python-lz4 0.4.0

python-lz4 provides bindings for the lz4 compression library by Yann Collet.

Install

The package is hosted on PyPI:

 pip install lz4
 easy_install lz4

Usage

The library is pretty simple to use:

>>> import lz4
>>> compressed_data = lz4.dumps(data)
>>> data == lz4.loads(compressed_data)
True
>>>

Methods

The bindings provides some aliases too:

 >>> import lz4
 >>> lz4.LZ4_compress == lz4.compress == lz4.dumps
 True
 >>> lz4.LZ4_uncompress == lz4.uncompress == lz4.loads
 True
 >>>

Is it fast ?

Yes. Here are the results on my 2011 Macbook Pro i7:

Compression:
200000 calls - LZ4:
 Best: 2.918570 seconds
 Worst: 2.966427 seconds
200000 calls - Snappy:
 Best: 3.634658 seconds
 Worst: 3.670079 seconds
Decompression
200000 calls - LZ4:
 Best: 0.458944 seconds
 Worst: 0.483467 seconds
200000 calls - Snappy:
 Best: 0.714303 seconds
 Worst: 0.753677 seconds

With the following code:

>>> import uuid
>>> import timeit
>>> import lz4
>>> import snappy
>>> from timeit import Timer

>>> DATA = "".join([ str(uuid.uuid4()) for _ in xrange(200)])
>>> LZ4_DATA = lz4.compress(DATA)
>>> SNAPPY_DATA = snappy.compress(DATA)
>>> LOOPS = 200000

>>> print "Compression:"
>>> times = [Timer("lz4.compress(DATA)", "from __main__ import DATA; import lz4").timeit(number=LOOPS) for x in xrange(10)]
>>> print "%d calls - LZ4:" % LOOPS
>>> print " Best: %f seconds" % min(times)
>>> print " Worst: %f seconds" % max(times)
>>> times = [Timer("snappy.compress(DATA)", "from __main__ import DATA; import snappy").timeit(number=LOOPS) for x in xrange(10)]
>>> print "%d calls - Snappy:" % LOOPS
>>> print " Best: %f seconds" % min(times)
>>> print " Worst: %f seconds" % max(times)

>>> print "Decompression"
>>> times = [Timer("lz4.uncompress(LZ4_DATA)", "from __main__ import LZ4_DATA; import lz4").timeit(number=LOOPS) for x in xrange(10)]
>>> print "%d calls - LZ4:" % LOOPS
>>> print " Best: %f seconds" % min(times)
>>> print " Worst: %f seconds" % max(times)
>>> times = [Timer("snappy.uncompress(SNAPPY_DATA)", "from __main__ import SNAPPY_DATA; import snappy").timeit(number=LOOPS) for x in xrange(10)]
>>> print "%d calls - Snappy:" % LOOPS
>>> print " Best: %f seconds" % min(times)
>>> print " Worst: %f seconds" % max(times)

Important note

Because LZ4 doesn't define a container format, the python bindings will insert the original data size as an integer at the start of the compressed payload, like most bindings do anyway (Java...)


Product's homepage

Requirements:

· Python