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

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How to use SQLAlchemy ORM to access Sybase Data in Python


Create Python applications and scripts that use SQLAlchemy Object-Relational Mappings of Sybase data.

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

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

Connecting to Sybase Data

Connecting to Sybase 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 Sybase, specify the following connection properties:

  • Server: Set this to the name or network address of the Sybase database instance.
  • Database: Set this to the name of the Sybase database running on the specified Server.

Optionally, you can also secure your connections with TLS/SSL by setting UseSSL to true.

Sybase supports several methods for authentication including Password and Kerberos.

Connect Using Password Authentication

Set the AuthScheme to Password and set the following connection properties to use Sybase authentication.

  • User: Set this to the username of the authenticating Sybase user.
  • Password: Set this to the username of the authenticating Sybase user.

Connect using LDAP Authentication

To connect with LDAP authentication, you will need to configure Sybase server-side to use the LDAP authentication mechanism.

After configuring Sybase for LDAP, you can connect using the same credentials as Password authentication.

Connect Using Kerberos Authentication

To leverage Kerberos authentication, begin by enabling it setting AuthScheme to Kerberos. See the Using Kerberos section in the Help documentation for more information on using Kerberos authentication.

You can find an example connection string below: Server=MyServer;Port=MyPort;User=SampleUser;Password=SamplePassword;Database=MyDB;Kerberos=true;KerberosKDC=MyKDC;KerberosRealm=MYREALM.COM;KerberosSPN=server-name

Follow the procedure below to install SQLAlchemy and start accessing Sybase 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 Sybase Data in Python

You can now connect with a connection string. Use the create_engine function to create an Engine for working with Sybase 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("sybase:///?User=myuser&Password=mypassword&Server=localhost&Database=mydatabase&Charset=iso_1")

Declare a Mapping Class for Sybase 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 Products 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 Products(base): __tablename__ = "Products" Id = Column(String,primary_key=True) ProductName = Column(String) ...

Query Sybase 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("sybase:///?User=myuser&Password=mypassword&Server=localhost&Database=mydatabase&Charset=iso_1") factory = sessionmaker(bind=engine) session = factory() for instance in session.query(Products).filter_by(ProductName="Konbu"): print("Id: ", instance.Id) print("ProductName: ", instance.ProductName) 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

Products_table = Products.metadata.tables["Products"] for instance in session.execute(Products_table.select().where(Products_table.c.ProductName == "Konbu")): print("Id: ", instance.Id) print("ProductName: ", instance.ProductName) print("---------")

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

Insert Sybase Data

To insert Sybase 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 Sybase.

new_rec = Products(Id="placeholder", ProductName="Konbu") session.add(new_rec) session.commit()

Update Sybase Data

To update Sybase 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 Sybase.

updated_rec = session.query(Products).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first() updated_rec.ProductName = "Konbu" session.commit()

Delete Sybase Data

To delete Sybase 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 records (rows).

deleted_rec = session.query(Products).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 CData Python Connector for Sybase to start building Python apps and scripts with connectivity to Sybase data. Reach out to our Support Team if you have any questions.