Metadata-Version: 1.1
Name: blaze
Version: 0.8.3
Summary: Blaze
Home-page: UNKNOWN
Author: Continuum Analytics
Author-email: blaze-dev@continuum.io
License: BSD
Description: .. image:: https://raw.github.com/blaze/blaze/master/docs/source/svg/blaze_med.png
           :align: center
        
        |Build Status| |Coverage Status| |Join the chat at
        https://gitter.im/blaze/blaze|
        
        **Blaze** translates a subset of modified NumPy and Pandas-like syntax
        to databases and other computing systems. Blaze allows Python users a
        familiar interface to query data living in other data storage systems.
        
        Example
        =======
        
        We point blaze to a simple dataset in a foreign database (PostgreSQL).
        Instantly we see results as we would see them in a Pandas DataFrame.
        
        .. code:: python
        
            >>> import blaze as bz
            >>> iris = bz.Data('postgresql://localhost::iris')
            >>> iris
                sepal_length  sepal_width  petal_length  petal_width      species
            0            5.1          3.5           1.4          0.2  Iris-setosa
            1            4.9          3.0           1.4          0.2  Iris-setosa
            2            4.7          3.2           1.3          0.2  Iris-setosa
            3            4.6          3.1           1.5          0.2  Iris-setosa
        
        These results occur immediately. Blaze does not pull data out of
        Postgres, instead it translates your Python commands into SQL (or
        others.)
        
        .. code:: python
        
            >>> iris.species.distinct()
                       species
            0      Iris-setosa
            1  Iris-versicolor
            2   Iris-virginica
        
            >>> bz.by(iris.species, smallest=iris.petal_length.min(),
            ...                      largest=iris.petal_length.max())
                       species  largest  smallest
            0      Iris-setosa      1.9       1.0
            1  Iris-versicolor      5.1       3.0
            2   Iris-virginica      6.9       4.5
        
        This same example would have worked with a wide range of databases,
        on-disk text or binary files, or remote data.
        
        What Blaze is not
        =================
        
        Blaze does not perform computation. It relies on other systems like SQL,
        Spark, or Pandas to do the actual number crunching. It is not a
        replacement for any of these systems.
        
        Blaze does not implement the entire NumPy/Pandas API, nor does it
        interact with libraries intended to work with NumPy/Pandas. This is the
        cost of using more and larger data systems.
        
        Blaze is a good way to inspect data living in a large database, perform
        a small but powerful set of operations to query that data, and then
        transform your results into a format suitable for your favorite Python
        tools.
        
        In the Abstract
        ===============
        
        Blaze separates the computations that we want to perform:
        
        .. code:: python
        
            >>> accounts = Symbol('accounts', 'var * {id: int, name: string, amount: int}')
        
            >>> deadbeats = accounts[accounts.amount < 0].name
        
        From the representation of data
        
        .. code:: python
        
            >>> L = [[1, 'Alice',   100],
            ...      [2, 'Bob',    -200],
            ...      [3, 'Charlie', 300],
            ...      [4, 'Denis',   400],
            ...      [5, 'Edith',  -500]]
        
        Blaze enables users to solve data-oriented problems
        
        .. code:: python
        
            >>> list(compute(deadbeats, L))
            ['Bob', 'Edith']
        
        But the separation of expression from data allows us to switch between
        different backends.
        
        Here we solve the same problem using Pandas instead of Pure Python.
        
        .. code:: python
        
            >>> df = DataFrame(L, columns=['id', 'name', 'amount'])
        
            >>> compute(deadbeats, df)
            1      Bob
            4    Edith
            Name: name, dtype: object
        
        Blaze doesn't compute these results, Blaze intelligently drives other
        projects to compute them instead. These projects range from simple Pure
        Python iterators to powerful distributed Spark clusters. Blaze is built
        to be extended to new systems as they evolve.
        
        Getting Started
        ===============
        
        Blaze is available on conda or on PyPI
        
        ::
        
            conda install blaze
            pip install blaze
        
        Development builds are accessible
        
        ::
        
            conda install blaze -c blaze
            pip install http://github.com/blaze/blaze --upgrade
        
        You may want to view `the docs <http://blaze.pydata.org>`__, `the
        tutorial <http://github.com/blaze/blaze-tutorial>`__, `some
        blogposts <http://continuum.io/blog/tags/blaze>`__, or the `mailing list
        archives <https://groups.google.com/a/continuum.io/forum/#!forum/blaze-dev>`__.
        
        
        Development setup
        =================
        
        The quickest way to install all Blaze dependencies with ``conda`` is as
        follows
        
        ::
        
            conda install blaze spark dynd-python -c libdynd -c blaze -c anaconda-cluster -y
            conda remove odo blaze blaze-core datashape -y
        
        After running these commands, clone ``odo``, ``blaze``, and ``datashape`` from
        GitHub directly.  These three projects release together.  Run ``python setup.py
        develop`` to make development installations of each.
        
        
        License
        =======
        
        Released under BSD license. See `LICENSE.txt <LICENSE.txt>`__ for
        details.
        
        Blaze development is sponsored by Continuum Analytics.
        
        .. |Build Status| image:: https://travis-ci.org/blaze/blaze.png
           :target: https://travis-ci.org/blaze/blaze
        .. |Coverage Status| image:: https://coveralls.io/repos/blaze/blaze/badge.png
           :target: https://coveralls.io/r/blaze/blaze
        .. |Join the chat at https://gitter.im/blaze/blaze| image:: https://badges.gitter.im/Join%20Chat.svg
           :target: https://gitter.im/blaze/blaze?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge
        
Platform: UNKNOWN
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
