Metadata-Version: 2.1
Name: cityhash
Version: 0.3.0.post3
Summary: Python bindings for CityHash and FarmHash
Home-page: https://github.com/escherba/python-cityhash
Author: Alexander [Amper] Marshalov
Author-email: alone.amper+cityhash@gmail.com
Maintainer: Eugene Scherba
Maintainer-email: escherba+cityhash@gmail.com
License: MIT
Download-URL: https://github.com/escherba/python-cityhash/tarball/master/0.3.0.post3
Keywords: google,hash,hashing,cityhash,farmhash,murmurhash
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: C++
Classifier: Programming Language :: Cython
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Utilities
Description-Content-Type: text/x-rst
License-File: LICENSE

CityHash
========

A Python wrapper around `FarmHash <https://github.com/google/farmhash>`__ and
`CityHash <https://github.com/google/cityhash>`__

.. image:: https://img.shields.io/pypi/v/cityhash.svg
    :target: https://pypi.python.org/pypi/cityhash
    :alt: Latest Version

.. image:: https://img.shields.io/pypi/dm/cityhash.svg
    :target: https://pypi.python.org/pypi/cityhash
    :alt: Downloads

.. image:: https://circleci.com/gh/escherba/python-cityhash.svg?style=shield
    :target: https://circleci.com/gh/escherba/python-cityhash
    :alt: Tests Status

.. image:: https://img.shields.io/pypi/pyversions/cityhash.svg
    :target: https://pypi.python.org/pypi/cityhash
    :alt: Supported Python versions

.. image:: https://img.shields.io/pypi/l/cityhash.svg
    :target: https://pypi.python.org/pypi/cityhash
    :alt: License

Getting Started
---------------

To use this package in your program, simply type

.. code-block:: bash

    pip install cityhash


After that, you should be able to import the module and do things with it (see
usage example below).

Usage Examples
--------------

Stateless hashing
~~~~~~~~~~~~~~~~~

This package exposes Python APIs for CityHash and FarmHash under ``cityhash``
and ``farmhash`` namespaces, respectively.  Each provides 32-, 64- and 128-bit
implementations. Usage example for `cityhash`:

.. code-block:: python

    >>> from cityhash import CityHash32, CityHash64, CityHash128
    >>> print(CityHash32("abc"))
    795041479
    >>> print(CityHash64("abc"))
    2640714258260161385
    >>> print(CityHash128("abc"))
    76434233956484675513733017140465933893

Hardware-independent fingerprints
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Fingerprints are seedless hashes which are guaranteed to be hardware- and
platform- independent.

.. code-block:: python

    >>> from farmhash import Fingerprint128
    >>> print(Fingerprint128("abc"))
    76434233956484675513733017140465933893

Incremental hashing
~~~~~~~~~~~~~~~~~~~

CityHash and FarmHash do not support incremental hashing. If you require this
feature, use `MetroHash <https://github.com/escherba/python-metrohash>`__
instead, which does support it.

Fast hashing of NumPy arrays
~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The methods in this module support Python `Buffer Protocol
<https://docs.python.org/3/c-api/buffer.html>`__, which allows them to be used
on any object that exports a buffer interface. Here is an example showing
hashing of a 4D NumPy array:

.. code-block:: python

    >>> import numpy as np
    >>> from farmhash import FarmHash64
    >>> arr = np.zeros((256, 256, 4))
    >>> FarmHash64(arr)
    1550282412043536862

Note that arrays need to be contiguous for this to work. To convert a
non-contiguous array, use ``np.ascontiguousarray()`` method.

SSE4.2 optimizations
~~~~~~~~~~~~~~~~~~~~

On CPUs that support SSE4.2 instruction set, optimized FarmHash has significant
advantage over non-optimized version and over CityHash, as can be seen below.
The numbers below were recoreded on a 2.4 GHz Intel Xeon CPU (E5-2620), and the
task was to hash a 512x512x3 NumPy array.

+--------------------+-------------------+-------------------+
| Method             | Time (64-bit)     | Time (128-bit)    |
+====================+===================+===================+
| FarmHash / SSE4.2  | 373 µs ± 48.3 µs  | 494 µs ± 30.2 µs  |
+--------------------+-------------------+-------------------+
| FarmHash           | 494 µs ± 13.8 µs  | 490 µs ± 23.0 µs  |
+--------------------+-------------------+-------------------+
| CityHash           | 497 µs ± 15.0 µs  | 493 µs ± 21.4 µs  |
+--------------------+-------------------+-------------------+

Currently, the ``setup.py`` script automatically detects whether the CPU
supports SSE4.2 instruction set and enables it during the compilation phase if
it does.

Development
-----------

For those who want to contribute, here is a quick start using some makefile
commands:

.. code-block:: bash

    git clone https://github.com/escherba/python-cityhash.git
    cd python-cityhash
    make env           # create a Python virtualenv
    make test          # run Python tests
    make cpp-test      # run C++ tests

The Makefiles provided have self-documenting targets. To find out which targets
are available, type:

.. code-block:: bash

    make help

See Also
--------
For other fast non-cryptographic hashing implementations available as Python
extensions, see `MetroHash <https://github.com/escherba/python-metrohash>`__
and `MurmurHash <https://github.com/hajimes/mmh3>`__.

Authors
-------
The original Python bindings were written by Alexander [Amper] Marshalov, then
were largely rewritten for more flexibility by Eugene Scherba. The CityHash and
FarmHash algorithms and their C++ implementation are by Google.

License
-------
This software is licensed under the `MIT License
<http://www.opensource.org/licenses/mit-license>`_.  See the included LICENSE
file for details.


