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AutoWIG: Automatic Generation of Python Bindings for C++ Libraries [PeerJ Computer Science]

Home Page: https://arxiv.org/abs/1705.11000

License: Apache License 2.0

Python 3.86% Jupyter Notebook 93.46% C 0.25% C++ 2.20% Shell 0.03% Batchfile 0.04% Dockerfile 0.15%

fp17's Introduction

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Material for the paper entitled "AutoWIG: automatic generation of Python bindings for C++ libraries" and submitted to PeerJ Computer Science

This repository contains supplementary material for the reproducibiliy of computational studies performed in the article "AutoWIG: automatic generation of Python bindings for C++ libraries" written by:

  • Pierre Fernique,
  • Christophe Pradal.

This article has been submitted to the "PeerJ Computer Science" journal. Here is the the citation formated as the bibtex standart.

@article{FP17,
  author    = {Pierre Fernique and Christophe Pradal},
  title     = {{AutoWIG}: Automatic Generation of {Python} Bindings for {C++} Libraries},
  journal   = {CoRR},
  volume    = {abs/1705.11000},
  year      = {2017},
  url       = {http://arxiv.org/abs/1705.11000},
  timestamp = {Wed, 07 Jun 2017 14:40:24 +0200},
  biburl    = {http://dblp.uni-trier.de/rec/bib/journals/corr/FerniqueP17},
  bibsource = {dblp computer science bibliography, http://dblp.org}
}

These studies are formatted as pre-executed Jupyter notebooks. Refers to the index.ipynb notebook which presents and references each study.

Test it !

To reproduce the studies with Docker use these images. After installing Docker, you can type the following commands in a shell:

docker run -i -t -p 8888:8888 statiskit/fp17

Then, follow the given instructions.

Install it !

You can also install required packages on your computer to reproduce these studies. In order to ease the installation of these packages on multiple operating systems, the Conda package and environment management system is used. For more information refers to the StatisKit software suite documentation concerning prerequisites to the installation step. Then, to install the required packages, proceed as as follows:

  1. Clone this repository,

    git clone --recursive https://github.com/StatisKit/FP17
  2. Create a Conda environment containing the meta-package fp17,

    conda create -n fp17 fp17 -c statiskit -c defaults --override-channels

    Note

    This meta-package do not corresponds to the one used for the article.

  3. Activate the Conda environment as advised in your terminal.

  4. Enter the directory containing Jupyter notebooks,

    cd FP17
    cd share
    cd jupyter
  5. Launch the Jupyter the index.ipynb notebook,

    jupyter notebook index.ipynb
  6. Execute the index.ipynb notebook to execute all examples or navigate among referenced notebooks to execute them separatly.

fp17's People

Contributors

pfernique avatar pradal avatar

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