text-hr 0.20
Morphological/Inflection/Lemmatization Engine for Croatian language, POS tagger, stopwords
Requires Python: >=3.3

Morphological/Inflection/Lemmatization Engine for Croatian language
===================================================================
"text-hr" is Morphological/Inflectional/Lemmatization Engine for Croatian
language written in Python programming language. Includes stopwords and
Part-Of-Speech tagging engine (POS tagging) based on inverse inflection
algorithm for detection.

Since API is not freezed, this project is still in alpha.

TAGS 
----
    Croatian language, lemmatization, stemming, inflection, python, natural
    language processing (NLP), Part-of-speech (POS) tagging, stopwords, inverse
    inflection, morphological lexicon


OZNAKE
------
    Hrvatski jezik, lematizacija, Python biblioteka, morfologija, infleksija,
    obrnuta infleksija, prepoznavanje vrsta riječi, računalna obrada govornog
    jezika, zaustavne riječi, morfološki leksikon

AUTHOR
======
Robert Lujo, Zagreb, Croatia, find mail address in LICENCE


FEATURES
========
To name the most important:
 - inflection system - for producing all forms of one word
 - detection of word types (POS tagging) - from existing list of word forms
 - list of stopwords

System is based on unicode strings, default codepage to convert from and to 
string is cp-1250.

Check `Getting started`_.

INSTALLATION
============
Installation instructions - if you have installed pip package 
http://pypi.python.org/pypi/pip::

    pip install text-hr

If not, then do it old-fashioned way:
    - download zip from http://pypi.python.org/pypi/text-hr/
    - unzip
    - open shell
    - go to distribution directory
    - python setup.py install


GETTING STARTED
===============
There are three important parts that this project provides:
 - `Inflection system`_ - for producing all forms of one word
 - `Detection of word types (POS tagging)`_ - from existing list of word forms
 - `List of stopwords`_

Inflection system
-----------------
Usage example - start python shell::

    >>> from text_hr import Verb
    >>> v = Verb("platiti")
    >>> for k in sorted(v.forms.keys()):
    ...     print(k, v.forms[k])
    ...
    AOR/P/1 [u'platismo']
    AOR/P/2 [u'platiste']
    AOR/P/3 [u'plati\u0161e']
    AOR/S/1 [u'platih']
    AOR/S/2 [u'plati']
    AOR/S/3 [u'plati']
    IMP/P/1 [u'platasmo', u'pla\u0107asmo', u'platijasmo']
    IMP/P/2 [u'plataste', u'pla\u0107aste', u'platijaste']
    IMP/P/3 [u'platahu', u'pla\u0107ahu', u'platijahu']
    ...
    VA_PA//P_O+S+V+N [u'pla\u0107eno']
    X_INF// [u'platiti']
    X_VAD_PAS// [u'plativ\u0161i']
    X_VAD_PRE// [u'plate\u0107i']
    X_VAD_PRE// [u'plate\u0107i']

Detection of word types (POS tagging)
-------------------------------------
TODO: to be done - check test_detect.txt for samples, and detect.py for the logic:

First example in test_detect.txt::

    >>> from text_hr.detect import WordTypeRecognizerExample
    >>> def test_it(word_list, wt_filter=None, level=2):
    ...     wdh = WordTypeRecognizerExample(word_list, silent=True)
    ...     if not wt_filter is None:
    ...         wdh.detect(wt_filter=wt_filter, level=level)  # e.g. wt_filter=["N"]
    ...     else:
    ...         wdh.detect(level=level)  # all word types
    ...     lines_file = LinesFile()
    ...     wdh.dump_result(lines_file) # doctest: +NORMALIZE_WHITESPACE +ELLIPSIS
    ...     print("\n".join(lines_file.lines))
    ...     return wdh

    >>> class LinesFile(object):
    ...     def __init__(self):
    ...         self.lines = []
    ...     def write(self, s):
    ...         self.lines.append(repr(s.rstrip()))

    >>> word_list = [
    ...   "Broj    84"
    ... , "broji   34"
    ... , "Brojila  28"
    ... , "broje   23"
    ... , "brojeći 22"
    ... , "brojim   7"
    ... , "brojimo  5"
    ... , "brojiš   4"
    ... , "brojahu  2"
    ... , "brojaše  1"
    ... , "brojite  1"
    ... , "-brijestovu 1"
    ... , "brijestovi 1"   #the only one checked with endswith, but all other will be checked with get_freq
    ... , "-brijestove 1"
    ... , "-brijestova 1"
    ... ]

    Lowest quality, but fastest
    >>> wdh = test_it(word_list, level=4) # doctest: +ELLIPSIS
    " 10/  183 -> brojati              (u'V-XX_-_JATI-je\\u0107i-0') 84/broj,34/broji,23/broje,22/broje\xe6i,7/brojim,5/brojimo,4/broji\x9a,2/brojahu,1/brojite,1/broja\x9ae"

List of stopwords
-----------------
Is located in std_words.txt, and you can read it directly from here

    http://bitbucket.org/trebor74hr/text-hr/src/tip/text_hr/std_words.txt

The list can be updated like this::

    >>> import text_hr
    >>> text_hr.dump_all_std_words()
    Totaly 2904 word forms dumped to r:\hg-clones\python\text-hr\text_hr\std_words.txt in codepage utf8

Iteration over all words goes like this::

    from text_hr import get_all_std_words

    for word_base, l_key, cnt, _suff_id, wform_key, wform in get_all_std_words():
        print(word_base, l_key, cnt, _suff_id, wform_key, wform)


Further
-------
Since there is currently no good documentation, the best source of 
further information is by reading tests inside of modules and
tests in tests directory (dev version). More information in `Running tests`_.
You can allways read a source.


DOCUMENTATION
=============
Currently there is no documentation. In progress ...


SUPPORT
=======
Since this project is limited by my free time, support is limited. 


REPORT BUG OR REQUEST FEATURE
-----------------------------
If you encounter bug, the best is to report it to the bitbucket web page
http://bitbucket.org/trebor74hr/text-hr.

If there will be an interest for development for other inflection rich
languages, I'd be glad to decouple language specific code and create new
project that will be capable to deal with multiple languages.

The best way to contact me is by mail (find in LICENCE).

TODO list is in readme.txt (dev version).


CONTRIBUTION
============
Since this project is not currently in the stable API phase, contribution
should wait for a while.


RUNNING TESTS
=============
All tests are doctests (not unittests). There are three type of tests in the
package: 

    1. doctests in each module - e.g. in verbs.py
    2. doctests in tests/test_*.txt - only development version
    3. tests which are not automatically compared - i.e. in special call mode
       detect.py can produce output file which needs to be compared 
       manually with some existing file. Such test(s) are very slow. This needs
       to be changed to be automatic.

Running each module directly will run 1. and 2. if running from development
version. To get development version
To use development version (http://bitbucket.org/trebor74hr/text-hr)::

 hg clone https://bitbucket.org/trebor74hr/text-hr


create text_hr.pth in python site-packages directory with path to text-hr e.g.::

    r:\hg-clones\python\text-hr

To run all tests:
    - go to tests directory
    - run tests.py like (with sample output)::

        > python tests.py
        testing module   __init__
        testing module   adjectives
        ...
        testing textfile R:\hg-clones\python\text-hr\tests\test_adj.txt
        ...
        testing textfile R:\hg-clones\python\text-hr\tests\test_verbs_type.txt

To run tests for just one module:
    - goto text_hr directory
    - run tests by running module, e.g.::

        > py pronouns.py
        __main__: running doctests
        ..\tests\test_pronouns.txt: running doctests

    - in the case you're not running from dev version, you'll get output like
      this::

        > py pronouns.py
        __main__: running doctests
        ..\tests\test_pronouns.txt: Not found, skipping

ADDITIONAL
==========
Master thesis pdf in Croatian (134 pages) with title::

    Lociranje sličnih logičkih cjelina u tekstualnim 
    dokumentima na hrvatskome jeziku

can be found at:

    http://bitbucket.org/trebor74hr/text-hr/downloads/magistarski-konacni.pdf

TODO
====
various things, see readme.txt for details.

CHANGES
=======
0.20
----
RL 200507
    - migration to python 3+, tested on python 3.7, all tests pass

0.18
----
RL 121210 
    - fixed wrong readme on bitbucket homepage

0.17 
----
RL 100617 
    - utf-8 setup 

0.16 
----
RL 100617 
    - master thesis pdf added to repository (in Croatian, 134 pages)

0.15 
----
RL 100617 
    - minor changes

0.14 
----
RL 100617 
    - beta release
    - tags: lemmatization, stemming

0.13 
----
RL 100610:
    - text_hr package reorganized (__init__.py with __all__ and imports ...)
    - word_types.py removed
    - std_words.txt

0.12 
----
RL 100608 :
    - README
    - enabled tests from tests.py for all 
    - enabled tests from directly from each modules

0.11 
----
RL 100607:
    - recreated repo at bitbucket
    - no .suff_registry.pickle and testing_*.out put in zip

0.10
----
RL 100605:
    - first installable release