Fixed issue with slicing function and transformation function instances being shared

[kevinmessiaen]

Description

Following code wasn't working as expected:

@slicing_function(name="slice cell level", cell_level=True)
def filter_cell_level_by(amount: int, min_value: int) -> bool:
    return amount >= min_value

df = pd.DataFrame({"quantity": [1, 2, 3, 5, 7, 11, 13]})
dataset = Dataset(df, cat_columns=[])

min_five = filter_cell_level_by(min_value=5)
min_six = filter_cell_level_by(min_value=6)

dataset_greater_equals_five = dataset.slice(min_five, column_name="quantity")
dataset_greater_equals_six = dataset.slice(min_six, column_name="quantity")

assert list(dataset_greater_equals_five.df["quantity"]) == [5, 7, 11, 13]
assert list(dataset_greater_equals_six.df["quantity"]) == [7, 11, 13]

Expected behaviour

• dataset_greater_equals_five contains values where quantity >= 5
• dataset_greater_equals_six contains values where quantity >= 6

Actual behaviour

dataset_greater_equals_five and dataset_greater_equals_six both contain values where quantity >= 6

This behaviour happens due to the @slicing_function decorator generating a "singleton' of SlicingFunction. Same issue is seen with the transformation functions.

Type of Change

• 📚 Examples / docs / tutorials / dependencies update
• 🔧 Bug fix (non-breaking change which fixes an issue)
• 🥂 Improvement (non-breaking change which improves an existing feature)
• 🚀 New feature (non-breaking change which adds functionality)
• 💥 Breaking change (fix or feature that would cause existing functionality to change)
• 🔐 Security fix

[sonarqubecloud]

Quality Gate failed

Failed conditions
24.0% Duplication on New Code (required ≤ 3%)

See analysis details on SonarCloud