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The fastest Python CRC Library

Project description

This is a Cython module with bindings to the crcany library. It supports calculating CRC hashes of arbitary sizes as well as updating a CRC hash over time. Anycrc supports all of the CRCs listed in the RevEng CRC Catalogue.

Installation

pip install anycrc

Usage

Use an existing model:

>>> import anycrc
>>> crc32 = anycrc.Model('CRC32')
>>> crc32.calc(b'Hello World!')
472456355

Read the data in chunks:

>>> crc32.update(b'Hello ')
3928882368
>>> crc32.update(b'World!')
472456355

The update method changes the internally stored CRC value, while calc doesn't. You can use get to retrieve the CRC value stored within the object:

>>> crc32.get()
472456355

To specify the starting CRC value:

>>> crc32.set(3928882368)
>>> crc32.calc('World!')
472456355

To go back to the initial value, use:

>>> crc32.reset()

Specify your own CRC parameters:

>>> # width, poly, init, refin, refout, xorout
>>> my_crc = anycrc.CRC(10, 0b0101010101, 0x3ff, True, False, 0)
>>> my_crc.calc('Hello World!')
35

The CRC will be computed in parallel when the input is large enough. If you want to disable parallelism, use:

>>> anycrc.set_parallel(False)

For a list of pre-built models, check models.py. To get a list of the models at any time, use the following command:

python -m anycrc models

The maximum possible CRC width is 128 bits.

Benchmarks

Calculating the CRC32 for lorem ipsum 1 million times:

Module Time Elapsed (s) Speed (GiB/s) Relative
anycrc 0.19 2.14 1.00
zlib 0.28 1.49 1.44
fastcrc 0.80 0.52 4.12
crcmod-plus 0.91 0.46 4.71

Calculating the CRC32 for the text of lorem ipsum repeated 1 million times in a single pass:

Module Time Elapsed (s) Speed (GiB/s) Relative
anycrc 0.13 3.21 1.00
zlib 0.22 1.93 1.66
fastcrc 0.67 0.62 5.18
crcmod-plus 0.67 0.62 5.18

Tested on a 10th generation Intel i7 processor. Parallel performance will depend on your system.

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