translation: Add Python and Java code for EN version (#1345)

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* Add Python and Java code for EN version

en/codes/python/chapter_sorting/bubble_sort.py

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+"""
+File: bubble_sort.py
+Created Time: 2022-11-25
+Author: timi (xisunyy@163.com)
+"""
+
+
+def bubble_sort(nums: list[int]):
+    """Bubble sort"""
+    n = len(nums)
+    # Outer loop: unsorted range is [0, i]
+    for i in range(n - 1, 0, -1):
+        # Inner loop: swap the largest element in the unsorted range [0, i] to the right end of the range
+        for j in range(i):
+            if nums[j] > nums[j + 1]:
+                # Swap nums[j] and nums[j + 1]
+                nums[j], nums[j + 1] = nums[j + 1], nums[j]
+
+
+def bubble_sort_with_flag(nums: list[int]):
+    """Bubble sort (optimized with flag)"""
+    n = len(nums)
+    # Outer loop: unsorted range is [0, i]
+    for i in range(n - 1, 0, -1):
+        flag = False  # Initialize flag
+        # Inner loop: swap the largest element in the unsorted range [0, i] to the right end of the range
+        for j in range(i):
+            if nums[j] > nums[j + 1]:
+                # Swap nums[j] and nums[j + 1]
+                nums[j], nums[j + 1] = nums[j + 1], nums[j]
+                flag = True  # Record swapped elements
+        if not flag:
+            break  # If no elements were swapped in this round of "bubbling", exit
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    nums = [4, 1, 3, 1, 5, 2]
+    bubble_sort(nums)
+    print("Bubble sort completed nums =", nums)
+
+    nums1 = [4, 1, 3, 1, 5, 2]
+    bubble_sort_with_flag(nums1)
+    print("Bubble sort completed nums =", nums1)

en/codes/python/chapter_sorting/bucket_sort.py

@@ -0,0 +1,35 @@
+"""
+File: bucket_sort.py
+Created Time: 2023-03-30
+Author: krahets (krahets@163.com)
+"""
+
+
+def bucket_sort(nums: list[float]):
+    """Bucket sort"""
+    # Initialize k = n/2 buckets, expected to allocate 2 elements per bucket
+    k = len(nums) // 2
+    buckets = [[] for _ in range(k)]
+    # 1. Distribute array elements into various buckets
+    for num in nums:
+        # Input data range is [0, 1), use num * k to map to index range [0, k-1]
+        i = int(num * k)
+        # Add num to bucket i
+        buckets[i].append(num)
+    # 2. Sort each bucket
+    for bucket in buckets:
+        # Use built-in sorting function, can also replace with other sorting algorithms
+        bucket.sort()
+    # 3. Traverse buckets to merge results
+    i = 0
+    for bucket in buckets:
+        for num in bucket:
+            nums[i] = num
+            i += 1
+
+
+if __name__ == "__main__":
+    # Assume input data is floating point, range [0, 1)
+    nums = [0.49, 0.96, 0.82, 0.09, 0.57, 0.43, 0.91, 0.75, 0.15, 0.37]
+    bucket_sort(nums)
+    print("Bucket sort completed nums =", nums)

en/codes/python/chapter_sorting/counting_sort.py

@@ -0,0 +1,64 @@
+"""
+File: counting_sort.py
+Created Time: 2023-03-21
+Author: krahets (krahets@163.com)
+"""
+
+
+def counting_sort_naive(nums: list[int]):
+    """Counting sort"""
+    # Simple implementation, cannot be used for sorting objects
+    # 1. Count the maximum element m in the array
+    m = 0
+    for num in nums:
+        m = max(m, num)
+    # 2. Count the occurrence of each digit
+    # counter[num] represents the occurrence of num
+    counter = [0] * (m + 1)
+    for num in nums:
+        counter[num] += 1
+    # 3. Traverse counter, filling each element back into the original array nums
+    i = 0
+    for num in range(m + 1):
+        for _ in range(counter[num]):
+            nums[i] = num
+            i += 1
+
+
+def counting_sort(nums: list[int]):
+    """Counting sort"""
+    # Complete implementation, can sort objects and is a stable sort
+    # 1. Count the maximum element m in the array
+    m = max(nums)
+    # 2. Count the occurrence of each digit
+    # counter[num] represents the occurrence of num
+    counter = [0] * (m + 1)
+    for num in nums:
+        counter[num] += 1
+    # 3. Calculate the prefix sum of counter, converting "occurrence count" to "tail index"
+    # counter[num]-1 is the last index where num appears in res
+    for i in range(m):
+        counter[i + 1] += counter[i]
+    # 4. Traverse nums in reverse order, placing each element into the result array res
+    # Initialize the array res to record results
+    n = len(nums)
+    res = [0] * n
+    for i in range(n - 1, -1, -1):
+        num = nums[i]
+        res[counter[num] - 1] = num  # Place num at the corresponding index
+        counter[num] -= 1  # Decrement the prefix sum by 1, getting the next index to place num
+    # Use result array res to overwrite the original array nums
+    for i in range(n):
+        nums[i] = res[i]
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    nums = [1, 0, 1, 2, 0, 4, 0, 2, 2, 4]
+
+    counting_sort_naive(nums)
+    print(f"Counting sort (unable to sort objects) completed nums = {nums}")
+
+    nums1 = [1, 0, 1, 2, 0, 4, 0, 2, 2, 4]
+    counting_sort(nums1)
+    print(f"Counting sort completed nums1 = {nums1}")

en/codes/python/chapter_sorting/heap_sort.py

@@ -0,0 +1,45 @@
+"""
+File: heap_sort.py
+Created Time: 2023-05-24
+Author: krahets (krahets@163.com)
+"""
+
+
+def sift_down(nums: list[int], n: int, i: int):
+    """Heap length is n, start heapifying node i, from top to bottom"""
+    while True:
+        # Determine the largest node among i, l, r, noted as ma
+        l = 2 * i + 1
+        r = 2 * i + 2
+        ma = i
+        if l < n and nums[l] > nums[ma]:
+            ma = l
+        if r < n and nums[r] > nums[ma]:
+            ma = r
+        # If node i is the largest or indices l, r are out of bounds, no further heapification needed, break
+        if ma == i:
+            break
+        # Swap two nodes
+        nums[i], nums[ma] = nums[ma], nums[i]
+        # Loop downwards heapification
+        i = ma
+
+
+def heap_sort(nums: list[int]):
+    """Heap sort"""
+    # Build heap operation: heapify all nodes except leaves
+    for i in range(len(nums) // 2 - 1, -1, -1):
+        sift_down(nums, len(nums), i)
+    # Extract the largest element from the heap and repeat for n-1 rounds
+    for i in range(len(nums) - 1, 0, -1):
+        # Swap the root node with the rightmost leaf node (swap the first element with the last element)
+        nums[0], nums[i] = nums[i], nums[0]
+        # Start heapifying the root node, from top to bottom
+        sift_down(nums, i, 0)
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    nums = [4, 1, 3, 1, 5, 2]
+    heap_sort(nums)
+    print("Heap sort completed nums =", nums)

en/codes/python/chapter_sorting/insertion_sort.py

@@ -0,0 +1,25 @@
+"""
+File: insertion_sort.py
+Created Time: 2022-11-25
+Author: timi (xisunyy@163.com)
+"""
+
+
+def insertion_sort(nums: list[int]):
+    """Insertion sort"""
+    # Outer loop: sorted range is [0, i-1]
+    for i in range(1, len(nums)):
+        base = nums[i]
+        j = i - 1
+        # Inner loop: insert base into the correct position within the sorted range [0, i-1]
+        while j >= 0 and nums[j] > base:
+            nums[j + 1] = nums[j]  # Move nums[j] to the right by one position
+            j -= 1
+        nums[j + 1] = base  # Assign base to the correct position
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    nums = [4, 1, 3, 1, 5, 2]
+    insertion_sort(nums)
+    print("Insertion sort completed nums =", nums)

en/codes/python/chapter_sorting/merge_sort.py

@@ -0,0 +1,55 @@
+"""
+File: merge_sort.py
+Created Time: 2022-11-25
+Author: timi (xisunyy@163.com), krahets (krahets@163.com)
+"""
+
+
+def merge(nums: list[int], left: int, mid: int, right: int):
+    """Merge left subarray and right subarray"""
+    # Left subarray interval is [left, mid], right subarray interval is [mid+1, right]
+    # Create a temporary array tmp to store the merged results
+    tmp = [0] * (right - left + 1)
+    # Initialize the start indices of the left and right subarrays
+    i, j, k = left, mid + 1, 0
+    # While both subarrays still have elements, compare and copy the smaller element into the temporary array
+    while i <= mid and j <= right:
+        if nums[i] <= nums[j]:
+            tmp[k] = nums[i]
+            i += 1
+        else:
+            tmp[k] = nums[j]
+            j += 1
+        k += 1
+    # Copy the remaining elements of the left and right subarrays into the temporary array
+    while i <= mid:
+        tmp[k] = nums[i]
+        i += 1
+        k += 1
+    while j <= right:
+        tmp[k] = nums[j]
+        j += 1
+        k += 1
+    # Copy the elements from the temporary array tmp back to the original array nums at the corresponding interval
+    for k in range(0, len(tmp)):
+        nums[left + k] = tmp[k]
+
+
+def merge_sort(nums: list[int], left: int, right: int):
+    """Merge sort"""
+    # Termination condition
+    if left >= right:
+        return  # Terminate recursion when subarray length is 1
+    # Partition stage
+    mid = (left + right) // 2  # Calculate midpoint
+    merge_sort(nums, left, mid)  # Recursively process the left subarray
+    merge_sort(nums, mid + 1, right)  # Recursively process the right subarray
+    # Merge stage
+    merge(nums, left, mid, right)
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    nums = [7, 3, 2, 6, 0, 1, 5, 4]
+    merge_sort(nums, 0, len(nums) - 1)
+    print("Merge sort completed nums =", nums)

en/codes/python/chapter_sorting/quick_sort.py

@@ -0,0 +1,129 @@
+"""
+File: quick_sort.py
+Created Time: 2022-11-25
+Author: timi (xisunyy@163.com)
+"""
+
+
+class QuickSort:
+    """Quick sort class"""
+
+    def partition(self, nums: list[int], left: int, right: int) -> int:
+        """Partition"""
+        # Use nums[left] as the pivot
+        i, j = left, right
+        while i < j:
+            while i < j and nums[j] >= nums[left]:
+                j -= 1  # Search from right to left for the first element smaller than the pivot
+            while i < j and nums[i] <= nums[left]:
+                i += 1  # Search from left to right for the first element greater than the pivot
+            # Swap elements
+            nums[i], nums[j] = nums[j], nums[i]
+        # Swap the pivot to the boundary between the two subarrays
+        nums[i], nums[left] = nums[left], nums[i]
+        return i  # Return the index of the pivot
+
+    def quick_sort(self, nums: list[int], left: int, right: int):
+        """Quick sort"""
+        # Terminate recursion when subarray length is 1
+        if left >= right:
+            return
+        # Partition
+        pivot = self.partition(nums, left, right)
+        # Recursively process the left subarray and right subarray
+        self.quick_sort(nums, left, pivot - 1)
+        self.quick_sort(nums, pivot + 1, right)
+
+
+class QuickSortMedian:
+    """Quick sort class (median pivot optimization)"""
+
+    def median_three(self, nums: list[int], left: int, mid: int, right: int) -> int:
+        """Select the median of three candidate elements"""
+        l, m, r = nums[left], nums[mid], nums[right]
+        if (l <= m <= r) or (r <= m <= l):
+            return mid  # m is between l and r
+        if (m <= l <= r) or (r <= l <= m):
+            return left  # l is between m and r
+        return right
+
+    def partition(self, nums: list[int], left: int, right: int) -> int:
+        """Partition (median of three)"""
+        # Use nums[left] as the pivot
+        med = self.median_three(nums, left, (left + right) // 2, right)
+        # Swap the median to the array's leftmost position
+        nums[left], nums[med] = nums[med], nums[left]
+        # Use nums[left] as the pivot
+        i, j = left, right
+        while i < j:
+            while i < j and nums[j] >= nums[left]:
+                j -= 1  # Search from right to left for the first element smaller than the pivot
+            while i < j and nums[i] <= nums[left]:
+                i += 1  # Search from left to right for the first element greater than the pivot
+            # Swap elements
+            nums[i], nums[j] = nums[j], nums[i]
+        # Swap the pivot to the boundary between the two subarrays
+        nums[i], nums[left] = nums[left], nums[i]
+        return i  # Return the index of the pivot
+
+    def quick_sort(self, nums: list[int], left: int, right: int):
+        """Quick sort"""
+        # Terminate recursion when subarray length is 1
+        if left >= right:
+            return
+        # Partition
+        pivot = self.partition(nums, left, right)
+        # Recursively process the left subarray and right subarray
+        self.quick_sort(nums, left, pivot - 1)
+        self.quick_sort(nums, pivot + 1, right)
+
+
+class QuickSortTailCall:
+    """Quick sort class (tail recursion optimization)"""
+
+    def partition(self, nums: list[int], left: int, right: int) -> int:
+        """Partition"""
+        # Use nums[left] as the pivot
+        i, j = left, right
+        while i < j:
+            while i < j and nums[j] >= nums[left]:
+                j -= 1  # Search from right to left for the first element smaller than the pivot
+            while i < j and nums[i] <= nums[left]:
+                i += 1  # Search from left to right for the first element greater than the pivot
+            # Swap elements
+            nums[i], nums[j] = nums[j], nums[i]
+        # Swap the pivot to the boundary between the two subarrays
+        nums[i], nums[left] = nums[left], nums[i]
+        return i  # Return the index of the pivot
+
+    def quick_sort(self, nums: list[int], left: int, right: int):
+        """Quick sort (tail recursion optimization)"""
+        # Terminate when subarray length is 1
+        while left < right:
+            # Partition operation
+            pivot = self.partition(nums, left, right)
+            # Perform quick sort on the shorter of the two subarrays
+            if pivot - left < right - pivot:
+                self.quick_sort(nums, left, pivot - 1)  # Recursively sort the left subarray
+                left = pivot + 1  # Remaining unsorted interval is [pivot + 1, right]
+            else:
+                self.quick_sort(nums, pivot + 1, right)  # Recursively sort the right subarray
+                right = pivot - 1  # Remaining unsorted interval is [left, pivot - 1]
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Quick sort
+    nums = [2, 4, 1, 0, 3, 5]
+    QuickSort().quick_sort(nums, 0, len(nums) - 1)
+    print("Quick sort completed nums =", nums)
+
+    # Quick sort (median pivot optimization)
+    nums1 = [2, 4, 1, 0, 3, 5]
+    QuickSortMedian().quick_sort(nums1, 0, len(nums1) - 1)
+    print("Quick sort (median pivot optimization) completed nums =", nums1)
+
+    # Quick sort (tail recursion optimization)
+    nums2 = [2, 4, 1, 0, 3, 5]
+    QuickSortTailCall().quick_sort(nums2, 0, len(nums2) - 1)
+    print("Quick sort (tail recursion optimization) completed nums =", nums2)

en/codes/python/chapter_sorting/radix_sort.py

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+"""
+File: radix_sort.py
+Created Time: 2023-03-26
+Author: krahets (krahets@163.com)
+"""
+
+
+def digit(num: int, exp: int) -> int:
+    """Get the k-th digit of element num, where exp = 10^(k-1)"""
+    # Passing exp instead of k can avoid repeated expensive exponentiation here
+    return (num // exp) % 10
+
+
+def counting_sort_digit(nums: list[int], exp: int):
+    """Counting sort (based on nums k-th digit)"""
+    # Decimal digit range is 0~9, therefore need a bucket array of length 10
+    counter = [0] * 10
+    n = len(nums)
+    # Count the occurrence of digits 0~9
+    for i in range(n):
+        d = digit(nums[i], exp)  # Get the k-th digit of nums[i], noted as d
+        counter[d] += 1  # Count the occurrence of digit d
+    # Calculate prefix sum, converting "occurrence count" into "array index"
+    for i in range(1, 10):
+        counter[i] += counter[i - 1]
+    # Traverse in reverse, based on bucket statistics, place each element into res
+    res = [0] * n
+    for i in range(n - 1, -1, -1):
+        d = digit(nums[i], exp)
+        j = counter[d] - 1  # Get the index j for d in the array
+        res[j] = nums[i]  # Place the current element at index j
+        counter[d] -= 1  # Decrease the count of d by 1
+    # Use result to overwrite the original array nums
+    for i in range(n):
+        nums[i] = res[i]
+
+
+def radix_sort(nums: list[int]):
+    """Radix sort"""
+    # Get the maximum element of the array, used to determine the maximum number of digits
+    m = max(nums)
+    # Traverse from the lowest to the highest digit
+    exp = 1
+    while exp <= m:
+        # Perform counting sort on the k-th digit of array elements
+        # k = 1 -> exp = 1
+        # k = 2 -> exp = 10
+        # i.e., exp = 10^(k-1)
+        counting_sort_digit(nums, exp)
+        exp *= 10
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Radix sort
+    nums = [
+        10546151,
+        35663510,
+        42865989,
+        34862445,
+        81883077,
+        88906420,
+        72429244,
+        30524779,
+        82060337,
+        63832996,
+    ]
+    radix_sort(nums)
+    print("Radix sort completed nums =", nums)

en/codes/python/chapter_sorting/selection_sort.py

@@ -0,0 +1,26 @@
+"""
+File: selection_sort.py
+Created Time: 2023-05-22
+Author: krahets (krahets@163.com)
+"""
+
+
+def selection_sort(nums: list[int]):
+    """Selection sort"""
+    n = len(nums)
+    # Outer loop: unsorted range is [i, n-1]
+    for i in range(n - 1):
+        # Inner loop: find the smallest element within the unsorted range
+        k = i
+        for j in range(i + 1, n):
+            if nums[j] < nums[k]:
+                k = j  # Record the index of the smallest element
+        # Swap the smallest element with the first element of the unsorted range
+        nums[i], nums[k] = nums[k], nums[i]
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    nums = [4, 1, 3, 1, 5, 2]
+    selection_sort(nums)
+    print("Selection sort completed nums =", nums)