Alternate keys not unique when assigned to a semantic type

[amontanez24]

Environment Details

Please indicate the following details about the environment in which you found the bug:

• SDV version: 1.0.0.dev
• Python version: any
• Operating System: any

Error Description

If a column is marked as an alternate key in the metadata, and also assigned to a semantic type, then the sampled values are not guaranteed to be unique. Alternate keys must always be unique. We should treat them similarly to primary keys.

Steps to reproduce

test_data = pd.DataFrame(data={
    'alternate_key': ['Discover', 'Maestro', 'VISA 19 digit'],
    'numerical_col': [1, 2, 3],
})

test_metadata = SingleTableMetadata()
test_metadata.detect_from_dataframe(test_data)
test_metadata.update_column(
    column_name='alternate_key',
    sdtype='credit_card_provider',
    pii=True
)
test_metadata.add_alternate_keys(column_names=['alternate_key'])
synthesizer = GaussianCopulaSynthesizer(test_metadata)
synthesizer.fit(test_data)
synthesizer.sample(5)