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

Use Dash to Build to Web Apps on ServiceNow Data



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

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

Connecting to ServiceNow Data

Connecting to ServiceNow 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.

ServiceNow uses the OAuth 2.0 authentication standard. To authenticate using OAuth, you will need to register an OAuth app with ServiceNow to obtain the OAuthClientId and OAuthClientSecret connection properties. In addition to the OAuth values, you will need to specify the Instance, Username, and Password connection properties.

See the "Getting Started" chapter in the help documentation for a guide on connecting to ServiceNow.

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

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

cnxn = mod.connect("OAuthClientId=MyOAuthClientId;OAuthClientSecret=MyOAuthClientSecret;Username=MyUsername;Password=MyPassword;Instance=MyInstance;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Execute SQL to ServiceNow

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 sys_id, priority FROM incident WHERE category = 'request'", 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-servicenowedataplot'

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 ServiceNow data and configure the app layout.

trace = go.Bar(x=df.sys_id, y=df.priority, name='sys_id')

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='ServiceNow incident 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 ServiceNow data.

python servicenow-dash.py

Free Trial & More Information

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

cnxn = mod.connect("OAuthClientId=MyOAuthClientId;OAuthClientSecret=MyOAuthClientSecret;Username=MyUsername;Password=MyPassword;Instance=MyInstance;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

df = pd.read_sql("SELECT sys_id, priority FROM incident WHERE category = 'request'", cnxn)
app_name = 'dash-servicenowdataplot'

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.sys_id, y=df.priority, name='sys_id')

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='ServiceNow incident Data', barmode='stack')
		})
], className="container")

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