Added AudioPath as an alias for the path definition

batdetect2/api.py

@@ -99,6 +99,7 @@ consult the API documentation in the code.
 import warnings
 from typing import List, Optional, Tuple, BinaryIO, Any, Union
 
+from .types import AudioPath
 import numpy as np
 import torch
 
@@ -244,9 +245,7 @@ def generate_spectrogram(
 
 
 def process_file(
-    path:  Union[
-        str, int, os.PathLike[Any], sf.SoundFile, audioread.AudioFile, BinaryIO
-    ],
+    path: AudioPath,
     model: DetectionModel = MODEL,
     config: Optional[ProcessingConfiguration] = None,
     device: torch.device = DEVICE,
@@ -256,9 +255,7 @@ def process_file(
 
     Parameters
     ----------
-    path :  Union[
-        str, int, os.PathLike[Any], sf.SoundFile, audioread.AudioFile, BinaryIO
-    ]
+    path : AudioPath
         Path to audio data.
     model : DetectionModel, optional
         Detection model. Uses default model if not specified.

batdetect2/types.py

@@ -1,6 +1,10 @@
 """Types used in the code base."""
 
-from typing import List, NamedTuple, Optional, Union
+from typing import List, NamedTuple, Optional, Union, Any, BinaryIO
+
+import audioread
+import os 
+import soundfile as sf
 
 import numpy as np
 import torch
@@ -40,6 +44,9 @@ __all__ = [
     "SpectrogramParameters",
 ]
 
+AudioPath =  Union[
+        str, int, os.PathLike[Any], sf.SoundFile, audioread.AudioFile, BinaryIO
+    ]
 
 class SpectrogramParameters(TypedDict):
     """Parameters for generating spectrograms."""

batdetect2/utils/audio_utils.py

@@ -1,6 +1,8 @@
 import warnings
 from typing import Optional, Tuple, Union, Any, BinaryIO
 
+from ..types import AudioPath
+
 import librosa
 import librosa.core.spectrum
 import numpy as np
@@ -146,9 +148,7 @@ def generate_spectrogram(
     return spec, spec_for_viz
 
 def load_audio(
-    path:  Union[
-        str, int, os.PathLike[Any], sf.SoundFile, audioread.AudioFile, BinaryIO
-    ],
+    path: AudioPath,
     time_exp_fact: float,
     target_samp_rate: int,
     scale: bool = False,
@@ -177,9 +177,7 @@ def load_audio(
     return sample_rate, audio_data
 
 def load_audio_and_samplerate(
-    path:  Union[
-        str, int, os.PathLike[Any], sf.SoundFile, audioread.AudioFile, BinaryIO
-    ],
+    path: AudioPath,
     time_exp_fact: float,
     target_samp_rate: int,
     scale: bool = False,

batdetect2/utils/detector_utils.py

@@ -2,6 +2,8 @@ import json
 import os
 from typing import Any, Iterator, List, Optional, Tuple, Union, BinaryIO
 
+from ..types import AudioPath
+
 import numpy as np
 import pandas as pd
 import torch
@@ -735,9 +737,7 @@ def process_audio_array(
 
 
 def process_file(
-    path:  Union[
-        str, int, os.PathLike[Any], sf.SoundFile, audioread.AudioFile, BinaryIO
-    ],
+    path: AudioPath,
     model: DetectionModel,
     config: ProcessingConfiguration,
     device: torch.device,
@@ -750,7 +750,7 @@ def process_file(
 
     Parameters
     ----------
-    path : str, int, os.PathLike[Any], sf.SoundFile, audioread.AudioFile, BinaryIO
+    path : AudioPath
         Path to audio file.
 
     model : torch.nn.Module
@@ -760,7 +760,7 @@ def process_file(
         Configuration for processing.
     
     file_id: Optional[str],
-        Give the data an id. Defaults to the filename if path is a string. Otherwise
+        Give the data an id. Defaults to the filename if path is a string. Otherwise an md5 will be calculated from the binary data.
 
     Returns
     -------
@@ -859,9 +859,7 @@ def process_file(
 
     return results
 
-def _generate_id(path:  Union[
-        str, int, os.PathLike[Any], sf.SoundFile, audioread.AudioFile, BinaryIO
-    ]) -> str:
+def _generate_id(path: AudioPath) -> str:
     """ Generate an id based on the path.
     
     If the path is a str or PathLike it will parsed as the basename.