How to use SQLAlchemy ORM to access Pushbullet Data in Python

Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Create Python applications and scripts that use SQLAlchemy Object-Relational Mappings of Pushbullet data.

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 Pushbullet-connected Python applications and scripts. This article shows how to use SQLAlchemy to connect to Pushbullet data to query Pushbullet data.

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

Connecting to Pushbullet Data

Connecting to Pushbullet 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.

Using API Key Authentication

Pushbullet uses token-based authentication (Access Token). To obtain an Access Token:

  1. Log in to your Pushbullet account at https://www.pushbullet.com
  2. Navigate to Settings > Account
  3. Click "Create Access Token"
  4. Copy the generated token

After obtaining your Access Token, set the following connection properties:

  • AuthScheme: Set this to APIKey.
Set the following in the ProfileSettings connection property:
  • APIKey: Set this to your Pushbullet Access Token.

Example Connection String

Profile=C:\profiles\Pushbullet.apip;ProfileSettings='APIKey=your_access_token;';AuthScheme=APIKey;

Connecting to Pushbullet

Once the authentication is configured, you can connect to Pushbullet and query data from any of the available tables such as Users, Pushes, Devices, Chats, Subscriptions, and Channels.

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

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

Declare a Mapping Class for Pushbullet 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 Users 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 Users(base):
	__tablename__ = "Users"
	 = Column(String,primary_key=True)
	 = Column(String)
	...

Query Pushbullet 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\Pushbullet.apip&ProfileSettings='APIKey=your_access_token&'&AuthScheme=APIKey")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(Users).filter_by(=""):
	print(": ", instance.)
	print(": ", instance.)
	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

Users_table = Users.metadata.tables["Users"]
for instance in session.execute(Users_table.select().where(Users_table.c. == "")):
	print(": ", instance.)
	print(": ", instance.)
	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 Pushbullet data. Reach out to our Support Team if you have any questions.

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