Ready to get started?

Connect to live data from ClickUp with the API Driver

Connect to ClickUp

How to use SQLAlchemy ORM to access ClickUp Data in Python



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

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

Connecting to ClickUp Data

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

ClickUp API Profile Settings

In order to authenticate to ClickUp, you'll need to provide your API Key. You can find this token in your user settings, under the Apps section. At the top of the page you have the option to generate a personal token. Set the API Key to your personal token in the ProfileSettings property to connect.

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

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

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

Query ClickUp 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\ClickUp.apip&ProfileSettings='APIKey=my_personal_token'") factory = sessionmaker(bind=engine) session = factory() for instance in session.query(Tasks).filter_by(Priority="High"): 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

Tasks_table = Tasks.metadata.tables["Tasks"] for instance in session.execute(Tasks_table.select().where(Tasks_table.c.Priority == "High")): 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 ClickUp data. Reach out to our Support Team if you have any questions.