Use SQLAlchemy ORMs to Access Twitter Ads Data in Python

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Twitter Ads Python Connector

Python Connector Libraries for Twitter Ads Data Connectivity. Integrate Twitter Ads with popular Python tools like Pandas, SQLAlchemy, Dash & petl.



The CData Python Connector for Twitter Ads enables you to create Python applications and scripts that use SQLAlchemy Object-Relational Mappings of Twitter Ads data.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems effectively. With the CData Python Connector for Twitter Ads and the SQLAlchemy toolkit, you can build Twitter Ads-connected Python applications and scripts. This article shows how to use SQLAlchemy to connect to Twitter Ads data to query Twitter Ads data.

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

Connecting to Twitter Ads Data

Connecting to Twitter Ads 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.

All tables require authentication. You must use OAuth to authenticate with Twitter. OAuth requires the authenticating user to interact with Twitter using the browser. For more information, refer to the OAuth section in the Help documentation.

Follow the procedure below to install SQLAlchemy and start accessing Twitter Ads through Python objects.

Install Required Modules

Use the pip utility to install the SQLAlchemy toolkit:

pip install sqlalchemy

Be sure to import the module with the following:

import sqlalchemy

Model Twitter Ads Data in Python

You can now connect with a connection string. Use the create_engine function to create an Engine for working with Twitter Ads data.

engine = create_engine("twitterads:///?InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Declare a Mapping Class for Twitter Ads 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 AdStats 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 AdStats(base):
	__tablename__ = "AdStats"
	EntityId = Column(String,primary_key=True)
	Entity = Column(String)
	...

Query Twitter Ads 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("twitterads:///?InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(AdStats).filter_by(Entity="ORGANIC_TWEET"):
	print("EntityId: ", instance.EntityId)
	print("Entity: ", instance.Entity)
	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

AdStats_table = AdStats.metadata.tables["AdStats"]
for instance in session.execute(AdStats_table.select().where(AdStats_table.c.Entity == "ORGANIC_TWEET")):
	print("EntityId: ", instance.EntityId)
	print("Entity: ", instance.Entity)
	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 Twitter Ads Python Connector to start building Python apps and scripts with connectivity to Twitter Ads data. Reach out to our Support Team if you have any questions.