Metadata-Version: 1.1
Name: blaze
Version: 0.1
Summary: Blaze
Home-page: UNKNOWN
Author: Continuum Analytics
Author-email: blaze-dev@continuum.io
License: BSD
Description: <p align="center" style="padding: 20px">
        <img src="https://raw.github.com/ContinuumIO/blaze/master/docs/source/svg/blaze_med.png">
        </p>
        
        **Blaze** is the next-generation of NumPy. It is designed as a
        foundational set of abstractions on which to build out-of-core and
        distributed algorithms over a wide variety of data sources and to extend
        the structure of NumPy itself.
        
        <p align="center" style="padding: 20px">
        <img src="https://raw.github.com/ContinuumIO/blaze/master/docs/source/svg/numpy_plus.png">
        </p>
        
        Blaze allows easy composition of low level computation kernels
        ( C, Fortran, Numba ) to form complex data transformations on large
        datasets.
        
        In Blaze, computations are described in a high-level language 
        (Python) but executed on a low-level runtime (outside of Python), 
        enabling the easy mapping of high-level expertise to data without sacrificing
        low-level performance. Blaze aims to bring Python and NumPy into the
        massively-multicore arena, allowing it to able to leverage many CPU and
        GPU cores across computers, virtual machines and cloud services.
        
        <p align="center" style="padding: 20px">
        <img src="https://raw.github.com/ContinuumIO/blaze/master/docs/source/svg/codepush.png">
        </p>
        
        Continuum Analytics' vision is to provide open technologies for data
        integration on a massive scale based on a vision of a structured,
        universal "data web". In the same way that URL, HTML, and HTTP form
        the basis of the World Wide Web for documents, Blaze could
        be a fabric for structured and numerical data spearheading
        innovations in data management, analytics, and distributed computation.
        
        Blaze aims to be a foundational project allowing many different users of
        other PyData projects ( Pandas, Theano, Numba, SciPy, Scikit-Learn)
        to interoperate at the application level and at the library level with
        the goal of being able to to lift their existing functionality into a
        distributed context.
        
        <p align="center" style="padding: 20px">
        <img src="https://raw.github.com/ContinuumIO/blaze/master/docs/source/svg/sources.png">
        </p>
        
        Status
        ------
        
        Blaze is a work in progress at the moment.  The 0.1 release is imminent with a first-usable release due at the end of August 2013. 
        
        Documentation
        -------------
        
        * [0.1 Dev Docs](http://blaze.pydata.org/docs/)
        
        Installing
        ----------
        
        If you are interested in the development version of Blaze you can
        obtain the source from Github.
        
        ```bash
        $ git clone git@github.com:ContinuumIO/blaze.git
        ```
        
        Many of the dependencies ( i.e. llvmpy ) are non-trivial to install.
        It is **highly recommend** that you build Blaze using the Anaconda
        distribution, a free Python distribution that comes with a host of
        scientific and numeric packages bundled and precompiled into a userspace
        Python environment.
        
        Anaconda can be downloaded for all platforms here: http://continuum.io/downloads.html.
        
        Introduction
        ------------
        
        Pre-requisites:
          * llvmpy >= 0.11.1
          * cython >= 0.16
          * numpy >= 1.5
        
        Install all pre-requisites and then run:
        
        python setup.py install
        
        Docs are generated using sphinx in the docs directory.
        
        
        Alternative Installation
        ------------------------
        
        If for some reason you wish to avoid using Anaconda 
        it is possible to build Blaze using standard Python tools. 
        This method is not recommended.
        
        1) After you have checked out the Blaze source, create a virtualenv
        under the root of the Blaze repo.
        
        ```bash
        $ virtualenv venv --distribute --no-site-packages 
        $ . venv/bin/activate
        ```
        
        2) Pull the Conda package manager for use inside of your virtualenv.
        
        ```bash
        $ git clone git@github.com:ContinuumIO/conda.git
        ```
        
        3) Build and install conda.
        
        ```bash
        $ cd conda
        $ python setup.py install
        $ cd ..
        ```
        
        4) Create a directory in your virtualenv to mimic the behavior of
        Anaconda and allow Continuum signed packages to be installed.
        
        ```bash
        $ mkdir venv/pkgs
        ```
        
        5) Add ``conda`` to your path.
        
        ```bash
        $ PATH=venv/bin:$PATH
        ```
        
        6) Use Anaconda to resolve Blaze dependencies. This method is
        experimental and not officially supported.
        
        ```bash
        $ conda install ply
        $ conda install numpy
        $ conda install llvmpy
        $ conda install cython
        $ conda install pycparser
        ```
        
        7) From inside the Blaze directory run the Makefile.
        
        ```bash
        $ make build
        ```
        
        Contributing
        ------------
        
        Anyone wishing to discuss on Blaze should join the
        [blaze-dev](https://groups.google.com/a/continuum.io/forum/#!forum/blaze-dev) 
        mailing list at: blaze-dev@continuum.io
        
        License
        -------
        
        Blaze development is sponsored by Continuum Analytics.
        
        Released under BSD license. See LICENSE for details.
        
Platform: any
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Utilities
