Pyupgrade to Python 3.9 (#4718)

* Pyupgrade to Python 3.9

* updating DIRECTORY.md

Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>

maths/area_under_curve.py

@@ -1,14 +1,15 @@
 """
 Approximates the area under the curve using the trapezoidal rule
 """
+from __future__ import annotations
 
-from typing import Callable, Union
+from typing import Callable
 
 
 def trapezoidal_area(
-    fnc: Callable[[Union[int, float]], Union[int, float]],
-    x_start: Union[int, float],
-    x_end: Union[int, float],
+    fnc: Callable[[int | float], int | float],
+    x_start: int | float,
+    x_end: int | float,
     steps: int = 100,
 ) -> float:
     """

maths/average_mean.py

@@ -1,7 +1,7 @@
-from typing import List
+from __future__ import annotations
 
 
-def mean(nums: List) -> float:
+def mean(nums: list) -> float:
     """
     Find mean of a list of numbers.
     Wiki: https://en.wikipedia.org/wiki/Mean

maths/average_median.py

@@ -1,7 +1,7 @@
-from typing import Union
+from __future__ import annotations
 
 
-def median(nums: list) -> Union[int, float]:
+def median(nums: list) -> int | float:
     """
     Find median of a list of numbers.
     Wiki: https://en.wikipedia.org/wiki/Median

maths/entropy.py

@@ -68,7 +68,7 @@ def calculate_prob(text: str) -> None:
             my_fir_sum += prob * math.log2(prob)  # entropy formula.
 
     # print entropy
-    print("{:.1f}".format(round(-1 * my_fir_sum)))
+    print(f"{round(-1 * my_fir_sum):.1f}")
 
     # two len string
     all_sum = sum(two_char_strings.values())
@@ -83,10 +83,10 @@ def calculate_prob(text: str) -> None:
                 my_sec_sum += prob * math.log2(prob)
 
     # print second entropy
-    print("{:.1f}".format(round(-1 * my_sec_sum)))
+    print(f"{round(-1 * my_sec_sum):.1f}")
 
     # print the difference between them
-    print("{:.1f}".format(round((-1 * my_sec_sum) - (-1 * my_fir_sum))))
+    print(f"{round((-1 * my_sec_sum) - (-1 * my_fir_sum)):.1f}")
 
 
 def analyze_text(text: str) -> tuple[dict, dict]:

maths/euclidean_distance.py

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 from typing import Iterable, Union
 
 import numpy as np

maths/extended_euclidean_algorithm.py

@@ -12,12 +12,12 @@ https://en.wikipedia.org/wiki/Extended_Euclidean_algorithm
 # @Email:  silentcat@protonmail.com
 # @Last modified by:   pikulet
 # @Last modified time: 2020-10-02
+from __future__ import annotations
 
 import sys
-from typing import Tuple
 
 
-def extended_euclidean_algorithm(a: int, b: int) -> Tuple[int, int]:
+def extended_euclidean_algorithm(a: int, b: int) -> tuple[int, int]:
     """
     Extended Euclidean Algorithm.
 

maths/hardy_ramanujanalgo.py

@@ -37,7 +37,7 @@ def exactPrimeFactorCount(n):
 if __name__ == "__main__":
     n = 51242183
     print(f"The number of distinct prime factors is/are {exactPrimeFactorCount(n)}")
-    print("The value of log(log(n)) is {:.4f}".format(math.log(math.log(n))))
+    print(f"The value of log(log(n)) is {math.log(math.log(n)):.4f}")
 
     """
     The number of distinct prime factors is/are 3

maths/line_length.py

@@ -1,11 +1,13 @@
+from __future__ import annotations
+
 import math
-from typing import Callable, Union
+from typing import Callable
 
 
 def line_length(
-    fnc: Callable[[Union[int, float]], Union[int, float]],
-    x_start: Union[int, float],
-    x_end: Union[int, float],
+    fnc: Callable[[int | float], int | float],
+    x_start: int | float,
+    x_end: int | float,
     steps: int = 100,
 ) -> float:
 

maths/max_sum_sliding_window.py

@@ -6,10 +6,10 @@ Instead of using a nested for loop, in a Brute force approach we will use a tech
 called 'Window sliding technique' where the nested loops can be converted to a single
 loop to reduce time complexity.
 """
-from typing import List
+from __future__ import annotations
 
 
-def max_sum_in_array(array: List[int], k: int) -> int:
+def max_sum_in_array(array: list[int], k: int) -> int:
     """
     Returns the maximum sum of k consecutive elements
     >>> arr = [1, 4, 2, 10, 2, 3, 1, 0, 20]

maths/median_of_two_arrays.py

@@ -1,7 +1,7 @@
-from typing import List
+from __future__ import annotations
 
 
-def median_of_two_arrays(nums1: List[float], nums2: List[float]) -> float:
+def median_of_two_arrays(nums1: list[float], nums2: list[float]) -> float:
     """
     >>> median_of_two_arrays([1, 2], [3])
     2

maths/numerical_integration.py

@@ -1,14 +1,15 @@
 """
 Approximates the area under the curve using the trapezoidal rule
 """
+from __future__ import annotations
 
-from typing import Callable, Union
+from typing import Callable
 
 
 def trapezoidal_area(
-    fnc: Callable[[Union[int, float]], Union[int, float]],
-    x_start: Union[int, float],
-    x_end: Union[int, float],
+    fnc: Callable[[int | float], int | float],
+    x_start: int | float,
+    x_end: int | float,
     steps: int = 100,
 ) -> float:
 

maths/sieve_of_eratosthenes.py

@@ -10,13 +10,12 @@ Reference: https://en.wikipedia.org/wiki/Sieve_of_Eratosthenes
 doctest provider: Bruno Simas Hadlich (https://github.com/brunohadlich)
 Also thanks to Dmitry (https://github.com/LizardWizzard) for finding the problem
 """
-
+from __future__ import annotations
 
 import math
-from typing import List
 
 
-def prime_sieve(num: int) -> List[int]:
+def prime_sieve(num: int) -> list[int]:
     """
     Returns a list with all prime numbers up to n.
 

maths/volume.py

@@ -3,11 +3,12 @@ Find Volumes of Various Shapes.
 
 Wikipedia reference: https://en.wikipedia.org/wiki/Volume
 """
+from __future__ import annotations
+
 from math import pi, pow
-from typing import Union
 
 
-def vol_cube(side_length: Union[int, float]) -> float:
+def vol_cube(side_length: int | float) -> float:
     """
     Calculate the Volume of a Cube.