This is a sample project built on Dagster and scaffolded with dagster project scaffold
.
It demonstrates how to create a Dagster workflow that sends user emails with user-specific chart assets.
First, install your Dagster code location as a Python package. By using the --editable flag, pip will install your Python package in "editable mode" so that as you develop, local code changes will automatically apply.
pip install -e ".[dev]"
Create the test database and install the sample data
python database.py
python sample_data.py
Then, start the Dagster UI web server:
dagster dev
Open http://localhost:3000 with your browser to see the project.
You can start writing assets in user_report/assets.py
. The assets are automatically loaded into the Dagster code location as you define them.
You can specify new Python dependencies in setup.py
.
Tests are in the user_report_tests
directory and you can run tests using pytest
:
pytest user_report_tests
If you want to enable Dagster Schedules or Sensors for your jobs, the Dagster Daemon process must be running. This is done automatically when you run dagster dev
.
Once your Dagster Daemon is running, you can start turning on schedules and sensors for your jobs.
The easiest way to deploy your Dagster project is to use Dagster Cloud.
Check out the Dagster Cloud Documentation to learn more.