In this example we show you how to create a simple hello world dataflow that creates a dataframe as a result. It performs a series of transforms on the input to create columns that appear in the output.
File organization:
my_functions.py houses the logic that we want to compute. Note how the functions are named, and what input parameters they require. That is how we create a DAG modeling the dataflow we want to happen.my_script.py houses how to get Hamilton to create the DAG and exercise it with some inputs.my_notebook.ipynb houses how one might iterate in a notebook environment and provide a way to inline define Hamilton functions and add them to the DAG constructed. To be clear, it is not used by my_script.py, but showing an alternate path to running/developing things.To run things:
> python my_script.py
If you have questions, or need help with this example, join us on slack, and we'll try to help!
Here is the graph of execution - pretty simple, right?
