pfernique

*.sublime-workspace

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for n in $(ls *svg | sed 's/.svg//'); do 
    inkscape -z -e $n.png $n.svg
    convert $n.png -trim +repage $n-trimmed.png
    rm $n.png
    mv $n-trimmed.png $n.png
done

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AutoWIG: Wrapping very large C++ libraries in Python automatically

Most of Python and R scientific packages incorporate compiled scientific libraries to speed up the execution of the code needed for high-performance computing and to reuse legacy libraries.

Several semi-automatic solutions exist to wrap these compiled libraries: SWIG, Cython, Boost.Python. However, the process of wrapping a large C++ library is cumbersome and time consuming, mainly due some high-level constructs that have no equivalent in Python (template, complex iterators, ...).

In this talk, we introduce AutoWIG, a Python package that enables full C++ introspection using LLVM/Clang technologies. Default strategies have been designed to transform any C++ construct into Python, using Boost.Python for instance. Based on the introspection, a set of classes, methods, namespaces are retrieve and Boost.Python code is generated using the Mako template engine.

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set -e
git clone https://github.com/StatisKit/Misc.git
cd Misc
docker build --no-cache --build-arg BUILD="true" -t statiskit/ubuntu:trusty .
docker run -t statiskit/ubuntu:trusty /bin/bash post-link.sh
cd ..
rm -rf Misc
for GITHUB in PyClangLite AutoWIG; do
  git clone https://github.com/StatisKit/$GITHUB.git
  cd $GITHUB

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#!/bin/bash
# Delete all containers
docker rm -f $(docker ps -a -q)
# Delete all images
docker rmi -f $(docker images -q)

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import subprocess
if not subprocess.check_output(["llvm-config", "--version"]).strip() == '3.8.1':
    raise Exception

subprocess.check_call(['clang++', '--version'])
if not subprocess.check_output(["llvm-config", "--has-rtti"]).strip() == 'YES':
    raise Exception

import sys
from path import path

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FROM ubuntu:14.04

# Update the OS
RUN apt-get update

# Install userful tools
RUN apt-get install -y build-essential git wget

# Add user for future work
RUN useradd -ms /bin/bash conda-user