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Python

LinkedIn Ads Python Connector

SQL-based access to LinkedIn Ads from Python

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

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GitHub Copilot
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CData Drivers now work with AI Coding tools

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

Features

SQL access to LinkedIn advertisement analytics
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 LinkedIn Ads data, for real-time data access with the LinkedIn Ads JDBC 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 LinkedIn Ads Connector.

Specifications

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

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


Connecting to LinkedIn Ads with Python

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


Connecting to LinkedIn 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.linkedinads as mod
conn = mod.connect("[email protected]; Password=password;")

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

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

df.plot()
plt.show()

Visualize LinkedIn Ads Data with pandas

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

Schema-aware AI

CData CLI gives AI coding tools access to your LinkedIn 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 LinkedIn 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