Merge branch 'TheAlgorithms:master' into master

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Siddharth Warrier 2023-10-03 13:15:36 +05:30 committed by GitHub
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4 changed files with 3 additions and 122 deletions

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@ -16,7 +16,7 @@ repos:
- id: auto-walrus
- repo: https://github.com/astral-sh/ruff-pre-commit
rev: v0.0.291
rev: v0.0.292
hooks:
- id: ruff
@ -33,7 +33,7 @@ repos:
- tomli
- repo: https://github.com/tox-dev/pyproject-fmt
rev: "1.1.0"
rev: "1.2.0"
hooks:
- id: pyproject-fmt

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@ -233,6 +233,7 @@
* [Merge Two Lists](data_structures/linked_list/merge_two_lists.py)
* [Middle Element Of Linked List](data_structures/linked_list/middle_element_of_linked_list.py)
* [Print Reverse](data_structures/linked_list/print_reverse.py)
* [Reverse K Group](data_structures/linked_list/reverse_k_group.py)
* [Rotate To The Right](data_structures/linked_list/rotate_to_the_right.py)
* [Singly Linked List](data_structures/linked_list/singly_linked_list.py)
* [Skip List](data_structures/linked_list/skip_list.py)

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@ -1,69 +0,0 @@
"""
Minimax helps to achieve maximum score in a game by checking all possible moves.
"""
from __future__ import annotations
import math
def minimax(
depth: int, node_index: int, is_max: bool, scores: list[int], height: float
) -> int:
"""
depth is current depth in game tree.
node_index is index of current node in scores[].
scores[] contains the leaves of game tree.
height is maximum height of game tree.
>>> scores = [90, 23, 6, 33, 21, 65, 123, 34423]
>>> height = math.log(len(scores), 2)
>>> minimax(0, 0, True, scores, height)
65
>>> minimax(-1, 0, True, scores, height)
Traceback (most recent call last):
...
ValueError: Depth cannot be less than 0
>>> minimax(0, 0, True, [], 2)
Traceback (most recent call last):
...
ValueError: Scores cannot be empty
>>> scores = [3, 5, 2, 9, 12, 5, 23, 23]
>>> height = math.log(len(scores), 2)
>>> minimax(0, 0, True, scores, height)
12
"""
if depth < 0:
raise ValueError("Depth cannot be less than 0")
if not scores:
raise ValueError("Scores cannot be empty")
if depth == height:
return scores[node_index]
return (
max(
minimax(depth + 1, node_index * 2, False, scores, height),
minimax(depth + 1, node_index * 2 + 1, False, scores, height),
)
if is_max
else min(
minimax(depth + 1, node_index * 2, True, scores, height),
minimax(depth + 1, node_index * 2 + 1, True, scores, height),
)
)
def main() -> None:
scores = [90, 23, 6, 33, 21, 65, 123, 34423]
height = math.log(len(scores), 2)
print(f"Optimal value : {minimax(0, 0, True, scores, height)}")
if __name__ == "__main__":
import doctest
doctest.testmod()
main()

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@ -1,51 +0,0 @@
import random
from .binary_exp_mod import bin_exp_mod
# This is a probabilistic check to test primality, useful for big numbers!
# if it's a prime, it will return true
# if it's not a prime, the chance of it returning true is at most 1/4**prec
def is_prime_big(n, prec=1000):
"""
>>> from maths.prime_check import is_prime
>>> # all(is_prime_big(i) == is_prime(i) for i in range(1000)) # 3.45s
>>> all(is_prime_big(i) == is_prime(i) for i in range(256))
True
"""
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
d = n - 1
exp = 0
while d % 2 == 0:
d /= 2
exp += 1
# n - 1=d*(2**exp)
count = 0
while count < prec:
a = random.randint(2, n - 1)
b = bin_exp_mod(a, d, n)
if b != 1:
flag = True
for _ in range(exp):
if b == n - 1:
flag = False
break
b = b * b
b %= n
if flag:
return False
count += 1
return True
if __name__ == "__main__":
n = abs(int(input("Enter bound : ").strip()))
print("Here's the list of primes:")
print(", ".join(str(i) for i in range(n + 1) if is_prime_big(i)))