Cortex Parses Reference
======================================

The parsers are available at ``cortex.parsers``. 

Parsers are simple functions or classes, built on top of a platform (using aspect-oriented programming), and easily deployable as microservices consuming raw data
from the queue, and producing parsed results to it. 


INFO: Parsers can be added easily as decribed in `Adding Parsers <https://github.com/AvivYaniv/Cortex#adding-Parsers>`__ 


1. API:

::

  >>> from cortex.parsers import run_parser     
  >>> data = …      
  >>> result = run_parser('pose', data)
  
Which accepts a parser name and some raw data, as consumed from the
message queue, and returns the result, as published to the message
queue. 

2. CLI:

::

  $ python -m cortex.parsers parse 'pose' 'snapshot.raw' > 'pose.result' 

Which accepts a parser name and a path to some raw data, as consumed from the message queue, and prints the result, as published to the message queue (optionally redirecting it to a file). This way of invocation runs the parser exactly once.

::

  $ python -m cortex.parsers run-parser 'pose' 'rabbitmq://127.0.0.1:5672/'

Which runs the parser as a service, which works with a message queue indefinitely. 
The following parsers are available: 

1. Pose  

 Collects the translation and the rotation of the user's head at a given timestamp, and publishes the result to a dedicated topic. 

2. Color Image  

 Collects the color image of what the user was seeing at a given timestamp, and publishes the result to a dedicated topic. 


NOTE: the data itself is
stored to disk, and only the metadata published. 

3. Depth Image

 Collects the depth image of what the user was seeing at a given timestamp, and publishes the result to a dedicated topic. A depth image is a width × height array of floats, where each float represents how far the nearest surface from the user was, in meters. So, if the user was looking at a chair, the depth of its outline would be its proximity to her (for example, 0.5 for half a meter), and the wall behind it would be farther (for example, 1.0 for one meter). 


NOTE: the data itself should
be stored to disk, and only the metadata published. 

4. Feelings

 Collects the feelings the user was experiencing at any timestamp, and
publishes the result to a dedicated topic.

API Functions:

.. function:: run_parser(<parser_type>, data)

    Which accepts a parser name and a path to some raw data, as consumed from the message queue, and prints the result, as published to the message queue (optionally redirecting it to a file). This way of invocation runs the parser exactly once.

Parser Service: 

.. autoclass:: cortex.parsers.parser_service.ParserService