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Get the Report →How to use SQLAlchemy ORM to access Certinia Data in Python
Create Python applications and scripts that use SQLAlchemy Object-Relational Mappings of Certinia data.
The rich ecosystem of Python modules lets you get to work quickly and integrate your systems effectively. With the CData Python Connector for Certinia and the SQLAlchemy toolkit, you can build Certinia-connected Python applications and scripts. This article shows how to use SQLAlchemy to connect to Certinia data to query, update, delete, and insert Certinia data.
With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Certinia data in Python. When you issue complex SQL queries from Certinia, the CData Connector pushes supported SQL operations, like filters and aggregations, directly to Certinia and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to Certinia Data
Connecting to Certinia 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.
There are several authentication methods available for connecting to Certinia: login credentials, SSO, and OAuth.
Authenticating with a Login and Token
Set the User and Password to your login credentials. Additionally, set the SecurityToken. By default, the SecurityToken is required, but you can make it optional by allowing a range of trusted IP addresses.
To disable the security token:
- Log in to Certinia and enter "Network Access" in the Quick Find box in the setup section.
- Add your IP address to the list of trusted IP addresses.
To obtain the security token:
- Open the personal information page on certinia.com.
- Click the link to reset your security token. The token will be emailed to you.
- Specify the security token in the SecurityToken connection property or append it to the Password.
Authenticating with OAuth
If you do not have access to the user name and password or do not want to require them, use the OAuth user consent flow. See the OAuth section in the Help for an authentication guide.
Connecting to Certinia Sandbox Accounts
Set UseSandbox to true (false by default) to use a Certinia sandbox account. Ensure that you specify a sandbox user name in User.
Follow the procedure below to install SQLAlchemy and start accessing Certinia 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 Certinia Data in Python
You can now connect with a connection string. Use the create_engine function to create an Engine for working with Certinia 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("certinia:///?User=myUser&Password=myPassword&Security Token=myToken&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
Declare a Mapping Class for Certinia 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 Account 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 Account(base):
__tablename__ = "Account"
BillingState = Column(String,primary_key=True)
Name = Column(String)
...
Query Certinia 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("certinia:///?User=myUser&Password=myPassword&Security Token=myToken&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(Account).filter_by(Industry="Floppy Disks"):
print("BillingState: ", instance.BillingState)
print("Name: ", instance.Name)
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
Account_table = Account.metadata.tables["Account"]
for instance in session.execute(Account_table.select().where(Account_table.c.Industry == "Floppy Disks")):
print("BillingState: ", instance.BillingState)
print("Name: ", instance.Name)
print("---------")
For examples of more complex querying, including JOINs, aggregations, limits, and more, refer to the Help documentation for the extension.
Insert Certinia Data
To insert Certinia 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 Certinia.
new_rec = Account(BillingState="placeholder", Industry="Floppy Disks")
session.add(new_rec)
session.commit()
Update Certinia Data
To update Certinia 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 Certinia.
updated_rec = session.query(Account).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first()
updated_rec.Industry = "Floppy Disks"
session.commit()
Delete Certinia Data
To delete Certinia 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(Account).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 Certinia to start building Python apps and scripts with connectivity to Certinia data. Reach out to our Support Team if you have any questions.