Use Dash to Build to Web Apps on Nuclia Data

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData API Driver for Python, the pandas module, and the Dash framework, you can build Nuclia-connected web applications for Nuclia data. This article shows how to connect to Nuclia with the CData Connector and use pandas and Dash to build a simple web app for visualizing Nuclia data.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Nuclia data in Python. When you issue complex SQL queries from Nuclia, the driver pushes supported SQL operations, like filters and aggregations, directly to Nuclia and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Nuclia Data

Connecting to Nuclia data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

Using API Key Authentication

Nuclia uses API key authentication for accessing Knowledge Box data. To obtain an API key:

1. Log in to the Nuclia Cloud Dashboard at https://nuclia.cloud
2. Navigate to your Knowledge Box settings
3. Go to the Service Accounts section
4. Create a new service account or copy an existing API key

After obtaining your API key, set the following connection properties:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your Nuclia service account API key.
• KbId: Set this to your Knowledge Box UUID.
• Zone: Set this to your Nuclia deployment zone (e.g., aws-us-east-2-1).

Example Connection String

Profile=C:\profiles\Nuclia.apip;AuthScheme=APIKey;APIKey=your_service_account_key;KbId=your_kb_uuid;Zone=aws-us-east-2-1;

Connecting to Nuclia

Once the authentication is configured, you can connect to Nuclia and query data from any of the available tables such as Resources, KnowledgeBox, LabelSets, and ProcessingStatus.

After installing the CData Nuclia Connector, follow the procedure below to install the other required modules and start accessing Nuclia through Python objects.

Install Required Modules

Use the pip utility to install the required modules and frameworks:

pip install pandas
pip install dash
pip install dash-daq

Visualize Nuclia Data in Python

Once the required modules and frameworks are installed, we are ready to build our web app. Code snippets follow, but the full source code is available at the end of the article.

First, be sure to import the modules (including the CData Connector) with the following:

import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.api as mod
import plotly.graph_objs as go

You can now connect with a connection string. Use the connect function for the CData Nuclia Connector to create a connection for working with Nuclia data.

cnxn = mod.connect("Profile=C:\profiles\Nuclia.apip;AuthScheme=APIKey;APIKey=your_service_account_key;KbId=your_kb_uuid;Zone=aws-us-east-2-1;")

Execute SQL to Nuclia

Use the read_sql function from pandas to execute any SQL statement and store the result set in a DataFrame.

df = pd.read_sql("SELECT ,  FROM KnowledgeBox WHERE  = ''", cnxn)

Configure the Web App

With the query results stored in a DataFrame, we can begin configuring the web app, assigning a name, stylesheet, and title.

app_name = 'dash-apiedataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'

Configure the Layout

The next step is to create a bar graph based on our Nuclia data and configure the app layout.

trace = go.Bar(x=df., y=df., name='')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='Nuclia KnowledgeBox Data', barmode='stack')
		})
], className="container")

Set the App to Run

With the connection, app, and layout configured, we are ready to run the app. The last lines of Python code follow.

if __name__ == '__main__':
    app.run_server(debug=True)

Now, use Python to run the web app and a browser to view the Nuclia data.

python api-dash.py

Free Trial & More Information

Download a free, 30-day trial of the CData API Driver for Python to start building Python apps with connectivity to Nuclia data. Reach out to our Support Team if you have any questions.

Full Source Code

import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.api as mod
import plotly.graph_objs as go

cnxn = mod.connect("Profile=C:\profiles\Nuclia.apip;AuthScheme=APIKey;APIKey=your_service_account_key;KbId=your_kb_uuid;Zone=aws-us-east-2-1;")

df = pd.read_sql("SELECT ,  FROM KnowledgeBox WHERE  = ''", cnxn)
app_name = 'dash-apidataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'
trace = go.Bar(x=df., y=df., name='')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='Nuclia KnowledgeBox Data', barmode='stack')
		})
], className="container")

if __name__ == '__main__':
    app.run_server(debug=True)