Metadata-Version: 2.0
Name: graphistry
Version: 0.9.34
Summary: Visualize node-link graphs using Graphistry's cloud
Home-page: https://github.com/graphistry/pygraphistry
Author: The Graphistry Team
Author-email: pygraphistry@graphistry.com
License: BSD
Download-URL: https://pypi.python.org/pypi/graphistry/
Keywords: Graph,Network,Plot,Visualization,Pandas,Igraph
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Requires-Dist: numpy
Requires-Dist: pandas (>=0.17.0)
Requires-Dist: requests
Requires-Dist: future (>=0.15.0)
Requires-Dist: protobuf (>=2.6.0)
Provides-Extra: networkx
Requires-Dist: networkx; extra == 'networkx'
Provides-Extra: pandas-extra
Requires-Dist: numexpr; extra == 'pandas-extra'
Requires-Dist: Bottleneck; extra == 'pandas-extra'
Provides-Extra: all
Requires-Dist: python-igraph; extra == 'all'
Requires-Dist: networkx; extra == 'all'
Requires-Dist: numexpr; extra == 'all'
Requires-Dist: Bottleneck; extra == 'all'
Requires-Dist: colorlover; extra == 'all'
Provides-Extra: igraph
Requires-Dist: python-igraph; extra == 'igraph'


**PyGraphistry** is a visual graph analytics library to extract, transform, and
load big graphs into `Graphistry's <http://www.graphistry.com>`_ GPU-cloud-accelerated
explorer.

PyGraphistry is...

- **Fast & Gorgeous**: Cluster, filter, and inspect large amounts of data at
  interactive speed. We layout graphs with a descendant of the gorgeous
  ForceAtlas2 layout algorithm introduced in Gephi. Our data explorer connects
  to Graphistry's GPU cluster to layout and render hundreds of thousand of
  nodes+edges in your browser at unparalleled speeds.

- **Notebook Friendly**: PyGraphistry plays well with interactive notebooks
  like IPython/Juypter, Zeppelin, and Databricks: Process, visualize, and drill
  into with graphs directly within your notebooks.

- **Batteries Included**: PyGraphistry works out-of-the-box with popular data
  science and graph analytics libraries. It is also very easy to use. To create
  the visualization shown above, download this dataset of Facebook communities
  from SNAP and load it with your favorite library


Try It Out!
-----------

Tutorial and API docs are on
`https://github.com/graphistry/pygraphistry <https://github.com/graphistry/pygraphistry>`_


