sklearn.utils.murmurhash3_32(key, seed=0, positive=False)#

Compute the 32bit murmurhash3 of key at seed.

The underlying implementation is MurmurHash3_x86_32 generating low latency 32bits hash suitable for implementing lookup tables, Bloom filters, count min sketch or feature hashing.

keynp.int32, bytes, unicode or ndarray of dtype=np.int32

The physical object to hash.

seedint, default=0

Integer seed for the hashing algorithm.

positivebool, default=False
True: the results is casted to an unsigned int

from 0 to 2 ** 32 - 1

False: the results is casted to a signed int

from -(2 ** 31) to 2 ** 31 - 1


>>> from sklearn.utils import murmurhash3_32
>>> murmurhash3_32(b"Hello World!", seed=42)