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Python CRC Computation 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. It takes advantage of crcany's ability to efficiently combine multiple CRCs to parallelize the CRC's calculation.

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. To go back to the initial value, use:

>>> crc32.reset()

Specify the starting CRC value:

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

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)

The CRC's width cannot exceed your system's maximum integer width.

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

Benchmarks

Calculating the CRC32 for lorem ipsum 1 million times:

Module Time Elapsed (s) Speed (GiB/s) Relative
anycrc 0.22 1.91 1.00
zlib 0.28 1.47 1.28
fastcrc 0.80 0.52 3.66
crcmod-plus 0.91 0.46 4.13

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 (parallel) 0.02 23.16 1.00
anycrc (serial) 0.20 2.08 11.15
zlib 0.22 1.92 12.05
fastcrc 0.68 0.61 37.89
crcmod-plus 0.67 0.62 37.40

Tested on a 12th generation Intel i7 processor. Parallel performance will depend on your system.

Notes

- Parallelism is disabled when the length of the input data is under 20k, as the serial method is faster in that case.

- The macOS build only supports the serial version.

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