pre-commit: Upgrade psf/black for stable style 2023

.pre-commit-config.yaml

@@ -15,7 +15,7 @@ repos:
     -   id: auto-walrus
 
   - repo: https://github.com/psf/black
-    rev: 22.12.0
+    rev: 23.1.0
     hooks:
       - id: black
 
@@ -26,6 +26,16 @@ repos:
         args:
           - --profile=black
 
+  - repo: https://github.com/tox-dev/pyproject-fmt
+    rev: "0.6.0"
+    hooks:
+      - id: pyproject-fmt
+
+  - repo: https://github.com/abravalheri/validate-pyproject
+    rev: v0.12.1
+    hooks:
+      - id: validate-pyproject
+
   - repo: https://github.com/asottile/pyupgrade
     rev: v3.3.1
     hooks:

arithmetic_analysis/newton_raphson_new.py

@@ -59,7 +59,6 @@ def newton_raphson(
 
 # Let's Execute
 if __name__ == "__main__":
-
     # Find root of trigonometric function
     # Find value of pi
     print(f"The root of sin(x) = 0 is {newton_raphson('sin(x)', 2)}")

backtracking/n_queens_math.py

@@ -107,7 +107,6 @@ def depth_first_search(
 
     # We iterate each column in the row to find all possible results in each row
     for col in range(n):
-
         # We apply that we learned previously. First we check that in the current board
         # (possible_board) there are not other same value because if there is it means
         # that there are a collision in vertical. Then we apply the two formulas we

blockchain/chinese_remainder_theorem.py

@@ -53,6 +53,7 @@ def chinese_remainder_theorem(n1: int, r1: int, n2: int, r2: int) -> int:
 
 # ----------SAME SOLUTION USING InvertModulo instead ExtendedEuclid----------------
 
+
 # This function find the inverses of a i.e., a^(-1)
 def invert_modulo(a: int, n: int) -> int:
     """

ciphers/enigma_machine2.py

@@ -230,7 +230,6 @@ def enigma(
     # encryption/decryption process --------------------------
     for symbol in text:
         if symbol in abc:
-
             # 1st plugboard --------------------------
             if symbol in plugboard:
                 symbol = plugboard[symbol]

ciphers/playfair_cipher.py

@@ -39,7 +39,6 @@ def prepare_input(dirty: str) -> str:
 
 
 def generate_table(key: str) -> list[str]:
-
     # I and J are used interchangeably to allow
     # us to use a 5x5 table (25 letters)
     alphabet = "ABCDEFGHIKLMNOPQRSTUVWXYZ"

ciphers/polybius.py

@@ -19,7 +19,6 @@
 
 class PolybiusCipher:
     def __init__(self) -> None:
-
         self.SQUARE = np.array(SQUARE)
 
     def letter_to_numbers(self, letter: str) -> np.ndarray:

ciphers/xor_cipher.py

@@ -130,7 +130,6 @@ def encrypt_file(self, file: str, key: int = 0) -> bool:
         try:
             with open(file) as fin:
                 with open("encrypt.out", "w+") as fout:
-
                     # actual encrypt-process
                     for line in fin:
                         fout.write(self.encrypt_string(line, key))
@@ -155,7 +154,6 @@ def decrypt_file(self, file: str, key: int) -> bool:
         try:
             with open(file) as fin:
                 with open("decrypt.out", "w+") as fout:
-
                     # actual encrypt-process
                     for line in fin:
                         fout.write(self.decrypt_string(line, key))

compression/lz77.py

@@ -89,7 +89,6 @@ def compress(self, text: str) -> list[Token]:
 
         # while there are still characters in text to compress
         while text:
-
             # find the next encoding phrase
             # - triplet with offset, length, indicator (the next encoding character)
             token = self._find_encoding_token(text, search_buffer)

computer_vision/cnn_classification.py

@@ -28,7 +28,6 @@
 from tensorflow.keras import layers, models
 
 if __name__ == "__main__":
-
     # Initialising the CNN
     # (Sequential- Building the model layer by layer)
     classifier = models.Sequential()

computer_vision/harris_corner.py

@@ -9,7 +9,6 @@
 
 class HarrisCorner:
     def __init__(self, k: float, window_size: int):
-
         """
         k : is an empirically determined constant in [0.04,0.06]
         window_size : neighbourhoods considered
@@ -25,7 +24,6 @@ def __str__(self) -> str:
         return str(self.k)
 
     def detect(self, img_path: str) -> tuple[cv2.Mat, list[list[int]]]:
-
         """
         Returns the image with corners identified
         img_path  : path of the image
@@ -68,7 +66,6 @@ def detect(self, img_path: str) -> tuple[cv2.Mat, list[list[int]]]:
 
 
 if __name__ == "__main__":
-
     edge_detect = HarrisCorner(0.04, 3)
     color_img, _ = edge_detect.detect("path_to_image")
     cv2.imwrite("detect.png", color_img)

conversions/decimal_to_binary.py

@@ -2,7 +2,6 @@
 
 
 def decimal_to_binary(num: int) -> str:
-
     """
     Convert an Integer Decimal Number to a Binary Number as str.
     >>> decimal_to_binary(0)

conversions/molecular_chemistry.py

@@ -86,7 +86,6 @@ def pressure_and_volume_to_temperature(
 
 
 if __name__ == "__main__":
-
     import doctest
 
     doctest.testmod()

conversions/roman_numerals.py

@@ -47,7 +47,7 @@ def int_to_roman(number: int) -> str:
     True
     """
     result = []
-    for (arabic, roman) in ROMAN:
+    for arabic, roman in ROMAN:
         (factor, number) = divmod(number, arabic)
         result.append(roman * factor)
         if number == 0:

conversions/temperature_conversions.py

@@ -380,7 +380,6 @@ def reaumur_to_rankine(reaumur: float, ndigits: int = 2) -> float:
 
 
 if __name__ == "__main__":
-
     import doctest
 
     doctest.testmod()

conversions/weight_conversion.py

@@ -307,7 +307,6 @@ def weight_conversion(from_type: str, to_type: str, value: float) -> float:
 
 
 if __name__ == "__main__":
-
     import doctest
 
     doctest.testmod()

data_structures/binary_tree/binary_tree_traversals.py

@@ -105,7 +105,6 @@ def populate_output(root: Node | None, level: int) -> None:
         if not root:
             return
         if level == 1:
-
             output.append(root.data)
         elif level > 1:
             populate_output(root.left, level - 1)

data_structures/binary_tree/inorder_tree_traversal_2022.py

@@ -58,7 +58,6 @@ def inorder(node: None | BinaryTreeNode) -> list[int]:  # if node is None,return
 
 
 def make_tree() -> BinaryTreeNode | None:
-
     root = insert(None, 15)
     insert(root, 10)
     insert(root, 25)

data_structures/hashing/double_hash.py

@@ -24,7 +24,6 @@ def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
 
     def __hash_function_2(self, value, data):
-
         next_prime_gt = (
             next_prime(value % self.size_table)
             if not is_prime(value % self.size_table)

data_structures/hashing/hash_table.py

@@ -32,7 +32,6 @@ def hash_function(self, key):
         return key % self.size_table
 
     def _step_by_step(self, step_ord):
-
         print(f"step {step_ord}")
         print(list(range(len(self.values))))
         print(self.values)
@@ -53,7 +52,6 @@ def _collision_resolution(self, key, data=None):
         new_key = self.hash_function(key + 1)
 
         while self.values[new_key] is not None and self.values[new_key] != key:
-
             if self.values.count(None) > 0:
                 new_key = self.hash_function(new_key + 1)
             else:

data_structures/heap/binomial_heap.py

@@ -174,7 +174,6 @@ def merge_heaps(self, other):
                 i.left_tree_size == i.parent.left_tree_size
                 and i.left_tree_size != i.parent.parent.left_tree_size
             ):
-
                 # Neighbouring Nodes
                 previous_node = i.left
                 next_node = i.parent.parent
@@ -233,7 +232,6 @@ def insert(self, val):
                 and self.bottom_root.left_tree_size
                 == self.bottom_root.parent.left_tree_size
             ):
-
                 # Next node
                 next_node = self.bottom_root.parent.parent
 

data_structures/heap/skew_heap.py

@@ -71,7 +71,6 @@ class SkewHeap(Generic[T]):
     """
 
     def __init__(self, data: Iterable[T] | None = ()) -> None:
-
         """
         >>> sh = SkewHeap([3, 1, 3, 7])
         >>> list(sh)

data_structures/linked_list/doubly_linked_list_two.py

@@ -80,7 +80,6 @@ def get_tail_data(self):
         return None
 
     def set_head(self, node: Node) -> None:
-
         if self.head is None:
             self.head = node
             self.tail = node
@@ -143,7 +142,6 @@ def get_node(self, item: int) -> Node:
         raise Exception("Node not found")
 
     def delete_value(self, value):
-
         if (node := self.get_node(value)) is not None:
             if node == self.head:
                 self.head = self.head.get_next()

data_structures/stacks/prefix_evaluation.py

@@ -36,7 +36,6 @@ def evaluate(expression):
 
     # iterate over the string in reverse order
     for c in expression.split()[::-1]:
-
         # push operand to stack
         if is_operand(c):
             stack.append(int(c))

data_structures/stacks/stack_with_doubly_linked_list.py

@@ -92,7 +92,6 @@ def print_stack(self) -> None:
 
 # Code execution starts here
 if __name__ == "__main__":
-
     # Start with the empty stack
     stack: Stack[int] = Stack()
 

data_structures/stacks/stock_span_problem.py

@@ -9,7 +9,6 @@
 
 
 def calculation_span(price, s):
-
     n = len(price)
     # Create a stack and push index of fist element to it
     st = []
@@ -20,7 +19,6 @@ def calculation_span(price, s):
 
     # Calculate span values for rest of the elements
     for i in range(1, n):
-
         # Pop elements from stack while stack is not
         # empty and top of stack is smaller than price[i]
         while len(st) > 0 and price[st[0]] <= price[i]:

digital_image_processing/filters/bilateral_filter.py

@@ -50,7 +50,6 @@ def bilateral_filter(
     size_x, size_y = img.shape
     for i in range(kernel_size // 2, size_x - kernel_size // 2):
         for j in range(kernel_size // 2, size_y - kernel_size // 2):
-
             img_s = get_slice(img, i, j, kernel_size)
             img_i = img_s - img_s[kernel_size // 2, kernel_size // 2]
             img_ig = vec_gaussian(img_i, intensity_variance)

digital_image_processing/filters/local_binary_pattern.py

@@ -61,7 +61,6 @@ def local_binary_value(image: np.ndarray, x_coordinate: int, y_coordinate: int)
 
 
 if __name__ == "__main__":
-
     # Reading the image and converting it to grayscale.
     image = cv2.imread(
         "digital_image_processing/image_data/lena.jpg", cv2.IMREAD_GRAYSCALE

dynamic_programming/bitmask.py

@@ -13,7 +13,6 @@
 
 class AssignmentUsingBitmask:
     def __init__(self, task_performed, total):
-
         self.total_tasks = total  # total no of tasks (N)
 
         # DP table will have a dimension of (2^M)*N
@@ -29,7 +28,6 @@ def __init__(self, task_performed, total):
         self.final_mask = (1 << len(task_performed)) - 1
 
     def count_ways_until(self, mask, task_no):
-
         # if mask == self.finalmask all persons are distributed tasks, return 1
         if mask == self.final_mask:
             return 1
@@ -49,7 +47,6 @@ def count_ways_until(self, mask, task_no):
         # assign for the remaining tasks.
         if task_no in self.task:
             for p in self.task[task_no]:
-
                 # if p is already given a task
                 if mask & (1 << p):
                     continue
@@ -64,7 +61,6 @@ def count_ways_until(self, mask, task_no):
         return self.dp[mask][task_no]
 
     def count_no_of_ways(self, task_performed):
-
         # Store the list of persons for each task
         for i in range(len(task_performed)):
             for j in task_performed[i]:
@@ -75,7 +71,6 @@ def count_no_of_ways(self, task_performed):
 
 
 if __name__ == "__main__":
-
     total_tasks = 5  # total no of tasks (the value of N)
 
     # the list of tasks that can be done by M persons.

dynamic_programming/iterating_through_submasks.py

@@ -9,7 +9,6 @@
 
 
 def list_of_submasks(mask: int) -> list[int]:
-
     """
     Args:
         mask : number which shows mask ( always integer > 0, zero does not have any

electronics/coulombs_law.py

@@ -8,7 +8,6 @@
 def couloumbs_law(
     force: float, charge1: float, charge2: float, distance: float
 ) -> dict[str, float]:
-
     """
     Apply Coulomb's Law on any three given values. These can be force, charge1,
     charge2, or distance, and then in a Python dict return name/value pair of

fractals/julia_sets.py

@@ -170,7 +170,6 @@ def ignore_overflow_warnings() -> None:
 
 
 if __name__ == "__main__":
-
     z_0 = prepare_grid(window_size, nb_pixels)
 
     ignore_overflow_warnings()  # See file header for explanations

fractals/mandelbrot.py

@@ -114,7 +114,6 @@ def get_image(
     # loop through the image-coordinates
     for image_x in range(image_width):
         for image_y in range(image_height):
-
             # determine the figure-coordinates based on the image-coordinates
             figure_height = figure_width / image_width * image_height
             figure_x = figure_center_x + (image_x / image_width - 0.5) * figure_width

geodesy/lamberts_ellipsoidal_distance.py

@@ -10,7 +10,6 @@
 def lamberts_ellipsoidal_distance(
     lat1: float, lon1: float, lat2: float, lon2: float
 ) -> float:
-
     """
     Calculate the shortest distance along the surface of an ellipsoid between
     two points on the surface of earth given longitudes and latitudes

graphs/a_star.py

@@ -16,7 +16,6 @@ def search(
     cost: int,
     heuristic: list[list[int]],
 ) -> tuple[list[list[int]], list[list[int]]]:
-
     closed = [
         [0 for col in range(len(grid[0]))] for row in range(len(grid))
     ]  # the reference grid

graphs/check_bipartite_graph_bfs.py

@@ -20,7 +20,6 @@ def bfs():
             visited[u] = True
 
             for neighbour in graph[u]:
-
                 if neighbour == u:
                     return False