Skip to main content

Python extension for MurmurHash (MurmurHash3), a set of fast and robust hash functions.

Project description


GitHub Super-Linter Build PyPi Version Python Versions License: MIT Total Downloads Recent Downloads

mmh3 is a Python extension for MurmurHash (MurmurHash3), a set of fast and robust non-cryptographic hash functions invented by Austin Appleby.

Combined with probabilistic techniques like a Bloom filter, MinHash, and feature hashing, mmh3 allows you to develop high-performance systems in fields such as data mining, machine learning, and natural language processing.

Another common use of mmh3 is to calculate favicon hashes used by Shodan, the world's first IoT search engine.

How to use


pip install mmh3 # for macOS, use "pip3 install mmh3" and python3

Simple functions


>>> import mmh3
>>> mmh3.hash("foo") # returns a 32-bit signed int
>>> mmh3.hash("foo", 42) # uses 42 as a seed
>>> mmh3.hash("foo", signed=False) # returns a 32-bit unsigned int

Other functions:

>>> mmh3.hash64("foo") # two 64 bit signed ints (by using the 128-bit algorithm as its backend)
(-2129773440516405919, 9128664383759220103)
>>> mmh3.hash64("foo", signed=False) #  two 64 bit unsigned ints
(16316970633193145697, 9128664383759220103)
>>> mmh3.hash128("foo", 42) # 128 bit unsigned int
>>> mmh3.hash128("foo", 42, signed=True) # 128 bit signed int
>>> mmh3.hash_bytes("foo") # 128 bit value as bytes
>>> import numpy as np
>>> a = np.zeros(2 ** 32, dtype=np.int8)
>>> mmh3.hash_bytes(a)

Beware that hash64 returns two values, because it uses the 128-bit version of MurmurHash3 as its backend.

hash_from_buffer hashes byte-likes without memory copying. The method is suitable when you hash a large memory-view such as numpy.ndarray.

>>> mmh3.hash_from_buffer(numpy.random.rand(100))
>>> mmh3.hash_from_buffer(numpy.random.rand(100), signed=False)

hash64, hash128, and hash_bytes have the third argument for architecture optimization. Use True for x64 and False for x86 (default: True):

>>> mmh3.hash64("foo", 42, True) 
(-840311307571801102, -6739155424061121879)

hashlib-style hashers

mmh3 implements hashers whose interfaces are similar to hashlib in the standard library: mmh3_32() for 32 bit hashing, mmh3_x64_128() for 128 bit hashing optimized for x64 architectures, and mmh3_x86_128() for 128 bit hashing optimized for x86 architectures.

In addition to the standard digest() method, each hasher has sintdigest(), which returns a signed integer, and uintdigest(), which returns an unsigned integer. 128 bit hashers also have stupledigest() and utupledigest() which return two 64 bit integers.

Note that as of version 4.0.1, the implementation is still experimental and its performance can be unsatisfactory (especially mmh3_x86_128()). Also, hexdigest() is not supported. Use digest().hex() instead.

>>> import mmh3
>>> hasher = mmh3.mmh3_x64_128(seed=42)
>>> hasher.update(b"foo")
>>> hasher.update(b"bar")
>>> hasher.update("foo") # str inputs are not allowed for hashers
TypeError: Strings must be encoded before hashing
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
>>> hasher.digest()
b'\x82_n\xdd \xac\xb6j\xef\x99\xb1e\xc4\n\xc9\xfd'
>>> hasher.sintdigest() # 128 bit signed int
>>> hasher.uintdigest() # 128 bit unsigned int
>>> hasher.stupledigest() # two 64 bit signed ints
(7689522670935629698, -159584473158936081)
>>> hasher.utupledigest() # two 64 bit unsigned ints
(7689522670935629698, 18287159600550615535)


4.0.1 (2023-07-14)

4.0.0 (2023-05-22)

3.1.0 (2023-03-24)

  • Add support for Python 3.10 and 3.11. Thanks wouter bolsterlee and Dušan Nikolić!
  • Drop support for Python 3.6; remove legacy code for Python 2.x at the source code level.
  • Add support for 32-bit architectures such as i686 and armv7l. From now on, hash and hash_from_buffer on these architectures will generate the same hash values as those on other environments. Thanks Danil Shein!
  • In relation to the above, manylinux2014_i686 wheels are now available.
  • Support for hashing huge data (>16GB). Thanks arieleizenberg!

See for the complete changelog.


MIT, unless otherwise noted within a file.

Known Issues

Getting different results from other MurmurHash3-based libraries

By default, mmh3 returns signed values for 32-bit and 64-bit versions and unsigned values for hash128, due to historical reasons. Please use the keyword argument signed to obtain a desired result.

From version 4.0.0, mmh3 returns the same value under big-endian platforms as that under little-endian ones, while the original C++ library is endian-sensitive. If you need to obtain the original-compliant results under big-endian environments, please use version 3.*.

For compatibility with Google Guava (Java), see

For compatibility with murmur3 (Go), see

Unexpected results when given non 32-bit seeds

Version 2.4 changed the type of seeds from signed 32-bit int to unsigned 32-bit int. The resulting values with signed seeds still remain the same as before, as long as they are 32-bit.

>>> mmh3.hash("aaaa", -1756908916) # signed representation for 0x9747b28c
>>> mmh3.hash("aaaa", 2538058380) # unsigned representation for 0x9747b28c

Be careful so that these seeds do not exceed 32-bit. Unexpected results may happen with invalid values.

>>> mmh3.hash("foo", 2 ** 33)
>>> mmh3.hash("foo", 2 ** 34)


MurmurHash3 was originally developed by Austin Appleby and distributed under public domain

Ported and modified for Python by Hajime Senuma.

See also

Tutorials (High-Performance Computing)

The following textbooks and tutorials are great sources to learn how to use mmh3 (and other hash algorithms in general) for high-performance computing.

Tutorials (Internet of Things)

Shodan, the world's first IoT search engine, uses MurmurHash3 hash values for favicons (icons associated with web pages). ZoomEye follows Shodan's convention. Calculating these values with mmh3 is useful for OSINT and cybersecurity activities.

Similar libraries

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mmh3-4.0.1.tar.gz (28.1 kB view hashes)

Uploaded source

Built Distributions

mmh3-4.0.1-cp311-cp311-win_arm64.whl (35.1 kB view hashes)

Uploaded cp311

mmh3-4.0.1-cp311-cp311-win_amd64.whl (36.2 kB view hashes)

Uploaded cp311

mmh3-4.0.1-cp311-cp311-win32.whl (36.2 kB view hashes)

Uploaded cp311

mmh3-4.0.1-cp311-cp311-musllinux_1_1_i686.whl (79.7 kB view hashes)

Uploaded cp311

mmh3-4.0.1-cp311-cp311-macosx_11_0_arm64.whl (35.7 kB view hashes)

Uploaded cp311

mmh3-4.0.1-cp311-cp311-macosx_10_9_x86_64.whl (34.7 kB view hashes)

Uploaded cp311

mmh3-4.0.1-cp310-cp310-win_arm64.whl (35.1 kB view hashes)

Uploaded cp310

mmh3-4.0.1-cp310-cp310-win_amd64.whl (36.2 kB view hashes)

Uploaded cp310

mmh3-4.0.1-cp310-cp310-win32.whl (36.2 kB view hashes)

Uploaded cp310

mmh3-4.0.1-cp310-cp310-musllinux_1_1_i686.whl (77.8 kB view hashes)

Uploaded cp310

mmh3-4.0.1-cp310-cp310-macosx_11_0_arm64.whl (35.7 kB view hashes)

Uploaded cp310

mmh3-4.0.1-cp310-cp310-macosx_10_9_x86_64.whl (34.7 kB view hashes)

Uploaded cp310

mmh3-4.0.1-cp39-cp39-win_arm64.whl (35.1 kB view hashes)

Uploaded cp39

mmh3-4.0.1-cp39-cp39-win_amd64.whl (36.2 kB view hashes)

Uploaded cp39

mmh3-4.0.1-cp39-cp39-win32.whl (36.2 kB view hashes)

Uploaded cp39

mmh3-4.0.1-cp39-cp39-musllinux_1_1_s390x.whl (80.9 kB view hashes)

Uploaded cp39

mmh3-4.0.1-cp39-cp39-musllinux_1_1_i686.whl (77.4 kB view hashes)

Uploaded cp39

mmh3-4.0.1-cp39-cp39-macosx_11_0_arm64.whl (35.7 kB view hashes)

Uploaded cp39

mmh3-4.0.1-cp39-cp39-macosx_10_9_x86_64.whl (34.7 kB view hashes)

Uploaded cp39

mmh3-4.0.1-cp38-cp38-win_amd64.whl (36.2 kB view hashes)

Uploaded cp38

mmh3-4.0.1-cp38-cp38-win32.whl (36.2 kB view hashes)

Uploaded cp38

mmh3-4.0.1-cp38-cp38-musllinux_1_1_s390x.whl (81.3 kB view hashes)

Uploaded cp38

mmh3-4.0.1-cp38-cp38-musllinux_1_1_i686.whl (77.6 kB view hashes)

Uploaded cp38

mmh3-4.0.1-cp38-cp38-macosx_11_0_arm64.whl (35.7 kB view hashes)

Uploaded cp38

mmh3-4.0.1-cp38-cp38-macosx_10_9_x86_64.whl (34.7 kB view hashes)

Uploaded cp38

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page