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Merge pull request #588 from enthought/doc/basic-pelican-webpage
Add pelican-based webpage
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.gitignore

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# Documentation generated files #
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#################################
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doc/frontpage/build
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doc/source/generated
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docs/sphinx/build/*
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docs/www/output/*
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docs/www/cache/*
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# Things specific to this project #
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###################################

.travis.yml

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- conda create -q -n test-environment python=$PYVERSION setuptools pip numpy=1.8.1 pyzmq ipython matplotlib cython sphinx mock coverage requests pyyaml
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- source activate test-environment
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- pip install sphinxcontrib-napoleon sphinxcontrib-programoutput coveralls
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- pip install pelican
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- if [[ "$PYVERSION" == "2.7" ]]; then
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conda install mpi4py;
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else
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- sudo apt-get install libhdf5-mpich2-7 libhdf5-mpich2-dev # from Nick Andrik's PPA
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- CC=mpicc pip install git+https://github.com/h5py/[email protected] --install-option="--mpi"
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install:
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- python setup.py install
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- (cd $TRAVIS_BUILD_DIR && cd docs && make html)
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- python setup.py install # build DistArray
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- (cd $TRAVIS_BUILD_DIR/docs/sphinx && make html) # build docs
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- (cd $TRAVIS_BUILD_DIR/docs/www && make html) # build docs
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before_script:
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- "export DISPLAY=:99.0" # for plotting.py
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- "sh -e /etc/init.d/xvfb start" # for plotting.py

Makefile

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-${PYTHON} setup.py clean --all
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-find . \( -iname '*.py[co]' -or -iname '*.so' -or -iname '*.c' -or -iname '__pycache__' -or -iname '.ipynb_checkpoints' \) -exec ${RM} -r '{}' +
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-${RM} -r ${PARALLEL_OUT_DIR} build coverage_report examples/julia_set/build
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-${MAKE} clean -C docs
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-${MAKE} clean -C docs/sphinx
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-${MAKE} clean -C docs/www
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.PHONY: clean
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cleanall: clean

docs/source/index.rst

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docs/sphinx/source/blurb.rst

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*Think globally, act locally.*
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DistArray provides general multidimensional NumPy-like distributed arrays to
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Python. It intends to bring the strengths of NumPy to data-parallel
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high-performance computing. DistArray has a similar API to `NumPy`_.
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DistArray is ready for real-world testing and deployment; however, the project
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is still evolving rapidly, and we appreciate continued input from the
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scientific-Python community.
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DistArray is for users who
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* know and love Python and NumPy,
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* want to scale NumPy to larger distributed datasets,
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* want to interactively play with distributed data but also
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* want to run batch-oriented distributed programs;
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* want an easier way to drive and coordinate existing MPI-based codes,
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* have a lot of data that may already be distributed,
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* want a global view ("think globally") with local control ("act locally"),
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* need to tap into existing parallel libraries like Trilinos, PETSc, or
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Elemental,
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* want the interactivity of IPython and the performance of MPI.
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DistArray is designed to work with other packages that implement the
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`Distributed Array Protocol`_.
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.. _Distributed Array Protocol: http://distributed-array-protocol.readthedocs.org
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.. _NumPy: http://www.numpy.org
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Building the docs
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-----------------
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Dependencies to build the documentation:
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* Sphinx
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* sphinxcontrib.napoleon
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* sphinxcontrib.programoutput
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If you have the dependencies listed above, and you want to build the
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documentation (also available at http://distarray.readthedocs.org), navigate to
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the ``docs/sphinx`` subdirectory of the DistArray source and use the Makefile there.
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For example, to build the html documentation::
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make html
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from the ``docs`` directory.
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Try::
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make help
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for more options.
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# The name of an image file (relative to this directory) to place at the top
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# of the sidebar.
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#html_logo = None
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html_logo = "../../../docs/www/output/images/distarray-logo.png"
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# The name of an image file (within the static path) to use as favicon of the
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# docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32

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