no more need for backported importlib_resources

kraken/blla.py

@@ -24,13 +24,14 @@
 import uuid
 from typing import Any, Callable, Dict, List, Literal, Optional, Union
 
-import importlib_resources
 import numpy as np
 import PIL
 import shapely.geometry as geom
 import torch
 import torch.nn.functional as F
 import torchvision.transforms as tf
+
+from importlib import resources
 from scipy.ndimage import gaussian_filter
 from skimage.filters import sobel
 
@@ -295,7 +296,7 @@ def segment(im: PIL.Image.Image,
     """
     if model is None:
         logger.info('No segmentation model given. Loading default model.')
-        model = vgsl.TorchVGSLModel.load_model(importlib_resources.files(__name__).joinpath('blla.mlmodel'))
+        model = vgsl.TorchVGSLModel.load_model(resources.files(__name__).joinpath('blla.mlmodel'))
 
     if isinstance(model, vgsl.TorchVGSLModel):
         model = [model]

kraken/ketos/repo.py

@@ -45,15 +45,15 @@ def publish(ctx, metadata, access_token, private, model):
     """
     import json
 
-    import importlib_resources
+    from importlib import resources
     from jsonschema import validate
     from jsonschema.exceptions import ValidationError
 
     from kraken import repo
     from kraken.lib import models
     from kraken.lib.progress import KrakenDownloadProgressBar
 
-    ref = importlib_resources.files('kraken').joinpath('metadata.schema.json')
+    ref = resources.files('kraken').joinpath('metadata.schema.json')
     with open(ref, 'rb') as fp:
         schema = json.load(fp)
 

kraken/kraken.py

@@ -29,8 +29,8 @@
 from typing import IO, Any, Callable, Dict, List, Union, cast
 
 import click
-import importlib_resources
 from PIL import Image
+from importlib import resources
 from rich.traceback import install
 
 from kraken.lib import log
@@ -44,7 +44,7 @@
 install(suppress=[click])
 
 APP_NAME = 'kraken'
-SEGMENTATION_DEFAULT_MODEL = importlib_resources.files(APP_NAME).joinpath('blla.mlmodel')
+SEGMENTATION_DEFAULT_MODEL = resources.files(APP_NAME).joinpath('blla.mlmodel')
 DEFAULT_MODEL = ['en_best.mlmodel']
 
 # raise default max image size to 20k * 20k pixels

kraken/lib/dataset/utils.py

@@ -21,10 +21,10 @@
 from functools import partial
 from typing import Any, Dict, List, Sequence, Tuple, Union
 
-import importlib_resources
 import torch
 import torch.nn.functional as F
 from torchvision import transforms
+from importlib import resources
 
 from kraken.lib import functional_im_transforms as F_t
 from kraken.lib.exceptions import KrakenInputException
@@ -319,7 +319,7 @@ def compute_confusions(algn1: Sequence[str], algn2: Sequence[str]):
         script substitutions.
     """
     counts: Dict[Tuple[str, str], int] = Counter()
-    ref = importlib_resources.files(__name__).joinpath('scripts.json')
+    ref = resources.files(__name__).joinpath('scripts.json')
     with ref.open('rb') as fp:
         script_map = json.load(fp)
 

setup.cfg

@@ -61,7 +61,6 @@ install_requires =
     lightning~=2.4.0
     torchmetrics>=1.1.0
     threadpoolctl~=3.5.0
-    importlib-resources>=1.3.0
     rich
 
 [options.extras_require]