Skip to content

base

A Meta-class for defining Schemas that can be created like dataclasses and used to validate tables.

Schema

Bases: Generic[RawDataType_T, RawSchema_T, RawTable_T]

Source code in flexible_schema/base.py 
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
class Schema(Generic[RawDataType_T, RawSchema_T, RawTable_T], metaclass=SchemaMeta):
    allow_extra_columns: ClassVar[bool] = True

    # The Schema class should behave like a dictionary:

    def __getitem__(self, key: str):
        return getattr(self, key)

    def __setitem__(self, key: str, value: Any):
        if hasattr(self, key) or self.allow_extra_columns:
            setattr(self, key, value)
        else:
            raise SchemaValidationError(f"Extra field not allowed: {key!r}")

    def keys(self):
        return self.to_dict().keys()

    def values(self):
        return self.to_dict().values()

    def items(self):
        return self.to_dict().items()

    def __iter__(self):
        return iter(self.keys())

    # The Schema class should be convertible to and from a dictionary:

    def to_dict(self):
        return {k: v for k, v in self.__dict__.items() if v is not None}

    @classmethod
    def from_dict(cls: type[S], data: dict) -> S:
        return cls(**data)

    # The schema should support type resolution and optional vs. required type determination:

    @classmethod
    def _columns(cls: type[S]) -> list[Column]:
        return [f.metadata["column"] for f in fields(cls)]

    @classmethod
    def _columns_map(cls: type[S]) -> dict[str, Column]:
        return {c.name: c for c in cls._columns()}

    @classmethod
    def optional_columns(cls: type[S]) -> list[str]:
        """Return a list of optional columns."""
        return [c.name for c in cls._columns() if c.is_optional]

    @classmethod
    def required_columns(cls: type[S]) -> list[str]:
        """Return a list of required columns."""
        return [c.name for c in cls._columns() if c.is_required]

    @classmethod
    def columns(cls: type[S]) -> list[str]:
        """Return a list of all columns, starting with required columns."""
        return cls.required_columns() + cls.optional_columns()

    @classmethod
    def column_type(cls: type[S], col: str) -> ColumnDType:
        """Return the type of a column."""
        return cls._columns_map()[col].dtype

    @classmethod
    @abstractmethod
    def map_type(cls: type[S], field_type: ColumnDType) -> RawDataType_T:
        raise NotImplementedError(f"_map_type_internal is not supported by {cls.__name__} objects.")

    # The schema should provide a way to produce an approximate "source schema"

    @classmethod
    @abstractmethod
    def schema(cls: type[S]) -> RawSchema_T:
        raise NotImplementedError(f"schema is not supported by {cls.__name__} objects.")

    # The schema should provide a way to validate or align tables:

    @classmethod
    @abstractmethod
    def _raw_schema_col_type(cls: type[S], schema: RawSchema_T, col: str) -> ColumnDType:
        """Get the type of a column in the schema."""
        raise NotImplementedError(f"__raw_schema_col_type is not supported by {cls.__name__} objects.")

    @classmethod
    @abstractmethod
    def _raw_schema_cols(cls: type[S], schema: RawSchema_T) -> list[str]:
        """Get all columns in the schema."""
        raise NotImplementedError(f"__raw_schema_cols is not supported by {cls.__name__} objects.")

    @classmethod
    def _disallowed_extra_cols(cls: type[S], schema: RawSchema_T) -> list[str]:
        """Get a list of extra columns that are not allowed in the schema."""
        if cls.allow_extra_columns:
            return []
        return [col for col in cls._raw_schema_cols(schema) if col not in set(cls.columns())]

    @classmethod
    def _missing_req_cols(cls: type[S], schema: RawSchema_T) -> list[str]:
        """Get a list of required columns that are missing in the schema."""
        return [col for col in cls.required_columns() if col not in set(cls._raw_schema_cols(schema))]

    @classmethod
    def _mistyped_cols(cls: type[S], schema: RawSchema_T) -> list[tuple[str, ColumnDType, ColumnDType]]:
        """Get a list of columns that have incorrect types in the schema."""
        raw_cols = set(cls._raw_schema_cols(schema))
        return [
            (col, cls.column_type(col), cls._raw_schema_col_type(schema, col))
            for col in cls.columns()
            if col in raw_cols and cls.column_type(col) != cls._raw_schema_col_type(schema, col)
        ]

    @classmethod
    def _validate_schema(cls: type[S], schema: RawSchema_T):
        """Validate the schema against the class schema and raise an error if invalid.

        Args:
            schema: The schema to validate.

        Raises:
            SchemaValidationError: If the schema is invalid.
        """

        disallowed_extra_cols = cls._disallowed_extra_cols(schema)
        missing_req_cols = cls._missing_req_cols(schema)
        mistyped_cols = cls._mistyped_cols(schema)

        if disallowed_extra_cols or missing_req_cols or mistyped_cols:
            raise SchemaValidationError(
                disallowed_extra_cols=disallowed_extra_cols,
                missing_req_cols=missing_req_cols,
                mistyped_cols=mistyped_cols,
            )

    @classmethod
    @abstractmethod
    def _raw_table_schema(cls: type[S], table: RawTable_T) -> RawSchema_T:
        """Get the schema of a table."""
        raise NotImplementedError(f"__raw_table_schema is not supported by {cls.__name__} objects.")

    @classmethod
    @abstractmethod
    def _any_null(cls: type[S], table: RawTable_T, col: str) -> bool:
        """Check if any values in the column are null."""
        raise NotImplementedError(f"_any_null is not supported by {cls.__name__} objects.")

    @classmethod
    @abstractmethod
    def _all_null(cls: type[S], table: RawTable_T, col: str) -> bool:
        """Check if all values in the column are null."""
        raise NotImplementedError(f"_all_null is not supported by {cls.__name__} objects.")

    @classmethod
    def _validate_table(cls: type[S], table: RawTable_T):
        """Validate the table against the schema."""
        cls._validate_schema(cls._raw_table_schema(table))

        nullability_none_err_cols = []
        nullability_some_err_cols = []
        for col in cls.columns():
            if col not in cls._raw_table_cols(table):
                continue

            match cls._columns_map()[col].nullable:
                case Nullability.NONE if cls._any_null(table, col):
                    nullability_none_err_cols.append(col)
                case Nullability.SOME if cls._all_null(table, col):
                    nullability_some_err_cols.append(col)
                case Nullability.ALL:
                    continue

        if nullability_none_err_cols or nullability_some_err_cols:
            raise TableValidationError(
                nullability_none_err_cols=nullability_none_err_cols,
                nullability_some_err_cols=nullability_some_err_cols,
            )

    @classmethod
    def _is_raw_schema(cls, arg: Any) -> bool:
        """Check if the argument is a raw schema (e.g., of type `RawSchema_T`).

        This is a "best-guess" approach for checking in the base class.

        Args:
            arg: The argument to check.

        Returns:
            True if the argument is a schema, False otherwise.
        """

        return isinstance(arg, type(cls.schema()))

    @classmethod
    @abstractmethod
    def _is_raw_table(cls, arg: Any) -> bool:
        """Check if the argument is a raw table (e.g., of type `RawTable_T`).

        Args:
            arg: The argument to check.

        Returns:
            True if the argument is a table, False otherwise.
        """
        raise NotImplementedError(f"_is_raw_table is not supported by {cls.__name__} objects.")

    @classmethod
    def validate(cls: type[S], arg: RawTable_T | RawSchema_T):
        """Validate the argument against the schema.

        Args:
            arg: The argument to validate. This can be a table or a schema.

        Returns:
            `True` if the argument is valid.

        Raises:
            SchemaValidationError: If the argument is a schema and invalid.
            TableValidationError: If the argument is a table and invalid.
            TypeError: If the argument is neither a schema nor a table.
        """
        if cls._is_raw_schema(arg):
            try:
                cls._validate_schema(arg)
            except SchemaValidationError as e:
                raise e
            except Exception as e:
                raise SchemaValidationError("Schema validation failed") from e
        elif cls._is_raw_table(arg):
            try:
                cls._validate_table(arg)
            except (TableValidationError, SchemaValidationError) as e:
                raise e
            except Exception as e:
                raise TableValidationError("Table validation failed") from e
        else:
            raise TypeError(f"Expected a schema or table, but got: {type(arg).__name__}")

    @classmethod
    def _raw_table_cols(cls: type[S], table: RawTable_T) -> list[str]:
        """Get all columns in the table."""
        return cls._raw_schema_cols(cls._raw_table_schema(table))

    @classmethod
    @abstractmethod
    def _reorder_raw_table(cls: type[S], table: RawTable_T, table_order: list[str]) -> RawTable_T:
        raise NotImplementedError(f"_reorder_raw_table is not supported by {cls.__name__} objects.")

    @classmethod
    def _align_col_order(cls: type[S], table: RawTable_T) -> RawTable_T:
        """Re-order the columns of the table to match the schema."""
        table_cols = cls._raw_table_cols(table)

        out_order = []
        for c in cls._columns():
            if c.is_required or c.name in table_cols:
                out_order.append(c.name)

        if cls.allow_extra_columns:
            out_order.extend([c for c in table_cols if c not in out_order])

        return cls._reorder_raw_table(table, out_order)

    @classmethod
    @abstractmethod
    def _cast_raw_table_column(
        cls: type[S], table: RawTable_T, col: str, want_type: ColumnDType
    ) -> RawTable_T:
        raise NotImplementedError(f"_cast_raw_table_column is not supported by {cls.__name__} objects.")

    @classmethod
    def _cast_raw_table(
        cls: type[S], table: RawTable_T, mistyped_cols: list[tuple[str, ColumnDType, ColumnDType]]
    ) -> RawTable_T:
        """Cast the columns of the table to match the schema."""

        for col, want_type, _ in mistyped_cols:
            table = cls._cast_raw_table_column(table, col, want_type)

        return table

    @classmethod
    def align(cls: type[S], table: RawTable_T) -> RawTable_T:
        """Align the table to the schema.

        > [!WARNING]
        > This method will only work if the implementation of the validation functions in the derived classes
        > return detailed errors indicating the source of validation errors during schema and table
        > validation.

        Args:
            table: The table to align.

        Returns:
            The aligned table.

        Raises:
            SchemaValidationError: If the schema is invalid to the degree that alignment is impossible.
            TableValidationError: If the table is invalid to the degree that alignment is impossible.
        """

        mistyped_cols = []

        try:
            cls.validate(table)
        except SchemaValidationError as e:
            if e.missing_req_cols or e.disallowed_extra_cols:
                raise SchemaValidationError(
                    disallowed_extra_cols=e.disallowed_extra_cols,
                    missing_req_cols=e.missing_req_cols,
                ) from e
            elif e.mistyped_cols:
                mistyped_cols = e.mistyped_cols
            else:
                raise e
        except:
            raise

        table = cls._align_col_order(table)

        if mistyped_cols:
            try:
                table = cls._cast_raw_table(table, mistyped_cols)
            except Exception as e:
                raise SchemaValidationError(mistyped_cols=mistyped_cols) from e

        return table

_align_col_order(table) classmethod

Re-order the columns of the table to match the schema.

Source code in flexible_schema/base.py 
323
324
325
326
327
328
329
330
331
332
333
334
335
336
@classmethod
def _align_col_order(cls: type[S], table: RawTable_T) -> RawTable_T:
    """Re-order the columns of the table to match the schema."""
    table_cols = cls._raw_table_cols(table)

    out_order = []
    for c in cls._columns():
        if c.is_required or c.name in table_cols:
            out_order.append(c.name)

    if cls.allow_extra_columns:
        out_order.extend([c for c in table_cols if c not in out_order])

    return cls._reorder_raw_table(table, out_order)

_all_null(table, col) abstractmethod classmethod

Check if all values in the column are null.

Source code in flexible_schema/base.py 
222
223
224
225
226
@classmethod
@abstractmethod
def _all_null(cls: type[S], table: RawTable_T, col: str) -> bool:
    """Check if all values in the column are null."""
    raise NotImplementedError(f"_all_null is not supported by {cls.__name__} objects.")

_any_null(table, col) abstractmethod classmethod

Check if any values in the column are null.

Source code in flexible_schema/base.py 
216
217
218
219
220
@classmethod
@abstractmethod
def _any_null(cls: type[S], table: RawTable_T, col: str) -> bool:
    """Check if any values in the column are null."""
    raise NotImplementedError(f"_any_null is not supported by {cls.__name__} objects.")

_cast_raw_table(table, mistyped_cols) classmethod

Cast the columns of the table to match the schema.

Source code in flexible_schema/base.py 
345
346
347
348
349
350
351
352
353
354
@classmethod
def _cast_raw_table(
    cls: type[S], table: RawTable_T, mistyped_cols: list[tuple[str, ColumnDType, ColumnDType]]
) -> RawTable_T:
    """Cast the columns of the table to match the schema."""

    for col, want_type, _ in mistyped_cols:
        table = cls._cast_raw_table_column(table, col, want_type)

    return table

_disallowed_extra_cols(schema) classmethod

Get a list of extra columns that are not allowed in the schema.

Source code in flexible_schema/base.py 
166
167
168
169
170
171
@classmethod
def _disallowed_extra_cols(cls: type[S], schema: RawSchema_T) -> list[str]:
    """Get a list of extra columns that are not allowed in the schema."""
    if cls.allow_extra_columns:
        return []
    return [col for col in cls._raw_schema_cols(schema) if col not in set(cls.columns())]

_is_raw_schema(arg) classmethod

Check if the argument is a raw schema (e.g., of type RawSchema_T).

This is a “best-guess” approach for checking in the base class.

Parameters:

Name Type Description Default
arg Any

The argument to check.

 required

Returns:

Type Description
bool

True if the argument is a schema, False otherwise.
Source code in flexible_schema/base.py 
253
254
255
256
257
258
259
260
261
262
263
264
265
266
@classmethod
def _is_raw_schema(cls, arg: Any) -> bool:
    """Check if the argument is a raw schema (e.g., of type `RawSchema_T`).

    This is a "best-guess" approach for checking in the base class.

    Args:
        arg: The argument to check.

    Returns:
        True if the argument is a schema, False otherwise.
    """

    return isinstance(arg, type(cls.schema()))

_is_raw_table(arg) abstractmethod classmethod

Check if the argument is a raw table (e.g., of type RawTable_T).

Parameters:

Name Type Description Default
arg Any

The argument to check.

 required

Returns:

Type Description
bool

True if the argument is a table, False otherwise.
Source code in flexible_schema/base.py 
268
269
270
271
272
273
274
275
276
277
278
279
@classmethod
@abstractmethod
def _is_raw_table(cls, arg: Any) -> bool:
    """Check if the argument is a raw table (e.g., of type `RawTable_T`).

    Args:
        arg: The argument to check.

    Returns:
        True if the argument is a table, False otherwise.
    """
    raise NotImplementedError(f"_is_raw_table is not supported by {cls.__name__} objects.")

_missing_req_cols(schema) classmethod

Get a list of required columns that are missing in the schema.

Source code in flexible_schema/base.py 
173
174
175
176
@classmethod
def _missing_req_cols(cls: type[S], schema: RawSchema_T) -> list[str]:
    """Get a list of required columns that are missing in the schema."""
    return [col for col in cls.required_columns() if col not in set(cls._raw_schema_cols(schema))]

_mistyped_cols(schema) classmethod

Get a list of columns that have incorrect types in the schema.

Source code in flexible_schema/base.py 
178
179
180
181
182
183
184
185
186
@classmethod
def _mistyped_cols(cls: type[S], schema: RawSchema_T) -> list[tuple[str, ColumnDType, ColumnDType]]:
    """Get a list of columns that have incorrect types in the schema."""
    raw_cols = set(cls._raw_schema_cols(schema))
    return [
        (col, cls.column_type(col), cls._raw_schema_col_type(schema, col))
        for col in cls.columns()
        if col in raw_cols and cls.column_type(col) != cls._raw_schema_col_type(schema, col)
    ]

_raw_schema_col_type(schema, col) abstractmethod classmethod

Get the type of a column in the schema.

Source code in flexible_schema/base.py 
154
155
156
157
158
@classmethod
@abstractmethod
def _raw_schema_col_type(cls: type[S], schema: RawSchema_T, col: str) -> ColumnDType:
    """Get the type of a column in the schema."""
    raise NotImplementedError(f"__raw_schema_col_type is not supported by {cls.__name__} objects.")

_raw_schema_cols(schema) abstractmethod classmethod

Get all columns in the schema.

Source code in flexible_schema/base.py 
160
161
162
163
164
@classmethod
@abstractmethod
def _raw_schema_cols(cls: type[S], schema: RawSchema_T) -> list[str]:
    """Get all columns in the schema."""
    raise NotImplementedError(f"__raw_schema_cols is not supported by {cls.__name__} objects.")

_raw_table_cols(table) classmethod

Get all columns in the table.

Source code in flexible_schema/base.py 
313
314
315
316
@classmethod
def _raw_table_cols(cls: type[S], table: RawTable_T) -> list[str]:
    """Get all columns in the table."""
    return cls._raw_schema_cols(cls._raw_table_schema(table))

_raw_table_schema(table) abstractmethod classmethod

Get the schema of a table.

Source code in flexible_schema/base.py 
210
211
212
213
214
@classmethod
@abstractmethod
def _raw_table_schema(cls: type[S], table: RawTable_T) -> RawSchema_T:
    """Get the schema of a table."""
    raise NotImplementedError(f"__raw_table_schema is not supported by {cls.__name__} objects.")

_validate_schema(schema) classmethod

Validate the schema against the class schema and raise an error if invalid.

Parameters:

Name Type Description Default
schema RawSchema_T

The schema to validate.

 required

Raises:

Type Description
SchemaValidationError

If the schema is invalid.
Source code in flexible_schema/base.py 
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
@classmethod
def _validate_schema(cls: type[S], schema: RawSchema_T):
    """Validate the schema against the class schema and raise an error if invalid.

    Args:
        schema: The schema to validate.

    Raises:
        SchemaValidationError: If the schema is invalid.
    """

    disallowed_extra_cols = cls._disallowed_extra_cols(schema)
    missing_req_cols = cls._missing_req_cols(schema)
    mistyped_cols = cls._mistyped_cols(schema)

    if disallowed_extra_cols or missing_req_cols or mistyped_cols:
        raise SchemaValidationError(
            disallowed_extra_cols=disallowed_extra_cols,
            missing_req_cols=missing_req_cols,
            mistyped_cols=mistyped_cols,
        )

_validate_table(table) classmethod

Validate the table against the schema.

Source code in flexible_schema/base.py 
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
@classmethod
def _validate_table(cls: type[S], table: RawTable_T):
    """Validate the table against the schema."""
    cls._validate_schema(cls._raw_table_schema(table))

    nullability_none_err_cols = []
    nullability_some_err_cols = []
    for col in cls.columns():
        if col not in cls._raw_table_cols(table):
            continue

        match cls._columns_map()[col].nullable:
            case Nullability.NONE if cls._any_null(table, col):
                nullability_none_err_cols.append(col)
            case Nullability.SOME if cls._all_null(table, col):
                nullability_some_err_cols.append(col)
            case Nullability.ALL:
                continue

    if nullability_none_err_cols or nullability_some_err_cols:
        raise TableValidationError(
            nullability_none_err_cols=nullability_none_err_cols,
            nullability_some_err_cols=nullability_some_err_cols,
        )

align(table) classmethod

Align the table to the schema.

Warning

This method will only work if the implementation of the validation functions in the derived classes return detailed errors indicating the source of validation errors during schema and table validation.

Parameters:

Name Type Description Default
table RawTable_T

The table to align.

 required

Returns:

Type Description
RawTable_T

The aligned table.

Raises:

Type Description
SchemaValidationError

If the schema is invalid to the degree that alignment is impossible.
TableValidationError

If the table is invalid to the degree that alignment is impossible.
Source code in flexible_schema/base.py 
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
@classmethod
def align(cls: type[S], table: RawTable_T) -> RawTable_T:
    """Align the table to the schema.

    > [!WARNING]
    > This method will only work if the implementation of the validation functions in the derived classes
    > return detailed errors indicating the source of validation errors during schema and table
    > validation.

    Args:
        table: The table to align.

    Returns:
        The aligned table.

    Raises:
        SchemaValidationError: If the schema is invalid to the degree that alignment is impossible.
        TableValidationError: If the table is invalid to the degree that alignment is impossible.
    """

    mistyped_cols = []

    try:
        cls.validate(table)
    except SchemaValidationError as e:
        if e.missing_req_cols or e.disallowed_extra_cols:
            raise SchemaValidationError(
                disallowed_extra_cols=e.disallowed_extra_cols,
                missing_req_cols=e.missing_req_cols,
            ) from e
        elif e.mistyped_cols:
            mistyped_cols = e.mistyped_cols
        else:
            raise e
    except:
        raise

    table = cls._align_col_order(table)

    if mistyped_cols:
        try:
            table = cls._cast_raw_table(table, mistyped_cols)
        except Exception as e:
            raise SchemaValidationError(mistyped_cols=mistyped_cols) from e

    return table

column_type(col) classmethod

Return the type of a column.

Source code in flexible_schema/base.py 
135
136
137
138
@classmethod
def column_type(cls: type[S], col: str) -> ColumnDType:
    """Return the type of a column."""
    return cls._columns_map()[col].dtype

columns() classmethod

Return a list of all columns, starting with required columns.

Source code in flexible_schema/base.py 
130
131
132
133
@classmethod
def columns(cls: type[S]) -> list[str]:
    """Return a list of all columns, starting with required columns."""
    return cls.required_columns() + cls.optional_columns()

optional_columns() classmethod

Return a list of optional columns.

Source code in flexible_schema/base.py 
120
121
122
123
@classmethod
def optional_columns(cls: type[S]) -> list[str]:
    """Return a list of optional columns."""
    return [c.name for c in cls._columns() if c.is_optional]

required_columns() classmethod

Return a list of required columns.

Source code in flexible_schema/base.py 
125
126
127
128
@classmethod
def required_columns(cls: type[S]) -> list[str]:
    """Return a list of required columns."""
    return [c.name for c in cls._columns() if c.is_required]

validate(arg) classmethod

Validate the argument against the schema.

Parameters:

Name Type Description Default
arg RawTable_T | RawSchema_T

The argument to validate. This can be a table or a schema.

 required

Returns:

Type Description

True if the argument is valid.

Raises:

Type Description
SchemaValidationError

If the argument is a schema and invalid.
TableValidationError

If the argument is a table and invalid.
TypeError

If the argument is neither a schema nor a table.
Source code in flexible_schema/base.py 
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
@classmethod
def validate(cls: type[S], arg: RawTable_T | RawSchema_T):
    """Validate the argument against the schema.

    Args:
        arg: The argument to validate. This can be a table or a schema.

    Returns:
        `True` if the argument is valid.

    Raises:
        SchemaValidationError: If the argument is a schema and invalid.
        TableValidationError: If the argument is a table and invalid.
        TypeError: If the argument is neither a schema nor a table.
    """
    if cls._is_raw_schema(arg):
        try:
            cls._validate_schema(arg)
        except SchemaValidationError as e:
            raise e
        except Exception as e:
            raise SchemaValidationError("Schema validation failed") from e
    elif cls._is_raw_table(arg):
        try:
            cls._validate_table(arg)
        except (TableValidationError, SchemaValidationError) as e:
            raise e
        except Exception as e:
            raise TableValidationError("Table validation failed") from e
    else:
        raise TypeError(f"Expected a schema or table, but got: {type(arg).__name__}")