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Source: bottleneck
Maintainer: Debian Python Modules Team <python-modules-team@lists.alioth.debian.org>
Uploaders: Ghislain Antony Vaillant <ghisvail@gmail.com>,
Pietro Battiston <me@pietrobattiston.it>
Section: python
Priority: optional
Build-Depends: debhelper-compat (= 10),
dh-python,
dpkg-dev (>= 1.17.14),
python3-all-dbg,
python3-all-dev,
python3-nose <!nocheck>,
python3-numpy (>= 1:1.14.3-1~),
python3-numpy-dbg,
python3-numpydoc <!nodoc>,
python3-setuptools,
python3-sphinx <!nodoc>,
sphinx-common
Standards-Version: 4.1.1
Vcs-Browser: https://salsa.debian.org/python-team/modules/bottleneck
Vcs-Git: https://salsa.debian.org/python-team/modules/bottleneck.git
Homepage: http://berkeleyanalytics.com/bottleneck
Package: python3-bottleneck
Architecture: any
Depends: ${misc:Depends},
${python3:Depends},
${shlibs:Depends}
Suggests: python-bottleneck-doc <!nodoc>
Enhances: python3-pandas
Description: Fast NumPy array functions written in C (Python 3)
Bottleneck is a collection of fast NumPy array functions written in C.
.
Only arrays with data type (dtype) int32, int64, float32, and float64 are
accelerated. All other dtypes result in calls to slower, unaccelerated
functions.
.
This package provides the modules for Python 3.
Package: python3-bottleneck-dbg
Architecture: any
Section: debug
Depends: ${misc:Depends},
${python3:Depends},
${shlibs:Depends},
python3-bottleneck (= ${binary:Version}),
python3-numpy-dbg
Description: debug extensions for bottleneck (Python 3)
Bottleneck is a collection of fast NumPy array functions written in C.
.
Only arrays with data type (dtype) int32, int64, float32, and float64 are
accelerated. All other dtypes result in calls to slower, unaccelerated
functions.
.
This package provides the debug extensions for Python 3.
Package: python-bottleneck-doc
Architecture: all
Section: doc
Depends: ${misc:Depends},
${sphinxdoc:Depends}
Built-Using: ${sphinxdoc:Built-Using}
Description: documentation for bottleneck
Bottleneck is a collection of fast NumPy array functions written in C.
.
Only arrays with data type (dtype) int32, int64, float32, and float64 are
accelerated. All other dtypes result in calls to slower, unaccelerated
functions.
.
This package provides the documentation for bottleneck.
Build-Profiles: <!nodoc>
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