Use old typing annotations

pymaid/fetch/annotations.py

@@ -391,7 +391,7 @@ def get_entity_graph(
 
     Neurons additionally have
 
-    - skeleton_ids: list[int]
+    - skeleton_ids: List[int]
 
     Skeletons additionally have
 

pymaid/fetch/stack.py

@@ -1,4 +1,4 @@
-from typing import Any, Optional, Union, Literal, Sequence
+from typing import Any, Optional, Union, Literal, Sequence, Tuple, Dict, List
 import numpy as np
 from ..utils import _eval_remote_instance
 from ..client import CatmaidInstance
@@ -17,7 +17,7 @@ class Orientation(IntEnum):
     def __bool__(self) -> bool:
         return True
 
-    def full_orientation(self, reverse=False) -> tuple[Dimension, Dimension, Dimension]:
+    def full_orientation(self, reverse=False) -> Tuple[Dimension, Dimension, Dimension]:
         out = [
             ("x", "y", "z"),
             ("x", "z", "y"),
@@ -48,7 +48,7 @@ class StackSummary:
     comment: str
 
 
-def get_stacks(remote_instance: Optional[CatmaidInstance] = None) -> list[StackSummary]:
+def get_stacks(remote_instance: Optional[CatmaidInstance] = None) -> List[StackSummary]:
     """Get summary of all stacks in the project.
 
     Parameters
@@ -95,23 +95,23 @@ class StackInfo:
     pid: int
     ptitle: str
     stitle: str
-    downsample_factors: Optional[list[dict[Dimension, float]]]
+    downsample_factors: Optional[List[Dict[Dimension, float]]]
     num_zoom_levels: int
-    translation: dict[Dimension, float]
-    resolution: dict[Dimension, float]
-    dimension: dict[Dimension, int]
+    translation: Dict[Dimension, float]
+    resolution: Dict[Dimension, float]
+    dimension: Dict[Dimension, int]
     comment: str
     description: str
     metadata: Optional[str]
-    broken_slices: dict[int, int]
-    mirrors: list[MirrorInfo]
+    broken_slices: Dict[int, int]
+    mirrors: List[MirrorInfo]
     orientation: Orientation
     attribution: str
-    canary_location: dict[Dimension, int]
+    canary_location: Dict[Dimension, int]
     placeholder_color: Color
 
     @classmethod
-    def from_jso(cls, sinfo: dict[str, Any]):
+    def from_jso(cls, sinfo: Dict[str, Any]):
         sinfo["orientation"] = Orientation(sinfo["orientation"])
         sinfo["placeholder_color"] = Color(**sinfo["placeholder_color"])
         sinfo["mirrors"] = [MirrorInfo(**m) for m in sinfo["mirrors"]]
@@ -120,7 +120,7 @@ def from_jso(cls, sinfo: dict[str, Any]):
     def to_jso(self):
         return asdict(self)
 
-    def get_downsample(self, scale_level=0) -> dict[Dimension, float]:
+    def get_downsample(self, scale_level=0) -> Dict[Dimension, float]:
         """Get the downsample factors for a given scale level.
 
         If the downsample factors are explicit in the stack info,
@@ -151,13 +151,13 @@ def get_downsample(self, scale_level=0) -> dict[Dimension, float]:
         first, second, slicing = self.orientation.full_orientation()
         return {first: 2**scale_level, second: 2**scale_level, slicing: 1}
 
-    def get_coords(self, scale_level: int = 0) -> dict[Dimension, np.ndarray]:
+    def get_coords(self, scale_level: int = 0) -> Dict[Dimension, np.ndarray]:
         dims = self.orientation.full_orientation()
         dims = dims[::-1]
 
         downsamples = self.get_downsample(scale_level)
 
-        out: dict[Dimension, np.ndarray] = dict()
+        out: Dict[Dimension, np.ndarray] = dict()
         for d in dims:
             c = np.arange(self.dimension[d], dtype=float)
             c *= self.resolution[d]

pymaid/neuron_label.py

@@ -1,6 +1,6 @@
 from abc import ABC, abstractmethod
 from functools import cache
-from typing import Optional, Union
+from typing import Optional, Union, List, Tuple
 import re
 
 import networkx as nx
@@ -38,7 +38,7 @@ def __init__(
         self,
         skeleton_id: Optional[int] = None,
         name: Optional[str] = None,
-        annotations: Optional[list[str]] = None,
+        annotations: Optional[List[str]] = None,
         remote_instance: Optional[CatmaidInstance] = None,
     ) -> None:
         """
@@ -51,7 +51,7 @@ def __init__(
             If None, determined from name.
         name : Optional[str], optional
             If None, determined from skeleton ID.
-        annotations : Optional[list[str]], optional
+        annotations : Optional[List[str]], optional
             If None, determined from skeleton ID or name.
         remote_instance : Optional[CatmaidInstance], optional
             If None, uses global instance.
@@ -90,7 +90,7 @@ def name(self) -> str:
         return self._name
 
     @property
-    def annotations(self) -> list[str]:
+    def annotations(self) -> List[str]:
         if self._annotations is None:
             skid = self.skeleton_id
             skid_to_anns = pymaid.get_annotations(skid)
@@ -155,8 +155,8 @@ def __init__(
         super().__init__()
 
     def _filter_by_author(
-        self, annotations: list[str], remote_instance: CatmaidInstance
-    ) -> list[str]:
+        self, annotations: List[str], remote_instance: CatmaidInstance
+    ) -> List[str]:
         if self.annotator_name is None or not annotations:
             return annotations
 
@@ -166,8 +166,8 @@ def _filter_by_author(
         return [a for a in annotations if a in allowed]
 
     def _filter_by_annotation(
-        self, annotations: list[str], remote_instance: CatmaidInstance
-    ) -> list[str]:
+        self, annotations: List[str], remote_instance: CatmaidInstance
+    ) -> List[str]:
         if self.annotated_with is None or not annotations:
             return annotations
 
@@ -193,7 +193,7 @@ def dedup_whitespace(s: str):
 @cache
 def parse_components(
     fmt: str,
-) -> tuple[list[str], list[tuple[str, int, Optional[str]]]]:
+) -> Tuple[List[str], List[Tuple[str, int, Optional[str]]]]:
     joiners = []
     components = []
     last_end = 0
@@ -264,7 +264,7 @@ class NeuronLabeller:
     """Class for calculating neurons' labels, as used in the CATMAID frontend."""
     def __init__(
         self,
-        components: Optional[list[LabelComponent]] = None,
+        components: Optional[List[LabelComponent]] = None,
         fmt="%0",
         trim_empty=True,
         remove_neighboring_duplicates=True,
@@ -273,7 +273,7 @@ def __init__(
 
         Parameters
         ----------
-        components : list[LabelComponent], optional
+        components : List[LabelComponent], optional
             The label components as used in CATMAID's user settings.
             See `SkeletonId`, `NeuronName`, and `Annotations`.
             First component should be ``SkeletonId()`` for compatibility with CATMAID.

pymaid/stack.py

@@ -29,7 +29,7 @@
 ENDIAN = "<" if sys.byteorder == "little" else ">"
 
 
-def select_cli(prompt: str, options: dict[int, str]) -> Optional[int]:
+def select_cli(prompt: str, options: Dict[int, str]) -> Optional[int]:
     out = None
     print(prompt)
     for k, v in sorted(options.items()):
@@ -52,7 +52,7 @@ def select_cli(prompt: str, options: dict[int, str]) -> Optional[int]:
 
 
 def to_array(
-    coord: Union[dict[Dimension, Any], ArrayLike],
+    coord: Union[Dict[Dimension, Any], ArrayLike],
     dtype: DTypeLike = np.float64,
     order: Sequence[Dimension] = ("z", "y", "x"),
 ) -> np.ndarray:
@@ -232,7 +232,7 @@ class TileStore5(JpegStore):
 #         return s
 
 
-tile_stores: dict[int, Type[JpegStore]] = {
+tile_stores: Dict[int, Type[JpegStore]] = {
     t.tile_source_type: t
     for t in [
         TileStore1,