Course prerequisites

This course is geared towards users who want to get the most out of their Dagster code. You don't need to be an expert in Dagster, but you should feel comfortable with the basics.

Intermediate level

  • Dagster familiarity

    You'll need to know the basics of Dagster to complete this course. We recommend completing check out the Dagster Essentials course if you've never used Dagster before or want a refresher before getting started.

  • Python Knowledge

    While you don’t need to be a Python expert to get started, you do need some Python familiarity to complete this course and use Dagster. In Lesson 2, we’ll cover Dagster’s specific installation requirements. Here are some Pythonic concepts used, along with resources to learn about them:

Course curriculum

    1. About this course

    2. Project preview

    3. Testing

    4. Testing data applications

    1. Prerequisites and installation

    2. Set up local

    3. Set up Codespace

    1. Overview

    2. Unit tests

    3. Testing dependencies

    4. Knowledge check

    5. Testing assets with run configurations

    6. Knowledge check

    7. Testing asset output types

    8. Testing assets with execution context

    1. Overview

    2. Testing with mocks

    3. Testing with resources

    4. Knowledge check

    5. Materializing resource tests

    6. Mocking resources for testing

    1. Overview

    2. The limits of mocks

    3. Integration tests

    4. Knowledge check

    5. Integration resources

    6. Configuring integration tests

    7. Integration fixtures

    1. Overview

    2. Asset checks

    3. Definitions

    4. Dagster objects

    5. Knowledge check

    6. Code locations

Skills you'll gain in this course

  • The importance of tests in data applications
  • How to use unit, mock and integrations in tests
  • Best practices for tests in Dagster