Browse Source

l/pandas: Added pandas-0.16.2.

slackware-14.2
Damien Goutte-Gattat 6 years ago
parent
commit
6ee6b62c7f
  1. 1
      l/pandas/pandas-0.16.2.tar.gz.sha1
  2. 120
      l/pandas/pandas.SlackBuild
  3. BIN
      l/pandas/pandas.pdf
  4. 12
      l/pandas/slack-desc

1
l/pandas/pandas-0.16.2.tar.gz.sha1

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c30ce30495e2c351cb8181d36dac5122dc14d440 pandas-0.16.2.tar.gz

120
l/pandas/pandas.SlackBuild

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#!/bin/bash
# Build script for Slackware
# Copyright (C) 2015 Damien Goutte-Gattat
#
# Redistribution and use of this script, with or without modifications,
# is permitted provided that the following conditions are met:
#
# 1. Redistributions of this script must retain the above copyright
# notice, this list of conditions and the following disclaimer.
#
# THIS SOFTWARE IS PROVIDED BY THE AUTHOR AS IS'' AND ANY EXPRESS OR
# IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
# WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT,
# INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
# (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
# HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
# STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING
# IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
#
# Contact: Damien Goutte-Gattat <dgouttegattat@incenp.org>
#
# Latest pandas sourcecode is available at: <http://pandas.pydata.org/>.
#
# Depends: l/numpy, l/python-dateutil, l/pytz
# Recommends: l/numexpr, l/python-bottleneck, l/scipy, l/pytables
# Recommends: l/matplotlib
# Source package infos
NAMESRC=${NAMESRC:-pandas}
VERSION=${VERSION:-0.16.2}
ARCHIVE=${ARCHIVE:-$NAMESRC-$VERSION.tar.gz}
WGET=${WGET:-https://pypi.python.org/packages/source/p/pandas/$ARCHIVE}
DOC_URL=${DOC_URL:-http://pandas.pydata.org/pandas-docs/version/$VERSION/pandas.pdf}
# Build infos
NAMEPKG=${NAMEPKG:-pandas}
BUILD=${BUILD:-1GGD}
ARCH=${ARCH:-$(uname -m | sed 's/^i.86$/i486/;s/^arm.*/arm/')}
JOBS=${JOBS:-1}
EXT=${EXT:-txz}
# Directories
TMP=${TMP:-/tmp}
OUT=${OUT:-$TMP/build}
PKG=${PKG:-$OUT/$NAMEPKG}
CWD=$(pwd)
set -e # Quit if a command returns non-zero
# Sanity checks
if [ $UID -eq 0 ]; then
echo "You should NOT run this script as ROOT!"
exit 1
fi
if [ ! -d $TMP ]; then
echo "$TMP does not exists or is not a directory!"
exit 1
fi
# Compilation flags
LIBDIRSUFFIX=""
case "$ARCH" in
i?86)
CPUOPT="-O2 -march=$ARCH -mtune=i686"
;;
x86_64)
CPUOPT="-O2 -fPIC"
LIBDIRSUFFIX="64"
;;
*)
CPUOPT="-O2"
;;
esac
# Get and verify the source archive
if [ ! -r $ARCHIVE ]; then
wget -c -O $ARCHIVE.part "$WGET"
mv $ARCHIVE.part $ARCHIVE
fi
sha1sum -c $ARCHIVE.sha1
NAME=$(tar ft $ARCHIVE | head -n 1 | cut -d / -f 1)
# Get the documentation
if [ ! -r pandas.pdf ]; then
wget -c -O pandas.pdf.part "$DOC_URL"
mv pandas.pdf.part pandas.pdf
fi
# Compile
cd $TMP
echo "Building $ARCHIVE..."
tar xf $CWD/$ARCHIVE
cd $NAME
python setup.py build
python setup.py install --root=$PKG
# Install the documentation
mkdir -p $PKG/usr/doc/$NAME
install -m 644 LICENSE PKG-INFO RELEASE.md $CWD/pandas.pdf $PKG/usr/doc/$NAME
# Copy slack-desc file
install -D -m 644 $CWD/slack-desc $PKG/install/slack-desc
# Package the tree
cd $PKG
mkdir -p $OUT
PACKAGING="
chown root:root . -R
/sbin/makepkg -l y -c n $OUT/$NAMEPKG-$VERSION-$ARCH-$BUILD.$EXT
rm -rf $PKG
rm -rf $TMP/$NAME
"
if type -p fakeroot ; then
echo "$PACKAGING" | fakeroot
else
su -c "$PACKAGING"
fi

BIN
l/pandas/pandas.pdf

Binary file not shown.

12
l/pandas/slack-desc

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|-----handy-ruler-----------------------------------------------------|
pandas: pandas (Python structures for data analysis)
pandas:
pandas: Pandas is a Python package providing fast, flexible, and expressive
pandas: data structures designed to make working with structured (tabular,
pandas: multidimensional, potentially heterogeneous) and time series data
pandas: both easy and intuitive. It aims to be the fundamental high-level
pandas: building block for doing practical real world data analysis in
pandas: Python.
pandas:
pandas:
pandas:
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