Winnowing
A Python implementation of the Winnowing (local algorithms for document fingerprinting)
Original Work
The original research paper can be found at http://dl.acm.org/citation.cfm?id=872770.
Installation
You may install winnowing package via pip as follows:
pip install winnowing
Alternatively, you may also install the package by cloning this repository.
git clone https://github.com/suminb/winnowing.git cd winnowing && python setup.py install
Usage
>>> from winnowing import winnow
>>> winnow('A do run run run, a do run run')
set([(5, 23942), (14, 2887), (2, 1966), (9, 23942), (20, 1966)])
>>> winnow('run run')
set([(0, 23942)]) # match found!Default Hash Function
Quite honestly, I did not know what hash function to use. The paper did not talk about it. So I decided to use a part of SHA-1; more precisely, the last 16 bits of the digest.
Custom Hash Function
You may use your own hash function as demonstrated below.
def hash_md5(text):
import hashlib
hs = hashlib.md5(text)
hs = hs.hexdigest()
hs = int(hs, 16)
return hs
# Override the hash function
winnow.hash_function = hash_md5
winnow('The cake was a lie')Lower Bound of Fingerprint Density
(TODO: Write this section)
1 maintainer
Metadata
1 maintainer
Release files for winnowing 0.2.1
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
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| winnowing-0.2.1.tar.gz | 2.6 kB | Without provenance | Details |
Release files / winnowing-0.2.1.tar.gz
| Download URL | winnowing-0.2.1.tar.gz |
|---|---|
| Size | 2.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
b74cf6fc2dbe1f3bec7d04ba0f593dc1bdad49553e0c7cec755b99792b512447
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twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.6.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.7.4
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Security for winnowing 0.2.1
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