Use Dash to Build to Web Apps on Smartsheet Data

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Smartsheet Python Connector

Python Connector Libraries for Smartsheet Data Connectivity. Integrate Smartsheet with popular Python tools like Pandas, SQLAlchemy, Dash & petl.



The CData Python Connector for Smartsheet enables you to create Python applications that use pandas and Dash to build Smartsheet-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 Smartsheet, the pandas module, and the Dash framework, you can build Smartsheet-connected web applications for Smartsheet data. This article shows how to connect to Smartsheet with the CData Connector and use pandas and Dash to build a simple web app for visualizing Smartsheet data.

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

Connecting to Smartsheet Data

Connecting to Smartsheet 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.

Smartsheet uses the OAuth authentication standard. To authenticate using OAuth, you will need to register an app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties.

However, for testing purposes you can instead use the Personal Access Token you get when you create an application; set this to the OAuthAccessToken connection property.

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

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

cnxn = mod.connect("OAuthClientId=MyOauthClientId;OAuthClientSecret=MyOAuthClientSecret;CallbackURL=http://localhost:33333;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Execute SQL to Smartsheet

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 TaskName, Progress FROM Sheet_Event_Plan_Budget WHERE Assigned = 'Ana Trujilo'", 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-smartsheetedataplot'

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 Smartsheet data and configure the app layout.

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

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='Smartsheet Sheet_Event_Plan_Budget 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 Smartsheet data.

python smartsheet-dash.py

Free Trial & More Information

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

cnxn = mod.connect("OAuthClientId=MyOauthClientId;OAuthClientSecret=MyOAuthClientSecret;CallbackURL=http://localhost:33333;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

df = pd.read_sql("SELECT TaskName, Progress FROM Sheet_Event_Plan_Budget WHERE Assigned = 'Ana Trujilo'", cnxn)
app_name = 'dash-smartsheetdataplot'

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.TaskName, y=df.Progress, name='TaskName')

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='Smartsheet Sheet_Event_Plan_Budget Data', barmode='stack')
		})
], className="container")

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