archivers/py-bitshuffle: Add py-bitshuffle 0.5.1

Bitshuffle is an algorithm that rearranges typed, binary data for improving
compression, as well as a python/C package that implements this algorithm within
the Numpy framework.

The library can be used along side HDF5 to compress and decompress datasets and
is integrated through the dynamically loaded filters framework. Bitshuffle is
HDF5 filter number 32008.

Algorithmically, Bitshuffle is closely related to HDF5's Shuffle filter except
it operates at the bit level instead of the byte level. Arranging a typed data
array in to a matrix with the elements as the rows and the bits within the
elements as the columns, Bitshuffle "transposes" the matrix, such that all the
least-significant-bits are in a row, etc.

This does not in itself compress data, only rearranges it for more efficient
compression. To perform the actual compression you will need a compression
library. Bitshuffle has been designed to be well matched to Marc Lehmann's LZF
as well as LZ4 and ZSTD. Note that because Bitshuffle modifies the data at the
bit level, sophisticated entropy reducing compression libraries such as GZIP and
BZIP are unlikely to achieve significantly better compression than simpler and
faster duplicate-string-elimination algorithms such as LZF, LZ4 and ZSTD.
Bitshuffle thus includes routines (and HDF5 filter options) to apply LZ4 and
ZSTD compression to each block after shuffling.
2024Q2
Po-Chuan Hsieh 2024-03-23 22:14:53 +08:00
parent c13c94d800
commit c8b4d6d391
No known key found for this signature in database
GPG Key ID: 9A4BD10F002DD04B
7 changed files with 91 additions and 0 deletions

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@ -178,6 +178,7 @@
SUBDIR += ppunpack
SUBDIR += pxz
SUBDIR += py-acefile
SUBDIR += py-bitshuffle
SUBDIR += py-blosc2
SUBDIR += py-borgbackup
SUBDIR += py-borgbackup11

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@ -0,0 +1,28 @@
PORTNAME= bitshuffle
PORTVERSION= 0.5.1
CATEGORIES= archivers python
MASTER_SITES= PYPI
PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX}
MAINTAINER= sunpoet@FreeBSD.org
COMMENT= Bitshuffle filter for improving typed data compression
WWW= https://github.com/kiyo-masui/bitshuffle
LICENSE= MIT
LICENSE_FILE= ${WRKSRC}/LICENSE
BUILD_DEPENDS= ${PYTHON_PKGNAMEPREFIX}h5py>=2.4.0:science/py-h5py@${PY_FLAVOR} \
${PYTHON_PKGNAMEPREFIX}numpy>=0,1:math/py-numpy@${PY_FLAVOR} \
${PYTHON_PKGNAMEPREFIX}setuptools>=0.7:devel/py-setuptools@${PY_FLAVOR} \
${PYTHON_PKGNAMEPREFIX}wheel>=0:devel/py-wheel@${PY_FLAVOR}
RUN_DEPENDS= ${PYTHON_PKGNAMEPREFIX}h5py>=2.4.0:science/py-h5py@${PY_FLAVOR} \
${PYTHON_PKGNAMEPREFIX}numpy>=1.6.1,1:math/py-numpy@${PY_FLAVOR} \
${PYTHON_PKGNAMEPREFIX}setuptools>=0.7:devel/py-setuptools@${PY_FLAVOR}
USES= pkgconfig python
USE_PYTHON= autoplist concurrent cython pep517
post-install:
${FIND} ${STAGEDIR}${PYTHON_SITELIBDIR} -name '*.so' -exec ${STRIP_CMD} {} +
.include <bsd.port.mk>

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@ -0,0 +1,3 @@
TIMESTAMP = 1710712300
SHA256 (bitshuffle-0.5.1.tar.gz) = 988f224739aa6858475a4c59172968c7b51cc657d2249580c8f96848708fbae3
SIZE (bitshuffle-0.5.1.tar.gz) = 229441

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@ -0,0 +1,14 @@
--- lzf/lzf_filter.c.orig 2022-11-26 00:17:16 UTC
+++ lzf/lzf_filter.c
@@ -51,11 +51,7 @@
macro H5_USE_16_API is set
*/
-#if H5_VERS_MAJOR == 1 && H5_VERS_MINOR == 8 && (H5_VERS_RELEASE < 3 || !H5_USE_16_API)
#define H5PY_H5Z_NEWCLS 1
-#else
-#define H5PY_H5Z_NEWCLS 0
-#endif
size_t lzf_filter(unsigned flags, size_t cd_nelmts,
const unsigned cd_values[], size_t nbytes,

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@ -0,0 +1,11 @@
--- pyproject.toml.orig 2022-11-26 00:17:16 UTC
+++ pyproject.toml
@@ -3,7 +3,7 @@ requires = [
requires = [
"setuptools>=0.7",
"Cython>=0.19",
- "oldest-supported-numpy",
+ "numpy",
"h5py>=2.4.0",
]

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@ -0,0 +1,11 @@
--- setup.py.orig 2022-11-26 00:17:16 UTC
+++ setup.py
@@ -371,7 +371,7 @@ class build_ext(build_ext_):
else:
openmpflag = "-fopenmp"
archi = platform.machine()
- if archi in ("i386", "x86_64"):
+ if archi in ("amd64", "i386", "x86_64"):
compileflags = COMPILE_FLAGS + ["-march=%s" % self.march]
else:
compileflags = COMPILE_FLAGS + ["-mcpu=%s" % self.march]

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@ -0,0 +1,23 @@
Bitshuffle is an algorithm that rearranges typed, binary data for improving
compression, as well as a python/C package that implements this algorithm within
the Numpy framework.
The library can be used along side HDF5 to compress and decompress datasets and
is integrated through the dynamically loaded filters framework. Bitshuffle is
HDF5 filter number 32008.
Algorithmically, Bitshuffle is closely related to HDF5's Shuffle filter except
it operates at the bit level instead of the byte level. Arranging a typed data
array in to a matrix with the elements as the rows and the bits within the
elements as the columns, Bitshuffle "transposes" the matrix, such that all the
least-significant-bits are in a row, etc.
This does not in itself compress data, only rearranges it for more efficient
compression. To perform the actual compression you will need a compression
library. Bitshuffle has been designed to be well matched to Marc Lehmann's LZF
as well as LZ4 and ZSTD. Note that because Bitshuffle modifies the data at the
bit level, sophisticated entropy reducing compression libraries such as GZIP and
BZIP are unlikely to achieve significantly better compression than simpler and
faster duplicate-string-elimination algorithms such as LZF, LZ4 and ZSTD.
Bitshuffle thus includes routines (and HDF5 filter options) to apply LZ4 and
ZSTD compression to each block after shuffling.