Use Dash to Build to Web Apps on Perigon 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 Perigon-connected web applications for Perigon data. This article shows how to connect to Perigon with the CData Connector and use pandas and Dash to build a simple web app for visualizing Perigon data.

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

Connecting to Perigon Data

Connecting to Perigon 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

To use the Perigon API, you need to obtain an API key from your Perigon account. Navigate to the Perigon dashboard and generate an API key from your account settings.

After setting the following connection properties, you are ready to connect:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your Perigon API key.

Example connection string:

Profile=C:\profiles\Perigon.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your_api_key"

Available Tables

The Perigon profile provides access to the following tables:

• Articles - News articles retrieved from the Perigon news intelligence API
• Headlines - Story clusters grouping related headline articles
• Sources - News sources tracked by the Perigon news intelligence API
• Journalists - Journalist profiles tracked by the Perigon news intelligence API

After installing the CData Perigon Connector, follow the procedure below to install the other required modules and start accessing Perigon 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 Perigon 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 Perigon Connector to create a connection for working with Perigon data.

cnxn = mod.connect("Profile=C:\profiles\Perigon.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your_api_key"")

Execute SQL to Perigon

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 Articles 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 Perigon 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='Perigon Articles 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 Perigon 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 Perigon 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\Perigon.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your_api_key"")

df = pd.read_sql("SELECT ,  FROM Articles 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='Perigon Articles Data', barmode='stack')
		})
], className="container")

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