Testing schemas
The team fixed the values in their expected DataFrame, but Polars inferred total_checkouts as 64-bit while the pipeline produces 32-bit. The two schemas are printed for you so you can see the mismatch. Fix the expected dtype, then assert the schemas match.
actual, expected, and assert_schema_equal are preloaded.
Questo esercizio fa parte del corso
Scaling and Optimizing Data Pipelines with Polars
Istruzioni dell'esercizio
- Cast
total_checkoutsinexpectedtopl.Int32. - Assert that the schemas of
actualandexpectedare equal.
esercizio interattivo pratico
Prova questo esercizio completando questo codice di esempio.
# Match the dtype the pipeline produces
expected = expected.with_columns(
pl.col("total_checkouts").cast(pl.____)
)
# Schema-level assertion
____(actual.schema, expected.schema)
print("Schema assertion passed.")
print(actual.schema)