mrshw 0.1.0b3

ctypes-based Python bindings for the mrsh CLI tool

mrshw

Thin, ctypes-based Python bindings for the mrsh CLI tool. Implements the Bloom-filter–based similarity hashing algorithm originally proposed by Frank Breitinger and Harald Baier in their paper Similarity Preserving Hashing: Eligible Properties and a new Algorithm MRSH-v2 (da/sec Biometrics and Internet Security Research Group, Hochschule Darmstadt). Use Bloom-filter–based fingerprinting directly from Python with minimal overhead.

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Installation

Install from PyPI:

pip install mrshw

Or directly from GitHub (tagged release v0.1.0b3):

pip install git+https://github.com/w4term3loon/mrsh.git@v0.1.0b3

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Quickstart

import mrshw as mrsh

# 1. Single-fingerprint API
fp = mrsh.fp("path/to/file.bin")
print(str(fp))            # raw metadata + hex-encoded Bloom filters
print(fp.meta())          # Metadata(name, filesize, filter_count)

# 2. Quick hash helper
print(mrsh.hash("path/to/file.bin"))

# 3. Fingerprint-list API
fpl = mrsh.fpl()
fpl += "a.bin"
fpl += ("b.bin", "label_b")
fpl += open('c.bin', 'rb').read()
print(str(fpl))           # one line per fingerprint

# 4. Compare two fingerprints
cmp = mrsh.compare(fp, mrsh.fp("other.bin"))
print(cmp.hash1, cmp.hash2, cmp.score)

# 5. Compare all in a list
results = fpl.compare_all(threshold=10)
for comp in results:
    print(comp.hash1, comp.hash2, comp.score)

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License

• Wrapper code: MIT License. See the LICENSE file for full terms.
• Underlying C library: Apache License 2.0. See its repository license.