Use SQLAlchemy ORMs to Access HCL Domino Data in Python

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

The CData Python Connector for HCL Domino enables you to create Python applications and scripts that use SQLAlchemy Object-Relational Mappings of HCL Domino data.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems effectively. With the CData Python Connector for HCL Domino and the SQLAlchemy toolkit, you can build HCL Domino-connected Python applications and scripts. This article shows how to use SQLAlchemy to connect to HCL Domino data to query HCL Domino data.

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 CData Connector 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.


The connector requires the Proton component to be installed. Normally, Proton is distributed as part of the AppDev pack. See the HCL documentation for instructions on acquiring and installing Proton or the AppDev pack.

Once the Proton service is installed and running, you will also need to create a user account and download its Internet certificate. This certificate can be used to set the connector certificate connection properties.

Authenticating to Domino

  • Server: The name or IP address of the server running Domino with the Proton service.
  • Port: The port number that the Proton service is listening on.
  • Database: The name of the database file, including the .nsf extension.
  • SSLClientCertType: This must match the format of the certificate file. Typically this will be either PEMKEY_FILE for .pem certificates or PFXFILE for .pfx certificates.
  • SSLClientCert: The path to the certificate file.
  • SSLServerCert: This can be set to (*) if you trust the server. This is usually the case, but if you want to perform SSL validation, you may provide a certificate or thumbprint instead. See the documentation for SSLServerCert for details.

Additional Server Configuration

The connector supports querying Domino views if any are defined. Before views can be queried by the connector they must be registered with the design catalog.

Please refer to the Catalog Administration section of the AppDev pack documentation for details on how to do this.

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

Install Required Modules

Use the pip utility to install the SQLAlchemy toolkit and SQLAlchemy ORM package:

pip install sqlalchemy pip install sqlalchemy.orm

Be sure to import the appropriate modules:

from sqlalchemy import create_engine, String, Column from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.orm import sessionmaker

Model 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.

NOTE: Users should URL encode the any connection string properties that include special characters. For more information, refer to the SQL Alchemy documentation.

engine = create_engine("domino:///?Server=*")

Declare a Mapping Class for HCL Domino Data

After establishing the connection, declare a mapping class for the table you wish to model in the ORM (in this article, we will model the ByName table). Use the sqlalchemy.ext.declarative.declarative_base function and create a new class with some or all of the fields (columns) defined.

base = declarative_base() class ByName(base): __tablename__ = "ByName" Name = Column(String,primary_key=True) Address = Column(String) ...

Query HCL Domino Data

With the mapping class prepared, you can use a session object to query the data source. After binding the Engine to the session, provide the mapping class to the session query method.

Using the query Method

engine = create_engine("domino:///?Server=*") factory = sessionmaker(bind=engine) session = factory() for instance in session.query(ByName).filter_by(City="Miami"): print("Name: ", instance.Name) print("Address: ", instance.Address) print("---------")

Alternatively, you can use the execute method with the appropriate table object. The code below works with an active session.

Using the execute Method

ByName_table = ByName.metadata.tables["ByName"] for instance in session.execute( == "Miami")): print("Name: ", instance.Name) print("Address: ", instance.Address) print("---------")

For examples of more complex querying, including JOINs, aggregations, limits, and more, refer to the Help documentation for the extension.

Free Trial & More Information

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