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Use Dash to Build to Web Apps on Streak Data

The CData Python Connector for Streak enables you to create Python applications that use pandas and Dash to build Streak-connected web apps.

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

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

Connecting to Streak Data

Connecting to Streak 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.

Use the following steps to generate a new API key for authenticating to Streak.

  1. Navigate to Gmail
  2. Click on the Streak dropdown to the right of the search bar
  3. Select the Integrations button. This will open a window where you can view existing integrations and create new API keys.
  4. Under the Streak API section of integrations, click the button to Create New Key.

After installing the CData Streak Connector, follow the procedure below to install the other required modules and start accessing Streak 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 Streak 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.streak as mod
import plotly.graph_objs as go

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

cnxn = mod.connect("ApiKey=8c84j9b4j54762ce809ej6a782d776j3;")

Execute SQL to Streak

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 UserKey, Email FROM Users WHERE Email = 'user@domain.com'", 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-streakedataplot'

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 Streak data and configure the app layout.

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

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='Streak Users 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 Streak data.

python streak-dash.py

Free Trial & More Information

Download a free, 30-day trial of the Streak Python Connector to start building Python apps with connectivity to Streak 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.streak as mod
import plotly.graph_objs as go

cnxn = mod.connect("ApiKey=8c84j9b4j54762ce809ej6a782d776j3;")

df = pd.read_sql("SELECT UserKey, Email FROM Users WHERE Email = 'user@domain.com'", cnxn)
app_name = 'dash-streakdataplot'

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.UserKey, y=df.Email, name='UserKey')

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='Streak Users Data', barmode='stack')
		})
], className="container")

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