Skip to main content

Python's Tensorflow Graph Library

Project description

TFGraph: Python's Tensorflow Graph Library

.. |travisci| image::

.. |codecov| image::

.. |docs| image::

.. |gitter| image::

.. |license| image::

.. |release| image::

|travisci| |codecov| |docs| |gitter| |license| |release|

This work consists of a study of a set of techniques and strategies related with algorithm's design, whose purpose is the resolution of problems on massive data sets, in an efficient way. This field is known as Algorithms for Big Data. In particular, this work has studied the Streaming Algorithms, which represents the basis of the data structures of sublinear order o(n) in space, known as Sketches. In addition, it has deepened in the study of problems applied to Graphs on the Semi-Streaming model. Next, the PageRank algorithm was analyzed as a concrete case study. Finally, the development of a library for the resolution of graph problems, implemented on the top of the intensive mathematical computation platform known as TensorFlow has been started.

* `Source Code <>`__
* `API Documentation <>`__
* `Code Examples <>`__
* `Tests <>`__

How to install

If you have git installed, you can try::

$ pip install git+

If you get any installation or compilation errors, make sure you have the latest pip and setuptools::

$ pip install --upgrade pip setuptools

How to run the tests

Install in editable mode and call `pytest`::

$ pip install -e .
$ pytest

Project details

Release history Release notifications | RSS feed

This version


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

tfgraph-0.2.tar.gz (17.6 kB view hashes)

Uploaded source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page