opencorpora.org python interface
Project description
This package provides Python interface to http://opencorpora.org/
Installation
pip install opencorpora-tools
If you have python 2.6 then argparse and ordereddict packages are required:
pip install argparse pip install ordereddict
Usage
Obtaining corpora
Opencorpora-tools works with XML from http://opencorpora.org/.
You can download and unpack the XML manually (from ‘Downloads’ page) or just use the provided command-line util:
$ opencorpora download
Run opencorpora download --help for more options.
Using corpora
Initialize:
>>> import opencorpora
>>> corpus = opencorpora.Corpora('annot.opcorpora.xml')
Get table of contents:
>>> corpus.catalog()
[('1', '"Частный корреспондент"'),
('2', '00021 Школа злословия'),
('3', '00022 Последнее восстание в Сеуле'),
('4', '00023 За кота - ответишь!'),
...
Work with documents:
>>> seoul_words = corpus.words('3')
>>> seoul_words
['«', 'Последнее', 'восстание', '»', 'в', 'Сеуле', ...
>>> corpus.documents(categories='Тема:ЧасКор:Книги*')
[Document: 21759 2001-2010-й: книги, которые потрясали,
Document: 12824 86 снов, вызванных полётом пчелы вокруг граната за секунду до пробуждения,
Document: 10930 А бойтесь единственно только того, кто скажет: «Я знаю, как надо!»,
...
opencorpora.Corpora is modelled after NLTK’s CorpusReader interface; consult with http://nltk.googlecode.com/svn/trunk/doc/book/ch02.html to get an idea how to work with the API.
It it not exactly the same, but is very similar. E.g. sents() in opencorpora-tools returns a list of Sentence instances and sents() in NLTK returns a list of list of strings, but Sentence instances quacks like a list of strings (it can be indexed, iterated, etc.).
Performance
OpenCorpora XML is huge (>250MB) so building full DOM tree requires a lot of memory (several GB) and should be avoided.
opencorpora-tools handles it this way:
corpus[doc_id] or corpus.get_document(doc_id) or corpus.documents(doc_ids) don’t load the original XML to memory and don’t parse it. They use precomputed offset information to slice the XML instead. The offset information is computed on first access and saved to “<name>.~” file.
Consider document loading O(1) regarding XML size. Individual documents are not huge so they and loaded and parsed as usual.
There are iterator methods for all corpora API (corpus.iterwords, etc).
Development
Development happens at github and bitbucket:
The main issue tracker is at github.
Feel free to submit ideas, bugs, pull requests (git or hg) or regular patches.
Running tests
Make sure tox is installed and run
$ tox
from the source checkout. Tests should pass under python 2.6..3.2 and pypy > 1.8.
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