Ready to get started?

Learn more about the CData Python Connector for Oracle or download a free trial:

Download Now

Use SQLAlchemy ORMs to Access Oracle Data in Python

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

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

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

Connecting to Oracle Data

Connecting to Oracle 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 connect to Oracle, you'll first need to update your PATH variable and ensure it contains a folder location that includes the native DLLs. The native DLLs can be found in the lib folder inside the installation directory. Once you've done this, set the following to connect:

  • Port: The port used to connect to the server hosting the Oracle database.
  • User: The user Id provided for authentication with the Oracle database.
  • Password: The password provided for authentication with the Oracle database.
  • Service Name: The service name of the Oracle database.

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

Install Required Modules

Use the pip utility to install the SQLAlchemy toolkit:

pip install sqlalchemy

Be sure to import the module with the following:

import sqlalchemy

Model Oracle Data in Python

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

engine = create_engine("oracleoci///?User=myuser&Password=mypassword&Server=localhost&Port=1521")

Declare a Mapping Class for Oracle 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 Customers 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 Customers(base):
	__tablename__ = "Customers"
	CompanyName = Column(String,primary_key=True)
	City = Column(String)
	...

Query Oracle 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("oracleoci///?User=myuser&Password=mypassword&Server=localhost&Port=1521")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(Customers).filter_by(Country="US"):
	print("CompanyName: ", instance.CompanyName)
	print("City: ", instance.City)
	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

Customers_table = Customers.metadata.tables["Customers"]
for instance in session.execute(Customers_table.select().where(Customers_table.c.Country == "US")):
	print("CompanyName: ", instance.CompanyName)
	print("City: ", instance.City)
	print("---------")

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

Insert Oracle Data

To insert Oracle data, define an instance of the mapped class and add it to the active session. Call the commit function on the session to push all added instances to Oracle.

new_rec = Customers(CompanyName="placeholder", Country="US")
session.add(new_rec)
session.commit()

Update Oracle Data

To update Oracle data, fetch the desired record(s) with a filter query. Then, modify the values of the fields and call the commit function on the session to push the modified record to Oracle.

updated_rec = session.query(Customers).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first()
updated_rec.Country = "US"
session.commit()

Delete Oracle Data

To delete Oracle data, fetch the desired record(s) with a filter query. Then delete the record with the active session and call the commit function on the session to perform the delete operation on the provided recoreds (rows).

deleted_rec = session.query(Customers).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first()
session.delete(deleted_rec)
session.commit()

Free Trial & More Information

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