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

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

Connecting to CleverPush Data

Connecting to CleverPush 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.

Start by setting the Profile connection property to the location of the Cleverpush Profile on disk (e.g. C:\profiles\Cleverpush.apip). Next, set the ProfileSettings connection property to the connection string for Cleverpush (see below).

Cleverpush API Profile Settings

CleverPush uses private API keys to authenticate requests. Your API key is passed as the Authorization request header value on every API call.

You can find your private API key in the CleverPush dashboard under Settings > API. Use the private key (not the public key) for server-side access.

After setting the following connection properties, you are ready to connect:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your CleverPush private API key.

Optional Connection Properties

• ChannelId: Set this to your default CleverPush channel identifier. Most tables require a channel filter. Setting this property allows queries without specifying ChannelId in every WHERE clause.

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

You can now connect with a connection string. Use the create_engine function to create an Engine for working with CleverPush 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\Cleverpush.apip&ProfileSettings='APIKey=my_api_key'")

Declare a Mapping Class for CleverPush 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 Segments 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 Segments(base):
	__tablename__ = "Segments"
	Id = Column(String,primary_key=True)
	Name = Column(String)
	...

Query CleverPush 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\Cleverpush.apip&ProfileSettings='APIKey=my_api_key'")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(Segments).filter_by(ChannelId="your_channel_id"):
	print("Id: ", instance.Id)
	print("Name: ", instance.Name)
	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

Segments_table = Segments.metadata.tables["Segments"]
for instance in session.execute(Segments_table.select().where(Segments_table.c.ChannelId == "your_channel_id")):
	print("Id: ", instance.Id)
	print("Name: ", instance.Name)
	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 CleverPush data. Reach out to our Support Team if you have any questions.