Collect movie metadata from Letterbox and OpenSubtitles, and generate a full movie summarization with the power of LLMs and LangChain.
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]"
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 dagster_essentials_capstone/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 dagster_essentials_capstone_tests
directory and you can run tests using pytest
:
pytest dagster_essentials_capstone_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.
Using the DuckDB CLI, it is possible to easily explore the contents of the local DuckDB by running the command:
duckdb data/data.duckdb
The easiest way to deploy your Dagster project is to use Dagster Cloud.
Check out the Dagster Cloud Documentation to learn more.