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How to use SQLAlchemy ORM to access Aha Data in Python


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

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

Connecting to Aha Data

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

Aha! API Profile Settings

The Aha! API uses OAuth-based authentication.

You will first need to register an OAuth app with Aha!. This can be done from your Aha! account under 'Settings' > 'Personal' > 'Developer' > 'OAuth Applications'. Additionally, you will need to set the Domain, found in the domain name of your Aha account. For example if your Aha account is acmeinc.aha.io, then the Domain should be 'acmeinc'.

After setting the following in the connection string, 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 you specified in your app settings.
  • Domain: Set this in the ProfileSettings to your Aha domain.

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

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

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

Query Aha 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\aha.apip&ProfileSettings='Domain=acmeinc'&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(Ideas).filter_by(AssignedToUserId="my_user_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

Ideas_table = Ideas.metadata.tables["Ideas"] for instance in session.execute(Ideas_table.select().where(Ideas_table.c.AssignedToUserId == "my_user_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 Aha data. Reach out to our Support Team if you have any questions.