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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.
- Navigate to Gmail
- Click on the Streak dropdown to the right of the search bar
- Select the Integrations button. This will open a window where you can view existing integrations and create new API keys.
- 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 CData Python Connector for Streak 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)