o _source .. ../setup.py && make html

Testing and Conventions

All unit tests are executed and their coverage is measured when using nose (see setup.cfg for configuration details):

python -m pip install nose coverage
nosetests --cover-erase

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

python symbolism/symbolism.py -v

Style conventions are enforced using Pylint:

python -m pip install pylint
pylint symbolism

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.