textmetrics

Automatic text metrics---BLEU, ROUGE, and METEOR, plus extras like vocab and ngrams.

Usage

# Compares each candidate (c) separately against all references (r).
python -m textmetrics.main c1.txt c2.txt --references r1.txt r2.txt r3.txt

Installation

Requires:

• Perl (for BLEU)
• Java 1.8 (for METEOR)
• Python 3.6+

pip install textmetrics

Features

• BLEU
• ROUGE
• METEOR

Notes

BLEU and METEOR use the refernce implementations (in Perl and Java, respectively). We originally used the reference Perl implementation for ROUGE as well, but it ran so slowly that we opted for a Python reimplementation instead. (ROUGE's original Perl implementation is also more difficult to setup, even with wrapper libraries.)

Worklist

• pypi

• API support

• ROUGE crashes things if it decides there aren't sentences (e.g., run with README.md as input and reference)

• Add back in orig ROUGE for completeness (place behind switch)

• ngrams has divide by zero error. With two simple files (two lines each, same first line, differing second line) running with 2.txt --references 1.txt 1.txt triggered this divide by zero

• Demo for better README

• Tests

• Early check in each module for whether program runnable + nice error message (e.g., no java or bad version, no perl or bad version, etc.)

Note to self: I followed this guide for packaging to pypi, and future uploads will probably look like:

# (1) ensure tests pass

# (2) bump version in setup.py

# (3) commit + push to github

# (4) generate distribution
python setup.py sdist bdist_wheel

# (5) Upload
twine upload dist/*