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DAWG-Python-0.7.2
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مشاهده بیشترتوضیحات
Pure-python reader for DAWGs (DAFSAs) created by dawgdic C++ library or DAWG Python extension.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | DAWG-Python-0.7.2 |
| نام | DAWG-Python |
| نسخه کتابخانه | 0.7.2 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Mikhail Korobov |
| ایمیل نویسنده | kmike84@gmail.com |
| آدرس صفحه اصلی | https://github.com/kmike/DAWG-Python/ |
| آدرس اینترنتی | https://pypi.org/project/DAWG-Python/ |
| مجوز | UNKNOWN |
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
----------------------
* Mikhail Korobov <kmike84@gmail.com>
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.
نحوه نصب
نصب پکیج whl DAWG-Python-0.7.2:
pip install DAWG-Python-0.7.2.whl
نصب پکیج tar.gz DAWG-Python-0.7.2:
pip install DAWG-Python-0.7.2.tar.gz