examples/polars/my_script.py

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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 "apache-hamilton[visualization]"` if you want these to work
# dr.visualize_execution(output_columns, './polars', {"format": "png"})
# dr.display_all_functions('./my_full_dag.dot')