lint fixed, pre-commit ran

pyproject.toml

@@ -34,6 +34,7 @@ dependencies = ["torch", "numpy"]
 test = [
   "pytest >=6",
   "pytest-cov >=3",
+  "pre-commit",
 ]
 dev = [
   "pytest >=6",

src/caked/__init__.py

@@ -3,6 +3,5 @@
 """
 from __future__ import annotations
 
-
 __all__ = ("__version__",)
 __version__ = "0.1.0"

src/caked/base.py

@@ -1,11 +1,17 @@
-from abc import ABC, abstractmethod
-from pathlib import Path
+from __future__ import annotations
 
-from torch.utils.data import DataLoader, Dataset
+from abc import ABC, abstractmethod
 
 
 class AbstractDataLoader(ABC):
-    def __init__(self, pipeline: str, classes: list[str], dataset_size: int, save_to_disk: bool, training: bool):
+    def __init__(
+        self,
+        pipeline: str,
+        classes: list[str],
+        dataset_size: int,
+        save_to_disk: bool,
+        training: bool,
+    ):
         self.pipeline = pipeline
         self.classes = classes
         self.dataset_size = dataset_size
@@ -26,16 +32,10 @@ def get_loader(self, split_size: float, batch_size: int):
 
 
 class AbstractDataset(ABC):
-    def __init__(self, origin: str, classes: Path) -> None:
-        pass
-
-    def __len__(self) -> int:
-        pass
-
     @abstractmethod
-    def set_len(self, length:int):
+    def set_len(self, length: int):
         pass
 
     @abstractmethod
-    def augment(self, augment:bool, aug_type:str):
+    def augment(self, augment: bool, aug_type: str):
         pass

src/caked/dataloader.py

@@ -1,14 +1,24 @@
+from __future__ import annotations
+
 from .base import AbstractDataLoader
 
+
 class DiskDataLoader(AbstractDataLoader):
-    def __init__(self, pipeline: str, classes: list[str], dataset_size: int, save_to_disk: bool, training: bool) -> None:
+    def __init__(
+        self,
+        pipeline: str,
+        classes: list[str],
+        dataset_size: int,
+        save_to_disk: bool,
+        training: bool,
+    ) -> None:
         super().__init__(pipeline, classes, dataset_size, save_to_disk, training)
-    
+
     def load(self):
         return super().load()
-    
+
     def process(self):
         return super().process()
-    
+
     def get_loader(self, split_size: float, batch_size: int):
-        return super().get_loader(split_size, batch_size)
+        return super().get_loader(split_size, batch_size)

tests/test_io.py

@@ -1,7 +1,14 @@
-from src.caked.dataloader import DiskDataLoader
-import pytest
+from __future__ import annotations
+
+from caked.dataloader import DiskDataLoader
 
 
 def test_class_instantiation():
-    test_loader = DiskDataLoader(pipeline="test", classes="test", dataset_size=3, save_to_disk=False, training=True)
-    assert isinstance(test_loader, DiskDataLoader)
+    test_loader = DiskDataLoader(
+        pipeline="test",
+        classes=["test"],
+        dataset_size=3,
+        save_to_disk=False,
+        training=True,
+    )
+    assert isinstance(test_loader, DiskDataLoader)