PRODUCT : Getting Started on Rapture: Data Research with Python/Jupyter

Created by Andrew Clark, last modified by Joe Grabenstein on Aug 23, 2016

 

Tutorial: Getting Started with Rapture and iPython Notebook / Jupyter

Objectives:

Jupyter notebook is an open source web application that supports a variety of data science projects including data normalization, visualizations, statistical modeling and machine learning. This tutorials details how to access and manipulate Rapture managed data via a locally running Jupyter notebook.

The specific use case presented here involves loading data received as a csv file into a Rapture managed series repository and charting this data in a Jupyter notebook.  

This will cover the following steps:

  1. Installing jupyter notebook
  2. Install rapture python modules
  3. Connecting to Rapture demo env
  4. Getting data from rapture
  5. Creating graphs
  6. Saving data to rapture

For the purposes of this tutorial:

  • We have created a Jupyter docker instance that you can connect to your Rapture Demo Env
  • We have created a notebook to get you started.  

Pre-req

Note: In order to complete this tutorial, you must have a running Rapture instance. If you do not have one, you may request one from dev.incapture.net, or use our docker-compose.yml

There are 2 ways to use Jupyter notebook with Rapture:

1.) Using Docker (easiest/fastest)

  • If you do not have Docker installed, please browse to https://docs.docker.com/engine/installation/ and select the appropriate installation method for your machine (OSX, Linux and Windows compatible)
  • Once you have the Docker engine installed, simply run the following command to launch your own Jupyter notebook:

 

**TODO if this is to remain an option: make tutorial notebook files available in a downloadable .zip file. 

docker 
docker run -d -p 9999:9999 --name jupyter incapture/jupyter

OR (if you are using our docker-compose.yml):

docker run -d -p 9999:9999 --link raptureapiserver --name jupyter incapture/jupyter

Then browse to <dockerMachineIP>:9999

2.) Install Jupyter locally

*Prerequisite: Anaconda must be installed locally

install jupyter 
conda install jupyter
pip install RaptureAPI
pip install requests
pip install xlrd
pip install bokeh
pip install quandl
pip install raptureAPI 

Then browse to: localhost:8888

 

2. Open Tutorial Notebook

  • Browse to <dockerMachineIP>:9999 or localhost:8888 depending on which install method you chose.
  • Navigate to tutorial/QMG/
  • Open the settings.py file and change the following:
    • Change the localInstance variable to http://<yourRaptureInstanceAddress>:8665/rapture
      • *Alternatively, you can use the name of the apiserver docker container, ex: "http://raptureapiserver:8665/rapture" if using the incapture/jupyter Docker image.
    • set localUser to your username on your Rapture instance.
      • *If you are using Docker, your default username is: rapture
    • set localPassword to your password on your Rapture instance.
      • *If you are using Docker, your default password is: rapture
  • You are now ready to begin the Data Science tutorial.

 

3. Begin the Tutorial

  • Navigate to Tutorial/QMG/Demo_QMG_1_import.ipynb
    • The purpose of this script is to extract data from a csv or xls file, and upload it as a BLOB to your Rapture instance.

  • At the top of this notebook file, you can see the RaptureAPI being imported:

    Import 
    from raptureAPI import raptureAPI

     

  • Also note that we are retrieving the variables you set in settings.py for our Rapture login:

    import settings
settings.init()

rapture = raptureAPI.raptureAPI(settings.localInstance, settings.localUser, settings.localPassword)

  • From here, you can follow the documentation within the notebook itself.