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

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

Connecting to ScrapingBee Data

Connecting to ScrapingBee 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

ScrapingBee uses API key authentication. To obtain an API key:

1. Sign in to your ScrapingBee account at https://app.scrapingbee.com
2. Navigate to the Dashboard and locate your API key in the top section.
3. Copy the API key for use in the connection string.

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

• AuthScheme: Set this to APIKey.

Set the following in the ProfileSettings connection property:

• APIKey: Set this to your ScrapingBee API key.

Example Connection String

Profile=C:\profiles\ScrapingBee.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your_api_key";

Connecting to ScrapingBee

Once the authentication is configured, you can connect to ScrapingBee and query data from any of the available tables. All tables require at least one input parameter (such as a search query or product ID) to retrieve data.

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

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

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

Query ScrapingBee 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\ScrapingBee.apip&AuthScheme=APIKey&ProfileSettings="APIKey=your_api_key"")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(GoogleSearchResults).filter_by(SearchQuery="cdata drivers"):
	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

GoogleSearchResults_table = GoogleSearchResults.metadata.tables["GoogleSearchResults"]
for instance in session.execute(GoogleSearchResults_table.select().where(GoogleSearchResults_table.c.SearchQuery == "cdata drivers")):
	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 ScrapingBee data. Reach out to our Support Team if you have any questions.