pyupgrade

Author: CPBridge

src/highdicom/_iods.py

@@ -3,7 +3,7 @@
 """
 from typing import Dict, List
 
-IOD_MODULE_MAP: Dict[str, List[Dict[str, str]]] = {
+IOD_MODULE_MAP: dict[str, list[dict[str, str]]] = {
     "12-lead-ecg": [
         {
             "ie": "Patient",

src/highdicom/_module_utils.py

@@ -1,5 +1,6 @@
 from enum import Enum
-from typing import Any, Dict, List, Optional, Sequence, Union
+from typing import Any, Dict, List, Optional, Union
+from collections.abc import Sequence
 
 from pydicom import Dataset
 
@@ -28,7 +29,7 @@ class ModuleUsageValues(Enum):
 def check_required_attributes(
     dataset: Dataset,
     module: str,
-    base_path: Optional[Sequence[str]] = None,
+    base_path: Sequence[str] | None = None,
     recursive: bool = True,
     check_optional_sequences: bool = True
 ) -> None:
@@ -98,8 +99,8 @@ def check_required_attributes(
     # Define recursive function
     def check(
         dataset: Dataset,
-        subtree: Dict[str, Any],
-        path: List[str]
+        subtree: dict[str, Any],
+        path: list[str]
     ) -> None:
         for kw, item in subtree['attributes'].items():
             required = item['type'] in types_to_check
@@ -140,7 +141,7 @@ def check(
     check(dataset, tree, [])
 
 
-def construct_module_tree(module: str) -> Dict[str, Any]:
+def construct_module_tree(module: str) -> dict[str, Any]:
     """Return module attributes arranged in a tree structure.
 
     Parameters
@@ -164,7 +165,7 @@ def construct_module_tree(module: str) -> Dict[str, Any]:
     from highdicom._modules import MODULE_ATTRIBUTE_MAP
     if module not in MODULE_ATTRIBUTE_MAP:
         raise AttributeError(f"No such module found: '{module}'.")
-    tree: Dict[str, Any] = {'attributes': {}}
+    tree: dict[str, Any] = {'attributes': {}}
     for item in MODULE_ATTRIBUTE_MAP[module]:
         location = tree['attributes']
         for p in item['path']:
@@ -180,7 +181,7 @@ def construct_module_tree(module: str) -> Dict[str, Any]:
 def get_module_usage(
     module_key: str,
     sop_class_uid: str
-) -> Union[ModuleUsageValues, None]:
+) -> ModuleUsageValues | None:
     """Get the usage (M/C/U) of a module within an IOD.
 
     Parameters

src/highdicom/_modules.py

@@ -1,7 +1,8 @@
 """DICOM modulesauto-generated on 2024-10-04 at 14:31:17."""
-from typing import Dict, List, Sequence, Union
+from typing import Dict, List, Union
+from collections.abc import Sequence
 
-MODULE_ATTRIBUTE_MAP: Dict[str, List[Dict[str, Union[str, Sequence[str]]]]] = {
+MODULE_ATTRIBUTE_MAP: dict[str, list[dict[str, str | Sequence[str]]]] = {
     "acquisition-context": [
         {
             "keyword": "AcquisitionContextSequence",

src/highdicom/ann/content.py

@@ -1,6 +1,7 @@
 """Content that is specific to Annotation IODs."""
 from copy import deepcopy
-from typing import cast, List, Optional, Sequence, Tuple, Union
+from typing import cast
+from collections.abc import Sequence
 from typing_extensions import Self
 
 import numpy as np
@@ -24,9 +25,9 @@ class Measurements(Dataset):
 
     def __init__(
         self,
-        name: Union[Code, CodedConcept],
+        name: Code | CodedConcept,
         values: np.ndarray,
-        unit: Union[Code, CodedConcept]
+        unit: Code | CodedConcept
     ) -> None:
         """
         Parameters
@@ -178,22 +179,22 @@ def __init__(
         number: int,
         uid: str,
         label: str,
-        annotated_property_category: Union[Code, CodedConcept],
-        annotated_property_type: Union[Code, CodedConcept],
-        graphic_type: Union[str, GraphicTypeValues],
+        annotated_property_category: Code | CodedConcept,
+        annotated_property_type: Code | CodedConcept,
+        graphic_type: str | GraphicTypeValues,
         graphic_data: Sequence[np.ndarray],
-        algorithm_type: Union[str, AnnotationGroupGenerationTypeValues],
-        algorithm_identification: Optional[
+        algorithm_type: str | AnnotationGroupGenerationTypeValues,
+        algorithm_identification: None | (
             AlgorithmIdentificationSequence
-        ] = None,
-        measurements: Optional[Sequence[Measurements]] = None,
-        description: Optional[str] = None,
-        anatomic_regions: Optional[
-            Sequence[Union[Code, CodedConcept]]
-        ] = None,
-        primary_anatomic_structures: Optional[
-            Sequence[Union[Code, CodedConcept]]
-        ] = None
+        ) = None,
+        measurements: Sequence[Measurements] | None = None,
+        description: str | None = None,
+        anatomic_regions: None | (
+            Sequence[Code | CodedConcept]
+        ) = None,
+        primary_anatomic_structures: None | (
+            Sequence[Code | CodedConcept]
+        ) = None
     ):
         """
         Parameters
@@ -479,7 +480,7 @@ def algorithm_type(self) -> AnnotationGroupGenerationTypeValues:
     @property
     def algorithm_identification(
         self
-    ) -> Union[AlgorithmIdentificationSequence, None]:
+    ) -> AlgorithmIdentificationSequence | None:
         """Union[highdicom.AlgorithmIdentificationSequence, None]:
             Information useful for identification of the algorithm, if any.
 
@@ -489,7 +490,7 @@ def algorithm_identification(
         return None
 
     @property
-    def anatomic_regions(self) -> List[CodedConcept]:
+    def anatomic_regions(self) -> list[CodedConcept]:
         """List[highdicom.sr.CodedConcept]:
             List of anatomic regions into which the annotations fall.
             May be empty.
@@ -500,7 +501,7 @@ def anatomic_regions(self) -> List[CodedConcept]:
         return list(self.AnatomicRegionSequence)
 
     @property
-    def primary_anatomic_structures(self) -> List[CodedConcept]:
+    def primary_anatomic_structures(self) -> list[CodedConcept]:
         """List[highdicom.sr.CodedConcept]:
             List of anatomic structures the annotations represent.
             May be empty.
@@ -512,8 +513,8 @@ def primary_anatomic_structures(self) -> List[CodedConcept]:
 
     def get_graphic_data(
         self,
-        coordinate_type: Union[str, AnnotationCoordinateTypeValues]
-    ) -> List[np.ndarray]:
+        coordinate_type: str | AnnotationCoordinateTypeValues
+    ) -> list[np.ndarray]:
         """Get spatial coordinates of all graphical annotations.
 
         Parameters
@@ -582,10 +583,10 @@ def get_graphic_data(
                 GraphicTypeValues.ELLIPSE,
             ):
                 # Fixed 4 coordinates per object
-                split_param: Union[
-                    int,
+                split_param: (
+                    int |
                     Sequence[int]
-                ] = len(decoded_coordinates_data) // 4
+                ) = len(decoded_coordinates_data) // 4
             elif graphic_type == GraphicTypeValues.POINT:
                 # Fixed 1 coordinate per object
                 split_param = len(decoded_coordinates_data)
@@ -619,7 +620,7 @@ def get_graphic_data(
     def get_coordinates(
         self,
         annotation_number: int,
-        coordinate_type: Union[str, AnnotationCoordinateTypeValues]
+        coordinate_type: str | AnnotationCoordinateTypeValues
     ) -> np.ndarray:
         """Get spatial coordinates of a graphical annotation.
 
@@ -653,9 +654,9 @@ def number_of_annotations(self) -> int:
 
     def get_measurements(
         self,
-        name: Optional[Union[Code, CodedConcept]] = None
-    ) -> Tuple[
-        List[CodedConcept], np.ndarray, List[CodedConcept]
+        name: Code | CodedConcept | None = None
+    ) -> tuple[
+        list[CodedConcept], np.ndarray, list[CodedConcept]
     ]:
         """Get measurements.
 

src/highdicom/ann/sop.py

@@ -7,13 +7,8 @@
     Any,
     BinaryIO,
     cast,
-    Dict,
-    List,
-    Optional,
-    Sequence,
-    Tuple,
-    Union,
 )
+from collections.abc import Sequence
 from typing_extensions import Self
 
 import numpy as np
@@ -46,24 +41,24 @@ class MicroscopyBulkSimpleAnnotations(SOPClass):
     def __init__(
         self,
         source_images: Sequence[Dataset],
-        annotation_coordinate_type: Union[str, AnnotationCoordinateTypeValues],
+        annotation_coordinate_type: str | AnnotationCoordinateTypeValues,
         annotation_groups: Sequence[AnnotationGroup],
         series_instance_uid: str,
         series_number: int,
         sop_instance_uid: str,
         instance_number: int,
         manufacturer: str,
         manufacturer_model_name: str,
-        software_versions: Union[str, Tuple[str]],
+        software_versions: str | tuple[str],
         device_serial_number: str,
-        content_description: Optional[str] = None,
-        content_creator_name: Optional[Union[str, PersonName]] = None,
-        transfer_syntax_uid: Union[str, UID] = ExplicitVRLittleEndian,
-        pixel_origin_interpretation: Union[
-            str,
+        content_description: str | None = None,
+        content_creator_name: str | PersonName | None = None,
+        transfer_syntax_uid: str | UID = ExplicitVRLittleEndian,
+        pixel_origin_interpretation: (
+            str |
             PixelOriginInterpretationValues
-        ] = PixelOriginInterpretationValues.VOLUME,
-        content_label: Optional[str] = None,
+        ) = PixelOriginInterpretationValues.VOLUME,
+        content_label: str | None = None,
         **kwargs: Any
     ) -> None:
         """
@@ -207,14 +202,14 @@ def __init__(
         ref.ReferencedSOPInstanceUID = src_img.SOPInstanceUID
         self.ReferencedImageSequence = [ref]
 
-        referenced_series: Dict[str, List[Dataset]] = defaultdict(list)
+        referenced_series: dict[str, list[Dataset]] = defaultdict(list)
         for img in source_images:
             ref = Dataset()
             ref.ReferencedSOPClassUID = img.SOPClassUID
             ref.ReferencedSOPInstanceUID = img.SOPInstanceUID
             referenced_series[img.SeriesInstanceUID].append(ref)
 
-        self.ReferencedSeriesSequence: List[Dataset] = []
+        self.ReferencedSeriesSequence: list[Dataset] = []
         for series_instance_uid, referenced_images in referenced_series.items():
             ref = Dataset()
             ref.SeriesInstanceUID = series_instance_uid
@@ -238,8 +233,8 @@ def __init__(
 
     def get_annotation_group(
         self,
-        number: Optional[int] = None,
-        uid: Optional[Union[str, UID]] = None,
+        number: int | None = None,
+        uid: str | UID | None = None,
     ) -> AnnotationGroup:
         """Get an individual annotation group.
 
@@ -303,17 +298,17 @@ def get_annotation_group(
 
     def get_annotation_groups(
         self,
-        annotated_property_category: Optional[Union[Code, CodedConcept]] = None,
-        annotated_property_type: Optional[Union[Code, CodedConcept]] = None,
-        label: Optional[str] = None,
-        graphic_type: Optional[Union[str, GraphicTypeValues]] = None,
-        algorithm_type: Optional[
-            Union[str, AnnotationGroupGenerationTypeValues]
-        ] = None,
-        algorithm_name: Optional[str] = None,
-        algorithm_family: Optional[Union[Code, CodedConcept]] = None,
-        algorithm_version: Optional[str] = None,
-    ) -> List[AnnotationGroup]:
+        annotated_property_category: Code | CodedConcept | None = None,
+        annotated_property_type: Code | CodedConcept | None = None,
+        label: str | None = None,
+        graphic_type: str | GraphicTypeValues | None = None,
+        algorithm_type: None | (
+            str | AnnotationGroupGenerationTypeValues
+        ) = None,
+        algorithm_name: str | None = None,
+        algorithm_family: Code | CodedConcept | None = None,
+        algorithm_version: str | None = None,
+    ) -> list[AnnotationGroup]:
         """Get annotation groups matching search criteria.
 
         Parameters
@@ -462,7 +457,7 @@ def from_dataset(
 
 
 def annread(
-    fp: Union[str, bytes, PathLike, BinaryIO],
+    fp: str | bytes | PathLike | BinaryIO,
 ) -> MicroscopyBulkSimpleAnnotations:
     """Read a bulk annotations object stored in DICOM File Format.