| Name | mmh3 JSON |
| Version |
5.0.1
JSON |
| download |
| home_page | None |
| Summary | Python extension for MurmurHash (MurmurHash3), a set of fast and robust hash functions. |
| upload_time | 2024-09-22 16:46:55 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | MIT License Copyright (c) 2011-2024 Hajime Senuma Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
utility
hash
murmurhash
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# mmh3
[](https://mmh3.readthedocs.io/en/latest/?badge=latest)
[](https://github.com/hajimes/mmh3/actions?query=workflow%3ASuper-Linter+branch%3Amaster)
[](https://github.com/hajimes/mmh3/actions/workflows/build.yml?branch=master)
[](https://pypi.org/project/mmh3/)
[](https://pypi.org/project/mmh3/)
[](https://opensource.org/license/mit/)
[](https://www.pepy.tech/projects/mmh3?versions=*&versions=5.*&versions=4.*&versions=3.*&versions=2.*)
[](https://www.pepy.tech/projects/mmh3?versions=*&versions=5.*&versions=4.*&versions=3.*&versions=2.*)
`mmh3` is a Python extension for
[MurmurHash (MurmurHash3)](https://en.wikipedia.org/wiki/MurmurHash), a set of
fast and robust non-cryptographic hash functions invented by Austin Appleby.
By combining `mmh3` with probabilistic techniques like
[Bloom filter](https://en.wikipedia.org/wiki/Bloom_filter),
[MinHash](https://en.wikipedia.org/wiki/MinHash), and
[feature hashing](https://en.wikipedia.org/wiki/Feature_hashing), you can
develop high-performance systems in fields such as data mining, machine
learning, and natural language processing.
Another popular use of `mmh3` is to
[calculate favicon hashes](https://gist.github.com/yehgdotnet/b9dfc618108d2f05845c4d8e28c5fc6a),
which are utilized by [Shodan](https://www.shodan.io), the world's first IoT
search engine.
This page provides a quick start guide. For more comprehensive information,
please refer to the [documentation](https://mmh3.readthedocs.io/en/latest/).
## Installation
```shell
pip install mmh3
```
## Usage
### Basic usage
```pycon
>>> import mmh3
>>> mmh3.hash(b"foo") # returns a 32-bit signed int
-156908512
>>> mmh3.hash("foo") # accepts str (UTF-8 encoded)
-156908512
>>> mmh3.hash(b"foo", 42) # uses 42 as the seed
-1322301282
>>> mmh3.hash(b"foo", 0, False) # returns a 32-bit unsigned int
4138058784
```
`mmh3.mmh3_x64_128_digest()`, introduced in version 5.0.0, efficienlty hashes
buffer objects that implement the buffer protocol
([PEP 688](https://peps.python.org/pep-0688/)) without internal memory copying.
The function returns a `bytes` object of 16 bytes (128 bits). It is
particularly suited for hashing large memory views, such as
`bytearray`, `memoryview`, and `numpy.ndarray`, and performs faster than
the 32-bit variants like `hash()` on 64-bit machines.
```pycon
>>> mmh3.mmh3_x64_128_digest(numpy.random.rand(100))
b'\x8c\xee\xc6z\xa9\xfeR\xe8o\x9a\x9b\x17u\xbe\xdc\xee'
```
Various alternatives are available, offering different return types (e.g.,
signed integers, tuples of unsigned integers) and optimized for different
architectures. For a comprehensive list of functions, refer to the
[API Reference](https://mmh3.readthedocs.io/en/latest/api.html).
### `hashlib`-style hashers
`mmh3` implements hasher objects with interfaces similar to those in `hashlib`
from the standard library, although they are still experimental. See
[Hasher Classes](https://mmh3.readthedocs.io/en/latest/api.html#hasher-classes)
in the API Reference for more information.
## Changelog
See [Changelog](https://mmh3.readthedocs.io/en/latest/changelog.html) for the
complete changelog.
### [5.0.1] - 2024-09-22
#### Fixed
- Fix the issue that the package cannot be built from the source distribution
([#90](https://github.com/hajimes/mmh3/issues/90)).
### [5.0.0] - 2024-09-18
#### Added
- Add support for Python 3.13.
- Improve the performance of the `hash()` function with
[METH_FASTCALL](https://docs.python.org/3/c-api/structures.html#c.METH_FASTCALL),
reducing the overhead of function calls. For data sizes between 1–2 KB
(e.g., 48x48 favicons), performance is 10%–20% faster. For smaller data
(~500 bytes, like 16x16 favicons), performance increases by approximately 30%
([#87](https://github.com/hajimes/mmh3/pull/87)).
- Add `digest` functions that support the new buffer protocol
([PEP 688](https://peps.python.org/pep-0688/)) as input
([#75](https://github.com/hajimes/mmh3/pull/75)).
These functions are implemented with `METH_FASTCALL` too, offering improved
performance ([#84](https://github.com/hajimes/mmh3/pull/84)).
- Slightly improve the performance of the `hash_bytes()` function
([#88](https://github.com/hajimes/mmh3/pull/88))
- Add Read the Docs documentation
([#54](https://github.com/hajimes/mmh3/issues/54)).
- Document benchmark results
([#53](https://github.com/hajimes/mmh3/issues/53)).
#### Changed
- **Backward-incompatible**: The `seed` argument is now strictly validated to
ensure it falls within the range [0, 0xFFFFFFFF]. A `ValueError` is raised
if the seed is out of range ([#84](https://github.com/hajimes/mmh3/pull/84)).
- **Backward-incompatible**: Change the constructors of hasher classes to
accept a buffer as the first argument
([#83](https://github.com/hajimes/mmh3/pull/83)).
- The type of flag argumens has been changed from `bool` to `Any`
([#84](https://github.com/hajimes/mmh3/pull/84)).
- Change the format of CHANGELOG.md to conform to the
[Keep a Changelog](https://keepachangelog.com/en/1.1.0/) standard
([#63](https://github.com/hajimes/mmh3/pull/63)).
#### Deprecated
- Deprecate the `hash_from_buffer()` function.
Use `mmh3_32_sintdigest()` or `mmh3_32_uintdigest()` as alternatives
([#84](https://github.com/hajimes/mmh3/pull/84)).
#### Fixed
- Fix a reference leak in the `hash_from_buffer()` function
([#75](https://github.com/hajimes/mmh3/pull/75)).
- Fix type hints ([#76](https://github.com/hajimes/mmh3/pull/76),
[#77](https://github.com/hajimes/mmh3/pull/77),
[#84](https://github.com/hajimes/mmh3/pull/84)).
### [4.1.0] - 2024-01-09
#### Added
- Add support for Python 3.12.
#### Fixed
- Fix issues with Bazel by changing the directory structure of the project
([#50](https://github.com/hajimes/mmh3/issues/50)).
- Fix incorrect type hints ([#51](https://github.com/hajimes/mmh3/issues/51)).
- Fix invalid results on s390x when the arg `x64arch` of `hash64` or
`hash_bytes()` is set to `False`
([#52](https://github.com/hajimes/mmh3/issues/52)).
## License
[MIT](https://github.com/hajimes/mmh3/blob/master/LICENSE), unless otherwise
noted within a file.
## Known Issues
### Different results from other MurmurHash3-based libraries
By default, `mmh3` returns **signed** values for the 32-bit and 64-bit versions
and **unsigned** values for `hash128` due to historical reasons. To get the
desired result, use the `signed` keyword argument.
Starting from version 4.0.0, **`mmh3` is endian-neutral**, meaning that its
hash functions return the same values on big-endian platforms as they do on
little-endian ones. In contrast, the original C++ library by Appleby is
endian-sensitive. If you need results that comply with the original library on
big-endian systems, please use version 3.\*.
For compatibility with [Google Guava (Java)](https://github.com/google/guava),
see
<https://stackoverflow.com/questions/29932956/murmur3-hash-different-result-between-python-and-java-implementation>.
For compatibility with
[murmur3 (Go)](https://pkg.go.dev/github.com/spaolacci/murmur3), see
<https://github.com/hajimes/mmh3/issues/46>.
## Contributing Guidelines
See [Contributing](https://mmh3.readthedocs.io/en/latest/CONTRIBUTING.html).
## Authors
MurmurHash3 was originally developed by Austin Appleby and distributed under
public domain
[https://github.com/aappleby/smhasher](https://github.com/aappleby/smhasher).
Ported and modified for Python by Hajime Senuma.
## External Tutorials
### High-performance computing
The following textbooks and tutorials are great resources for learning how to
use `mmh3` (and other hash algorithms in general) for high-performance computing.
- Chapter 11: _Using Less Ram_ in Micha Gorelick and Ian Ozsvald. 2014. _High
Performance Python: Practical Performant Programming for Humans_. O'Reilly
Media. [ISBN: 978-1-4493-6159-4](https://www.amazon.com/dp/1449361595).
- 2nd edition of the above (2020).
[ISBN: 978-1492055020](https://www.amazon.com/dp/1492055026).
- Max Burstein. February 2, 2013.
_[Creating a Simple Bloom Filter](http://www.maxburstein.com/blog/creating-a-simple-bloom-filter/)_.
- Duke University. April 14, 2016.
_[Efficient storage of data in memory](http://people.duke.edu/~ccc14/sta-663-2016/20B_Big_Data_Structures.html)_.
- Bugra Akyildiz. August 24, 2016.
_[A Gentle Introduction to Bloom Filter](https://www.kdnuggets.com/2016/08/gentle-introduction-bloom-filter.html)_.
KDnuggets.
### Internet of things
[Shodan](https://www.shodan.io), the world's first
[IoT](https://en.wikipedia.org/wiki/Internet_of_things) search engine, uses
MurmurHash3 hash values for [favicons](https://en.wikipedia.org/wiki/Favicon)
(icons associated with web pages). [ZoomEye](https://www.zoomeye.org) follows
Shodan's convention.
[Calculating these values with mmh3](https://gist.github.com/yehgdotnet/b9dfc618108d2f05845c4d8e28c5fc6a)
is useful for OSINT and cybersecurity activities.
- Jan Kopriva. April 19, 2021.
_[Hunting phishing websites with favicon hashes](https://isc.sans.edu/diary/Hunting+phishing+websites+with+favicon+hashes/27326)_.
SANS Internet Storm Center.
- Nikhil Panwar. May 2, 2022.
_[Using Favicons to Discover Phishing & Brand Impersonation Websites](https://bolster.ai/blog/how-to-use-favicons-to-find-phishing-websites)_.
Bolster.
- Faradaysec. July 25, 2022.
_[Understanding Spring4Shell: How used is it?](https://faradaysec.com/understanding-spring4shell/)_.
Faraday Security.
- Debjeet. August 2, 2022.
_[How To Find Assets Using Favicon Hashes](https://payatu.com/blog/favicon-hash/)_.
Payatu.
## Related Libraries
- <https://github.com/wc-duck/pymmh3>: mmh3 in pure python (Fredrik Kihlander
and Swapnil Gusani)
- <https://github.com/escherba/python-cityhash>: Python bindings for CityHash
(Eugene Scherba)
- <https://github.com/veelion/python-farmhash>: Python bindings for FarmHash
(Veelion Chong)
- <https://github.com/escherba/python-metrohash>: Python bindings for MetroHash
(Eugene Scherba)
- <https://github.com/ifduyue/python-xxhash>: Python bindings for xxHash (Yue
Du)
[5.0.1]: https://github.com/hajimes/mmh3/compare/v5.0.0...v5.0.1
[5.0.0]: https://github.com/hajimes/mmh3/compare/v4.1.0...v5.0.0
[4.1.0]: https://github.com/hajimes/mmh3/compare/v4.0.1...v4.1.0
Raw data
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"description": "# mmh3\n\n[](https://mmh3.readthedocs.io/en/latest/?badge=latest)\n[](https://github.com/hajimes/mmh3/actions?query=workflow%3ASuper-Linter+branch%3Amaster)\n[](https://github.com/hajimes/mmh3/actions/workflows/build.yml?branch=master)\n[](https://pypi.org/project/mmh3/)\n[](https://pypi.org/project/mmh3/)\n[](https://opensource.org/license/mit/)\n[](https://www.pepy.tech/projects/mmh3?versions=*&versions=5.*&versions=4.*&versions=3.*&versions=2.*)\n[](https://www.pepy.tech/projects/mmh3?versions=*&versions=5.*&versions=4.*&versions=3.*&versions=2.*)\n\n`mmh3` is a Python extension for\n[MurmurHash (MurmurHash3)](https://en.wikipedia.org/wiki/MurmurHash), a set of\nfast and robust non-cryptographic hash functions invented by Austin Appleby.\n\nBy combining `mmh3` with probabilistic techniques like\n[Bloom filter](https://en.wikipedia.org/wiki/Bloom_filter),\n[MinHash](https://en.wikipedia.org/wiki/MinHash), and\n[feature hashing](https://en.wikipedia.org/wiki/Feature_hashing), you can\ndevelop high-performance systems in fields such as data mining, machine\nlearning, and natural language processing.\n\nAnother popular use of `mmh3` is to\n[calculate favicon hashes](https://gist.github.com/yehgdotnet/b9dfc618108d2f05845c4d8e28c5fc6a),\nwhich are utilized by [Shodan](https://www.shodan.io), the world's first IoT\nsearch engine.\n\nThis page provides a quick start guide. For more comprehensive information,\nplease refer to the [documentation](https://mmh3.readthedocs.io/en/latest/).\n\n## Installation\n\n```shell\npip install mmh3\n```\n\n## Usage\n\n### Basic usage\n\n```pycon\n>>> import mmh3\n>>> mmh3.hash(b\"foo\") # returns a 32-bit signed int\n-156908512\n>>> mmh3.hash(\"foo\") # accepts str (UTF-8 encoded)\n-156908512\n>>> mmh3.hash(b\"foo\", 42) # uses 42 as the seed\n-1322301282\n>>> mmh3.hash(b\"foo\", 0, False) # returns a 32-bit unsigned int\n4138058784\n```\n\n`mmh3.mmh3_x64_128_digest()`, introduced in version 5.0.0, efficienlty hashes\nbuffer objects that implement the buffer protocol\n([PEP 688](https://peps.python.org/pep-0688/)) without internal memory copying.\nThe function returns a `bytes` object of 16 bytes (128 bits). It is\nparticularly suited for hashing large memory views, such as\n`bytearray`, `memoryview`, and `numpy.ndarray`, and performs faster than\nthe 32-bit variants like `hash()` on 64-bit machines.\n\n```pycon\n>>> mmh3.mmh3_x64_128_digest(numpy.random.rand(100))\nb'\\x8c\\xee\\xc6z\\xa9\\xfeR\\xe8o\\x9a\\x9b\\x17u\\xbe\\xdc\\xee'\n```\n\nVarious alternatives are available, offering different return types (e.g.,\nsigned integers, tuples of unsigned integers) and optimized for different\narchitectures. For a comprehensive list of functions, refer to the\n[API Reference](https://mmh3.readthedocs.io/en/latest/api.html).\n\n### `hashlib`-style hashers\n\n`mmh3` implements hasher objects with interfaces similar to those in `hashlib`\nfrom the standard library, although they are still experimental. See\n[Hasher Classes](https://mmh3.readthedocs.io/en/latest/api.html#hasher-classes)\nin the API Reference for more information.\n\n## Changelog\n\nSee [Changelog](https://mmh3.readthedocs.io/en/latest/changelog.html) for the\ncomplete changelog.\n\n### [5.0.1] - 2024-09-22\n\n#### Fixed\n\n- Fix the issue that the package cannot be built from the source distribution\n ([#90](https://github.com/hajimes/mmh3/issues/90)).\n\n### [5.0.0] - 2024-09-18\n\n#### Added\n\n- Add support for Python 3.13.\n- Improve the performance of the `hash()` function with\n [METH_FASTCALL](https://docs.python.org/3/c-api/structures.html#c.METH_FASTCALL),\n reducing the overhead of function calls. For data sizes between 1\u20132 KB\n (e.g., 48x48 favicons), performance is 10%\u201320% faster. For smaller data\n (~500 bytes, like 16x16 favicons), performance increases by approximately 30%\n ([#87](https://github.com/hajimes/mmh3/pull/87)).\n- Add `digest` functions that support the new buffer protocol\n ([PEP 688](https://peps.python.org/pep-0688/)) as input\n ([#75](https://github.com/hajimes/mmh3/pull/75)).\n These functions are implemented with `METH_FASTCALL` too, offering improved\n performance ([#84](https://github.com/hajimes/mmh3/pull/84)).\n- Slightly improve the performance of the `hash_bytes()` function\n ([#88](https://github.com/hajimes/mmh3/pull/88))\n- Add Read the Docs documentation\n ([#54](https://github.com/hajimes/mmh3/issues/54)).\n- Document benchmark results\n ([#53](https://github.com/hajimes/mmh3/issues/53)).\n\n#### Changed\n\n- **Backward-incompatible**: The `seed` argument is now strictly validated to\n ensure it falls within the range [0, 0xFFFFFFFF]. A `ValueError` is raised\n if the seed is out of range ([#84](https://github.com/hajimes/mmh3/pull/84)).\n- **Backward-incompatible**: Change the constructors of hasher classes to\n accept a buffer as the first argument\n ([#83](https://github.com/hajimes/mmh3/pull/83)).\n- The type of flag argumens has been changed from `bool` to `Any`\n ([#84](https://github.com/hajimes/mmh3/pull/84)).\n- Change the format of CHANGELOG.md to conform to the\n [Keep a Changelog](https://keepachangelog.com/en/1.1.0/) standard\n ([#63](https://github.com/hajimes/mmh3/pull/63)).\n\n#### Deprecated\n\n- Deprecate the `hash_from_buffer()` function.\n Use `mmh3_32_sintdigest()` or `mmh3_32_uintdigest()` as alternatives\n ([#84](https://github.com/hajimes/mmh3/pull/84)).\n\n#### Fixed\n\n- Fix a reference leak in the `hash_from_buffer()` function\n ([#75](https://github.com/hajimes/mmh3/pull/75)).\n- Fix type hints ([#76](https://github.com/hajimes/mmh3/pull/76),\n [#77](https://github.com/hajimes/mmh3/pull/77),\n [#84](https://github.com/hajimes/mmh3/pull/84)).\n\n### [4.1.0] - 2024-01-09\n\n#### Added\n\n- Add support for Python 3.12.\n\n#### Fixed\n\n- Fix issues with Bazel by changing the directory structure of the project\n ([#50](https://github.com/hajimes/mmh3/issues/50)).\n- Fix incorrect type hints ([#51](https://github.com/hajimes/mmh3/issues/51)).\n- Fix invalid results on s390x when the arg `x64arch` of `hash64` or\n `hash_bytes()` is set to `False`\n ([#52](https://github.com/hajimes/mmh3/issues/52)).\n\n## License\n\n[MIT](https://github.com/hajimes/mmh3/blob/master/LICENSE), unless otherwise\nnoted within a file.\n\n## Known Issues\n\n### Different results from other MurmurHash3-based libraries\n\nBy default, `mmh3` returns **signed** values for the 32-bit and 64-bit versions\nand **unsigned** values for `hash128` due to historical reasons. To get the\ndesired result, use the `signed` keyword argument.\n\nStarting from version 4.0.0, **`mmh3` is endian-neutral**, meaning that its\nhash functions return the same values on big-endian platforms as they do on\nlittle-endian ones. In contrast, the original C++ library by Appleby is\nendian-sensitive. If you need results that comply with the original library on\nbig-endian systems, please use version 3.\\*.\n\nFor compatibility with [Google Guava (Java)](https://github.com/google/guava),\nsee\n<https://stackoverflow.com/questions/29932956/murmur3-hash-different-result-between-python-and-java-implementation>.\n\nFor compatibility with\n[murmur3 (Go)](https://pkg.go.dev/github.com/spaolacci/murmur3), see\n<https://github.com/hajimes/mmh3/issues/46>.\n\n## Contributing Guidelines\n\nSee [Contributing](https://mmh3.readthedocs.io/en/latest/CONTRIBUTING.html).\n\n## Authors\n\nMurmurHash3 was originally developed by Austin Appleby and distributed under\npublic domain\n[https://github.com/aappleby/smhasher](https://github.com/aappleby/smhasher).\n\nPorted and modified for Python by Hajime Senuma.\n\n## External Tutorials\n\n### High-performance computing\n\nThe following textbooks and tutorials are great resources for learning how to\nuse `mmh3` (and other hash algorithms in general) for high-performance computing.\n\n- Chapter 11: _Using Less Ram_ in Micha Gorelick and Ian Ozsvald. 2014. _High\n Performance Python: Practical Performant Programming for Humans_. O'Reilly\n Media. [ISBN: 978-1-4493-6159-4](https://www.amazon.com/dp/1449361595).\n - 2nd edition of the above (2020).\n [ISBN: 978-1492055020](https://www.amazon.com/dp/1492055026).\n- Max Burstein. February 2, 2013.\n _[Creating a Simple Bloom Filter](http://www.maxburstein.com/blog/creating-a-simple-bloom-filter/)_.\n- Duke University. April 14, 2016.\n _[Efficient storage of data in memory](http://people.duke.edu/~ccc14/sta-663-2016/20B_Big_Data_Structures.html)_.\n- Bugra Akyildiz. August 24, 2016.\n _[A Gentle Introduction to Bloom Filter](https://www.kdnuggets.com/2016/08/gentle-introduction-bloom-filter.html)_.\n KDnuggets.\n\n### Internet of things\n\n[Shodan](https://www.shodan.io), the world's first\n[IoT](https://en.wikipedia.org/wiki/Internet_of_things) search engine, uses\nMurmurHash3 hash values for [favicons](https://en.wikipedia.org/wiki/Favicon)\n(icons associated with web pages). [ZoomEye](https://www.zoomeye.org) follows\nShodan's convention.\n[Calculating these values with mmh3](https://gist.github.com/yehgdotnet/b9dfc618108d2f05845c4d8e28c5fc6a)\nis useful for OSINT and cybersecurity activities.\n\n- Jan Kopriva. April 19, 2021.\n _[Hunting phishing websites with favicon hashes](https://isc.sans.edu/diary/Hunting+phishing+websites+with+favicon+hashes/27326)_.\n SANS Internet Storm Center.\n- Nikhil Panwar. May 2, 2022.\n _[Using Favicons to Discover Phishing & Brand Impersonation Websites](https://bolster.ai/blog/how-to-use-favicons-to-find-phishing-websites)_.\n Bolster.\n- Faradaysec. July 25, 2022.\n _[Understanding Spring4Shell: How used is it?](https://faradaysec.com/understanding-spring4shell/)_.\n Faraday Security.\n- Debjeet. August 2, 2022.\n _[How To Find Assets Using Favicon Hashes](https://payatu.com/blog/favicon-hash/)_.\n Payatu.\n\n## Related Libraries\n\n- <https://github.com/wc-duck/pymmh3>: mmh3 in pure python (Fredrik Kihlander\n and Swapnil Gusani)\n- <https://github.com/escherba/python-cityhash>: Python bindings for CityHash\n (Eugene Scherba)\n- <https://github.com/veelion/python-farmhash>: Python bindings for FarmHash\n (Veelion Chong)\n- <https://github.com/escherba/python-metrohash>: Python bindings for MetroHash\n (Eugene Scherba)\n- <https://github.com/ifduyue/python-xxhash>: Python bindings for xxHash (Yue\n Du)\n\n[5.0.1]: https://github.com/hajimes/mmh3/compare/v5.0.0...v5.0.1\n[5.0.0]: https://github.com/hajimes/mmh3/compare/v4.1.0...v5.0.0\n[4.1.0]: https://github.com/hajimes/mmh3/compare/v4.0.1...v4.1.0\n",
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"license": "MIT License Copyright (c) 2011-2024 Hajime Senuma Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.",
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