Initial groundwork for the rewrite

pandas_schema/column.py

@@ -4,24 +4,51 @@
 from . import validation
 from .validation_warning import ValidationWarning
 
-class Column:
-    def __init__(self, name: str, validations: typing.Iterable['validation._BaseValidation'] = [], allow_empty=False):
-        """
-        Creates a new Column object
 
-        :param name: The column header that defines this column. This must be identical to the header used in the CSV/Data Frame you are validating.
-        :param validations: An iterable of objects implementing _BaseValidation that will generate ValidationErrors
-        :param allow_empty: True if an empty column is considered valid. False if we leave that logic up to the Validation
-        """
-        self.name = name
-        self.validations = list(validations)
-        self.allow_empty = allow_empty
+def _column(
+        validations: typing.Iterable[validation.IndexSeriesValidation],
+        index: typing.Union[int, str] = None,
+        position: bool = False
+):
+    """
+    A utility method for setting the index data on a set of Validations
+    :param validations: A list of validations to modify
+    :param index: The index of the series that these validations will now consider
+    :param position: If true, these validations use positional indexing.
+    See :py:class:`pandas_schema.validation.IndexSeriesValidation`
+    """
+    for valid in validations:
+        valid.index = index
+        valid.position = position
 
-    def validate(self, series: pd.Series) -> typing.List[ValidationWarning]:
-        """
-        Creates a list of validation errors using the Validation objects contained in the Column
 
-        :param series: A pandas Series to validate
-        :return: An iterable of ValidationError instances generated by the validation
-        """
-        return [error for validation in self.validations for error in validation.get_errors(series, self)]
+def label_column(
+        validations: typing.Iterable[validation.IndexSeriesValidation],
+        index: typing.Union[int, str],
+):
+    """
+    A utility method for setting the label-based column for each validation
+    :param validations: A list of validations to modify
+    :param index: The label of the series that these validations will now consider
+    """
+    return _column(
+        validations,
+        index,
+        position=False
+    )
+
+
+def positional_column(
+        validations: typing.Iterable[validation.IndexSeriesValidation],
+        index: int,
+):
+    """
+    A utility method for setting the position-based column for each validation
+    :param validations: A list of validations to modify
+    :param index: The index of the series that these validations will now consider
+    """
+    return _column(
+        validations,
+        index,
+        position=True
+    )

pandas_schema/errors.py

@@ -10,6 +10,12 @@ class PanSchInvalidSchemaError(PanSchError):
     """
 
 
+class PanSchNoIndexError(PanSchInvalidSchemaError):
+    """
+    A validation was provided that has not specified an index
+    """
+
+
 class PanSchArgumentError(PanSchError):
     """
     An argument passed to a function has an invalid type or value

pandas_schema/schema.py

@@ -11,7 +11,7 @@ class Schema:
     A schema that defines the columns required in the target DataFrame
     """
 
-    def __init__(self, columns: typing.Iterable[Column], ordered: bool = False):
+    def __init__(self, columns: typing.Iterable[Column],  ordered: bool = False):
         """
         :param columns: A list of column objects
         :param ordered: True if the Schema should associate its Columns with DataFrame columns by position only, ignoring