# mrshw
Thin, ctypes-based Python bindings for the [mrsh CLI tool](https://github.com/w4term3loon/mrsh). 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.
> [!IMPORTANT]
> For a more complete api ducumentation please refer to [docs/api.md](./docs/api.md)
---
## Installation
Install from PyPI:
```bash
pip install mrshw
```
Or directly from GitHub (tagged release `v0.1.0b4`):
```bash
pip install git+https://github.com/w4term3loon/mrsh.git@v0.1.0b4
```
---
## Quickstart
```python
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)
```
---
## License
* **Wrapper code:** MIT License. See the [LICENSE file](https://github.com/w4term3loon/mrsh/blob/master/bindings/LICENSE) for full terms.
* **Underlying C library:** Apache License 2.0. See its [repository license](https://github.com/w4term3loon/mrsh/blob/master/LICENSE.md).
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"description": "# mrshw\n\nThin, ctypes-based Python bindings for the [mrsh CLI tool](https://github.com/w4term3loon/mrsh). Implements the Bloom-filter\u2013based 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\u2013based fingerprinting directly from Python with minimal overhead.\n\n> [!IMPORTANT]\n> For a more complete api ducumentation please refer to [docs/api.md](./docs/api.md)\n\n---\n\n## Installation\n\nInstall from PyPI:\n\n```bash\npip install mrshw\n```\n\nOr directly from GitHub (tagged release `v0.1.0b4`):\n\n```bash\npip install git+https://github.com/w4term3loon/mrsh.git@v0.1.0b4\n```\n\n---\n\n## Quickstart\n\n```python\nimport mrshw as mrsh\n\n# 1. Single-fingerprint API\nfp = mrsh.fp(\"path/to/file.bin\")\nprint(str(fp)) # raw metadata + hex-encoded Bloom filters\nprint(fp.meta()) # Metadata(name, filesize, filter_count)\n\n# 2. Quick hash helper\nprint(mrsh.hash(\"path/to/file.bin\"))\n\n# 3. Fingerprint-list API\nfpl = mrsh.fpl()\nfpl += \"a.bin\"\nfpl += (\"b.bin\", \"label_b\")\nfpl += open('c.bin', 'rb').read()\nprint(str(fpl)) # one line per fingerprint\n\n# 4. Compare two fingerprints\ncmp = mrsh.compare(fp, mrsh.fp(\"other.bin\"))\nprint(cmp.hash1, cmp.hash2, cmp.score)\n\n# 5. Compare all in a list\nresults = fpl.compare_all(threshold=10)\nfor comp in results:\n print(comp.hash1, comp.hash2, comp.score)\n```\n\n---\n\n## License\n\n* **Wrapper code:** MIT License. See the [LICENSE file](https://github.com/w4term3loon/mrsh/blob/master/bindings/LICENSE) for full terms.\n* **Underlying C library:** Apache License 2.0. See its [repository license](https://github.com/w4term3loon/mrsh/blob/master/LICENSE.md).\n\n",
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