Fix constraints evaluating int or float instances

.github/workflows/integration.yml

@@ -29,6 +29,9 @@ jobs:
           python -m pip install --upgrade pip
           python -m pip install invoke .[test]
     - name: Run integration tests
+      env:
+        PYDRIVE_CREDENTIALS: ${{ secrets.PYDRIVE_CREDENTIALS }}
+
       run: |
         invoke integration
         invoke benchmark-dtypes

sdv/_utils.py

@@ -9,6 +9,7 @@
 from pathlib import Path
 
 import pandas as pd
+from pandas.api.types import is_float, is_integer
 from pandas.core.tools.datetimes import _guess_datetime_format_for_array
 from rdt.transformers.utils import _GENERATORS
 
@@ -439,3 +440,11 @@ def get_possible_chars(regex, num_subpatterns=None):
         possible_chars += _get_chars_for_option(option, params)
 
     return possible_chars
+
+
+def _is_numerical(value):
+    """Determine if the input is a numerical type or not."""
+    try:
+        return is_integer(value) or is_float(value)
+    except Exception:
+        return False

sdv/constraints/tabular.py

@@ -36,7 +36,7 @@
 import numpy as np
 import pandas as pd
 
-from sdv._utils import _convert_to_timedelta, _create_unique_name, _is_datetime_type
+from sdv._utils import _convert_to_timedelta, _create_unique_name, _is_datetime_type, _is_numerical
 from sdv.constraints.base import Constraint
 from sdv.constraints.errors import (
     AggregateConstraintsError,
@@ -604,7 +604,7 @@ def _validate_metadata_specific_to_constraint(metadata, **kwargs):
         sdtype = metadata.columns.get(column_name, {}).get('sdtype')
         value = kwargs.get('value')
         if sdtype == 'numerical':
-            if not isinstance(value, (int, float)):
+            if not _is_numerical(value):
                 raise ConstraintMetadataError("'value' must be an int or float.")
 
         elif sdtype == 'datetime':
@@ -632,7 +632,7 @@ def _validate_init_inputs(column_name, value, relation):
         if relation not in ['>', '>=', '<', '<=']:
             raise ValueError('`relation` must be one of the following: `>`, `>=`, `<`, `<=`')
 
-        if not (isinstance(value, (int, float)) or value_is_datetime):
+        if not (_is_numerical(value) or value_is_datetime):
             raise ValueError('`value` must be a number or a string that represents a datetime.')
 
         if value_is_datetime and not isinstance(value, str):
@@ -1071,9 +1071,7 @@ def _validate_init_inputs(low_value, high_value):
         if values_are_datetimes and not values_are_strings:
             raise ValueError('Datetime must be represented as a string.')
 
-        values_are_numerical = bool(
-            isinstance(low_value, (int, float)) and isinstance(high_value, (int, float))
-        )
+        values_are_numerical = bool(_is_numerical(low_value) and _is_numerical(high_value))
         if not (values_are_numerical or values_are_datetimes):
             raise ValueError(
                 '``low_value`` and ``high_value`` must be a number or a string that '
@@ -1092,7 +1090,7 @@ def _validate_metadata_specific_to_constraint(metadata, **kwargs):
         high_value = kwargs.get('high_value')
         low_value = kwargs.get('low_value')
         if sdtype == 'numerical':
-            if not isinstance(high_value, (int, float)) or not isinstance(low_value, (int, float)):
+            if not _is_numerical(high_value) or not _is_numerical(low_value):
                 raise ConstraintMetadataError(
                     "Both 'high_value' and 'low_value' must be ints or floats"
                 )

tests/unit/test__utils.py

@@ -17,6 +17,7 @@
     _get_datetime_format,
     _get_root_tables,
     _is_datetime_type,
+    _is_numerical,
     _validate_foreign_keys_not_null,
     check_sdv_versions_and_warn,
     check_synthesizer_version,
@@ -713,3 +714,33 @@ def test_get_possible_chars():
     nums = [str(i) for i in range(10)]
     lowercase_letters = list(string.ascii_lowercase)
     assert possible_chars == prefix + nums + ['_'] + lowercase_letters
+
+
+def test__is_numerical():
+    """Test that ensures that if passed any numerical data type we will get a ``True``."""
+    # Setup
+    np_int = np.int16(10)
+    np_nan = np.nan
+
+    # Run
+    np_int_result = _is_numerical(np_int)
+    np_nan_result = _is_numerical(np_nan)
+
+    # Assert
+    assert np_int_result
+    assert np_nan_result
+
+
+def test__is_numerical_string():
+    """Test that ensures that if passed any other value but numerical it will return `False`."""
+    # Setup
+    str_value = 'None'
+    datetime_value = pd.to_datetime('2012-01-01')
+
+    # Run
+    str_result = _is_numerical(str_value)
+    datetime_result = _is_numerical(datetime_value)
+
+    # Assert
+    assert str_result is False
+    assert datetime_result is False