| # Hamilton |
| |
|  |
| > Hamilton dataflow materialization plan |
| |
| ## File structure |
| |
| The Hamilton refactor achieves the same data transformations. The project fits in essentially 2 files: |
| - `dataflow.py` contains regular Python functions to define the dataflow (equivalent to Dagster `tutorial/assets.py`). |
| - `run.py` contains the "driver code" to load and execute the dataflow (equivalent to Dagster `tutorial/__init__.py`). |
| - `notebook.ipynb` contains code to execute the dataflow (similar code to `run.py`), but allows for an interactive exploration of results. |
| |
| The directory also include `mock_api.py` which simulates a `ressource` in the Dagster tutorial, and `dataflow.png` which is an artifact generated by the Hamilton `Driver`. |
| |
| ## Instructions |
| 1. Run the code |
| ```console |
| python run.py |
| ``` |
| |
| ## Going further |
| - Learn the basics of Hamilton via the `Concepts/` [documentation section](https://hamilton.dagworks.io/en/latest/concepts/node/) |
| - Visit [tryhamilton.dev](tryhamilton.dev) for an interactive tutorial in your browser |
| - Visit the [DAGWorks blog](https://blog.dagworks.io/) for more detailed guides |
