| import logging |
| import sys |
| |
| from hamilton import base, driver |
| from hamilton.plugins import h_polars_lazyframe |
| |
| logging.basicConfig(stream=sys.stdout) |
| |
| # Create a driver instance. If you want to run the compute in the final node you can also use |
| # h_polars.PolarsDataFrameResult() and you don't need to run collect at the end. Which you use |
| # probably depends on whether you want to use the LazyFrame in more nodes in another DAG before |
| # computing the result. |
| adapter = base.SimplePythonGraphAdapter(result_builder=h_polars_lazyframe.PolarsLazyFrameResult()) |
| import my_functions # where our functions are defined |
| |
| dr = driver.Driver({}, my_functions, adapter=adapter) |
| output_columns = [ |
| "spend_per_signup", |
| ] |
| # let's create the lazyframe! |
| df = dr.execute(output_columns) |
| # Here we just print the Lazyframe plan |
| print(df) |
| |
| # Now we run the query |
| df = df.collect() |
| |
| # And print the table. |
| 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') |
