[Pydantic III] Use list/dict annotations (#1021)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Cody Baker <[email protected]>
Co-authored-by: CodyCBakerPhD <[email protected]>

CHANGELOG.md

@@ -32,6 +32,7 @@
 * `BaseRecordingInterface` now calls default metadata when metadata is not passing mimicking `run_conversion` behavior. [PR #1012](https://github.com/catalystneuro/neuroconv/pull/1012)
 * Added `get_json_schema_from_method_signature` which constructs Pydantic models automatically from the signature of any function with typical annotation types used throughout NeuroConv. [PR #1016](https://github.com/catalystneuro/neuroconv/pull/1016)
 * Replaced all interface annotations with Pydantic types. [PR #1017](https://github.com/catalystneuro/neuroconv/pull/1017)
+* Changed typehint collections (e.g. `List`) to standard collections (e.g. `list`). [PR #1021](https://github.com/catalystneuro/neuroconv/pull/1021)
 
 
 

src/neuroconv/basedatainterface.py

@@ -3,7 +3,7 @@
 import uuid
 from abc import ABC, abstractmethod
 from pathlib import Path
-from typing import Literal, Optional, Tuple, Union
+from typing import Literal, Optional, Union
 
 from jsonschema.validators import validate
 from pydantic import FilePath
@@ -30,8 +30,8 @@ class BaseDataInterface(ABC):
     """Abstract class defining the structure of all DataInterfaces."""
 
     display_name: Union[str, None] = None
-    keywords: Tuple[str] = tuple()
-    associated_suffixes: Tuple[str] = tuple()
+    keywords: tuple[str] = tuple()
+    associated_suffixes: tuple[str] = tuple()
     info: Union[str, None] = None
 
     @classmethod

src/neuroconv/datainterfaces/behavior/audio/audiointerface.py

@@ -1,6 +1,6 @@
 import json
 from pathlib import Path
-from typing import List, Literal, Optional
+from typing import Literal, Optional
 
 import numpy as np
 import scipy
@@ -28,7 +28,7 @@ class AudioInterface(BaseTemporalAlignmentInterface):
     associated_suffixes = (".wav",)
     info = "Interface for writing audio recordings to an NWB file."
 
-    def __init__(self, file_paths: List[FilePath], verbose: bool = False):
+    def __init__(self, file_paths: list[FilePath], verbose: bool = False):
         """
         Data interface for writing acoustic recordings to an NWB file.
 
@@ -105,7 +105,7 @@ def get_original_timestamps(self) -> np.ndarray:
     def get_timestamps(self) -> Optional[np.ndarray]:
         raise NotImplementedError("The AudioInterface does not yet support timestamps.")
 
-    def set_aligned_timestamps(self, aligned_timestamps: List[np.ndarray]):
+    def set_aligned_timestamps(self, aligned_timestamps: list[np.ndarray]):
         raise NotImplementedError("The AudioInterface does not yet support timestamps.")
 
     def set_aligned_starting_time(self, aligned_starting_time: float):
@@ -132,7 +132,7 @@ def set_aligned_starting_time(self, aligned_starting_time: float):
                 "Please set them using 'set_aligned_segment_starting_times'."
             )
 
-    def set_aligned_segment_starting_times(self, aligned_segment_starting_times: List[float]):
+    def set_aligned_segment_starting_times(self, aligned_segment_starting_times: list[float]):
         """
         Align the individual starting time for each audio file in this interface relative to the common session start time.
 

src/neuroconv/datainterfaces/behavior/deeplabcut/_dlc_utils.py

@@ -2,7 +2,7 @@
 import pickle
 import warnings
 from pathlib import Path
-from typing import List, Optional, Union
+from typing import Optional, Union
 
 import numpy as np
 import pandas as pd
@@ -305,7 +305,7 @@ def add_subject_to_nwbfile(
     h5file: FilePath,
     individual_name: str,
     config_file: FilePath,
-    timestamps: Optional[Union[List, np.ndarray]] = None,
+    timestamps: Optional[Union[list, np.ndarray]] = None,
     pose_estimation_container_kwargs: Optional[dict] = None,
 ) -> NWBFile:
     """

src/neuroconv/datainterfaces/behavior/deeplabcut/deeplabcutdatainterface.py

@@ -1,5 +1,5 @@
 from pathlib import Path
-from typing import List, Optional, Union
+from typing import Optional, Union
 
 import numpy as np
 from pydantic import FilePath
@@ -76,7 +76,7 @@ def get_timestamps(self) -> np.ndarray:
             "Unable to retrieve timestamps for this interface! Define the `get_timestamps` method for this interface."
         )
 
-    def set_aligned_timestamps(self, aligned_timestamps: Union[List, np.ndarray]):
+    def set_aligned_timestamps(self, aligned_timestamps: Union[list, np.ndarray]):
         """
         Set aligned timestamps vector for DLC data with user defined timestamps
 

src/neuroconv/datainterfaces/behavior/lightningpose/lightningposeconverter.py

@@ -1,5 +1,5 @@
 from copy import deepcopy
-from typing import List, Optional
+from typing import Optional
 
 from pydantic import FilePath
 from pynwb import NWBFile
@@ -106,8 +106,8 @@ def add_to_nwbfile(
         reference_frame: Optional[str] = None,
         confidence_definition: Optional[str] = None,
         external_mode: bool = True,
-        starting_frames_original_videos: Optional[List[int]] = None,
-        starting_frames_labeled_videos: Optional[List[int]] = None,
+        starting_frames_original_videos: Optional[list[int]] = None,
+        starting_frames_labeled_videos: Optional[list[int]] = None,
         stub_test: bool = False,
     ):
         original_video_interface = self.data_interface_objects["OriginalVideo"]

src/neuroconv/datainterfaces/behavior/lightningpose/lightningposedatainterface.py

@@ -2,7 +2,7 @@
 from copy import deepcopy
 from datetime import datetime
 from pathlib import Path
-from typing import Optional, Tuple
+from typing import Optional
 
 import numpy as np
 from pydantic import FilePath
@@ -116,7 +116,7 @@ def _load_source_data(self):
         pose_estimation_data = pd.read_csv(self.file_path, header=[0, 1, 2])
         return pose_estimation_data
 
-    def _get_original_video_shape(self) -> Tuple[int, int]:
+    def _get_original_video_shape(self) -> tuple[int, int]:
         with self._vc(file_path=str(self.original_video_file_path)) as video:
             video_shape = video.get_frame_shape()
         # image size of the original video is in height x width

src/neuroconv/datainterfaces/behavior/neuralynx/nvt_utils.py

@@ -5,7 +5,7 @@
 import os
 from datetime import datetime
 from shutil import copy
-from typing import Dict, List, Union
+from typing import Union
 
 import numpy as np
 from pydantic import FilePath
@@ -26,7 +26,7 @@
 ]
 
 
-def read_header(filename: str) -> Dict[str, Union[str, datetime, float, int, List[int]]]:
+def read_header(filename: str) -> dict[str, Union[str, datetime, float, int, list[int]]]:
     """
     Parses a Neuralynx NVT File Header and returns it as a dictionary.
 
@@ -83,7 +83,7 @@ def parse_bool(x):
     return out
 
 
-def read_data(filename: str) -> Dict[str, np.ndarray]:
+def read_data(filename: str) -> dict[str, np.ndarray]:
     """
     Reads a NeuroLynx NVT file and returns its data.
 
@@ -97,7 +97,7 @@ def read_data(filename: str) -> Dict[str, np.ndarray]:
 
     Returns
     -------
-    Dict[str, np.ndarray]
+    dict[str, np.ndarray]
         Dictionary containing the parsed data.
 
     Raises

src/neuroconv/datainterfaces/behavior/video/video_utils.py

@@ -222,7 +222,7 @@ def _get_frame_details(self):
         min_frame_size_mb = (math.prod(frame_shape) * self._get_dtype().itemsize) / 1e6
         return min_frame_size_mb, frame_shape
 
-    def _get_data(self, selection: Tuple[slice]) -> np.ndarray:
+    def _get_data(self, selection: tuple[slice]) -> np.ndarray:
         start_frame = selection[0].start
         end_frame = selection[0].stop
         frames = np.empty(shape=[end_frame - start_frame, *self._maxshape[1:]])

src/neuroconv/datainterfaces/behavior/video/videodatainterface.py

@@ -1,7 +1,7 @@
 import warnings
 from copy import deepcopy
 from pathlib import Path
-from typing import List, Literal, Optional
+from typing import Literal, Optional
 
 import numpy as np
 import psutil
@@ -30,7 +30,7 @@ class VideoInterface(BaseDataInterface):
 
     def __init__(
         self,
-        file_paths: List[FilePath],
+        file_paths: list[FilePath],
         verbose: bool = False,
         *,
         metadata_key_name: str = "Videos",
@@ -104,7 +104,7 @@ def get_metadata(self):
 
         return metadata
 
-    def get_original_timestamps(self, stub_test: bool = False) -> List[np.ndarray]:
+    def get_original_timestamps(self, stub_test: bool = False) -> list[np.ndarray]:
         """
         Retrieve the original unaltered timestamps for the data in this interface.
 
@@ -159,7 +159,7 @@ def get_timing_type(self) -> Literal["starting_time and rate", "timestamps"]:
                 "Please specify the temporal alignment of each video."
             )
 
-    def get_timestamps(self, stub_test: bool = False) -> List[np.ndarray]:
+    def get_timestamps(self, stub_test: bool = False) -> list[np.ndarray]:
         """
         Retrieve the timestamps for the data in this interface.
 
@@ -176,7 +176,7 @@ def get_timestamps(self, stub_test: bool = False) -> List[np.ndarray]:
         """
         return self._timestamps or self.get_original_timestamps(stub_test=stub_test)
 
-    def set_aligned_timestamps(self, aligned_timestamps: List[np.ndarray]):
+    def set_aligned_timestamps(self, aligned_timestamps: list[np.ndarray]):
         """
         Replace all timestamps for this interface with those aligned to the common session start time.
 
@@ -221,7 +221,7 @@ def set_aligned_starting_time(self, aligned_starting_time: float, stub_test: boo
         else:
             raise ValueError("There are no timestamps or starting times set to shift by a common value!")
 
-    def set_aligned_segment_starting_times(self, aligned_segment_starting_times: List[float], stub_test: bool = False):
+    def set_aligned_segment_starting_times(self, aligned_segment_starting_times: list[float], stub_test: bool = False):
         """
         Align the individual starting time for each video (segment) in this interface relative to the common session start time.
 
@@ -264,7 +264,7 @@ def add_to_nwbfile(
         metadata: Optional[dict] = None,
         stub_test: bool = False,
         external_mode: bool = True,
-        starting_frames: Optional[List[int]] = None,
+        starting_frames: Optional[list[int]] = None,
         chunk_data: bool = True,
         module_name: Optional[str] = None,
         module_description: Optional[str] = None,

src/neuroconv/datainterfaces/ecephys/baserecordingextractorinterface.py

@@ -1,4 +1,4 @@
-from typing import List, Literal, Optional, Union
+from typing import Literal, Optional, Union
 
 import numpy as np
 from pynwb import NWBFile
@@ -106,7 +106,7 @@ def get_metadata(self) -> DeepDict:
 
         return metadata
 
-    def get_original_timestamps(self) -> Union[np.ndarray, List[np.ndarray]]:
+    def get_original_timestamps(self) -> Union[np.ndarray, list[np.ndarray]]:
         """
         Retrieve the original unaltered timestamps for the data in this interface.
 
@@ -128,7 +128,7 @@ def get_original_timestamps(self) -> Union[np.ndarray, List[np.ndarray]]:
                 for segment_index in range(self._number_of_segments)
             ]
 
-    def get_timestamps(self) -> Union[np.ndarray, List[np.ndarray]]:
+    def get_timestamps(self) -> Union[np.ndarray, list[np.ndarray]]:
         """
         Retrieve the timestamps for the data in this interface.
 
@@ -152,7 +152,7 @@ def set_aligned_timestamps(self, aligned_timestamps: np.ndarray):
 
         self.recording_extractor.set_times(times=aligned_timestamps)
 
-    def set_aligned_segment_timestamps(self, aligned_segment_timestamps: List[np.ndarray]):
+    def set_aligned_segment_timestamps(self, aligned_segment_timestamps: list[np.ndarray]):
         """
         Replace all timestamps for all segments in this interface with those aligned to the common session start time.
 
@@ -185,7 +185,7 @@ def set_aligned_starting_time(self, aligned_starting_time: float):
                 ]
             )
 
-    def set_aligned_segment_starting_times(self, aligned_segment_starting_times: List[float]):
+    def set_aligned_segment_starting_times(self, aligned_segment_starting_times: list[float]):
         """
         Align the starting time for each segment in this interface relative to the common session start time.
 

src/neuroconv/datainterfaces/ecephys/basesortingextractorinterface.py

@@ -1,5 +1,5 @@
 from copy import deepcopy
-from typing import List, Literal, Optional, Union
+from typing import Literal, Optional, Union
 
 import numpy as np
 from pynwb import NWBFile
@@ -83,7 +83,7 @@ def get_original_timestamps(self) -> np.ndarray:
             "Unable to fetch original timestamps for a SortingInterface since it relies upon an attached recording."
         )
 
-    def get_timestamps(self) -> Union[np.ndarray, List[np.ndarray]]:
+    def get_timestamps(self) -> Union[np.ndarray, list[np.ndarray]]:
         if not self.sorting_extractor.has_recording():
             raise NotImplementedError(
                 "In order to align timestamps for a SortingInterface, it must have a recording "
@@ -138,7 +138,7 @@ def set_aligned_timestamps(self, aligned_timestamps: np.ndarray):
                     times=aligned_timestamps[segment_index], segment_index=segment_index
                 )
 
-    def set_aligned_segment_timestamps(self, aligned_segment_timestamps: List[np.ndarray]):
+    def set_aligned_segment_timestamps(self, aligned_segment_timestamps: list[np.ndarray]):
         """
         Replace all timestamps for all segments in this interface with those aligned to the common session start time.
 
@@ -182,7 +182,7 @@ def set_aligned_starting_time(self, aligned_starting_time: float):
                 else:
                     sorting_segment._t_start += aligned_starting_time
 
-    def set_aligned_segment_starting_times(self, aligned_segment_starting_times: List[float]):
+    def set_aligned_segment_starting_times(self, aligned_segment_starting_times: list[float]):
         """
         Align the starting time for each segment in this interface relative to the common session start time.
 

src/neuroconv/datainterfaces/ecephys/neuralynx/neuralynxdatainterface.py

@@ -1,5 +1,5 @@
 import json
-from typing import List, Optional
+from typing import Optional
 
 import numpy as np
 from pydantic import DirectoryPath
@@ -18,7 +18,7 @@ class NeuralynxRecordingInterface(BaseRecordingExtractorInterface):
     info = "Interface for Neuralynx recording data."
 
     @classmethod
-    def get_stream_names(cls, folder_path: DirectoryPath) -> List[str]:
+    def get_stream_names(cls, folder_path: DirectoryPath) -> list[str]:
         from spikeinterface.extractors import NeuralynxRecordingExtractor
 
         stream_names, _ = NeuralynxRecordingExtractor.get_streams(folder_path=folder_path)
@@ -158,16 +158,16 @@ def extract_neo_header_metadata(neo_reader) -> dict:
     return common_header
 
 
-def _dict_intersection(dict_list: List) -> dict:
+def _dict_intersection(dict_list: list[dict]) -> dict:
     """
     Intersect dict_list and return only common keys and values
     Parameters
     ----------
-    dict_list: list of dicitionaries each representing a header
+    dict_list: list of dictionaries each representing a header
     Returns
     -------
     dict:
-        Dictionary containing key-value pairs common to all input dicitionary_list
+        Dictionary containing key-value pairs common to all input dictionary_list
     """
 
     # Collect keys appearing in all dictionaries

src/neuroconv/datainterfaces/ecephys/neuroscope/neuroscopedatainterface.py

@@ -269,7 +269,7 @@ def __init__(
         self,
         folder_path: DirectoryPath,
         keep_mua_units: bool = True,
-        exclude_shanks: Optional[list] = None,
+        exclude_shanks: Optional[list[int]] = None,
         xml_file_path: Optional[FilePath] = None,
         verbose: bool = True,
     ):
@@ -282,7 +282,7 @@ def __init__(
             Path to folder containing .clu and .res files.
         keep_mua_units : bool, default: True
             Optional. Whether to return sorted spikes from multi-unit activity.
-        exclude_shanks : list, optional
+        exclude_shanks : list of integers, optional
             List of indices to ignore. The set of all possible indices is chosen by default, extracted as the
             final integer of all the .res.%i and .clu.%i pairs.
         xml_file_path : FilePathType, optional

src/neuroconv/datainterfaces/ecephys/openephys/openephysbinarydatainterface.py

@@ -1,4 +1,4 @@
-from typing import List, Optional
+from typing import Optional
 
 from pydantic import DirectoryPath
 
@@ -20,7 +20,7 @@ class OpenEphysBinaryRecordingInterface(BaseRecordingExtractorInterface):
     ExtractorName = "OpenEphysBinaryRecordingExtractor"
 
     @classmethod
-    def get_stream_names(cls, folder_path: DirectoryPath) -> List[str]:
+    def get_stream_names(cls, folder_path: DirectoryPath) -> list[str]:
         from spikeinterface.extractors import OpenEphysBinaryRecordingExtractor
 
         stream_names, _ = OpenEphysBinaryRecordingExtractor.get_streams(folder_path=folder_path)