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Python

Google Search Python Connector

SQL-based access to Google Search from Python

Easily connect Python-based data access, visualization, ORM, ETL, AI/ML, and custom apps with Google Search!

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Python Connector Libraries for Google Search Data Connectivity. Integrate Google Search with popular Python tools like Pandas, SQLAlchemy, Dash & petl. Easy-to-use Python Database API (DB-API) Modules connect Google Search data with Python and any Python-based applications.

Features

Connect to live Google Search data, for real-time data access with the Google Search Python Connectors
Full support for data aggregation and complex JOINs in SQL queries
Secure connectivity through modern cryptography, including TLS 1.2, SHA-256, ECC, etc.
Seamless integration with leading BI, reporting, and ETL tools and with custom applications via the Google Search Connector.

Specifications

Python Database API (DB-API) Modules for Google Search.
Write SQL, get Google Search data. Access Google Search through standard Python Database Connectivity.
Integration with popular Python tools like Pandas, SQLAlchemy, Dash & petl.
Full Unicode support for data, parameter, & metadata.

CData Python connectors in action!

Watch the video overview for a first hand-look at the powerful data integration capabilities included in the CData Python Connectors.

Watch the Python Connector Video Overview

Python connectivity with Google Search

Full-featured and consistent SQL access to any supported data source through Python


Connecting to Google Search with Python

CData Python Connectors leverage the Database API (DB-API) interface to make it easy to work with Google Search from a wide range of standard Python data tools. Connecting to and working with your data in Python follows a basic pattern, regardless of data source:

  • Configure the connection properties to Google Search
  • Query Google Search to retrieve or update data
  • Connect your Google Search data with Python data tools.


Connecting to Google Search in Python

To connect to your data from Python, import the extension and create a connection:

Once you import the extension, you can work with all of your enterprise data using the python modules and toolkits that you already know and love, quickly building apps that help you drive business.

import cdata.googlesearch as mod
conn = mod.connect("[email protected]; Password=password;")

#Create cursor and iterate over results
cur = conn.cursor()
cur.execute("SELECT * FROM SearchResults")
	
rs = cur.fetchall()
	
for row in rs:
print(row)
		
engine = create_engine("googlesearch///Password=password&User=user")

df = pandas.read_sql("SELECT * FROM SearchResults", engine)

df.plot()
plt.show()

Visualize Google Search Data with pandas

The data-centric interfaces of the Google Search Python Connector make it easy to integrate with popular tools like pandas and SQLAlchemy to visualize data in real-time.

AI-assisted development with CData CLI

Build Google Search integrations faster with AI that understands your schema

Schema-aware AI

CData CLI gives AI coding tools access to your Google Search schema. No more guessing table names or column types—AI sees the same metadata in your Python Connectors.

Your AI Knows SQL

How to find table names, column names, and how to generate SQL syntax are things that AI knows well from millions of training data. No need for customization, no hallucinations. Your AI acts like a domain specialist to Google Search.

More Accurate, More Token-Efficient

With CData CLI's queryable schema detection and highly efficient queries with filters, aggregation, joins with correct pushdown, your AI will achieve more accuracy with less token usage.

Supported AI Coding Tools
Download CData CLI