| Name | pyspamsum JSON |
| Version |
1.0.7
JSON |
| download |
| home_page | None |
| Summary | A Python wrapper for Andrew Tridgell's spamsum algorithm |
| upload_time | 2025-02-19 06:52:58 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | New BSD |
| keywords |
spamsum
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
PySpamSum
=========
.. image:: https://img.shields.io/pypi/pyversions/pyspamsum.svg
:target: https://pypi.org/project/pyspamsum
.. image:: https://img.shields.io/pypi/v/pyspamsum.svg
:target: https://pypi.org/project/pyspamsum
.. image:: https://img.shields.io/pypi/status/pyspamsum.svg
:target: https://pypi.org/project/pyspamsum
.. image:: https://img.shields.io/pypi/l/pyspamsum.svg
:target: https://github.com/pybee/pyspamsum/blob/master/LICENSE
.. image:: https://travis-ci.org/pybee/pyspamsum.svg?branch=master
:target: https://travis-ci.org/pybee/pyspamsum
spamsum is a fuzzy hash specifically designed for hashing email messages
to detect if they are SPAM. The spamsum utility includes the ability to
generate the spamsum hash and check a new message against a existing set
of hashes to find a match.
pyspamsum is a Python wrapper for the core API of spamsum.
The original spamsum code has been licensed under the terms of the
the Perl Artistic License. It has been slightly modified
The original code is Copyright Andrew Tridgell <tridge@samba.org> 2002.
It forms part of Andrew's junkcode, and is available here:
http://www.samba.org/junkcode/#spamsum
The spamsum code in this project is derived from an updated version that
was published at Linux.conf.au 2004:
http://linux.anu.edu.au/linux.conf.au/2004/papers/junkcode/spamsum
For details on spamsum itself, please see the spamsum README:
http://samba.org/ftp/unpacked/junkcode/spamsum/README
Installation
------------
At a prompt, run::
$ python setup.py install
Usage
-----
Once installed, here are some examples of usage::
# Import spamsum and set up some strings
>>> import spamsum
>>> s1 = "I am the very model of a modern Major-General, I've information animal and vegetable and mineral"
>>> s2 = "I am the very model of a modern Brigadier, I've information animal and vegetable and something else"
>>> s3 = "Huh? Gilbert and Who?"
# Evaluate the edit distance between two strings
>>> spamsum.edit_distance(s1, s2)
27
# Evaluate the spamsum of some strings
>>> sum1 = spamsum.spamsum(s1)
>>> sum2 = spamsum.spamsum(s2)
>>> sum3 = spamsum.spamsum(s3)
>>> print(sum1)
3:kEvyc/sFIKwYclQY4MKLFE4Igu0uLzIKygn:kE6Ai3KQ/MKOgDKZn
# Compare two spamsums. 0 = no match, 100 = perfect match.
>>> spamsum.match(sum1, sum1)
100
>>> spamsum.match(sum1, sum2)
72
>>> spamsum.match(sum1, sum3)
0
Raw data
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"description": "PySpamSum\n=========\n\n.. image:: https://img.shields.io/pypi/pyversions/pyspamsum.svg\n :target: https://pypi.org/project/pyspamsum\n\n.. image:: https://img.shields.io/pypi/v/pyspamsum.svg\n :target: https://pypi.org/project/pyspamsum\n\n.. image:: https://img.shields.io/pypi/status/pyspamsum.svg\n :target: https://pypi.org/project/pyspamsum\n\n.. image:: https://img.shields.io/pypi/l/pyspamsum.svg\n :target: https://github.com/pybee/pyspamsum/blob/master/LICENSE\n\n.. image:: https://travis-ci.org/pybee/pyspamsum.svg?branch=master\n :target: https://travis-ci.org/pybee/pyspamsum\n\nspamsum is a fuzzy hash specifically designed for hashing email messages\nto detect if they are SPAM. The spamsum utility includes the ability to\ngenerate the spamsum hash and check a new message against a existing set\nof hashes to find a match.\n\npyspamsum is a Python wrapper for the core API of spamsum.\n\nThe original spamsum code has been licensed under the terms of the\nthe Perl Artistic License. It has been slightly modified\n\nThe original code is Copyright Andrew Tridgell <tridge@samba.org> 2002.\nIt forms part of Andrew's junkcode, and is available here:\n\n http://www.samba.org/junkcode/#spamsum\n\nThe spamsum code in this project is derived from an updated version that\nwas published at Linux.conf.au 2004:\n\n http://linux.anu.edu.au/linux.conf.au/2004/papers/junkcode/spamsum\n\nFor details on spamsum itself, please see the spamsum README:\n\n http://samba.org/ftp/unpacked/junkcode/spamsum/README\n\nInstallation\n------------\n\nAt a prompt, run::\n\n $ python setup.py install\n\nUsage\n-----\n\nOnce installed, here are some examples of usage::\n\n # Import spamsum and set up some strings\n >>> import spamsum\n >>> s1 = \"I am the very model of a modern Major-General, I've information animal and vegetable and mineral\"\n >>> s2 = \"I am the very model of a modern Brigadier, I've information animal and vegetable and something else\"\n >>> s3 = \"Huh? Gilbert and Who?\"\n\n # Evaluate the edit distance between two strings\n >>> spamsum.edit_distance(s1, s2)\n 27\n\n # Evaluate the spamsum of some strings\n >>> sum1 = spamsum.spamsum(s1)\n >>> sum2 = spamsum.spamsum(s2)\n >>> sum3 = spamsum.spamsum(s3)\n >>> print(sum1)\n 3:kEvyc/sFIKwYclQY4MKLFE4Igu0uLzIKygn:kE6Ai3KQ/MKOgDKZn\n\n # Compare two spamsums. 0 = no match, 100 = perfect match.\n >>> spamsum.match(sum1, sum1)\n 100\n >>> spamsum.match(sum1, sum2)\n 72\n >>> spamsum.match(sum1, sum3)\n 0\n",
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