How to use SQLAlchemy ORM to access Onfleet 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 Onfleet-connected Python applications and scripts. This article shows how to use SQLAlchemy to connect to Onfleet data to query Onfleet data.
With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Onfleet data in Python. When you issue complex SQL queries from Onfleet, the CData Connector pushes supported SQL operations, like filters and aggregations, directly to Onfleet and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to Onfleet Data
Connecting to Onfleet 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.
Onfleet uses HTTP ApiKey Authentication. Your Onfleet API Key is used to authenticate requests. You can generate or view your API Key in the Onfleet dashboard under Settings > API.
Using ApiKey Authentication
After setting the following connection properties, you are ready to connect:
- AuthScheme: Set this to APIKey.
- APIKey: Set this to your Onfleet API Key.
Example connection string:
Profile=C:\profiles\Onfleet.apip;AuthScheme=APIKey;ProfileSettings="ApiKey=your_api_key";
Follow the procedure below to install SQLAlchemy and start accessing Onfleet 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 Onfleet Data in Python
You can now connect with a connection string. Use the create_engine function to create an Engine for working with Onfleet 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\Onfleet.apip&AuthScheme=APIKey&ProfileSettings="ApiKey=your_api_key"")
Declare a Mapping Class for Onfleet 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 Administrators 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 Administrators(base): __tablename__ = "Administrators" = Column(String,primary_key=True) = Column(String) ...
Query Onfleet 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\Onfleet.apip&AuthScheme=APIKey&ProfileSettings="ApiKey=your_api_key"")
factory = sessionmaker(bind=engine)
session = factory()
for instance in session.query(Administrators).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
Administrators_table = Administrators.metadata.tables["Administrators"]
for instance in session.execute(Administrators_table.select().where(Administrators_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 Onfleet data. Reach out to our Support Team if you have any questions.