Use SQLAlchemy ORMs to Access Zoho CRM Data in Python

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Zoho CRM Python Connector

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

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

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

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

Connecting to Zoho CRM Data

Connecting to Zoho CRM 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 is already registered with Zoho CRM as an OAuth application. As such, OAuth Credentials are embedded by default. If you would prefer to use your own custom OAuth app, see the Custom Credentials section in the Help documentation.

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

You can now connect with a connection string. Use the create_engine function to create an Engine for working with Zoho CRM 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("zohocrm:///?InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Declare a Mapping Class for Zoho CRM 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 Accounts 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 Accounts(base): __tablename__ = "Accounts" Account_Name = Column(String,primary_key=True) Annual_Revenue = Column(String) ...

Query Zoho CRM 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("zohocrm:///?InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt") factory = sessionmaker(bind=engine) session = factory() for instance in session.query(Accounts).filter_by(Industry="Data/Telecom OEM"): print("Account_Name: ", instance.Account_Name) print("Annual_Revenue: ", instance.Annual_Revenue) 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

Accounts_table = Accounts.metadata.tables["Accounts"] for instance in session.execute( == "Data/Telecom OEM")): print("Account_Name: ", instance.Account_Name) print("Annual_Revenue: ", instance.Annual_Revenue) print("---------")

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

Insert Zoho CRM Data

To insert Zoho CRM 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 Zoho CRM.

new_rec = Accounts(Account_Name="placeholder", Industry="Data/Telecom OEM") session.add(new_rec) session.commit()

Update Zoho CRM Data

To update Zoho CRM 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 Zoho CRM.

updated_rec = session.query(Accounts).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first() updated_rec.Industry = "Data/Telecom OEM" session.commit()

Delete Zoho CRM Data

To delete Zoho CRM 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(Accounts).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 Zoho CRM Python Connector to start building Python apps and scripts with connectivity to Zoho CRM data. Reach out to our Support Team if you have any questions.