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        "author": "TileDB, Inc.",
        "author_email": "help@tiledb.io",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "Intended Audience :: Information Technology",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Operating System :: MacOS :: MacOS X",
            "Operating System :: POSIX :: Linux",
            "Operating System :: Unix",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Programming Language :: Python :: 3.8",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": ".. image:: https://github.com/TileDB-Inc/TileDB/raw/dev/doc/source/_static/tileDB_uppercase_600_112.png\n    :target: https://tiledb.io\n    :alt: TileDB logo\n    :width: 400\n\n|\n\n.. image:: https://travis-ci.org/TileDB-Inc/TileDB-Py.svg?branch=dev\n    :target: https://travis-ci.org/TileDB-Inc/TileDB-Py\n    :alt: Travis status\n\n.. image:: https://readthedocs.com/projects/tiledb-inc-tiledb-py/badge/?version=latest\n    :target: https://tiledb-inc-tiledb-py.readthedocs-hosted.com/en/latest/?badge=latest\n    :alt: Documentation Status\n\n|\n\n**Array data management made fast and easy.**\n\n`TileDB <https://tiledb.io>`_ is an efficient multi-dimensional array management system which introduces a novel on-disk format that can effectively store dense and sparse array data with support for fast updates and reads. It also features excellent compression and an efficient parallel I/O system with high scalability.\n\n**TileDB-Py** is the official Python interface to TileDB.\n\nQuickstart\n----------\n\nFirst, install TileDB-Py with ``pip``::\n\n    $ pip install tiledb\n\nThis may take a while, as the pip package will automatically download and build the native TileDB library in addition to the Python bindings.\n\nNext, save the `quickstart program <https://github.com/TileDB-Inc/TileDB-Py/blob/dev/examples/quickstart_dense.py>`_ into a file and run it::\n\n    $ wget https://raw.githubusercontent.com/TileDB-Inc/TileDB-Py/dev/examples/quickstart_dense.py\n    $ python quickstart_dense.py\n    [[2 3 4]\n     [6 7 8]]\n\nThe dense quickstart program simply creates a dense array on disk, writes some simple data to it, and reads a slice of the data back, printing the slice to the console.\n\nDocumentation\n-------------\n\nThe full TileDB documentation can be found at `<https://docs.tiledb.io>`_ and includes many tutorials and examples to get you started.\n\nThe latest Python API reference can be found at `<https://docs.tiledb.io/projects/tiledb-py/en/latest/python-api.html>`_.\n\nInstallation\n------------\n\nPip\n~~~\n\nA PyPI package is available which can be installed with Pip. This package will download and install the native TileDB library inside the site package if TileDB is not already installed on your system.\n\n::\n\n    $ pip install tiledb\n\nNote: if the Numpy and Cython dependencies are not installed, pip will try to build them from source.  This can take a **long** time and make the install appear to \"hang.\"  Pass the ``-v`` flag to pip to monitor the build process.\n\nIf you wish to use a custom version of the TileDB library and the install location is not in the compiler search path, create a requirements.txt file that specifies the tiledb install path manually.\n\n::\n\n    $ cat > tiledb_requirements.txt <<EOF\n      tiledb==<version> --install-option=\"--tiledb=<path/to/tiledb/install>\"\n      EOF\n    $ pip install -r tiledb_requirements.txt\n\nDo not forget to put the built ``.so / .dylib / .dll`` on the dynamic linker path, otherwise TileDB-Py will fail to load the shared library upon import.\n\n\nConda Package\n~~~~~~~~~~~~~\n\nA pre-built Conda package is available that will install TileDB as well.\n\n::\n\n    $ conda install -c conda-forge tiledb-py\n\nNote: Currently the pre-built TileDB conda package does not include the HDFS storage backend.\n\nInstalling From Source\n~~~~~~~~~~~~~~~~~~~~~~\n\nTileDB-Py Build Dependencies\n''''''''''''''''''''''''''''\n\n* Numpy\n* Cython\n* C++11 compiler\n* CMake\n\nTileDB-Py Runtime Dependencies\n''''''''''''''''''''''''''''''\n\n* Numpy\n\nLinux / OSX\n'''''''''''\n\nSimply execute the following commands::\n\n   $ git clone https://github.com/TileDB-Inc/TileDB-Py.git\n   $ cd TileDB-Py\n   $ pip install -r requirements_dev.txt\n   $ python setup.py build_ext --inplace\n   $ python setup.py install\n\nIf you wish to use a custom version of the TileDB library and it is installed in a non-standard location, pass the path to ``setup.py`` with the ``--tiledb=`` flag.\nIf you want to pass extra compiler/linker flags during the C++ extension compilation step use ``--cxxflags=`` or ``--lflags=``.\n\n::\n\n  $ python setup.py build_ext --inplace --tiledb=/home/tiledb/dist \n\nIf TileDB is installed in a non-standard location, you also need to make the dynamic linker aware of ``libtiledb``'s location.\nOtherwise when importing the ``tiledb`` module you will get an error that the built extension module cannot find\n``libtiledb``'s symbols::\n\n  $ env LD_LIBRARY_PATH=\"/home/tiledb/dist/lib:$LD_LIBRARY_PATH\" python -m unittest -v\n\nFor macOS the linker environment variable is ``DYLD_LIBRARY_PATH``\n\nInstalling on Windows\n'''''''''''''''''''''\n\nIf you are building the extension on Windows, first install a Python distribution such as `Miniconda <https://conda.io/miniconda.html>`_. You can then either build TileDB from source, or download the pre-built binaries.\n\nOnce you've installed Miniconda and TileDB, open the Miniconda command prompt and execute:\n\n::\n\n   > cd TileDB-Py\n   > conda install conda-build\n   > conda install virtualenv\n   > virtualenv venv\n   > venv\\Scripts\\activate\n   > pip install -r requirements_dev.txt\n   > python setup.py build_ext --inplace --tiledb=C:\\path\\to\\TileDB\\\n   > set PATH=%PATH%;C:\\path\\to\\TileDB\\bin\n   > python -m unittest -v\n\nNote that if you built TileDB from source, then replace ``C:\\path\\to\\TileDB`` with ``C:\\path\\to\\TileDB\\dist``.\n\nDeveloping and testing TileDB-Py\n--------------------------------\n\nTileDB-Py includes a handy Conda environment definition file for setting up a test environment::\n\n    $ conda env create -f environment.yml\n\nThis will create a ``tiledbpy`` conda environment with all the development library dependencies.\n\nThe easiest way to test / develop TileDB-Py across Python versions (2.7, 3.5, and 3.6),\nis using `tox <https://tox.readthedocs.io/en/latest/index.html>`_.\nTileDB includes a tox.ini file, simply run ``tox`` in the toplevel source directory to run the test suite against multiple installed Python versions::\n\n    $ tox\n\nYou can specify a particular Python version using the ``-e`` flag::\n\n    $ tox -e py27\n\nIf TileDB is not installed in a global system location, you must specify the install path to tox::\n\n    $ env TILEDB_PATH=/path/to/tiledb LD_LIBRARY_PATH=/path/to/tiledb/libdir:${LD_LIBRARY_PATH} tox\n\nYou can also run the unittests from the source folder without having the package installed. 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