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

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

Connecting to Deepgram Data

Connecting to Deepgram 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.

Start by setting the Profile connection property to the location of the Deepgram Profile on disk (e.g. C:\profiles\Deepgram.apip). Next, set the ProfileSettings connection property to the connection string for Deepgram (see below).

Deepgram API Profile Settings

Deepgram uses API key authentication for all endpoints. API keys are scoped to a project and carry permission scopes (member, administrator, or owner). Create and manage API keys in the Deepgram console.

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

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

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

cnxn = mod.connect("Profile=C:\profiles\Deepgram.apip;AuthScheme=APIKey;ProfileSettings='APIKey=YOUR_DEEPGRAM_API_KEY';")

Execute SQL to Deepgram

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 ApiKeyId, MemberEmail FROM Keys WHERE ProjectId = 'your-project-id'", 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 Deepgram data and configure the app layout.

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

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='Deepgram Keys 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 Deepgram 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 Deepgram 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\Deepgram.apip;AuthScheme=APIKey;ProfileSettings='APIKey=YOUR_DEEPGRAM_API_KEY';")

df = pd.read_sql("SELECT ApiKeyId, MemberEmail FROM Keys WHERE ProjectId = 'your-project-id'", 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.ApiKeyId, y=df.MemberEmail, name='ApiKeyId')

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='Deepgram Keys Data', barmode='stack')
		})
], className="container")

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