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Use SQLAlchemy ORMs to Access EDGAR Online Data in Python

The CData Python Connector for EDGAR Online enables you to create Python applications and scripts that use SQLAlchemy Object-Relational Mappings of EDGAR 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 EDGAR Online and the SQLAlchemy toolkit, you can build EDGAR Online-connected Python applications and scripts. This article shows how to use SQLAlchemy to connect to EDGAR Online data to query, update, delete, and insert EDGAR Online data.

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

Connecting to EDGAR Online Data

Connecting to EDGAR 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.

  1. Navigate to https://developer.edgar-online.com/ and create an account.
  2. Register a new application and retrieve the AppKey. You should select one of the available Web APIs this application will use like HackPack, Insider Trades or Institutional Ownership.
    Note: HackPack is the most important Web API that an application can use since it supports a large number of endpoints. If you are getting the "Access Denied" error you must create a new app and select the correct Web API which supports the resource you are querying.
  3. After successfully creating a new app, you can access your keys through your "my account" area. Set the AppKey connection property value equal to the Key of your application.

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

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

engine = create_engine("edgaronline///?AppKey=20dd8ce9904d422ed89ebde1ad40d")

Declare a Mapping Class for EDGAR 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 Subscriptions 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 Subscriptions(base):
	__tablename__ = "Subscriptions"
	Id = Column(String,primary_key=True)
	Name = Column(String)
	...

Query EDGAR 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("edgaronline///?AppKey=20dd8ce9904d422ed89ebde1ad40d")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(Subscriptions).filter_by(SubscriberEmail="user@domain.com"):
	print("Id: ", instance.Id)
	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

Subscriptions_table = Subscriptions.metadata.tables["Subscriptions"]
for instance in session.execute(Subscriptions_table.select().where(Subscriptions_table.c.SubscriberEmail == "user@domain.com")):
	print("Id: ", instance.Id)
	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 EDGAR Online Data

To insert EDGAR 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 EDGAR Online.

new_rec = Subscriptions(Id="placeholder", SubscriberEmail="user@domain.com")
session.add(new_rec)
session.commit()

Update EDGAR Online Data

To update EDGAR 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 EDGAR Online.

updated_rec = session.query(Subscriptions).filter_by(SOME_ID_COLUMN="SOME_ID_VALUE").first()
updated_rec.SubscriberEmail = "user@domain.com"
session.commit()

Delete EDGAR Online Data

To delete EDGAR 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 recoreds (rows).

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