More pathlib stuff

Author: davecom

KNN/__main__.py

@@ -15,7 +15,7 @@
 # limitations under the License.
 from KNN.knn import KNN
 from KNN.digit import Digit
-import os
+from pathlib import Path
 import sys
 import pygame
 import numpy as np
@@ -33,9 +33,9 @@ def run():
     digit_pixels = np.zeros((PIXEL_HEIGHT, PIXEL_WIDTH, 3),
                             dtype=np.uint32)
     # Load the training data
-    os.chdir(os.path.dirname(os.path.abspath(__file__)))
-    digits_knn = KNN(Digit, './datasets/digits/digits.csv',
-                     has_header=False)
+    digits_file = (Path(__file__).resolve().parent
+                   / "datasets" / "digits" / "digits.csv")
+    digits_knn = KNN(Digit, digits_file, has_header=False)
     # Startup Pygame, create the window
     pygame.init()
     screen = pygame.display.set_mode(size=(PIXEL_WIDTH, PIXEL_HEIGHT),

tests/test_knn.py

@@ -31,7 +31,7 @@ def setUp(self) -> None:
 
     def test_nearest(self):
         k: int = 3
-        fish_knn = KNN(Fish, str(self.data_file))
+        fish_knn = KNN(Fish, self.data_file)
         test_fish: Fish = Fish("", 0.0, 30.0, 32.5, 38.0, 12.0, 5.0)
         nearest_fish: list[Fish] = fish_knn.nearest(k, test_fish)
         self.assertEqual(len(nearest_fish), k)
@@ -42,7 +42,7 @@ def test_nearest(self):
 
     def test_classify(self):
         k: int = 5
-        fish_knn = KNN(Fish, str(self.data_file))
+        fish_knn = KNN(Fish, self.data_file)
         test_fish: Fish = Fish("", 0.0, 20.0, 23.5, 24.0, 10.0, 4.0)
         classify_fish: str = fish_knn.classify(k, test_fish)
         self.assertEqual(classify_fish, "Parkki")