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dev-python/numpy (gentoo)

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Install

Install this package:

emerge -a dev-python/numpy

If the package is masked, you can unmask it using the autounmask tool or standard emerge options:

autounmask dev-python/numpy

Or alternatively:

emerge --autounmask-write -a dev-python/numpy

Package Information

Description:
NumPy is a general-purpose array-processing Python package designed to efficiently manipulate large multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional arrays. There are also basic facilities for discrete fourier transform, basic linear algebra and random number generation. It is the successor of Numeric and numarray.
Homepage:
https://numpy.org/ https://github.com/numpy/numpy/ https://pypi.org/project/numpy/
License:
BSD

Versions

Version EAPI Keywords Slot
2.4.4 8 ~alpha ~amd64 ~arm ~arm64 ~hppa ~loong ~m68k ~mips ~ppc ~ppc64 ~riscv ~s390 ~sparc ~x86 0/2
2.3.5 8 ~alpha amd64 arm arm64 ~hppa ~loong ~m68k ~mips ~ppc ~ppc64 ~riscv ~s390 ~sparc x86 0/2
2.3.2 8 ~alpha amd64 arm arm64 ~hppa ~loong ~m68k ~mips ~ppc ppc64 ~riscv ~s390 ~sparc x86 0/2
2.2.6 8 ~alpha amd64 arm arm64 ~hppa ~loong ~m68k ~mips ppc ppc64 ~riscv ~s390 ~sparc x86 0/2

Metadata

Description

Maintainers

Upstream

Raw Metadata XML 
<pkgmetadata>
	<maintainer type="project">
		<email>sci@gentoo.org</email>
		<name>Gentoo Science Project</name>
	</maintainer>
	<maintainer type="project">
		<email>python@gentoo.org</email>
		<name>Python</name>
	</maintainer>
	<longdescription lang="en">
  NumPy is a general-purpose array-processing Python package designed to
  efficiently manipulate large multi-dimensional arrays of arbitrary
  records without sacrificing too much speed for small multi-dimensional
  arrays. There are also basic facilities for discrete fourier transform,
  basic linear algebra and random number generation.
  It is the successor of Numeric and numarray.
  </longdescription>
	<use>
		<flag name="cpudetection">
      Enable dynamic dispatch to additional CPU extensions not covered
      by enabled CPU_FLAGS_*.  This permits NumPy to benefit from improved
      performance when CPUs support more instruction sets, while preserving
      compatibility with the baseline set by CPU_FLAGS_*.
    </flag>
	</use>
	<upstream>
		<remote-id type="github">numpy/numpy</remote-id>
		<remote-id type="pypi">numpy</remote-id>
	</upstream>
</pkgmetadata>

Lint Warnings

USE Flags

Manage flags for this package: euse -i <flag> -p dev-python/numpy | euse -E <flag> -p dev-python/numpy | euse -D <flag> -p dev-python/numpy

Flag Description 2.4.4 2.3.5 2.3.2 2.2.6
${ARM_FLAGS[*]/#/cpu_flags_arm_} ⚠️ ✓ ✓ ✗ ✗
${PPC_FLAGS[*]/#/cpu_flags_ppc_} ⚠️ ✓ ✓ ✗ ✗
${X86_FLAGS[*]/#/cpu_flags_x86_} ⚠️ ✓ ✓ ✗ ✗
big-endian Big-endian toolchain support ✓ ✓ ✓ ✓
cpudetection Enable dynamic dispatch to additional CPU extensions not covered by enabled CPU_FLAGS_*. This permits NumPy to benefit from improved performance when CPUs support more instruction sets, while preserving compatibility with the baseline set by CPU_FLAGS_*. ⊕ ⊕ ✗ ✗
index64 Enable 64-bit array indexing support ✓ ✓ ✗ ✗
lapack Add support for the virtual/lapack numerical library ⊕ ⊕ ⊕ ⊕

Files

Manifest

Type File Size Versions
Unmatched Entries
Type File Size
DIST numpy-2.2.6.tar.gz 20276440 bytes
DIST numpy-2.3.2.tar.gz 20489306 bytes
DIST numpy-2.3.5.tar.gz 20584950 bytes
DIST numpy-2.3.5.tar.gz.provenance 9651 bytes
DIST numpy-2.4.4.tar.gz 20731587 bytes
DIST numpy-2.4.4.tar.gz.provenance 9927 bytes