Use Dash to Build to Web Apps on Active Directory Data

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

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

Connecting to Active Directory Data

Connecting to Active Directory 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.

To establish a connection, set the following properties:

• Valid User and Password credentials (e.g., Domain\BobF or cn=Bob F,ou=Employees,dc=Domain).
• Server information, including the IP or host name of the Server, as well as the Port.

• BaseDN: This will limit the scope of LDAP searches to the height of the distinguished name provided.

  Note: Specifying a narrow BaseDN may greatly increase performance; for example, cn=users,dc=domain will only return results contained within cn=users and its children.

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

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

cnxn = mod.connect("User=cn=Bob F,ou=Employees,dc=Domain;Password=bob123;Server=10.0.1.2;Port=389;")

Execute SQL to Active Directory

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 Id, LogonCount FROM User WHERE CN = 'Administrator'", 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-activedirectoryedataplot'

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 Active Directory data and configure the app layout.

trace = go.Bar(x=df.Id, y=df.LogonCount, name='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='Active Directory User 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 Active Directory data.

python activedirectory-dash.py

👁 Active Directory data in a Dash web app (Salesforce is shown).

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Active Directory to start building Python apps with connectivity to Active Directory data. Reach out to our Support Team if you have any questions.

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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.activedirectory as mod
import plotly.graph_objs as go

cnxn = mod.connect("User=cn=Bob F,ou=Employees,dc=Domain;Password=bob123;Server=10.0.1.2;Port=389;")

df = pd.read_sql("SELECT Id, LogonCount FROM User WHERE CN = 'Administrator'", cnxn)
app_name = 'dash-activedirectorydataplot'

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.Id, y=df.LogonCount, name='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='Active Directory User Data', barmode='stack')
		})
], className="container")

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