Resolve remaining type checking and linting issues

Signed-off-by: Deepyaman Datta <deepyaman.datta@utexas.edu>

pandera/api/base/error_handler.py

@@ -2,7 +2,7 @@
 
 from collections import defaultdict
 from enum import Enum
-from typing import Any, Dict, List, Union
+from typing import Any, Dict, List, Optional, Union
 
 from pandera.api.checks import Check
 from pandera.config import ValidationDepth, get_config_context
@@ -40,7 +40,7 @@ def lazy(self) -> bool:
     def collect_error(
         self,
         error_type: ErrorCategory,
-        reason_code: SchemaErrorReason,
+        reason_code: Optional[SchemaErrorReason],
         schema_error: SchemaError,
         original_exc: Union[BaseException, None] = None,
     ):

pandera/api/dataframe/container.py

@@ -167,7 +167,7 @@ def __init__(
             metadata=metadata,
         )
 
-        self.columns: Dict[Any, Any] = (  # type: ignore [name-defined]
+        self.columns: Dict[Any, Any] = (  # type: ignore[name-defined]
             {} if columns is None else columns
         )
 

pandera/api/ibis/container.py

@@ -93,7 +93,7 @@ def validate(
             inplace=inplace,
         )
 
-    @_DataFrameSchema.dtype.setter
+    @_DataFrameSchema.dtype.setter  # type: ignore[attr-defined]
     def dtype(self, value) -> None:
         """Set the dtype property."""
         self._dtype = ibis_engine.Engine.dtype(value) if value else None

pandera/api/ibis/model.py

@@ -8,6 +8,7 @@
 
 from pandera.api.checks import Check
 from pandera.api.dataframe.model import DataFrameModel as _DataFrameModel
+from pandera.api.dataframe.model import get_dtype_kwargs
 from pandera.api.dataframe.model_components import FieldInfo
 from pandera.api.ibis.components import Column
 from pandera.api.ibis.container import DataFrameSchema
@@ -45,7 +46,9 @@ def _build_columns(  # pylint:disable=too-many-locals
             check_name = getattr(field, "check_name", None)
 
             try:
-                engine_dtype = ibis_engine.Engine.dtype(annotation.raw_annotation)
+                engine_dtype = ibis_engine.Engine.dtype(
+                    annotation.raw_annotation
+                )
                 if inspect.isclass(annotation.raw_annotation) and issubclass(
                     annotation.raw_annotation, ibis_engine.DataType
                 ):

pandera/api/pandas/container.py

@@ -20,7 +20,7 @@ def _register_default_backends(self):
 
         register_pandas_backends()
 
-    @_DataFrameSchema.dtype.setter
+    @_DataFrameSchema.dtype.setter  # type: ignore[attr-defined]
     def dtype(self, value: PandasDtypeInputTypes) -> None:
         """Set the dtype property."""
         self._dtype = pandas_engine.Engine.dtype(value) if value else None

pandera/api/polars/container.py

@@ -70,7 +70,7 @@ def validate(
 
         return output
 
-    @_DataFrameSchema.dtype.setter
+    @_DataFrameSchema.dtype.setter  # type: ignore[attr-defined]
     def dtype(self, value) -> None:
         """Set the dtype property."""
         self._dtype = polars_engine.Engine.dtype(value) if value else None

pandera/backends/ibis/components.py

@@ -78,7 +78,7 @@ def validate(
         if lazy and error_handler.collected_errors:
             raise SchemaErrors(
                 schema=schema,
-                schema_errors=error_handler.collected_errors,
+                schema_errors=error_handler.schema_errors,
                 data=check_obj,
             )
 

pandera/backends/ibis/container.py

@@ -2,7 +2,7 @@
 
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, List, Optional
+from typing import TYPE_CHECKING, Iterable, List, Optional
 
 import ibis.expr.types as ir
 
@@ -85,7 +85,7 @@ def validate(
             else:
                 raise SchemaErrors(
                     schema=schema,
-                    schema_errors=error_handler.collected_errors,
+                    schema_errors=error_handler.schema_errors,
                     data=check_obj,
                 )
 
@@ -94,7 +94,7 @@ def validate(
     def run_schema_component_checks(
         self,
         check_obj: ir.Table,
-        schema_components: List,
+        schema_components: Iterable,
         lazy: bool,
     ) -> List[CoreCheckResult]:
         """Run checks for all schema components."""

pandera/backends/pandas/container.py

@@ -155,7 +155,7 @@ def run_checks_and_handle_errors(
             (self.run_checks, (sample, schema)),
         ]
         for check, args in core_checks:
-            results = check(*args)  # type: ignore [operator]
+            results = check(*args)
             if isinstance(results, CoreCheckResult):
                 results = [results]
 

pandera/engines/ibis_engine.py

@@ -63,7 +63,9 @@ def dtype(cls, data_type: Any) -> dtypes.DataType:
         try:
             return engine.Engine.dtype(cls, data_type)
         except TypeError:
-            np_dtype = data_type().to_numpy()  # XXX(deepyaman): Make sure this is right???
+            np_dtype = (
+                data_type().to_numpy()  # XXX(deepyaman): Make sure this is right???
+            )
 
         return engine.Engine.dtype(cls, np_dtype)
 
@@ -81,7 +83,6 @@ class Int32(DataType, dtypes.Int32):
     """Semantic representation of a :class:`dt.Int32`."""
 
 
-
 @Engine.register_dtype(
     equivalents=[np.int64, dtypes.Int64, dtypes.Int64(), dt.Int64, dt.int64]
 )

tests/ibis/test_ibis_container.py

@@ -13,10 +13,12 @@
 @pytest.fixture
 def t_basic():
     """Basic Ibis table fixture."""
-    df = pd.DataFrame({
-        "string_col": ["0", "1", "2"],
-        "int_col": [0, 1, 2],
-    })
+    df = pd.DataFrame(
+        {
+            "string_col": ["0", "1", "2"],
+            "int_col": [0, 1, 2],
+        }
+    )
     return ibis.memtable(df, name="t")