File: README.md

package info (click to toggle)
python-pattern 2.6%2Bgit20180818-4.1
  • links: PTS
  • area: main
  • in suites: sid, trixie
  • size: 95,160 kB
  • sloc: python: 28,135; xml: 15,085; javascript: 5,810; makefile: 194
file content (160 lines) | stat: -rw-r--r-- 5,344 bytes parent folder | download | duplicates (2)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
Pattern
=======

[![Build Status](http://img.shields.io/travis/clips/pattern/master.svg?style=flat)](https://travis-ci.org/clips/pattern/branches)
[![Coverage](https://img.shields.io/coveralls/clips/pattern/master.svg?style=flat)](https://coveralls.io/github/clips/pattern?branch=master)
[![PyPi version](http://img.shields.io/pypi/v/pattern.svg?style=flat)](https://pypi.python.org/pypi/pattern)
[![License](https://img.shields.io/badge/License-BSD%203--Clause-green.svg?style=flat)](https://github.com/clips/pattern/blob/master/LICENSE.txt)

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 workflow](https://raw.githubusercontent.com/clips/pattern/master/docs/g/pattern_schema.gif)

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`.

```python
from pattern.web import Twitter
from pattern.en import tag
from 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:
```bash
cd pattern-3.6
python setup.py install
```

If you have pip, you can automatically download and install from the [PyPI repository](https://pypi.python.org/pypi/pattern):
```bash
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:

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

Documentation
-------------

For documentation and examples see the [user documentation](https://github.com/clips/pattern/wiki).

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