Add flake8 pluin flake8 bugbear to pre-commit (#7132)

* ci(pre-commit): Add ``flake8-builtins`` additional dependency to ``pre-commit`` (#7104)

* refactor: Fix ``flake8-builtins`` (#7104)

* fix(lru_cache): Fix naming conventions in docstrings (#7104)

* ci(pre-commit): Order additional dependencies alphabetically (#7104)

* fix(lfu_cache): Correct function name in docstring (#7104)

* Update strings/snake_case_to_camel_pascal_case.py

Co-authored-by: Christian Clauss <cclauss@me.com>

* Update data_structures/stacks/next_greater_element.py

Co-authored-by: Christian Clauss <cclauss@me.com>

* Update digital_image_processing/index_calculation.py

Co-authored-by: Christian Clauss <cclauss@me.com>

* Update graphs/prim.py

Co-authored-by: Christian Clauss <cclauss@me.com>

* Update hashes/djb2.py

Co-authored-by: Christian Clauss <cclauss@me.com>

* refactor: Rename `_builtin` to `builtin_` ( #7104)

* fix: Rename all instances (#7104)

* refactor: Update variable names (#7104)

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* ci: Create ``tox.ini`` and ignore ``A003`` (#7123)

* revert: Remove function name changes (#7104)

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Rename tox.ini to .flake8

* Update data_structures/heap/heap.py

Co-authored-by: Dhruv Manilawala <dhruvmanila@gmail.com>

* refactor: Rename `next_` to `next_item` (#7104)

* ci(pre-commit): Add `flake8` plugin `flake8-bugbear` (#7127)

* refactor: Follow `flake8-bugbear` plugin (#7127)

* fix: Correct `knapsack` code (#7127)

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Co-authored-by: Christian Clauss <cclauss@me.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Dhruv Manilawala <dhruvmanila@gmail.com>

.pre-commit-config.yaml

@@ -40,7 +40,10 @@ repos:
           - --ignore=E203,W503
           - --max-complexity=25
           - --max-line-length=88
-        additional_dependencies: [flake8-builtins, pep8-naming]
+        additional_dependencies:
+          - flake8-bugbear
+          - flake8-builtins
+          - pep8-naming
 
   - repo: https://github.com/pre-commit/mirrors-mypy
     rev: v0.982

arithmetic_analysis/jacobi_iteration_method.py

@@ -110,7 +110,7 @@ def jacobi_iteration_method(
     strictly_diagonally_dominant(table)
 
     # Iterates the whole matrix for given number of times
-    for i in range(iterations):
+    for _ in range(iterations):
         new_val = []
         for row in range(rows):
             temp = 0

arithmetic_analysis/newton_forward_interpolation.py

@@ -23,7 +23,7 @@ def ucal(u: float, p: int) -> float:
 def main() -> None:
     n = int(input("enter the numbers of values: "))
     y: list[list[float]] = []
-    for i in range(n):
+    for _ in range(n):
         y.append([])
     for i in range(n):
         for j in range(n):

arithmetic_analysis/secant_method.py

@@ -20,7 +20,7 @@ def secant_method(lower_bound: float, upper_bound: float, repeats: int) -> float
     """
     x0 = lower_bound
     x1 = upper_bound
-    for i in range(0, repeats):
+    for _ in range(0, repeats):
         x0, x1 = x1, x1 - (f(x1) * (x1 - x0)) / (f(x1) - f(x0))
     return x1
 

audio_filters/butterworth_filter.py

@@ -11,7 +11,7 @@ Alternatively you can use scipy.signal.butter, which should yield the same resul
 
 
 def make_lowpass(
-    frequency: int, samplerate: int, q_factor: float = 1 / sqrt(2)
+    frequency: int, samplerate: int, q_factor: float = 1 / sqrt(2)  # noqa: B008
 ) -> IIRFilter:
     """
     Creates a low-pass filter
@@ -39,7 +39,7 @@ def make_lowpass(
 
 
 def make_highpass(
-    frequency: int, samplerate: int, q_factor: float = 1 / sqrt(2)
+    frequency: int, samplerate: int, q_factor: float = 1 / sqrt(2)  # noqa: B008
 ) -> IIRFilter:
     """
     Creates a high-pass filter
@@ -67,7 +67,7 @@ def make_highpass(
 
 
 def make_bandpass(
-    frequency: int, samplerate: int, q_factor: float = 1 / sqrt(2)
+    frequency: int, samplerate: int, q_factor: float = 1 / sqrt(2)  # noqa: B008
 ) -> IIRFilter:
     """
     Creates a band-pass filter
@@ -96,7 +96,7 @@ def make_bandpass(
 
 
 def make_allpass(
-    frequency: int, samplerate: int, q_factor: float = 1 / sqrt(2)
+    frequency: int, samplerate: int, q_factor: float = 1 / sqrt(2)  # noqa: B008
 ) -> IIRFilter:
     """
     Creates an all-pass filter
@@ -121,7 +121,10 @@ def make_allpass(
 
 
 def make_peak(
-    frequency: int, samplerate: int, gain_db: float, q_factor: float = 1 / sqrt(2)
+    frequency: int,
+    samplerate: int,
+    gain_db: float,
+    q_factor: float = 1 / sqrt(2),  # noqa: B008
 ) -> IIRFilter:
     """
     Creates a peak filter
@@ -150,7 +153,10 @@ def make_peak(
 
 
 def make_lowshelf(
-    frequency: int, samplerate: int, gain_db: float, q_factor: float = 1 / sqrt(2)
+    frequency: int,
+    samplerate: int,
+    gain_db: float,
+    q_factor: float = 1 / sqrt(2),  # noqa: B008
 ) -> IIRFilter:
     """
     Creates a low-shelf filter
@@ -184,7 +190,10 @@ def make_lowshelf(
 
 
 def make_highshelf(
-    frequency: int, samplerate: int, gain_db: float, q_factor: float = 1 / sqrt(2)
+    frequency: int,
+    samplerate: int,
+    gain_db: float,
+    q_factor: float = 1 / sqrt(2),  # noqa: B008
 ) -> IIRFilter:
     """
     Creates a high-shelf filter

backtracking/sum_of_subsets.py

@@ -39,14 +39,14 @@ def create_state_space_tree(
     if sum(path) == max_sum:
         result.append(path)
         return
-    for num_index in range(num_index, len(nums)):
+    for index in range(num_index, len(nums)):
         create_state_space_tree(
             nums,
             max_sum,
-            num_index + 1,
-            path + [nums[num_index]],
+            index + 1,
+            path + [nums[index]],
             result,
-            remaining_nums_sum - nums[num_index],
+            remaining_nums_sum - nums[index],
         )
 
 

boolean_algebra/quine_mc_cluskey.py

@@ -56,7 +56,7 @@ def decimal_to_binary(no_of_variable: int, minterms: Sequence[float]) -> list[st
     temp = []
     for minterm in minterms:
         string = ""
-        for i in range(no_of_variable):
+        for _ in range(no_of_variable):
             string = str(minterm % 2) + string
             minterm //= 2
         temp.append(string)

ciphers/mixed_keyword_cypher.py

@@ -40,7 +40,7 @@ def mixed_keyword(key: str = "college", pt: str = "UNIVERSITY") -> str:
     k = 0
     for _ in range(r):
         s = []
-        for j in range(len_temp):
+        for _ in range(len_temp):
             s.append(temp[k])
             if not (k < 25):
                 break

ciphers/rabin_miller.py

@@ -11,7 +11,7 @@ def rabin_miller(num: int) -> bool:
         s = s // 2
         t += 1
 
-    for trials in range(5):
+    for _ in range(5):
         a = random.randrange(2, num - 1)
         v = pow(a, s, num)
         if v != 1:

compression/burrows_wheeler.py

@@ -154,7 +154,7 @@ def reverse_bwt(bwt_string: str, idx_original_string: int) -> str:
         )
 
     ordered_rotations = [""] * len(bwt_string)
-    for x in range(len(bwt_string)):
+    for _ in range(len(bwt_string)):
         for i in range(len(bwt_string)):
             ordered_rotations[i] = bwt_string[i] + ordered_rotations[i]
         ordered_rotations.sort()

data_structures/binary_tree/binary_search_tree_recursive.py

@@ -357,7 +357,7 @@ class BinarySearchTreeTest(unittest.TestCase):
         assert t.root.left.left.parent == t.root.left
         assert t.root.left.left.label == 1
 
-        with self.assertRaises(Exception):
+        with self.assertRaises(Exception):  # noqa: B017
             t.put(1)
 
     def test_search(self) -> None:
@@ -369,7 +369,7 @@ class BinarySearchTreeTest(unittest.TestCase):
         node = t.search(13)
         assert node.label == 13
 
-        with self.assertRaises(Exception):
+        with self.assertRaises(Exception):  # noqa: B017
             t.search(2)
 
     def test_remove(self) -> None:
@@ -515,7 +515,7 @@ class BinarySearchTreeTest(unittest.TestCase):
         assert t.get_max_label() == 14
 
         t.empty()
-        with self.assertRaises(Exception):
+        with self.assertRaises(Exception):  # noqa: B017
             t.get_max_label()
 
     def test_get_min_label(self) -> None:
@@ -524,7 +524,7 @@ class BinarySearchTreeTest(unittest.TestCase):
         assert t.get_min_label() == 1
 
         t.empty()
-        with self.assertRaises(Exception):
+        with self.assertRaises(Exception):  # noqa: B017
             t.get_min_label()
 
     def test_inorder_traversal(self) -> None:

data_structures/linked_list/circular_linked_list.py

@@ -94,25 +94,25 @@ def test_circular_linked_list() -> None:
 
     try:
         circular_linked_list.delete_front()
-        assert False  # This should not happen
+        raise AssertionError()  # This should not happen
     except IndexError:
         assert True  # This should happen
 
     try:
         circular_linked_list.delete_tail()
-        assert False  # This should not happen
+        raise AssertionError()  # This should not happen
     except IndexError:
         assert True  # This should happen
 
     try:
         circular_linked_list.delete_nth(-1)
-        assert False
+        raise AssertionError()
     except IndexError:
         assert True
 
     try:
         circular_linked_list.delete_nth(0)
-        assert False
+        raise AssertionError()
     except IndexError:
         assert True
 

data_structures/linked_list/doubly_linked_list.py

@@ -96,7 +96,7 @@ class DoublyLinkedList:
             self.tail = new_node
         else:
             temp = self.head
-            for i in range(0, index):
+            for _ in range(0, index):
                 temp = temp.next
             temp.previous.next = new_node
             new_node.previous = temp.previous
@@ -145,7 +145,7 @@ class DoublyLinkedList:
             self.tail.next = None
         else:
             temp = self.head
-            for i in range(0, index):
+            for _ in range(0, index):
                 temp = temp.next
             delete_node = temp
             temp.next.previous = temp.previous
@@ -194,13 +194,13 @@ def test_doubly_linked_list() -> None:
 
     try:
         linked_list.delete_head()
-        assert False  # This should not happen.
+        raise AssertionError()  # This should not happen.
     except IndexError:
         assert True  # This should happen.
 
     try:
         linked_list.delete_tail()
-        assert False  # This should not happen.
+        raise AssertionError()  # This should not happen.
     except IndexError:
         assert True  # This should happen.
 

data_structures/linked_list/middle_element_of_linked_list.py

@@ -62,7 +62,7 @@ class LinkedList:
 
 if __name__ == "__main__":
     link = LinkedList()
-    for i in range(int(input().strip())):
+    for _ in range(int(input().strip())):
         data = int(input().strip())
         link.push(data)
     print(link.middle_element())

data_structures/linked_list/singly_linked_list.py

@@ -132,7 +132,7 @@ class LinkedList:
         if not 0 <= index < len(self):
             raise ValueError("list index out of range.")
         current = self.head
-        for i in range(index):
+        for _ in range(index):
             current = current.next
         current.data = data
 
@@ -352,13 +352,13 @@ def test_singly_linked_list() -> None:
 
     try:
         linked_list.delete_head()
-        assert False  # This should not happen.
+        raise AssertionError()  # This should not happen.
     except IndexError:
         assert True  # This should happen.
 
     try:
         linked_list.delete_tail()
-        assert False  # This should not happen.
+        raise AssertionError()  # This should not happen.
     except IndexError:
         assert True  # This should happen.
 

data_structures/linked_list/skip_list.py

@@ -205,7 +205,7 @@ class SkipList(Generic[KT, VT]):
 
             if level > self.level:
                 # After level increase we have to add additional nodes to head.
-                for i in range(self.level - 1, level):
+                for _ in range(self.level - 1, level):
                     update_vector.append(self.head)
                 self.level = level
 
@@ -407,7 +407,7 @@ def test_iter_always_yields_sorted_values():
 
 
 def pytests():
-    for i in range(100):
+    for _ in range(100):
         # Repeat test 100 times due to the probabilistic nature of skip list
         # random values == random bugs
         test_insert()

data_structures/queue/queue_on_list.py

@@ -37,7 +37,7 @@ class Queue:
         number of times to rotate queue"""
 
     def rotate(self, rotation):
-        for i in range(rotation):
+        for _ in range(rotation):
             self.put(self.get())
 
     """Enqueues {@code item}

data_structures/queue/queue_on_pseudo_stack.py

@@ -37,7 +37,7 @@ class Queue:
         number of times to rotate queue"""
 
     def rotate(self, rotation: int) -> None:
-        for i in range(rotation):
+        for _ in range(rotation):
             temp = self.stack[0]
             self.stack = self.stack[1:]
             self.put(temp)

data_structures/stacks/stack.py

@@ -92,13 +92,13 @@ def test_stack() -> None:
 
     try:
         _ = stack.pop()
-        assert False  # This should not happen
+        raise AssertionError()  # This should not happen
     except StackUnderflowError:
         assert True  # This should happen
 
     try:
         _ = stack.peek()
-        assert False  # This should not happen
+        raise AssertionError()  # This should not happen
     except StackUnderflowError:
         assert True  # This should happen
 
@@ -118,7 +118,7 @@ def test_stack() -> None:
 
     try:
         stack.push(200)
-        assert False  # This should not happen
+        raise AssertionError()  # This should not happen
     except StackOverflowError:
         assert True  # This should happen
 

divide_and_conquer/convex_hull.py

@@ -458,16 +458,16 @@ def convex_hull_melkman(points: list[Point]) -> list[Point]:
             convex_hull[1] = points[i]
     i += 1
 
-    for i in range(i, n):
+    for j in range(i, n):
         if (
-            _det(convex_hull[0], convex_hull[-1], points[i]) > 0
+            _det(convex_hull[0], convex_hull[-1], points[j]) > 0
             and _det(convex_hull[-1], convex_hull[0], points[1]) < 0
         ):
             # The point lies within the convex hull
             continue
 
-        convex_hull.insert(0, points[i])
-        convex_hull.append(points[i])
+        convex_hull.insert(0, points[j])
+        convex_hull.append(points[j])
         while _det(convex_hull[0], convex_hull[1], convex_hull[2]) >= 0:
             del convex_hull[1]
         while _det(convex_hull[-1], convex_hull[-2], convex_hull[-3]) <= 0:

divide_and_conquer/strassen_matrix_multiplication.py

@@ -132,12 +132,12 @@ def strassen(matrix1: list, matrix2: list) -> list:
     # power of 2
     for i in range(0, maxim):
         if i < dimension1[0]:
-            for j in range(dimension1[1], maxim):
+            for _ in range(dimension1[1], maxim):
                 new_matrix1[i].append(0)
         else:
             new_matrix1.append([0] * maxim)
         if i < dimension2[0]:
-            for j in range(dimension2[1], maxim):
+            for _ in range(dimension2[1], maxim):
                 new_matrix2[i].append(0)
         else:
             new_matrix2.append([0] * maxim)
@@ -147,7 +147,7 @@ def strassen(matrix1: list, matrix2: list) -> list:
     # Removing the additional zeros
     for i in range(0, maxim):
         if i < dimension1[0]:
-            for j in range(dimension2[1], maxim):
+            for _ in range(dimension2[1], maxim):
                 final_matrix[i].pop()
         else:
             final_matrix.pop()

dynamic_programming/all_construct.py

@@ -21,7 +21,7 @@ def all_construct(target: str, word_bank: list[str] | None = None) -> list[list[
     table_size: int = len(target) + 1
 
     table: list[list[list[str]]] = []
-    for i in range(table_size):
+    for _ in range(table_size):
         table.append([])
     # seed value
     table[0] = [[]]  # because empty string has empty combination

dynamic_programming/knapsack.py

@@ -30,13 +30,13 @@ def knapsack(w, wt, val, n):
     dp = [[0 for i in range(w + 1)] for j in range(n + 1)]
 
     for i in range(1, n + 1):
-        for w in range(1, w + 1):
-            if wt[i - 1] <= w:
-                dp[i][w] = max(val[i - 1] + dp[i - 1][w - wt[i - 1]], dp[i - 1][w])
+        for w_ in range(1, w + 1):
+            if wt[i - 1] <= w_:
+                dp[i][w_] = max(val[i - 1] + dp[i - 1][w_ - wt[i - 1]], dp[i - 1][w_])
             else:
-                dp[i][w] = dp[i - 1][w]
+                dp[i][w_] = dp[i - 1][w_]
 
-    return dp[n][w], dp
+    return dp[n][w_], dp
 
 
 def knapsack_with_example_solution(w: int, wt: list, val: list):

fractals/julia_sets.py

@@ -118,7 +118,7 @@ def iterate_function(
     """
 
     z_n = z_0.astype("complex64")
-    for i in range(nb_iterations):
+    for _ in range(nb_iterations):
         z_n = eval_function(function_params, z_n)
         if infinity is not None:
             numpy.nan_to_num(z_n, copy=False, nan=infinity)

fractals/koch_snowflake.py

@@ -46,7 +46,7 @@ def iterate(initial_vectors: list[numpy.ndarray], steps: int) -> list[numpy.ndar
 0.28867513]), array([0.66666667, 0.        ]), array([1, 0])]
     """
     vectors = initial_vectors
-    for i in range(steps):
+    for _ in range(steps):
         vectors = iteration_step(vectors)
     return vectors
 

fractals/mandelbrot.py

@@ -36,7 +36,7 @@ def get_distance(x: float, y: float, max_step: int) -> float:
     """
     a = x
     b = y
-    for step in range(max_step):
+    for step in range(max_step):  # noqa: B007
         a_new = a * a - b * b + x
         b = 2 * a * b + y
         a = a_new

genetic_algorithm/basic_string.py

@@ -80,7 +80,7 @@ def basic(target: str, genes: list[str], debug: bool = True) -> tuple[int, int,
             score = len(
                 [g for position, g in enumerate(item) if g == main_target[position]]
             )
-            return (item, float(score))
+            return (item, float(score))  # noqa: B023
 
         # Adding a bit of concurrency can make everything faster,
         #
@@ -129,7 +129,10 @@ def basic(target: str, genes: list[str], debug: bool = True) -> tuple[int, int,
             child_n = int(parent_1[1] * 100) + 1
             child_n = 10 if child_n >= 10 else child_n
             for _ in range(child_n):
-                parent_2 = population_score[random.randint(0, N_SELECTED)][0]
+                parent_2 = population_score[  # noqa: B023
+                    random.randint(0, N_SELECTED)
+                ][0]
+
                 child_1, child_2 = crossover(parent_1[0], parent_2)
                 # Append new string to the population list
                 pop.append(mutate(child_1))

graphs/basic_graphs.py

@@ -188,7 +188,7 @@ def topo(g, ind=None, q=None):
 def adjm():
     n = input().strip()
     a = []
-    for i in range(n):
+    for _ in range(n):
         a.append(map(int, input().strip().split()))
     return a, n
 
@@ -264,7 +264,7 @@ def prim(g, s):
 def edglist():
     n, m = map(int, input().split(" "))
     edges = []
-    for i in range(m):
+    for _ in range(m):
         edges.append(map(int, input().split(" ")))
     return edges, n
 

graphs/bellman_ford.py

@@ -36,7 +36,7 @@ def bellman_ford(
     distance = [float("inf")] * vertex_count
     distance[src] = 0.0
 
-    for i in range(vertex_count - 1):
+    for _ in range(vertex_count - 1):
         for j in range(edge_count):
             u, v, w = (graph[j][k] for k in ["src", "dst", "weight"])
 

graphs/dijkstra_2.py

@@ -19,23 +19,23 @@ def min_dist(mdist, vset, v):
 
 
 def dijkstra(graph, v, src):
-    mdist = [float("inf") for i in range(v)]
-    vset = [False for i in range(v)]
+    mdist = [float("inf") for _ in range(v)]
+    vset = [False for _ in range(v)]
     mdist[src] = 0.0
 
-    for i in range(v - 1):
+    for _ in range(v - 1):
         u = min_dist(mdist, vset, v)
         vset[u] = True
 
-        for v in range(v):
+        for i in range(v):
             if (
-                (not vset[v])
-                and graph[u][v] != float("inf")
-                and mdist[u] + graph[u][v] < mdist[v]
+                (not vset[i])
+                and graph[u][i] != float("inf")
+                and mdist[u] + graph[u][i] < mdist[i]
             ):
-                mdist[v] = mdist[u] + graph[u][v]
+                mdist[i] = mdist[u] + graph[u][i]
 
-    print_dist(mdist, v)
+    print_dist(mdist, i)
 
 
 if __name__ == "__main__":

graphs/frequent_pattern_graph_miner.py

@@ -79,7 +79,7 @@ def get_nodes(frequency_table):
     {'11111': ['ab', 'ac', 'df', 'bd', 'bc']}
     """
     nodes = {}
-    for i, item in enumerate(frequency_table):
+    for _, item in enumerate(frequency_table):
         nodes.setdefault(item[2], []).append(item[0])
     return nodes
 

graphs/kahns_algorithm_long.py

@@ -4,7 +4,7 @@ def longest_distance(graph):
     queue = []
     long_dist = [1] * len(graph)
 
-    for key, values in graph.items():
+    for values in graph.values():
         for i in values:
             indegree[i] += 1
 

graphs/kahns_algorithm_topo.py

@@ -8,7 +8,7 @@ def topological_sort(graph):
     topo = []
     cnt = 0
 
-    for key, values in graph.items():
+    for values in graph.values():
         for i in values:
             indegree[i] += 1
 

graphs/minimum_spanning_tree_prims.py

@@ -91,7 +91,7 @@ def prisms_algorithm(l):  # noqa: E741
         distance_tv[x[0]] = x[1]
     heapify(distance_tv, positions)
 
-    for i in range(1, len(l)):
+    for _ in range(1, len(l)):
         vertex = delete_minimum(distance_tv, positions)
         if visited[vertex] == 0:
             tree_edges.append((nbr_tv[vertex], vertex))

graphs/page_rank.py

@@ -41,7 +41,7 @@ def page_rank(nodes, limit=3, d=0.85):
 
     for i in range(limit):
         print(f"======= Iteration {i + 1} =======")
-        for j, node in enumerate(nodes):
+        for _, node in enumerate(nodes):
             ranks[node.name] = (1 - d) + d * sum(
                 ranks[ib] / outbounds[ib] for ib in node.inbound
             )

graphs/scc_kosaraju.py

@@ -39,10 +39,10 @@ if __name__ == "__main__":
     # n - no of nodes, m - no of edges
     n, m = list(map(int, input().strip().split()))
 
-    graph: list[list[int]] = [[] for i in range(n)]  # graph
+    graph: list[list[int]] = [[] for _ in range(n)]  # graph
     reversed_graph: list[list[int]] = [[] for i in range(n)]  # reversed graph
     # input graph data (edges)
-    for i in range(m):
+    for _ in range(m):
         u, v = list(map(int, input().strip().split()))
         graph[u].append(v)
         reversed_graph[v].append(u)

greedy_methods/optimal_merge_pattern.py

@@ -41,7 +41,7 @@ def optimal_merge_pattern(files: list) -> float:
     while len(files) > 1:
         temp = 0
         # Consider two files with minimum cost to be merged
-        for i in range(2):
+        for _ in range(2):
             min_index = files.index(min(files))
             temp += files[min_index]
             files.pop(min_index)

hashes/chaos_machine.py

@@ -53,7 +53,7 @@ def pull():
     key = machine_time % m
 
     # Evolution (Time Length)
-    for i in range(0, t):
+    for _ in range(0, t):
         # Variables (Position + Parameters)
         r = params_space[key]
         value = buffer_space[key]

hashes/enigma_machine.py

@@ -48,7 +48,7 @@ if __name__ == "__main__":
             break
         except Exception as error:
             print(error)
-    for i in range(token):
+    for _ in range(token):
         rotator()
     for j in decode:
         engine(j)

machine_learning/self_organizing_map.py

@@ -47,7 +47,7 @@ def main() -> None:
     epochs = 3
     alpha = 0.5
 
-    for i in range(epochs):
+    for _ in range(epochs):
         for j in range(len(training_samples)):
 
             # training sample

maths/area_under_curve.py

@@ -35,7 +35,7 @@ def trapezoidal_area(
     x1 = x_start
     fx1 = fnc(x_start)
     area = 0.0
-    for i in range(steps):
+    for _ in range(steps):
         # Approximates small segments of curve as linear and solve
         # for trapezoidal area
         x2 = (x_end - x_start) / steps + x1

maths/line_length.py

@@ -40,7 +40,7 @@ def line_length(
     fx1 = fnc(x_start)
     length = 0.0
 
-    for i in range(steps):
+    for _ in range(steps):
 
         # Approximates curve as a sequence of linear lines and sums their length
         x2 = (x_end - x_start) / steps + x1

maths/lucas_lehmer_primality_test.py

@@ -31,7 +31,7 @@ def lucas_lehmer_test(p: int) -> bool:
 
     s = 4
     m = (1 << p) - 1
-    for i in range(p - 2):
+    for _ in range(p - 2):
         s = ((s * s) - 2) % m
     return s == 0
 

maths/lucas_series.py

@@ -50,7 +50,7 @@ def dynamic_lucas_number(n_th_number: int) -> int:
     if not isinstance(n_th_number, int):
         raise TypeError("dynamic_lucas_number accepts only integer arguments.")
     a, b = 2, 1
-    for i in range(n_th_number):
+    for _ in range(n_th_number):
         a, b = b, a + b
     return a
 

maths/miller_rabin.py

@@ -33,7 +33,7 @@ def is_prime_big(n, prec=1000):
         b = bin_exp_mod(a, d, n)
         if b != 1:
             flag = True
-            for i in range(exp):
+            for _ in range(exp):
                 if b == n - 1:
                     flag = False
                     break

maths/monte_carlo_dice.py

@@ -35,7 +35,7 @@ def throw_dice(num_throws: int, num_dice: int = 2) -> list[float]:
     """
     dices = [Dice() for i in range(num_dice)]
     count_of_sum = [0] * (len(dices) * Dice.NUM_SIDES + 1)
-    for i in range(num_throws):
+    for _ in range(num_throws):
         count_of_sum[sum(dice.roll() for dice in dices)] += 1
     probability = [round((count * 100) / num_throws, 2) for count in count_of_sum]
     return probability[num_dice:]  # remove probability of sums that never appear

maths/numerical_integration.py

@@ -39,7 +39,7 @@ def trapezoidal_area(
     fx1 = fnc(x_start)
     area = 0.0
 
-    for i in range(steps):
+    for _ in range(steps):
 
         # Approximates small segments of curve as linear and solve
         # for trapezoidal area

maths/pi_monte_carlo_estimation.py

@@ -47,7 +47,7 @@ def estimate_pi(number_of_simulations: int) -> float:
         raise ValueError("At least one simulation is necessary to estimate PI.")
 
     number_in_unit_circle = 0
-    for simulation_index in range(number_of_simulations):
+    for _ in range(number_of_simulations):
         random_point = Point.random_unit_square()
 
         if random_point.is_in_unit_circle():

maths/pollard_rho.py

@@ -73,7 +73,7 @@ def pollard_rho(
         """
         return (pow(value, 2) + step) % modulus
 
-    for attempt in range(attempts):
+    for _ in range(attempts):
         # These track the position within the cycle detection logic.
         tortoise = seed
         hare = seed

maths/primelib.py

@@ -406,14 +406,14 @@ def kg_v(number1, number2):
                 count1 = prime_fac_1.count(n)
                 count2 = prime_fac_2.count(n)
 
-                for i in range(max(count1, count2)):
+                for _ in range(max(count1, count2)):
                     ans *= n
 
             else:
 
                 count1 = prime_fac_1.count(n)
 
-                for i in range(count1):
+                for _ in range(count1):
                     ans *= n
 
             done.append(n)
@@ -425,7 +425,7 @@ def kg_v(number1, number2):
 
             count2 = prime_fac_2.count(n)
 
-            for i in range(count2):
+            for _ in range(count2):
                 ans *= n
 
             done.append(n)
@@ -637,7 +637,7 @@ def fib(n):
     fib1 = 1
     ans = 1  # this will be return
 
-    for i in range(n - 1):
+    for _ in range(n - 1):
 
         tmp = ans
         ans += fib1

maths/proth_number.py

@@ -49,7 +49,7 @@ def proth(number: int) -> int:
         proth_index = 2
         increment = 3
         for block in range(1, block_index):
-            for move in range(increment):
+            for _ in range(increment):
                 proth_list.append(2 ** (block + 1) + proth_list[proth_index - 1])
                 proth_index += 1
             increment *= 2

maths/square_root.py

@@ -49,7 +49,7 @@ def square_root_iterative(
 
     value = get_initial_point(a)
 
-    for i in range(max_iter):
+    for _ in range(max_iter):
         prev_value = value
         value = value - fx(value, a) / fx_derivative(value)
         if abs(prev_value - value) < tolerance:

maths/ugly_numbers.py

@@ -32,7 +32,7 @@ def ugly_numbers(n: int) -> int:
     next_3 = ugly_nums[i3] * 3
     next_5 = ugly_nums[i5] * 5
 
-    for i in range(1, n):
+    for _ in range(1, n):
         next_num = min(next_2, next_3, next_5)
         ugly_nums.append(next_num)
         if next_num == next_2:

matrix/matrix_class.py

@@ -351,7 +351,7 @@ class Matrix:
                 "Only invertable matrices can be raised to a negative power"
             )
         result = self
-        for i in range(other - 1):
+        for _ in range(other - 1):
             result *= self
         return result
 

matrix/nth_fibonacci_using_matrix_exponentiation.py

@@ -65,7 +65,7 @@ def nth_fibonacci_bruteforce(n: int) -> int:
         return n
     fib0 = 0
     fib1 = 1
-    for i in range(2, n + 1):
+    for _ in range(2, n + 1):
         fib0, fib1 = fib1, fib0 + fib1
     return fib1
 

neural_network/back_propagation_neural_network.py

@@ -128,7 +128,7 @@ class BPNN:
         self.ax_loss.hlines(self.accuracy, 0, self.train_round * 1.1)
 
         x_shape = np.shape(xdata)
-        for round_i in range(train_round):
+        for _ in range(train_round):
             all_loss = 0
             for row in range(x_shape[0]):
                 _xdata = np.asmatrix(xdata[row, :]).T

neural_network/perceptron.py

@@ -69,7 +69,7 @@ class Perceptron:
         for sample in self.sample:
             sample.insert(0, self.bias)
 
-        for i in range(self.col_sample):
+        for _ in range(self.col_sample):
             self.weight.append(random.random())
 
         self.weight.insert(0, self.bias)

other/lfu_cache.py

@@ -303,7 +303,7 @@ class LFUCache(Generic[T, U]):
             def cache_info() -> LFUCache[T, U]:
                 return cls.decorator_function_to_instance_map[func]
 
-            setattr(cache_decorator_wrapper, "cache_info", cache_info)
+            setattr(cache_decorator_wrapper, "cache_info", cache_info)  # noqa: B010
 
             return cache_decorator_wrapper
 

other/lru_cache.py

@@ -321,7 +321,7 @@ class LRUCache(Generic[T, U]):
             def cache_info() -> LRUCache[T, U]:
                 return cls.decorator_function_to_instance_map[func]
 
-            setattr(cache_decorator_wrapper, "cache_info", cache_info)
+            setattr(cache_decorator_wrapper, "cache_info", cache_info)  # noqa: B010
 
             return cache_decorator_wrapper
 

other/magicdiamondpattern.py

@@ -8,9 +8,9 @@ def floyd(n):
     n : size of pattern
     """
     for i in range(0, n):
-        for j in range(0, n - i - 1):  # printing spaces
+        for _ in range(0, n - i - 1):  # printing spaces
             print(" ", end="")
-        for k in range(0, i + 1):  # printing stars
+        for _ in range(0, i + 1):  # printing stars
             print("* ", end="")
         print()
 
@@ -22,10 +22,10 @@ def reverse_floyd(n):
     n : size of pattern
     """
     for i in range(n, 0, -1):
-        for j in range(i, 0, -1):  # printing stars
+        for _ in range(i, 0, -1):  # printing stars
             print("* ", end="")
         print()
-        for k in range(n - i + 1, 0, -1):  # printing spaces
+        for _ in range(n - i + 1, 0, -1):  # printing spaces
             print(" ", end="")
 
 

other/scoring_algorithm.py

@@ -77,7 +77,7 @@ def procentual_proximity(
     final_scores: list[float] = [0 for i in range(len(score_lists[0]))]
 
     # generate final scores
-    for i, slist in enumerate(score_lists):
+    for slist in score_lists:
         for j, ele in enumerate(slist):
             final_scores[j] = final_scores[j] + ele
 

physics/lorentz_transformation_four_vector.py

@@ -145,7 +145,7 @@ def transformation_matrix(velocity: float) -> np.array:
 
 
 def transform(
-    velocity: float, event: np.array = np.zeros(4), symbolic: bool = True
+    velocity: float, event: np.array = np.zeros(4), symbolic: bool = True  # noqa: B008
 ) -> np.array:
     """
     >>> transform(29979245,np.array([1,2,3,4]), False)

physics/n_body_simulation.py

@@ -310,7 +310,7 @@ def example_3() -> BodySystem:
     """
 
     bodies = []
-    for i in range(10):
+    for _ in range(10):
         velocity_x = random.uniform(-0.5, 0.5)
         velocity_y = random.uniform(-0.5, 0.5)
 

project_euler/problem_011/sol2.py

@@ -36,7 +36,7 @@ def solution():
     """
     with open(os.path.dirname(__file__) + "/grid.txt") as f:
         l = []  # noqa: E741
-        for i in range(20):
+        for _ in range(20):
             l.append([int(x) for x in f.readline().split()])
 
         maximum = 0

project_euler/problem_025/sol3.py

@@ -45,7 +45,7 @@ def solution(n: int = 1000) -> int:
         f = f1 + f2
         f1, f2 = f2, f
         index += 1
-        for j in str(f):
+        for _ in str(f):
             i += 1
         if i == n:
             break

project_euler/problem_026/sol1.py

@@ -41,7 +41,7 @@ def solution(numerator: int = 1, digit: int = 1000) -> int:
     for divide_by_number in range(numerator, digit + 1):
         has_been_divided: list[int] = []
         now_divide = numerator
-        for division_cycle in range(1, digit + 1):
+        for _ in range(1, digit + 1):
             if now_divide in has_been_divided:
                 if longest_list_length < len(has_been_divided):
                     longest_list_length = len(has_been_divided)

project_euler/problem_188/sol1.py

@@ -58,7 +58,7 @@ def solution(base: int = 1777, height: int = 1855, digits: int = 8) -> int:
     # calculate base↑↑height by right-assiciative repeated modular
     # exponentiation
     result = base
-    for i in range(1, height):
+    for _ in range(1, height):
         result = _modexpt(base, result, 10**digits)
 
     return result

project_euler/problem_203/sol1.py

@@ -49,7 +49,7 @@ def get_pascal_triangle_unique_coefficients(depth: int) -> set[int]:
     """
     coefficients = {1}
     previous_coefficients = [1]
-    for step in range(2, depth + 1):
+    for _ in range(2, depth + 1):
         coefficients_begins_one = previous_coefficients + [0]
         coefficients_ends_one = [0] + previous_coefficients
         previous_coefficients = []

scheduling/multi_level_feedback_queue.py

@@ -205,7 +205,7 @@ class MLFQ:
         """
         finished: deque[Process] = deque()  # sequence deque of terminated process
         # just for 1 cycle and unfinished processes will go back to queue
-        for i in range(len(ready_queue)):
+        for _ in range(len(ready_queue)):
             cp = ready_queue.popleft()  # current process
 
             # if process's arrival time is later than current time, update current time

sorts/double_sort.py

@@ -15,7 +15,7 @@ def double_sort(lst):
     True
     """
     no_of_elements = len(lst)
-    for i in range(
+    for _ in range(
         0, int(((no_of_elements - 1) / 2) + 1)
     ):  # we don't need to traverse to end of list as
         for j in range(0, no_of_elements - 1):

web_programming/open_google_results.py

@@ -1,10 +1,10 @@
 import webbrowser
 from sys import argv
-from urllib.parse import quote, parse_qs
-from fake_useragent import UserAgent
+from urllib.parse import parse_qs, quote
 
 import requests
 from bs4 import BeautifulSoup
+from fake_useragent import UserAgent
 
 if __name__ == "__main__":
     if len(argv) > 1:
@@ -18,9 +18,7 @@ if __name__ == "__main__":
 
     res = requests.get(
         url,
-        headers={
-            "User-Agent": str(UserAgent().random)
-        },
+        headers={"User-Agent": str(UserAgent().random)},
     )
 
     try: