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

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How to use SQLAlchemy ORM to access Exact Online Data in Python


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

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

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

Connecting to Exact Online Data

Connecting to Exact Online 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.

Exact Online uses the OAuth authentication standard. You can use the embedded OAuth credentials or you can register an OAuth app with Exact to obtain your own. In addition to the OAuth values, provide the Region. If Division is not set, the default Division is determined.

See the "Getting Started" chapter of the help documentation for more information.

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

You can now connect with a connection string. Use the create_engine function to create an Engine for working with Exact Online 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("exactonline:///?Region='United States'&Division=5512&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Declare a Mapping Class for Exact Online 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" Name = Column(String,primary_key=True) CreditLinePurchase = Column(String) ...

Query Exact Online 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("exactonline:///?Region='United States'&Division=5512&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt") factory = sessionmaker(bind=engine) session = factory() for instance in session.query(Accounts).filter_by(IsCompetitor="False"): print("Name: ", instance.Name) print("CreditLinePurchase: ", instance.CreditLinePurchase) 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(Accounts_table.select().where(Accounts_table.c.IsCompetitor == "False")): print("Name: ", instance.Name) print("CreditLinePurchase: ", instance.CreditLinePurchase) print("---------")

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

Insert Exact Online Data

To insert Exact Online 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 Exact Online.

new_rec = Accounts(Name="placeholder", IsCompetitor="False") session.add(new_rec) session.commit()

Update Exact Online Data

To update Exact Online 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 Exact Online.

updated_rec = session.query(Accounts).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first() updated_rec.IsCompetitor = "False" session.commit()

Delete Exact Online Data

To delete Exact Online 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 CData Python Connector for Exact Online to start building Python apps and scripts with connectivity to Exact Online data. Reach out to our Support Team if you have any questions.