Use SQLAlchemy ORMs to Access PayPal Data in Python

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PayPal Python Connector

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



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

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

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

Connecting to PayPal Data

Connecting to PayPal 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 provider surfaces tables from two PayPal APIs. The APIs use different authentication methods.

  • The REST API uses the OAuth standard. To authenticate to the REST API, you will need to set the OAuthClientId, OAuthClientSecret, and CallbackURL properties.
  • The Classic API requires Signature API credentials. To authenticate to the Classic API, you will need to obtain an API username, password, and signature.

See the "Getting Started" chapter of the help documentation for a guide to obtaining the necessary API credentials.

To select the API you want to work with, you can set the Schema property to REST or SOAP. By default the SOAP schema will be used.

For testing purposes you can set UseSandbox to true and use sandbox credentials.

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

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

engine = create_engine("paypal:///?Schema=SOAP&Username=sandbox-facilitator_api1.test.com&Password=xyz123&Signature=zx2127&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Declare a Mapping Class for PayPal 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 Transactions 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 Transactions(base):
	__tablename__ = "Transactions"
	Date = Column(String,primary_key=True)
	GrossAmount = Column(String)
	...

Query PayPal 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("paypal:///?Schema=SOAP&Username=sandbox-facilitator_api1.test.com&Password=xyz123&Signature=zx2127&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(Transactions).filter_by(TransactionClass="Received"):
	print("Date: ", instance.Date)
	print("GrossAmount: ", instance.GrossAmount)
	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

Transactions_table = Transactions.metadata.tables["Transactions"]
for instance in session.execute(Transactions_table.select().where(Transactions_table.c.TransactionClass == "Received")):
	print("Date: ", instance.Date)
	print("GrossAmount: ", instance.GrossAmount)
	print("---------")

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

Free Trial & More Information

Download a free, 30-day trial of the PayPal Python Connector to start building Python apps and scripts with connectivity to PayPal data. Reach out to our Support Team if you have any questions.