ngramratio 0.0.4

N-grams based similarity score

python-ngramratio

A method for similarity scoring of two strings.

The method, namely nratio, belongs to the class SequenceMatcherExtended, which is an extension of the SequenceMatcher class of the difflib package. In particular, nratio (method of SequenceMatcherExtended) is an augmenation of ratio (method of SequenceMatcher).

ngramratio is to be pronounced as "n gram ratio". The library uses n-grams to find a similarity score via a division (ratio) of the number of matched characters by the total number of characters. See below for more details.

Motivation

To compute a similarity score based on matching n-grams (with n>=1 chosen by the user) rather than matching single characters (as in the case of the ratio method).

Installation

To install the Python library run:

pip install ngramratio

The library will be installed as ngramratio to bin on Linux (e.g. /usr/bin); or as ngramratio.exe to Scripts in your Python installation on Windows (e.g. C:\Python27\Scripts\ngramratio.exe).

You may consider installing the library only for the current user:

pip install ngramratio --user

In this case the library will be installed to ~/.local/bin/ngramratio on Linux and to %APPDATA%\Python\Scripts\ngramratio.exe on Windows.

Library usage

The module provides a method, nratio, which takes an integer number (the user's required minimum n-gram length, i.e. number of consecutive characters, to be matched) and outputs a similarity index (float number in [0,1]).

First step: initialize an object of class SequenceMatcherExtended specifying the two strings to be compared:

    >>> import ngramratio from ngramratio

    >>> SequenceMatcherExtended = ngrmaratio.SequenceMatcherExtended

    >>> string_one = "ab cde"
    >>> string_two = "bcde"

    >>> s = SequenceMatcherExtended(None, string_one, string_two, None)
    >>> # The "None" arguments prevents from any character being considered junk..
    >>> # .. see the difflib documentation for more information on this.

Second step: apply the ratio and nratio methods and compare similarity scores:

    >>> s.ratio()
    >>> # Matches any character. Matches: "b" (length 1), "cde"(length 3). Score: (3+1)*2/10.
    0.8
    >>> s.nratio(1)
    >>> # Matches substring of length 1 or more. It replicates `ratio()`'s functionality.
    0.8
    >>> s.nratio(2)
    >>> # Matches substring of length 2 or more. Matches: "cde"(length 3). Score: 3*2/10.
    0.6
    >>> s.nratio(3)
    >>> # Matches substring of length 3 or more. Matches: "cde"(length 3). Score: 3*2/10.
    0.6
    >>> s.nratio(4)
    >>> # Matches substring of length 3 or more. Score 0/10.
    0.0

The similarity score is computed as the number of characters matched (m) mutiplied by two (2) and divided by the total numer of characters (T) of the two strings, i.e. similarity score = 2m/T. Note that Python always returns a float upon computing a division.

Testing in a virtual environment

This project uses pytest testing framework with tox and docker to automate testing in different python environments. Tests are stored in the test/ folder.

To test a specific python version, for example version 3.6, edit the last few characters of the startTest.sh script to py36 AND change the image to python 3.6 on line 4 of the docker-compose.yaml file.

To run tests, run bash _scripts/startTest.sh. This will start a docker container using the specified python image. After testing, or before testing a different python version, run bash _scripts/teardown.sh to remove the docker container.

The library has been tested successfully for python >= 3.6.

Testing on your local machine with no v.e.

You can use tox directly in your local machine. Make sure to install tox, pytest before testing.

On Linux tox expects to find executables like python3.6, python3.10 etc. On Windows it looks for C:\Python36\python.exe and C:\Python310\python.exe respectively.

To test a Python environments, use the -e option. For example, to test against Python 3.7 run:

tox -e py37

in the root of the project source tree.

To fix code formatting (it will install pre-commit as a dependency):

tox -e lint

See tox.ini file to learn more about testing.

Contributions

Contributions should include tests and an explanation for the changes they propose. Documentation (examples, docstrings, README.md) should be updated accordingly.