How to use SQLAlchemy ORM to access Alchemy Data in Python

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

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

Connecting to Alchemy Data

Connecting to Alchemy 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.

Start by setting the Profile connection property to the location of the Alchemy Profile on disk (e.g. C:\profiles\Alchemy.apip). Next, set the ProfileSettings connection property to the connection string for Alchemy (see below).

Alchemy API Profile Settings

Alchemy uses API key authentication. The API key is supplied in the request URL path. To obtain an API key:

1. Sign in to your Alchemy account at https://dashboard.alchemy.com.
2. Open an existing app or create a new one.
3. Copy the app's API key from the API Key dialog.

After obtaining your API key, set the following connection properties:

• AuthScheme: Set this to APIKey.
• Network: Optional. The blockchain network slug for NFT API requests (for example, eth-mainnet, base-mainnet, polygon-mainnet). Defaults to eth-mainnet.

Set the following in the ProfileSettings connection property:

• APIKey: Set this to your Alchemy app API key.

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

You can now connect with a connection string. Use the create_engine function to create an Engine for working with Alchemy 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("api:///?Profile=C:\profiles\Alchemy.apip&AuthScheme=APIKey&Network=eth-mainnet&ProfileSettings='APIKey=your_api_key'")

Declare a Mapping Class for Alchemy 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 ContractsForOwner 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 ContractsForOwner(base):
	__tablename__ = "ContractsForOwner"
	Address = Column(String,primary_key=True)
	Name = Column(String)
	...

Query Alchemy 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("api:///?Profile=C:\profiles\Alchemy.apip&AuthScheme=APIKey&Network=eth-mainnet&ProfileSettings='APIKey=your_api_key'")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(ContractsForOwner).filter_by(Owner="0xd8dA6BF26964aF9D7eEd9e03E53415D37aA96045"):
	print("Address: ", instance.Address)
	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

ContractsForOwner_table = ContractsForOwner.metadata.tables["ContractsForOwner"]
for instance in session.execute(ContractsForOwner_table.select().where(ContractsForOwner_table.c.Owner == "0xd8dA6BF26964aF9D7eEd9e03E53415D37aA96045")):
	print("Address: ", instance.Address)
	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.

Free Trial & More Information

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