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How to use SQLAlchemy ORM to access Clio Data in Python


Create Python applications and scripts that use SQLAlchemy Object-Relational Mappings of Clio 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 Clio-connected Python applications and scripts. This article shows how to use SQLAlchemy to connect to Clio data to query Clio data.

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

Connecting to Clio Data

Connecting to Clio 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 Clio Profile on disk (e.g. C:\profiles\Clio.apip). Next, set the ProfileSettings connection property to the connection string for Clio (see below).

Clio API Profile Settings

Clio uses OAuth-based authentication.

First, register an OAuth application with Clio. You can do so by logging to your Developer Account and clicking the Add button. Enter details and select the scope of your application here - these details will be shown to Clio users when they're asked to authorize your application. Your Oauth application will be assigned a client id (key) and a client secret (secret). Additionally you will need to set the Region in ProfileSettings connection property.

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

  • AuthScheme: Set this to OAuth.
  • InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to manage the process to obtain the OAuthAccessToken.
  • OAuthClientId: Set this to the client_id that is specified in you app settings.
  • OAuthClientSecret: Set this to the client_secret that is specified in you app settings.
  • CallbackURL: Set this to the Redirect URI that is specified in your app settings.
  • Region: Set this in ProfileSettings to your Clio geographic region. Defaults to app.clio.com.

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

You can now connect with a connection string. Use the create_engine function to create an Engine for working with Clio 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\Clio.apip&ProfileSettings='Region=your_region'&Authscheme=OAuth&OAuthClientId=your_client_id&OAuthClientSecret=your_client_secret&CallbackUrl=your_callback_url")

Declare a Mapping Class for Clio 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 Bills 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 Bills(base): __tablename__ = "Bills" Id = Column(String,primary_key=True) Total = Column(String) ...

Query Clio 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\Clio.apip&ProfileSettings='Region=your_region'&Authscheme=OAuth&OAuthClientId=your_client_id&OAuthClientSecret=your_client_secret&CallbackUrl=your_callback_url") factory = sessionmaker(bind=engine) session = factory() for instance in session.query(Bills).filter_by(State="awaiting_payment"): print("Id: ", instance.Id) print("Total: ", instance.Total) 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

Bills_table = Bills.metadata.tables["Bills"] for instance in session.execute(Bills_table.select().where(Bills_table.c.State == "awaiting_payment")): print("Id: ", instance.Id) print("Total: ", instance.Total) 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 Clio data. Reach out to our Support Team if you have any questions.