Overview
========

Jubakit is a Python module to access Jubatus features easily.
The goal of Jubakit is to:

* Accelerate cycles of data analysis by integrating powerful scikit-learn features into Jubatus
* Conceal the system architecture of Jubatus (config files, TCP port number assignment, process invocation, RPC call, etc.) to provide an interface that users can focus on data analysis

Here is a shortest example of code using Jubakit.
You can perform anomaly detection on CSV dataset only by 4 lines of Python code:

.. code-block:: python

  dataset = Dataset(CSVLoader("dataset.csv"))
  service = Anomaly.run(Config())
  for result in service.add(dataset):
    print(result)

Jubakit provides a simple-to-use APIs while allowing users to customize detailed behaviors.
Jubakit also comes with configuration parameters that works well in most cases, so you don't have to configure them until necessary.