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This is a pure-Python library for computing context triggered piecewise hashes (CTPH), also called fuzzy hashes, or often ssdeep after the name of a popular tool. At a very high level, fuzzy hashing is a way to determine whether two inputs are similar, rather than identical. Fuzzy hashes are widely adopted in digital forensics and malware detection.

This implementation is based on SpamSum by Dr. Andrews Tridgell.

Usage

To compute a fuzzy hash, simply use hash() function:

`python >>> import ppdeep >>> h1 = ppdeep.hash('The equivalence of mass and energy translates into the well-known E = mc²') >>> h1 '3:RC0qYX4LBFA0dxEq4z2LRK+oCKI9VnXn:RvqpLB60dx8ilK+owX' >>> h2 = ppdeep.hash('The equivalence of mass and energy translates into the well-known E = MC2') >>> h2 '3:RC0qYX4LBFA0dxEq4z2LRK+oCKI99:RvqpLB60dx8ilK+oA' `

To calculate level of similarity, use compare() function which returns an integer value from 0 to 100 (full match):

`python >>> ppdeep.compare(h1, h2) 29 `

Function hash_from_file() accepts a filename as argument and calculates the hash of the contents of the file:

`python >>> ppdeep.hash_from_file('.bash_history') '1536:EXM36dG36x3KW732vOAcg3EP1qKlKozcK0z5G+lEPTssl/7eO7HOBF:tKlKozcWT0' `

Metadata

Release files for ppdeep 20200503

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ppdeep-20200503-py3-none-any.whl Python 3 none any Details

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Release files / ppdeep-20200503.tar.gz

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SHA-256 checksum
How to use checksums
86f7e0739cf0d6cdae1a9f1e58eddd63eccaa5a2767329f1d24638c8bd536a86
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How to use checksums
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Download URL ppdeep-20200503-py3-none-any.whl
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Tags Python 3
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How to use checksums
4a36c8fc41b9a1d4d5f4e61f7b459e4394db9037955b2124ef40003f9a582393
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How to use checksums
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