1.
Data Science Apps: Beyond Notebooks
Natalino Busa - Head of Data Science

2.
2
Linkedin and Twitter:
@natbusa

3.
3
Icons made by Gregor Cresnar
from www.flaticon.com is licensed by CC 3.0 BY
Learning: The Scientific Method
Ørsted's "First Introduction to General Physics" (1811)
https://en.m.wikipedia.org/wiki/History_of_scientific_method
observation hypothesis deduction synthesis
Hans Christian Ørsted
experiment

4.
4
Data Scientist Experience

5.
5
CloudTools AI & ML

6.
6
The Jupyter Project
http://jupyter.org

7.
7
Jupyter notebook: what is it?
The Jupyter Notebook

8.
8
Jupyter notebook: why?
Language of choice
The Notebook has support for
over 40 programming
languages, including those
popular in Data Science such as
Python, R, Julia and Scala.
Share notebooks
Notebooks can be shared with
others using email, Dropbox,
GitHub and the Jupyter
Notebook Viewer.
Interactive widgets
Code can produce rich output
such as images, videos, LaTeX,
and JavaScript. Interactive
widgets can be used to
manipulate and visualize data in
realtime.
Big data integration
Leverage big data tools, such as
Apache Spark, from Python, R
and Scala. Explore that same
data with pandas, scikit-learn,
ggplot2, dplyr, etc.

9.
9
Text Cell
Code Cell
Cell Input
Cell Output
Edit, Run, Kernel, Widgets Menu’s
Kernel Type
Cell output: ASCII, HTML, Image. etc

10.
10
Architecture of a Jupyter Notebook
∅MQ
Notebook files
HTTP
Websockets

11.
11
Architecture of a Jupyter Notebook
• Modular architecture:
Web App, Server, Kernel
• Kernels:
Python, R, Scala, Julia, Bash, SPARKQL
• Web App:
Asynchronous, rich editing, syntax highlight, export and share

12.
12
Jupyter Notebook
● Narratives and Use Cases
Narratives are collaborative, shareable, publishable, and reproducible. We believe that
Narratives help both yourself and other researchers by sharing your use of Jupyter
projects, technical specifics of your deployment, and installation and configuration tips so
that others can learn from your experiences.
From https://jupyter.readthedocs.io/en/latest/use-cases/content-user.html

13.
13
Jupyter is more than Notebooks

14.
14
Examples of Jupyter powered narratives
●
●

15.
15
Orioles: A powerful educational narrative

16.
16
Orioles: A powerful educational narrative
∅MQ
Notebook files
HTTP
Websockets
Video files
Docker
Containers

17.
17

18.
18
Build your own narrative!
What do you need?
Understand how to communicate to the jupyter server
Two ways: websockets or http api endpoints
Build your own web application
Many ways: e.g. angular, polymer, dart, etc
1
2

19.
19
Example: autoscience demo
Purpose:
- Quick exploration of data sets
- No coding required
- Visual analysis of outliers

20.
20

21.
21

22.
22

23.
23

24.
24
Jupyter Gateway: expose API endpoints
Declare the endpoint
Produce the JSON payload
GET http://localhost:8800/cog/datasets/1

25.
25
Jupyter Gateway: consume the data
Consume the JSON payload
GET http://localhost:8800/cog/datasets/1
app.controller('datasetCtrl', function ($scope, $routeParams, $http) {
var id= $routeParams.id;
$http({
method: 'GET',
url: '/cog/datasets/'+id
}).then(function successCallback(response) {
// this callback will be called asynchronously
// when the response is available
$scope.d = response.data
}, function errorCallback(response) {
// called asynchronously if an error occurs
// or server returns response with an error status.
});
});

26.
26
<div class="row">
<div class="col-md-9 offset-md-2">
<p class="small">{{d.ds.rows}} obs. of {{d.ds.cols}} variables <br/>
NA rows:{{d.ds.na.rows}}, columns:{{d.ds.na.cols}}</p>
</div>
</div>
...
<tr ng-repeat="v in d.vars">
<td><a href="#/ds/{{d.ds.id}}/variables/{{v.id}}">{{v.name}}</a></td>
<td class="small">{{ v.sample.toString() }}</td>
<td>{{v.type.vtype}}</td>
<td>{{v.type.tcoerce}}</td>
<td>{{v.type.unique}}</td>
<td>{{v.type.nan}}</td>
<td>{{v.type.valid}}</td>
<td>{{v.type.quality}}</td>
...
Jupyter Gateway: consume the data
$scope.d
Render the angular
scope object

27.
27

28.
28
Jupyter: docker stacks
Docker container:
jupyter notebook + apache toree

29.
29
Dockerize your jupyter gateway api
Add the jupyter gateway
FROM jupyter/all-spark-notebook
...
# add some extra packages
ADD packages /srv/
RUN pip install -r /srv/packages
# install the kernel gateway
RUN pip install jupyter_kernel_gateway
ENV JUPYTER_GATEWAY=1
# REST API is designed as notebooks
ADD notebooks /srv/notebooks
Add the notebook which powers the API

30.
30
Dockerize your jupyter gateway api
IMAGE=autoscience/kernel_gateway
docker build -t $(IMAGE) .
docker run --rm -ti -p 8888:8888 $(IMAGE)
jupyter kernelgateway
--KernelGatewayApp.ip=0.0.0.0
--KernelGatewayApp.port=8888
--KernelGatewayApp.api=notebook-http
--KernelGatewayApp.seed_uri=/srv/notebooks/autoscience.ipynb

31.
31
Dockerize your jupyter gateway api
∅MQ
Notebook files
HTTP REST API
Docker
Containers

32.
32
Summary
• Jupyter notebook is a great way to create and share
data-driven uses cases and projects
• Jupyter is more than notebooks
– gateway, kernels, hub, etc
• Narratives powered by jupyter
– O’ Reilly Orioles
– build your own: autoscience example

33.
33
Resources

34.
34
Linkedin and Twitter:
@natbusa