blob: 112078b6062337b36ed88cd4ae7a96ef96dc6d2b [file] [log] [blame]
import logging
import sys
from hamilton import base, driver
from hamilton.plugins import h_polars
logging.basicConfig(stream=sys.stdout)
# Create a driver instance.
adapter = base.SimplePythonGraphAdapter(result_builder=h_polars.PolarsDataFrameResult())
config = {
"base_df_location": "dummy_value",
}
import my_functions # where our functions are defined
dr = driver.Driver(config, my_functions, adapter=adapter)
# note -- currently the result builder does not handle mixed outputs, e.g. Series and scalars.
output_columns = [
"spend",
"signups",
"avg_3wk_spend",
"spend_per_signup",
"spend_zero_mean_unit_variance",
]
# let's create the dataframe!
df = dr.execute(output_columns)
print(df)
# To visualize do `pip install "sf-hamilton[visualization]"` if you want these to work
# dr.visualize_execution(output_columns, './polars', {"format": "png"})
# dr.display_all_functions('./my_full_dag.dot')