Pattern

This version was modified by Jonathan Pyle for compatibility with docassemble running on Python 3.8. Many of the features of the package have been removed.

Pattern is a web mining module for Python. It has tools for:

Data Mining: web services (Google, Twitter, Wikipedia), web crawler, HTML DOM parser
Natural Language Processing: part-of-speech taggers, n-gram search, sentiment analysis, WordNet
Machine Learning: vector space model, clustering, classification (KNN, SVM, Perceptron)
Network Analysis: graph centrality and visualization.

It is well documented, thoroughly tested with 350+ unit tests and comes bundled with 50+ examples. The source code is licensed under BSD.

Example

This example trains a classifier on adjectives mined from Twitter using Python 3. First, tweets that contain hashtag #win or #fail are collected. For example: "$20 tip off a sweet little old lady today #win". The word part-of-speech tags are then parsed, keeping only adjectives. Each tweet is transformed to a vector, a dictionary of adjective → count items, labeled WIN or FAIL. The classifier uses the vectors to learn which other tweets look more like WIN or more like FAIL.

from docassemble_pattern.web import Twitter
from docassemble_pattern.en import tag
from docassemble_pattern.vector import KNN, count

twitter, knn = Twitter(), KNN()

for i in range(1, 3):
    for tweet in twitter.search('#win OR #fail', start=i, count=100):
        s = tweet.text.lower()
        p = '#win' in s and 'WIN' or 'FAIL'
        v = tag(s)
        v = [word for word, pos in v if pos == 'JJ'] # JJ = adjective
        v = count(v) # {'sweet': 1}
        if v:
            knn.train(v, type=p)

print(knn.classify('sweet potato burger'))
print(knn.classify('stupid autocorrect'))

Installation

Pattern supports Python 2.7 and Python 3.6. To install Pattern so that it is available in all your scripts, unzip the download and from the command line do:

cd pattern-3.6
python setup.py install

If you have pip, you can automatically download and install from the PyPI repository:

pip install pattern

If none of the above works, you can make Python aware of the module in three ways:

Put the pattern folder in the same folder as your script.
Put the pattern folder in the standard location for modules so it is available to all scripts:
- c:\python36\Lib\site-packages\ (Windows),
- /Library/Python/3.6/site-packages/ (Mac OS X),
- /usr/lib/python3.6/site-packages/ (Unix).
Add the location of the module to sys.path in your script, before importing it:

MODULE = '/users/tom/desktop/pattern'
import sys; if MODULE not in sys.path: sys.path.append(MODULE)
from docassemble_pattern.en import parsetree

Documentation

For documentation and examples see the user documentation.

Version

3.6

License

BSD, see LICENSE.txt for further details.

Reference

De Smedt, T., Daelemans, W. (2012). Pattern for Python. Journal of Machine Learning Research, 13, 2031–2035.

Contribute

The source code is hosted on GitHub and contributions or donations are welcomed.

Bundled dependencies

Pattern is bundled with the following data sets, algorithms and Python packages:

Brill tagger, Eric Brill
Brill tagger for Dutch, Jeroen Geertzen
Brill tagger for German, Gerold Schneider & Martin Volk
Brill tagger for Spanish, trained on Wikicorpus (Samuel Reese & Gemma Boleda et al.)
Brill tagger for French, trained on Lefff (Benoît Sagot & Lionel Clément et al.)
Brill tagger for Italian, mined from Wiktionary
English pluralization, Damian Conway
Spanish verb inflection, Fred Jehle
French verb inflection, Bob Salita
Graph JavaScript framework, Aslak Hellesoy & Dave Hoover
LIBSVM, Chih-Chung Chang & Chih-Jen Lin
LIBLINEAR, Rong-En Fan et al.
NetworkX centrality, Aric Hagberg, Dan Schult & Pieter Swart
spelling corrector, Peter Norvig

Acknowledgements

Authors:

Tom De Smedt (tom@organisms.be)
Walter Daelemans (walter.daelemans@ua.ac.be)

Contributors (chronological):

Frederik De Bleser
Jason Wiener
Daniel Friesen
Jeroen Geertzen
Thomas Crombez
Ken Williams
Peteris Erins
Rajesh Nair
F. De Smedt
Radim Řehůřek
Tom Loredo
John DeBovis
Thomas Sileo
Gerold Schneider
Martin Volk
Samuel Joseph
Shubhanshu Mishra
Robert Elwell
Fred Jehle
Antoine Mazières + fabelier.org
Rémi de Zoeten + closealert.nl
Kenneth Koch
Jens Grivolla
Fabio Marfia
Steven Loria
Colin Molter + tevizz.com
Peter Bull
Maurizio Sambati
Dan Fu
Salvatore Di Dio
Vincent Van Asch
Frederik Elwert

jhpyle/pattern