Comparable

Comparable is a library providing abstract base classes that enable subclasses to be compared for "equality" and "similarity" based on their attributes.

Getting Started

Requirements

• Python 3.3+

Installation

Comparable can be installed with pip:

$ pip install comparable

or directly from the source code:

$ git clone https://github.com/jacebrowning/comparable.git
$ cd comparable
$ python setup.py install

Basic Usage

After installation, abstract base classes can be imported from the package:

$ python
>>> import comparable
>>> comparable.__version__
>>> from comparable import SimpleComparable, CompoundComparable

Comparable classes use == as the operation for "equality" and % as the operation for "similarity". They may also override a threshold attribute to set the "similarity" ratio.

Simple Comparables

Simple comparable types must override the equality and similarity methods to return bool and Similarity objects, respectively. See comparable.simple for examples.

Compound Comparables

Compound comparable types contain multiple simple comparable types. They must override the attributes property to define which attributes should be used for comparison. See comparable.compund for examples.

Examples

Comparable includes many generic comparable types:

$ python
>>> from comparable.simple import Number, Text, TextEnum, TextTitle
>>> from comparable.compound import Group

A basic script might look similar to the following:

from comparable.simple import TextTitle
from comparable import tools

base = TextTitle("The Cat and the Hat")
items = [TextTitle("cat & hat"), TextTitle("cat & the hat")]

print("Equality: {}".format(base == items[0]))
print("Similarity: {}".format(base % items[0]))

print("Duplicates: {}".format(tools.duplicates(base, items)))

For Contributors

Requirements

• Make:
  • Windows: http://cygwin.com/install.html
  • Mac: https://developer.apple.com/xcode
  • Linux: http://www.gnu.org/software/make (likely already installed)
• virtualenv: https://pypi.python.org/pypi/virtualenv#installation
• Pandoc: http://johnmacfarlane.net/pandoc/installing.html
• Graphviz: http://www.graphviz.org/Download.php

Installation

Create a virtualenv:

$ make env

Run the tests:

$ make test
$ make tests  # includes integration tests

Build the documentation:

$ make doc

Run static analysis:

$ make pep8
$ make pep257
$ make pylint
$ make check  # includes all checks

Prepare a release:

$ make dist  # dry run
$ make upload