[pre-commit.ci] pre-commit autoupdate -- ruff 2025 stable format

.pre-commit-config.yaml

@@ -16,7 +16,7 @@ repos:
       - id: auto-walrus
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.8.6
+    rev: v0.9.1
     hooks:
       - id: ruff
       - id: ruff-format

ciphers/base64_cipher.py

@@ -105,13 +105,13 @@ def base64_decode(encoded_data: str) -> bytes:
 
     # Check if the encoded string contains non base64 characters
     if padding:
-        assert all(
-            char in B64_CHARSET for char in encoded_data[:-padding]
-        ), "Invalid base64 character(s) found."
+        assert all(char in B64_CHARSET for char in encoded_data[:-padding]), (
+            "Invalid base64 character(s) found."
+        )
     else:
-        assert all(
-            char in B64_CHARSET for char in encoded_data
-        ), "Invalid base64 character(s) found."
+        assert all(char in B64_CHARSET for char in encoded_data), (
+            "Invalid base64 character(s) found."
+        )
 
     # Check the padding
     assert len(encoded_data) % 4 == 0 and padding < 3, "Incorrect padding"

ciphers/caesar_cipher.py

@@ -225,7 +225,7 @@ def brute_force(input_string: str, alphabet: str | None = None) -> dict[int, str
 
 if __name__ == "__main__":
     while True:
-        print(f'\n{"-" * 10}\n Menu\n{"-" * 10}')
+        print(f"\n{'-' * 10}\n Menu\n{'-' * 10}")
         print(*["1.Encrypt", "2.Decrypt", "3.BruteForce", "4.Quit"], sep="\n")
 
         # get user input

computer_vision/flip_augmentation.py

@@ -33,7 +33,7 @@ def main() -> None:
         file_name = paths[index].split(os.sep)[-1].rsplit(".", 1)[0]
         file_root = f"{OUTPUT_DIR}/{file_name}_FLIP_{letter_code}"
         cv2.imwrite(f"{file_root}.jpg", image, [cv2.IMWRITE_JPEG_QUALITY, 85])
-        print(f"Success {index+1}/{len(new_images)} with {file_name}")
+        print(f"Success {index + 1}/{len(new_images)} with {file_name}")
         annos_list = []
         for anno in new_annos[index]:
             obj = f"{anno[0]} {anno[1]} {anno[2]} {anno[3]} {anno[4]}"

computer_vision/mosaic_augmentation.py

@@ -41,7 +41,7 @@ def main() -> None:
         file_name = path.split(os.sep)[-1].rsplit(".", 1)[0]
         file_root = f"{OUTPUT_DIR}/{file_name}_MOSAIC_{letter_code}"
         cv2.imwrite(f"{file_root}.jpg", new_image, [cv2.IMWRITE_JPEG_QUALITY, 85])
-        print(f"Succeeded {index+1}/{NUMBER_IMAGES} with {file_name}")
+        print(f"Succeeded {index + 1}/{NUMBER_IMAGES} with {file_name}")
         annos_list = []
         for anno in new_annos:
             width = anno[3] - anno[1]

data_structures/hashing/number_theory/prime_numbers.py

@@ -32,9 +32,9 @@ def is_prime(number: int) -> bool:
     """
 
     # precondition
-    assert isinstance(number, int) and (
-        number >= 0
-    ), "'number' must been an int and positive"
+    assert isinstance(number, int) and (number >= 0), (
+        "'number' must been an int and positive"
+    )
 
     if 1 < number < 4:
         # 2 and 3 are primes

data_structures/heap/min_heap.py

@@ -124,9 +124,9 @@ def is_empty(self):
         return len(self.heap) == 0
 
     def decrease_key(self, node, new_value):
-        assert (
-            self.heap[self.idx_of_element[node]].val > new_value
-        ), "newValue must be less that current value"
+        assert self.heap[self.idx_of_element[node]].val > new_value, (
+            "newValue must be less that current value"
+        )
         node.val = new_value
         self.heap_dict[node.name] = new_value
         self.sift_up(self.idx_of_element[node])

data_structures/kd_tree/tests/test_kdtree.py

@@ -48,14 +48,14 @@ def test_build_kdtree(num_points, cube_size, num_dimensions, depth, expected_res
         assert kdtree is not None, "Expected a KDNode, got None"
 
         # Check if root has correct dimensions
-        assert (
-            len(kdtree.point) == num_dimensions
-        ), f"Expected point dimension {num_dimensions}, got {len(kdtree.point)}"
+        assert len(kdtree.point) == num_dimensions, (
+            f"Expected point dimension {num_dimensions}, got {len(kdtree.point)}"
+        )
 
         # Check that the tree is balanced to some extent (simplistic check)
-        assert isinstance(
-            kdtree, KDNode
-        ), f"Expected KDNode instance, got {type(kdtree)}"
+        assert isinstance(kdtree, KDNode), (
+            f"Expected KDNode instance, got {type(kdtree)}"
+        )
 
 
 def test_nearest_neighbour_search():

data_structures/suffix_tree/tests/test_suffix_tree.py

@@ -22,37 +22,37 @@ def test_search_existing_patterns(self) -> None:
         patterns = ["ana", "ban", "na"]
         for pattern in patterns:
             with self.subTest(pattern=pattern):
-                assert self.suffix_tree.search(
-                    pattern
-                ), f"Pattern '{pattern}' should be found."
+                assert self.suffix_tree.search(pattern), (
+                    f"Pattern '{pattern}' should be found."
+                )
 
     def test_search_non_existing_patterns(self) -> None:
         """Test searching for patterns that do not exist in the suffix tree."""
         patterns = ["xyz", "apple", "cat"]
         for pattern in patterns:
             with self.subTest(pattern=pattern):
-                assert not self.suffix_tree.search(
-                    pattern
-                ), f"Pattern '{pattern}' should not be found."
+                assert not self.suffix_tree.search(pattern), (
+                    f"Pattern '{pattern}' should not be found."
+                )
 
     def test_search_empty_pattern(self) -> None:
         """Test searching for an empty pattern."""
         assert self.suffix_tree.search(""), "An empty pattern should be found."
 
     def test_search_full_text(self) -> None:
         """Test searching for the full text."""
-        assert self.suffix_tree.search(
-            self.text
-        ), "The full text should be found in the suffix tree."
+        assert self.suffix_tree.search(self.text), (
+            "The full text should be found in the suffix tree."
+        )
 
     def test_search_substrings(self) -> None:
         """Test searching for substrings of the full text."""
         substrings = ["ban", "ana", "a", "na"]
         for substring in substrings:
             with self.subTest(substring=substring):
-                assert self.suffix_tree.search(
-                    substring
-                ), f"Substring '{substring}' should be found."
+                assert self.suffix_tree.search(substring), (
+                    f"Substring '{substring}' should be found."
+                )
 
 
 if __name__ == "__main__":

dynamic_programming/climbing_stairs.py

@@ -25,9 +25,9 @@ def climb_stairs(number_of_steps: int) -> int:
         ...
     AssertionError: number_of_steps needs to be positive integer, your input -7
     """
-    assert (
-        isinstance(number_of_steps, int) and number_of_steps > 0
-    ), f"number_of_steps needs to be positive integer, your input {number_of_steps}"
+    assert isinstance(number_of_steps, int) and number_of_steps > 0, (
+        f"number_of_steps needs to be positive integer, your input {number_of_steps}"
+    )
     if number_of_steps == 1:
         return 1
     previous, current = 1, 1

dynamic_programming/iterating_through_submasks.py

@@ -37,9 +37,9 @@ def list_of_submasks(mask: int) -> list[int]:
 
     """
 
-    assert (
-        isinstance(mask, int) and mask > 0
-    ), f"mask needs to be positive integer, your input {mask}"
+    assert isinstance(mask, int) and mask > 0, (
+        f"mask needs to be positive integer, your input {mask}"
+    )
 
     """
     first submask iterated will be mask itself then operation will be performed

dynamic_programming/matrix_chain_multiplication.py

@@ -134,7 +134,7 @@ def elapsed_time(msg: str) -> Iterator:
 
     start = perf_counter_ns()
     yield
-    print(f"Finished: {msg} in {(perf_counter_ns() - start) / 10 ** 9} seconds.")
+    print(f"Finished: {msg} in {(perf_counter_ns() - start) / 10**9} seconds.")
 
 
 if __name__ == "__main__":

machine_learning/linear_discriminant_analysis.py

@@ -322,7 +322,7 @@ def main():
             user_count = valid_input(
                 input_type=int,
                 condition=lambda x: x > 0,
-                input_msg=(f"Enter The number of instances for class_{i+1}: "),
+                input_msg=(f"Enter The number of instances for class_{i + 1}: "),
                 err_msg="Number of instances should be positive!",
             )
             counts.append(user_count)
@@ -333,7 +333,7 @@ def main():
         for a in range(n_classes):
             user_mean = valid_input(
                 input_type=float,
-                input_msg=(f"Enter the value of mean for class_{a+1}: "),
+                input_msg=(f"Enter the value of mean for class_{a + 1}: "),
                 err_msg="This is an invalid value.",
             )
             user_means.append(user_mean)

maths/dual_number_automatic_differentiation.py

@@ -19,7 +19,7 @@
     def __repr__(self):
         return (
             f"{self.real}+"
-            f"{'+'.join(str(dual)+'E'+str(n+1)for n,dual in enumerate(self.duals))}"
+            f"{'+'.join(str(dual) + 'E' + str(n + 1) for n, dual in enumerate(self.duals))}"
         )
 
     def reduce(self):

maths/max_sum_sliding_window.py

@@ -43,4 +43,6 @@ def max_sum_in_array(array: list[int], k: int) -> int:
     testmod()
     array = [randint(-1000, 1000) for i in range(100)]
     k = randint(0, 110)
-    print(f"The maximum sum of {k} consecutive elements is {max_sum_in_array(array,k)}")
+    print(
+        f"The maximum sum of {k} consecutive elements is {max_sum_in_array(array, k)}"
+    )

maths/numerical_analysis/integration_by_simpson_approx.py

@@ -88,18 +88,18 @@ def simpson_integration(function, a: float, b: float, precision: int = 4) -> flo
     AssertionError: precision should be positive integer your input : -1
 
     """
-    assert callable(
-        function
-    ), f"the function(object) passed should be callable your input : {function}"
+    assert callable(function), (
+        f"the function(object) passed should be callable your input : {function}"
+    )
     assert isinstance(a, (float, int)), f"a should be float or integer your input : {a}"
     assert isinstance(function(a), (float, int)), (
         "the function should return integer or float return type of your function, "
         f"{type(a)}"
     )
     assert isinstance(b, (float, int)), f"b should be float or integer your input : {b}"
-    assert (
-        isinstance(precision, int) and precision > 0
-    ), f"precision should be positive integer your input : {precision}"
+    assert isinstance(precision, int) and precision > 0, (
+        f"precision should be positive integer your input : {precision}"
+    )
 
     # just applying the formula of simpson for approximate integration written in
     # mentioned article in first comment of this file and above this function

maths/prime_check.py

@@ -73,12 +73,12 @@ def test_primes(self):
     def test_not_primes(self):
         with pytest.raises(ValueError):
             is_prime(-19)
-        assert not is_prime(
-            0
-        ), "Zero doesn't have any positive factors, primes must have exactly two."
-        assert not is_prime(
-            1
-        ), "One only has 1 positive factor, primes must have exactly two."
+        assert not is_prime(0), (
+            "Zero doesn't have any positive factors, primes must have exactly two."
+        )
+        assert not is_prime(1), (
+            "One only has 1 positive factor, primes must have exactly two."
+        )
         assert not is_prime(2 * 2)
         assert not is_prime(2 * 3)
         assert not is_prime(3 * 3)

maths/primelib.py

@@ -66,9 +66,9 @@ def is_prime(number: int) -> bool:
     """
 
     # precondition
-    assert isinstance(number, int) and (
-        number >= 0
-    ), "'number' must been an int and positive"
+    assert isinstance(number, int) and (number >= 0), (
+        "'number' must been an int and positive"
+    )
 
     status = True
 
@@ -254,9 +254,9 @@ def greatest_prime_factor(number):
     """
 
     # precondition
-    assert isinstance(number, int) and (
-        number >= 0
-    ), "'number' must been an int and >= 0"
+    assert isinstance(number, int) and (number >= 0), (
+        "'number' must been an int and >= 0"
+    )
 
     ans = 0
 
@@ -296,9 +296,9 @@ def smallest_prime_factor(number):
     """
 
     # precondition
-    assert isinstance(number, int) and (
-        number >= 0
-    ), "'number' must been an int and >= 0"
+    assert isinstance(number, int) and (number >= 0), (
+        "'number' must been an int and >= 0"
+    )
 
     ans = 0
 
@@ -399,9 +399,9 @@ def goldbach(number):
     """
 
     # precondition
-    assert (
-        isinstance(number, int) and (number > 2) and is_even(number)
-    ), "'number' must been an int, even and > 2"
+    assert isinstance(number, int) and (number > 2) and is_even(number), (
+        "'number' must been an int, even and > 2"
+    )
 
     ans = []  # this list will returned
 
@@ -525,9 +525,9 @@ def kg_v(number1, number2):
             done.append(n)
 
     # precondition
-    assert isinstance(ans, int) and (
-        ans >= 0
-    ), "'ans' must been from type int and positive"
+    assert isinstance(ans, int) and (ans >= 0), (
+        "'ans' must been from type int and positive"
+    )
 
     return ans
 
@@ -574,9 +574,9 @@ def get_prime(n):
             ans += 1
 
     # precondition
-    assert isinstance(ans, int) and is_prime(
-        ans
-    ), "'ans' must been a prime number and from type int"
+    assert isinstance(ans, int) and is_prime(ans), (
+        "'ans' must been a prime number and from type int"
+    )
 
     return ans
 
@@ -705,9 +705,9 @@ def is_perfect_number(number):
     """
 
     # precondition
-    assert isinstance(number, int) and (
-        number > 1
-    ), "'number' must been an int and >= 1"
+    assert isinstance(number, int) and (number > 1), (
+        "'number' must been an int and >= 1"
+    )
 
     divisors = get_divisors(number)
 

matrix/matrix_based_game.py

@@ -273,7 +273,7 @@ def process_game(size: int, matrix: list[str], moves: list[tuple[int, int]]) ->
         size = int(input("Enter the size of the matrix: "))
         validate_matrix_size(size)
         print(f"Enter the {size} rows of the matrix:")
-        matrix = [input(f"Row {i+1}: ") for i in range(size)]
+        matrix = [input(f"Row {i + 1}: ") for i in range(size)]
         validate_matrix_content(matrix, size)
         moves_input = input("Enter the moves (e.g., '0 0, 1 1'): ")
         moves = parse_moves(moves_input)

neural_network/input_data.py

@@ -160,9 +160,9 @@ def __init__(
             self._num_examples = 10000
             self.one_hot = one_hot
         else:
-            assert (
-                images.shape[0] == labels.shape[0]
-            ), f"images.shape: {images.shape} labels.shape: {labels.shape}"
+            assert images.shape[0] == labels.shape[0], (
+                f"images.shape: {images.shape} labels.shape: {labels.shape}"
+            )
             self._num_examples = images.shape[0]
 
             # Convert shape from [num examples, rows, columns, depth]

scripts/validate_solutions.py

@@ -94,6 +94,6 @@ def test_project_euler(solution_path: pathlib.Path) -> None:
     solution_module = convert_path_to_module(solution_path)
     answer = str(solution_module.solution())
     answer = hashlib.sha256(answer.encode()).hexdigest()
-    assert (
-        answer == expected
-    ), f"Expected solution to {problem_number} to have hash {expected}, got {answer}"
+    assert answer == expected, (
+        f"Expected solution to {problem_number} to have hash {expected}, got {answer}"
+    )