Project: dawg-python

Pure-python reader for DAWGs (DAFSAs) created by dawgdic C++ library or DAWG Python extension.

Project Details

Latest version
0.7.2
Home Page
https://github.com/kmike/DAWG-Python/
PyPI Page
https://pypi.org/project/dawg-python/

Project Popularity

PageRank
0.003949919513450994
Number of downloads
104338

DAWG-Python

.. image:: https://travis-ci.org/kmike/DAWG-Python.png?branch=master :target: https://travis-ci.org/kmike/DAWG-Python .. image:: https://coveralls.io/repos/kmike/DAWG-Python/badge.png?branch=master :target: https://coveralls.io/r/kmike/DAWG-Python

This pure-python package provides read-only access for files created by dawgdic_ C++ library and DAWG_ python package.

.. _dawgdic: https://code.google.com/p/dawgdic/ .. _DAWG: https://github.com/kmike/DAWG

This package is not capable of creating DAWGs. It works with DAWGs built by dawgdic_ C++ library or DAWG_ Python extension module. The main purpose of DAWG-Python is to provide an access to DAWGs without requiring compiled extensions. It is also quite fast under PyPy (see benchmarks).

Installation

pip install DAWG-Python

Usage

The aim of DAWG-Python is to be API- and binary-compatible with DAWG_ when it is possible.

First, you have to create a dawg using DAWG_ module::

import dawg
d = dawg.DAWG(data)
d.save('words.dawg')

And then this dawg can be loaded without requiring C extensions::

import dawg_python
d = dawg_python.DAWG().load('words.dawg')

Please consult DAWG_ docs for detailed usage. Some features (like constructor parameters or save method) are intentionally unsupported.

Benchmarks

Benchmark results (100k unicode words, integer values (lenghts of the words), PyPy 1.9, macbook air i5 1.8 Ghz)::

dict __getitem__ (hits):        11.090M ops/sec
DAWG __getitem__ (hits):        not supported
BytesDAWG __getitem__ (hits):   0.493M ops/sec
RecordDAWG __getitem__ (hits):  0.376M ops/sec

dict get() (hits):              10.127M ops/sec
DAWG get() (hits):              not supported
BytesDAWG get() (hits):         0.481M ops/sec
RecordDAWG get() (hits):        0.402M ops/sec
dict get() (misses):            14.885M ops/sec
DAWG get() (misses):            not supported
BytesDAWG get() (misses):       1.259M ops/sec
RecordDAWG get() (misses):      1.337M ops/sec

dict __contains__ (hits):           11.100M ops/sec
DAWG __contains__ (hits):           1.317M ops/sec
BytesDAWG __contains__ (hits):      1.107M ops/sec
RecordDAWG __contains__ (hits):     1.095M ops/sec

dict __contains__ (misses):         10.567M ops/sec
DAWG __contains__ (misses):         1.902M ops/sec
BytesDAWG __contains__ (misses):    1.873M ops/sec
RecordDAWG __contains__ (misses):   1.862M ops/sec

dict items():           44.401 ops/sec
DAWG items():           not supported
BytesDAWG items():      3.226 ops/sec
RecordDAWG items():     2.987 ops/sec
dict keys():            426.250 ops/sec
DAWG keys():            not supported
BytesDAWG keys():       6.050 ops/sec
RecordDAWG keys():      6.363 ops/sec

DAWG.prefixes (hits):    0.756M ops/sec
DAWG.prefixes (mixed):   1.965M ops/sec
DAWG.prefixes (misses):  1.773M ops/sec

RecordDAWG.keys(prefix="xxx"), avg_len(res)==415:       1.429K ops/sec
RecordDAWG.keys(prefix="xxxxx"), avg_len(res)==17:      36.994K ops/sec
RecordDAWG.keys(prefix="xxxxxxxx"), avg_len(res)==3:    121.897K ops/sec
RecordDAWG.keys(prefix="xxxxx..xx"), avg_len(res)==1.4: 265.015K ops/sec
RecordDAWG.keys(prefix="xxx"), NON_EXISTING:            2450.898K ops/sec

Under CPython expect it to be about 50x slower. Memory consumption of DAWG-Python should be the same as of DAWG_.

.. _marisa-trie: https://github.com/kmike/marisa-trie

Current limitations

  • This package is not capable of creating DAWGs;
  • all the limitations of DAWG_ apply.

Contributions are welcome!

Contributing

Development happens at github: https://github.com/kmike/DAWG-Python Issue tracker: https://github.com/kmike/DAWG-Python/issues

Feel free to submit ideas, bugs or pull requests.

Running tests and benchmarks

Make sure tox_ is installed and run

::

$ tox

from the source checkout. Tests should pass under python 2.6, 2.7, 3.2, 3.3, 3.4 and PyPy >= 1.9.

In order to run benchmarks, type

::

$ tox -c bench.ini -e pypy

This runs benchmarks under PyPy (they are about 50x slower under CPython).

.. _tox: http://tox.testrun.org

Authors & Contributors

The algorithms are from dawgdic_ C++ library by Susumu Yata & contributors.

License

This package is licensed under MIT License.

Changes

0.7.2 (2015-04-18)

  • minor speedup;
  • bitbucket mirror is no longer maintained.

0.7.1 (2014-06-05)

  • Switch to setuptools;
  • upload wheel tp pypi;
  • check Python 3.4 compatibility.

0.7 (2013-10-13)

IntDAWG and IntCompletionDAWG are implemented.

0.6 (2013-03-23)

Use less shared state internally. This should fix thread-safety bugs and make iterkeys/iteritems reenterant.

0.5.1 (2013-03-01)

Internal tweaks: memory usage is reduced; something is a bit faster, something is a bit slower.

0.5 (2012-10-08)

Storage scheme is updated to match DAWG==0.5. This enables the alphabetical ordering of BytesDAWG and RecordDAWG items.

In order to read BytesDAWG or RecordDAWG created with versions of DAWG < 0.5 use payload_separator constructor argument::

>>> BytesDAWG(payload_separator=b'\xff').load('old.dawg')

0.3.1 (2012-10-01)

Bug with empty DAWGs is fixed.

0.3 (2012-09-26)

  • iterkeys and iteritems methods.

0.2 (2012-09-24)

prefixes support.

0.1 (2012-09-20)

Initial release.