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Python

Facebook Ads Python Connector

SQL-based access to Facebook Ads from Python

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

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

Features

Compatible with the Facebook Graph and Marketing APIs
Powerful metadata querying enables SQL-like access to non-database sources
Push down query optimization pushes SQL operations down to the server whenever possible, increasing performance
Client-side query execution engine, supports SQL-92 operations that are not available server-side
Connect to live Facebook Ads data, for real-time data access with the Facebook Ads ODBC Driver
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 Facebook Ads Connector.

Specifications

Python Database API (DB-API) Modules for Facebook Ads .
Write SQL, get Facebook Ads data. Access Facebook Ads 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 Facebook Ads

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


Connecting to Facebook Ads with Python

CData Python Connectors leverage the Database API (DB-API) interface to make it easy to work with Facebook Ads 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 Facebook Ads
  • Query Facebook Ads to retrieve or update data
  • Connect your Facebook Ads data with Python data tools.


Connecting to Facebook Ads 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.facebookads as mod
conn = mod.connect("[email protected]; Password=password;")

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

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

df.plot()
plt.show()

Visualize Facebook Ads Data with pandas

The data-centric interfaces of the Facebook Ads 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 Facebook Ads integrations faster with AI that understands your schema

Schema-aware AI

CData CLI gives AI coding tools access to your Facebook Ads 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 Facebook Ads.

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