How to Visualize HCL Domino Data in Python with pandas

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for HCL Domino, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build HCL Domino-connected Python applications and scripts for visualizing HCL Domino data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to HCL Domino data, execute queries, and visualize the results.

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

Connecting to HCL Domino Data

Connecting to HCL Domino 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.

Connecting to Domino

To connect to Domino data, set the following properties:

• URL: The host name or IP of the server hosting the Domino database. Include the port of the server hosting the Domino database. For example: http://sampleserver:1234/
• DatabaseScope: The name of a scope in the Domino Web UI. The driver exposes forms and views for the schema governed by the specified scope. In the Domino Admin UI, select the Scopes menu in the sidebar. Set this property to the name of an existing scope.

Authenticating with Domino

Domino supports authenticating via login credentials or an Azure Active Directory OAuth application:

Login Credentials

To authenticate with login credentials, set the following properties:

• AuthScheme: Set this to "OAuthPassword"
• User: The username of the authenticating Domino user
• Password: The password associated with the authenticating Domino user

The driver uses the login credentials to automatically perform an OAuth token exchange.

AzureAD

This authentication method uses Azure Active Directory as an IdP to obtain a JWT token. You need to create a custom OAuth application in Azure Active Directory and configure it as an IdP. To do so, follow the instructions in the Help documentation. Then set the following properties:

• AuthScheme: Set this to "AzureAD"
• InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to avoid repeating the OAuth exchange and manually setting the OAuthAccessToken.
• OAuthClientId: The Client ID obtained when setting up the custom OAuth application.
• OAuthClientSecret: The Client secret obtained when setting up the custom OAuth application.
• CallbackURL: The redirect URI defined when you registered your app. For example: https://localhost:33333
• AzureTenant: The Microsoft Online tenant being used to access data. Supply either a value in the form companyname.microsoft.com or the tenant ID.

  The tenant ID is the same as the directory ID shown in the Azure Portal's Azure Active Directory > Properties page.

Follow the procedure below to install the required modules and start accessing HCL Domino through Python objects.

Install Required Modules

Use the pip utility to install the pandas & Matplotlib modules and the SQLAlchemy toolkit:

pip install pandas
pip install matplotlib
pip install sqlalchemy

Be sure to import the module with the following:

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engine

Visualize HCL Domino Data in Python

You can now connect with a connection string. Use the create_engine function to create an Engine for working with HCL Domino data.

engine = create_engine("domino:///?Server=https://domino.corp.com&AuthScheme=OAuthPassword&User=my_domino_user&Password=my_domino_password")

Execute SQL to HCL Domino

Use the read_sql function from pandas to execute any SQL statement and store the resultset in a DataFrame.

df = pandas.read_sql("SELECT Name, Address FROM ByName WHERE City = 'Miami'", engine)

Visualize HCL Domino Data

With the query results stored in a DataFrame, use the plot function to build a chart to display the HCL Domino data. The show method displays the chart in a new window.

df.plot(kind="bar", x="Name", y="Address")
plt.show()

Free Trial & More Information

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

Full Source Code

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin

engine = create_engine("domino:///?Server=https://domino.corp.com&AuthScheme=OAuthPassword&User=my_domino_user&Password=my_domino_password")
df = pandas.read_sql("SELECT Name, Address FROM ByName WHERE City = 'Miami'", engine)

df.plot(kind="bar", x="Name", y="Address")
plt.show()