How to use SQLAlchemy ORM to access Vercel 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 Vercel-connected Python applications and scripts. This article shows how to use SQLAlchemy to connect to Vercel data to query Vercel data.

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

Connecting to Vercel Data

Connecting to Vercel 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.

Using API Key Authentication

Vercel uses Bearer token authentication. You can use either a personal access token or an OAuth access token as the API key.

To obtain a personal access token:

1. Log into your Vercel account at https://vercel.com/
2. Navigate to Account Settings > Tokens.
3. Click Create Token, enter a name and expiration, and click Create.
4. Copy the generated token (it will only be shown once).

After obtaining your token, set the following connection properties:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your Vercel personal access token or OAuth access token.

Example Connection String

Profile=C:\profiles\Vercel.apip;AuthScheme=APIKey;APIKey=your_access_token;

Working with Teams

Many Vercel resources are scoped to a team. To scope all requests to a specific team, set the TeamId connection property to your team's ID. You can find your team ID by querying the Teams table or from the Vercel dashboard. Alternatively, you can specify TeamId in your SQL queries using the WHERE clause where supported.

Connecting to Vercel

Once the authentication is configured, you can connect to Vercel and query data from any of the available tables such as Projects, Deployments, Teams, and Domains.

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

You can now connect with a connection string. Use the create_engine function to create an Engine for working with Vercel 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\Vercel.apip&AuthScheme=APIKey&APIKey=your_access_token")

Declare a Mapping Class for Vercel 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 User 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 User(base):
	__tablename__ = "User"
	 = Column(String,primary_key=True)
	 = Column(String)
	...

Query Vercel 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\Vercel.apip&AuthScheme=APIKey&APIKey=your_access_token")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(User).filter_by(=""):
	print(": ", instance.)
	print(": ", instance.)
	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

User_table = User.metadata.tables["User"]
for instance in session.execute(User_table.select().where(User_table.c. == "")):
	print(": ", instance.)
	print(": ", instance.)
	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 CData API Driver for Python to start building Python apps and scripts with connectivity to Vercel data. Reach out to our Support Team if you have any questions.