Package: pattern3
Pattern=======.. image:: https://travis-ci.org/pattern3/pattern.svg?branch=master:target: https://travis-ci.org/pattern3/patternPattern 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 and bundled with 50+ examples and 350+ unit tests.The source code is licensed under BSD and available fromhttp://www.clips.ua.ac.be/pages/pattern... figure:: http://www.clips.ua.ac.be/media/pattern_schema.gif:alt: Pattern example workflowPattern example workflowVersion-------2.6License-------**BSD**, see ``LICENSE.txt`` for further details.Installation------------Pattern is written for Python 2.5+ (no support for Python 3 yet). Themodule has no external dependencies except when using LSA in thepattern.vector module, which requires NumPy (installed by default on MacOS X). To install Pattern so that it is available in all your scripts,unzip the download and from the command line do:.. code:: bashcd pattern-2.6python setup.py installIf you have pip, you can automatically download and install from thePyPi repository:.. code:: bashpip install patternIf none of the above works, you can make Python aware of the module inthree ways: - Put the pattern folder in the same folder as your script.- Put the pattern folder in the standard location for modules so it isavailable to all scripts: \* ``c:\python26\Lib\site-packages\``(Windows), \* ``/Library/Python/2.6/site-packages/`` (Mac OS X), \*``/usr/lib/python2.6/site-packages/`` (Unix). - Add the location of themodule to ``sys.path`` in your script, before importing it:.. code:: pythonMODULE = '/users/tom/desktop/pattern'import sys; if MODULE not in sys.path: sys.path.append(MODULE)from pattern.en import parsetreeExample-------This example trains a classifier on adjectives mined from Twitter.First, tweets that contain hashtag #win or #fail are collected. Forexample: "$20 tip off a sweet little old lady today #win". The wordpart-of-speech tags are then parsed, keeping only adjectives. Each tweetis transformed to a vector, a dictionary of adjective → count items,labeled ``WIN`` or ``FAIL``. The classifier uses the vectors to learnwhich other tweets look more like ``WIN`` or more like ``FAIL``... code:: pythonfrom pattern.web    import Twitterfrom pattern.en     import tagfrom pattern.vector import KNN, counttwitter, 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 = adjectivev = count(v) # {'sweet': 1}if v:knn.train(v, type=p)print knn.classify('sweet potato burger')print knn.classify('stupid autocorrect')Documentation-------------http://www.clips.ua.ac.be/pages/patternReference---------De Smedt, T., Daelemans, W. (2012). Pattern for Python. *Journal ofMachine Learning Research, 13*, 2031–2035.Contribute----------The source code is hosted on GitHub and contributions or donations arewelcomed, see the `developerdocumentation <http://www.clips.ua.ac.be/pages/pattern#contribute>`__.If you use Pattern in your work, please cite our reference paper.Bundled dependencies--------------------Pattern is bundled with the following data sets, algorithms and Pythonpackages:-  **Beautiful Soup**, Leonard Richardson-  **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 & LionelClément 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-  **PDFMiner**, Yusuke Shinyama-  **Python docx**, Mike Maccana-  **PyWordNet**, Oliver Steele-  **simplejson**, Bob Ippolito-  **spelling corrector**, Peter Norvig-  **Universal Feed Parser**, Mark Pilgrim-  **WordNet**, Christiane Fellbaum et al.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