[pre-commit.ci] pre-commit autoupdate (TheAlgorithms#11322)

* [pre-commit.ci] pre-commit autoupdate

updates:
- [github.com/astral-sh/ruff-pre-commit: v0.2.2 → v0.3.2](astral-sh/ruff-pre-commit@v0.2.2...v0.3.2)
- [github.com/pre-commit/mirrors-mypy: v1.8.0 → v1.9.0](pre-commit/mirrors-mypy@v1.8.0...v1.9.0)

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

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

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: pre-commit-ci[bot]

.pre-commit-config.yaml

@@ -16,7 +16,7 @@ repos:
       - id: auto-walrus
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.2.2
+    rev: v0.3.2
     hooks:
       - id: ruff
       - id: ruff-format
@@ -47,7 +47,7 @@ repos:
       - id: validate-pyproject
 
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.8.0
+    rev: v1.9.0
     hooks:
       - id: mypy
         args:

backtracking/all_combinations.py

@@ -1,9 +1,10 @@
 """
-        In this problem, we want to determine all possible combinations of k
-        numbers out of 1 ... n. We use backtracking to solve this problem.
+In this problem, we want to determine all possible combinations of k
+numbers out of 1 ... n. We use backtracking to solve this problem.
 
-        Time complexity: O(C(n,k)) which is O(n choose k) = O((n!/(k! * (n - k)!))),
+Time complexity: O(C(n,k)) which is O(n choose k) = O((n!/(k! * (n - k)!))),
 """
+
 from __future__ import annotations
 
 from itertools import combinations

backtracking/all_permutations.py

@@ -1,10 +1,11 @@
 """
-        In this problem, we want to determine all possible permutations
-        of the given sequence. We use backtracking to solve this problem.
+In this problem, we want to determine all possible permutations
+of the given sequence. We use backtracking to solve this problem.
 
-        Time complexity: O(n! * n),
-        where n denotes the length of the given sequence.
+Time complexity: O(n! * n),
+where n denotes the length of the given sequence.
 """
+
 from __future__ import annotations
 
 

backtracking/all_subsequences.py

@@ -5,6 +5,7 @@
 Time complexity: O(2^n),
 where n denotes the length of the given sequence.
 """
+
 from __future__ import annotations
 
 from typing import Any

backtracking/coloring.py

@@ -1,9 +1,9 @@
 """
-    Graph Coloring also called "m coloring problem"
-    consists of coloring a given graph with at most m colors
-    such that no adjacent vertices are assigned the same color
+Graph Coloring also called "m coloring problem"
+consists of coloring a given graph with at most m colors
+such that no adjacent vertices are assigned the same color
 
-    Wikipedia: https://en.wikipedia.org/wiki/Graph_coloring
+Wikipedia: https://en.wikipedia.org/wiki/Graph_coloring
 """
 
 

backtracking/hamiltonian_cycle.py

@@ -1,10 +1,10 @@
 """
-    A Hamiltonian cycle (Hamiltonian circuit) is a graph cycle
-    through a graph that visits each node exactly once.
-    Determining whether such paths and cycles exist in graphs
-    is the 'Hamiltonian path problem', which is NP-complete.
+A Hamiltonian cycle (Hamiltonian circuit) is a graph cycle
+through a graph that visits each node exactly once.
+Determining whether such paths and cycles exist in graphs
+is the 'Hamiltonian path problem', which is NP-complete.
 
-    Wikipedia: https://en.wikipedia.org/wiki/Hamiltonian_path
+Wikipedia: https://en.wikipedia.org/wiki/Hamiltonian_path
 """
 
 

backtracking/minimax.py

@@ -7,6 +7,7 @@
 leaves of game tree is stored in scores[]
 height is maximum height of Game tree
 """
+
 from __future__ import annotations
 
 import math

backtracking/n_queens.py

@@ -1,12 +1,13 @@
 """
 
- The nqueens problem is of placing N queens on a N * N
- chess board such that no queen can attack any other queens placed
- on that chess board.
- This means that one queen cannot have any other queen on its horizontal, vertical and
- diagonal lines.
+The nqueens problem is of placing N queens on a N * N
+chess board such that no queen can attack any other queens placed
+on that chess board.
+This means that one queen cannot have any other queen on its horizontal, vertical and
+diagonal lines.
 
 """
+
 from __future__ import annotations
 
 solution = []

backtracking/n_queens_math.py

@@ -75,6 +75,7 @@
 for another one or vice versa.
 
 """
+
 from __future__ import annotations
 
 

backtracking/sudoku.py

@@ -9,6 +9,7 @@
 have solved the puzzle. else, we backtrack and place another number
 in that cell and repeat this process.
 """
+
 from __future__ import annotations
 
 Matrix = list[list[int]]

backtracking/sum_of_subsets.py

@@ -1,11 +1,12 @@
 """
-        The sum-of-subsetsproblem states that a set of non-negative integers, and a
-        value M, determine all possible subsets of the given set whose summation sum
-        equal to given M.
+The sum-of-subsetsproblem states that a set of non-negative integers, and a
+value M, determine all possible subsets of the given set whose summation sum
+equal to given M.
 
-        Summation of the chosen numbers must be equal to given number M and one number
-        can be used only once.
+Summation of the chosen numbers must be equal to given number M and one number
+can be used only once.
 """
+
 from __future__ import annotations
 
 

boolean_algebra/nor_gate.py

@@ -12,6 +12,7 @@
     Code provided by Akshaj Vishwanathan
 https://www.geeksforgeeks.org/logic-gates-in-python
 """
+
 from collections.abc import Callable
 
 

cellular_automata/conways_game_of_life.py

@@ -2,6 +2,7 @@
 Conway's Game of Life implemented in Python.
 https://en.wikipedia.org/wiki/Conway%27s_Game_of_Life
 """
+
 from __future__ import annotations
 
 from PIL import Image

cellular_automata/game_of_life.py

@@ -26,7 +26,8 @@
  4.
  Any dead cell with exactly three live neighbours be-
  comes a live cell, as if by reproduction.
- """
+"""
+
 import random
 import sys
 

cellular_automata/nagel_schrekenberg.py

@@ -24,6 +24,7 @@
 >>> simulate(construct_highway(5, 2, -2), 3, 0, 2)
 [[0, -1, 0, -1, 0], [0, -1, 0, -1, -1], [0, -1, -1, 1, -1], [-1, 1, -1, 0, -1]]
 """
+
 from random import randint, random
 
 

ciphers/a1z26.py

@@ -5,6 +5,7 @@
 https://www.dcode.fr/letter-number-cipher
 http://bestcodes.weebly.com/a1z26.html
 """
+
 from __future__ import annotations
 
 

ciphers/atbash.py

@@ -1,4 +1,5 @@
-""" https://en.wikipedia.org/wiki/Atbash """
+"""https://en.wikipedia.org/wiki/Atbash"""
+
 import string
 
 

ciphers/base32.py

@@ -3,6 +3,7 @@
 
 https://en.wikipedia.org/wiki/Base32
 """
+
 B32_CHARSET = "ABCDEFGHIJKLMNOPQRSTUVWXYZ234567"
 
 

ciphers/enigma_machine2.py

@@ -14,6 +14,7 @@
 
 Created by TrapinchO
 """
+
 from __future__ import annotations
 
 RotorPositionT = tuple[int, int, int]

ciphers/fractionated_morse_cipher.py

@@ -8,6 +8,7 @@
 
 http://practicalcryptography.com/ciphers/fractionated-morse-cipher/
 """
+
 import string
 
 MORSE_CODE_DICT = {

ciphers/hill_cipher.py

@@ -35,6 +35,7 @@
 https://www.youtube.com/watch?v=4RhLNDqcjpA
 
 """
+
 import string
 
 import numpy

ciphers/permutation_cipher.py

@@ -7,6 +7,7 @@
 
 For more info: https://www.nku.edu/~christensen/1402%20permutation%20ciphers.pdf
 """
+
 import random
 
 

ciphers/rail_fence_cipher.py

@@ -1,4 +1,4 @@
-""" https://en.wikipedia.org/wiki/Rail_fence_cipher """
+"""https://en.wikipedia.org/wiki/Rail_fence_cipher"""
 
 
 def encrypt(input_string: str, key: int) -> str:

ciphers/rsa_factorization.py

@@ -7,6 +7,7 @@
 More readable source: https://www.di-mgt.com.au/rsa_factorize_n.html
 large number can take minutes to factor, therefore are not included in doctest.
 """
+
 from __future__ import annotations
 
 import math

ciphers/xor_cipher.py

@@ -1,21 +1,22 @@
 """
-        author: Christian Bender
-        date: 21.12.2017
-        class: XORCipher
-
-        This class implements the XOR-cipher algorithm and provides
-        some useful methods for encrypting and decrypting strings and
-        files.
-
-        Overview about methods
-
-        - encrypt : list of char
-        - decrypt : list of char
-        - encrypt_string : str
-        - decrypt_string : str
-        - encrypt_file : boolean
-        - decrypt_file : boolean
+author: Christian Bender
+date: 21.12.2017
+class: XORCipher
+
+This class implements the XOR-cipher algorithm and provides
+some useful methods for encrypting and decrypting strings and
+files.
+
+Overview about methods
+
+- encrypt : list of char
+- decrypt : list of char
+- encrypt_string : str
+- decrypt_string : str
+- encrypt_file : boolean
+- decrypt_file : boolean
 """
+
 from __future__ import annotations
 
 

compression/burrows_wheeler.py

@@ -10,6 +10,7 @@
 original character. The BWT is thus a "free" method of improving the efficiency
 of text compression algorithms, costing only some extra computation.
 """
+
 from __future__ import annotations
 
 from typing import TypedDict

compression/lempel_ziv.py

@@ -1,6 +1,6 @@
 """
-    One of the several implementations of Lempel–Ziv–Welch compression algorithm
-    https://en.wikipedia.org/wiki/Lempel%E2%80%93Ziv%E2%80%93Welch
+One of the several implementations of Lempel–Ziv–Welch compression algorithm
+https://en.wikipedia.org/wiki/Lempel%E2%80%93Ziv%E2%80%93Welch
 """
 
 import math

compression/lempel_ziv_decompress.py

@@ -1,6 +1,6 @@
 """
-    One of the several implementations of Lempel–Ziv–Welch decompression algorithm
-    https://en.wikipedia.org/wiki/Lempel%E2%80%93Ziv%E2%80%93Welch
+One of the several implementations of Lempel–Ziv–Welch decompression algorithm
+https://en.wikipedia.org/wiki/Lempel%E2%80%93Ziv%E2%80%93Welch
 """
 
 import math

compression/lz77.py

@@ -28,7 +28,6 @@
 en.wikipedia.org/wiki/LZ77_and_LZ78
 """
 
-
 from dataclasses import dataclass
 
 __version__ = "0.1"

computer_vision/haralick_descriptors.py

@@ -2,6 +2,7 @@
 https://en.wikipedia.org/wiki/Image_texture
 https://en.wikipedia.org/wiki/Co-occurrence_matrix#Application_to_image_analysis
 """
+
 import imageio.v2 as imageio
 import numpy as np
 

computer_vision/horn_schunck.py

@@ -1,12 +1,12 @@
 """
-    The Horn-Schunck method estimates the optical flow for every single pixel of
-    a sequence of images.
-    It works by assuming brightness constancy between two consecutive frames
-    and smoothness in the optical flow.
-
-    Useful resources:
-    Wikipedia: https://en.wikipedia.org/wiki/Horn%E2%80%93Schunck_method
-    Paper: http://image.diku.dk/imagecanon/material/HornSchunckOptical_Flow.pdf
+The Horn-Schunck method estimates the optical flow for every single pixel of
+a sequence of images.
+It works by assuming brightness constancy between two consecutive frames
+and smoothness in the optical flow.
+
+Useful resources:
+Wikipedia: https://en.wikipedia.org/wiki/Horn%E2%80%93Schunck_method
+Paper: http://image.diku.dk/imagecanon/material/HornSchunckOptical_Flow.pdf
 """
 
 from typing import SupportsIndex

conversions/decimal_to_hexadecimal.py

@@ -1,4 +1,4 @@
-""" Convert Base 10 (Decimal) Values to Hexadecimal Representations """
+"""Convert Base 10 (Decimal) Values to Hexadecimal Representations"""
 
 # set decimal value for each hexadecimal digit
 values = {

conversions/prefix_conversions.py

@@ -1,6 +1,7 @@
 """
 Convert International System of Units (SI) and Binary prefixes
 """
+
 from __future__ import annotations
 
 from enum import Enum

conversions/temperature_conversions.py

@@ -1,4 +1,4 @@
-""" Convert between different units of temperature """
+"""Convert between different units of temperature"""
 
 
 def celsius_to_fahrenheit(celsius: float, ndigits: int = 2) -> float:

data_structures/arrays/pairs_with_given_sum.py

@@ -6,6 +6,7 @@
 
 https://practice.geeksforgeeks.org/problems/count-pairs-with-given-sum5022/0
 """
+
 from itertools import combinations