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

* Add the intial translation of code of all the languages

* test

* revert

* Remove

* Add Python and Java code for EN version

en/codes/python/.gitignore

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+__pycache__

en/codes/python/chapter_array_and_linkedlist/array.py

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+"""
+File: array.py
+Created Time: 2022-11-25
+Author: krahets (krahets@163.com)
+"""
+
+import random
+
+
+def random_access(nums: list[int]) -> int:
+    """Random access to elements"""
+    # Randomly select a number from the interval [0, len(nums)-1]
+    random_index = random.randint(0, len(nums) - 1)
+    # Retrieve and return a random element
+    random_num = nums[random_index]
+    return random_num
+
+
+# Note that Python's list is a dynamic array that can be extended
+# For ease of learning, this function treats the list as a static array
+def extend(nums: list[int], enlarge: int) -> list[int]:
+    """Extend array length"""
+    # Initialize an extended length array
+    res = [0] * (len(nums) + enlarge)
+    # Copy all elements from the original array to the new array
+    for i in range(len(nums)):
+        res[i] = nums[i]
+    # Return the new array after expansion
+    return res
+
+
+def insert(nums: list[int], num: int, index: int):
+    """Insert element num at `index`"""
+    # Move all elements after `index` one position backward
+    for i in range(len(nums) - 1, index, -1):
+        nums[i] = nums[i - 1]
+    # Assign num to the element at index
+    nums[index] = num
+
+
+def remove(nums: list[int], index: int):
+    """Remove the element at `index`"""
+    # Move all elements after `index` one position forward
+    for i in range(index, len(nums) - 1):
+        nums[i] = nums[i + 1]
+
+
+def traverse(nums: list[int]):
+    """Traverse array"""
+    count = 0
+    # Traverse array by index
+    for i in range(len(nums)):
+        count += nums[i]
+    # Traverse array elements
+    for num in nums:
+        count += num
+    # Traverse both data index and elements
+    for i, num in enumerate(nums):
+        count += nums[i]
+        count += num
+
+
+def find(nums: list[int], target: int) -> int:
+    """Search for a specified element in the array"""
+    for i in range(len(nums)):
+        if nums[i] == target:
+            return i
+    return -1
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize an array
+    arr = [0] * 5
+    print("Array arr =", arr)
+    nums = [1, 3, 2, 5, 4]
+    print("Array nums =", nums)
+
+    # Random access
+    random_num: int = random_access(nums)
+    print("Retrieve a random element in nums", random_num)
+
+    # Length extension
+    nums: list[int] = extend(nums, 3)
+    print("Extend the array length to 8, resulting in nums =", nums)
+
+    # Insert element
+    insert(nums, 6, 3)
+    print("Insert number 6 at index 3, resulting in nums =", nums)
+
+    # Remove element
+    remove(nums, 2)
+    print("Remove the element at index 2, resulting in nums =", nums)
+
+    # Traverse array
+    traverse(nums)
+
+    # Search for elements
+    index: int = find(nums, 3)
+    print("Search for element 3 in nums, resulting in index =", index)

en/codes/python/chapter_array_and_linkedlist/linked_list.py

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+"""
+File: linked_list.py
+Created Time: 2022-11-25
+Author: krahets (krahets@163.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import ListNode, print_linked_list
+
+
+def insert(n0: ListNode, P: ListNode):
+    """Insert node P after node n0 in the linked list"""
+    n1 = n0.next
+    P.next = n1
+    n0.next = P
+
+
+def remove(n0: ListNode):
+    """Remove the first node after node n0 in the linked list"""
+    if not n0.next:
+        return
+    # n0 -> P -> n1
+    P = n0.next
+    n1 = P.next
+    n0.next = n1
+
+
+def access(head: ListNode, index: int) -> ListNode | None:
+    """Access the node at `index` in the linked list"""
+    for _ in range(index):
+        if not head:
+            return None
+        head = head.next
+    return head
+
+
+def find(head: ListNode, target: int) -> int:
+    """Search for the first node with value target in the linked list"""
+    index = 0
+    while head:
+        if head.val == target:
+            return index
+        head = head.next
+        index += 1
+    return -1
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize linked list
+    # Initialize each node
+    n0 = ListNode(1)
+    n1 = ListNode(3)
+    n2 = ListNode(2)
+    n3 = ListNode(5)
+    n4 = ListNode(4)
+    # Build references between nodes
+    n0.next = n1
+    n1.next = n2
+    n2.next = n3
+    n3.next = n4
+    print("The initialized linked list is")
+    print_linked_list(n0)
+
+    # Insert node
+    p = ListNode(0)
+    insert(n0, p)
+    print("Linked list after inserting the node is")
+    print_linked_list(n0)
+
+    # Remove node
+    remove(n0)
+    print("Linked list after removing the node is")
+    print_linked_list(n0)
+
+    # Access node
+    node: ListNode = access(n0, 3)
+    print("The value of the node at index 3 in the linked list = {}".format(node.val))
+
+    # Search node
+    index: int = find(n0, 2)
+    print("The index of the node with value 2 in the linked list = {}".format(index))

en/codes/python/chapter_array_and_linkedlist/list.py

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+"""
+File: list.py
+Created Time: 2022-11-25
+Author: krahets (krahets@163.com)
+"""
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize list
+    nums: list[int] = [1, 3, 2, 5, 4]
+    print("\nList nums =", nums)
+
+    # Access element
+    x: int = nums[1]
+    print("\nAccess the element at index 1, resulting in x =", x)
+
+    # Update element
+    nums[1] = 0
+    print("\nUpdate the element at index 1 to 0, resulting in nums =", nums)
+
+    # Clear list
+    nums.clear()
+    print("\nAfter clearing the list, nums =", nums)
+
+    # Add element at the end
+    nums.append(1)
+    nums.append(3)
+    nums.append(2)
+    nums.append(5)
+    nums.append(4)
+    print("\nAfter adding the element, nums =", nums)
+
+    # Insert element in the middle
+    nums.insert(3, 6)
+    print("\nInsert number 6 at index 3, resulting in nums =", nums)
+
+    # Remove element
+    nums.pop(3)
+    print("\nRemove the element at index 3, resulting in nums =", nums)
+
+    # Traverse the list by index
+    count = 0
+    for i in range(len(nums)):
+        count += nums[i]
+    # Traverse the list elements
+    for num in nums:
+        count += num
+
+    # Concatenate two lists
+    nums1 = [6, 8, 7, 10, 9]
+    nums += nums1
+    print("\nConcatenate list nums1 to nums, resulting in nums =", nums)
+
+    # Sort list
+    nums.sort()
+    print("\nAfter sorting the list, nums =", nums)

en/codes/python/chapter_array_and_linkedlist/my_list.py

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+"""
+File: my_list.py
+Created Time: 2022-11-25
+Author: krahets (krahets@163.com)
+"""
+
+
+class MyList:
+    """List class"""
+
+    def __init__(self):
+        """Constructor"""
+        self._capacity: int = 10  # List capacity
+        self._arr: list[int] = [0] * self._capacity  # Array (stores list elements)
+        self._size: int = 0  # List length (current number of elements)
+        self._extend_ratio: int = 2  # Multiple for each list expansion
+
+    def size(self) -> int:
+        """Get list length (current number of elements)"""
+        return self._size
+
+    def capacity(self) -> int:
+        """Get list capacity"""
+        return self._capacity
+
+    def get(self, index: int) -> int:
+        """Access element"""
+        # If the index is out of bounds, throw an exception, as below
+        if index < 0 or index >= self._size:
+            raise IndexError("Index out of bounds")
+        return self._arr[index]
+
+    def set(self, num: int, index: int):
+        """Update element"""
+        if index < 0 or index >= self._size:
+            raise IndexError("Index out of bounds")
+        self._arr[index] = num
+
+    def add(self, num: int):
+        """Add element at the end"""
+        # When the number of elements exceeds capacity, trigger the expansion mechanism
+        if self.size() == self.capacity():
+            self.extend_capacity()
+        self._arr[self._size] = num
+        self._size += 1
+
+    def insert(self, num: int, index: int):
+        """Insert element in the middle"""
+        if index < 0 or index >= self._size:
+            raise IndexError("Index out of bounds")
+        # When the number of elements exceeds capacity, trigger the expansion mechanism
+        if self._size == self.capacity():
+            self.extend_capacity()
+        # Move all elements after `index` one position backward
+        for j in range(self._size - 1, index - 1, -1):
+            self._arr[j + 1] = self._arr[j]
+        self._arr[index] = num
+        # Update the number of elements
+        self._size += 1
+
+    def remove(self, index: int) -> int:
+        """Remove element"""
+        if index < 0 or index >= self._size:
+            raise IndexError("Index out of bounds")
+        num = self._arr[index]
+        # Move all elements after `index` one position forward
+        for j in range(index, self._size - 1):
+            self._arr[j] = self._arr[j + 1]
+        # Update the number of elements
+        self._size -= 1
+        # Return the removed element
+        return num
+
+    def extend_capacity(self):
+        """Extend list"""
+        # Create a new array of _extend_ratio times the length of the original array and copy the original array to the new array
+        self._arr = self._arr + [0] * self.capacity() * (self._extend_ratio - 1)
+        # Update list capacity
+        self._capacity = len(self._arr)
+
+    def to_array(self) -> list[int]:
+        """Return a list of valid lengths"""
+        return self._arr[: self._size]
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize list
+    nums = MyList()
+    # Add element at the end
+    nums.add(1)
+    nums.add(3)
+    nums.add(2)
+    nums.add(5)
+    nums.add(4)
+    print(f"List nums = {nums.to_array()} ，capacity = {nums.capacity()} ，length = {nums.size()}")
+
+    # Insert element in the middle
+    nums.insert(6, index=3)
+    print("Insert number 6 at index 3, resulting in nums =", nums.to_array())
+
+    # Remove element
+    nums.remove(3)
+    print("Remove the element at index 3, resulting in nums =", nums.to_array())
+
+    # Access element
+    num = nums.get(1)
+    print("Access the element at index 1, resulting in num =", num)
+
+    # Update element
+    nums.set(0, 1)
+    print("Update the element at index 1 to 0, resulting in nums =", nums.to_array())
+
+    # Test expansion mechanism
+    for i in range(10):
+        # At i = 5, the list length will exceed the list capacity, triggering the expansion mechanism at this time
+        nums.add(i)
+    print(f"After expansion, the list {nums.to_array()} ，capacity = {nums.capacity()} ，length = {nums.size()}")

en/codes/python/chapter_backtracking/n_queens.py

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+"""
+File: n_queens.py
+Created Time: 2023-04-26
+Author: krahets (krahets@163.com)
+"""
+
+
+def backtrack(
+    row: int,
+    n: int,
+    state: list[list[str]],
+    res: list[list[list[str]]],
+    cols: list[bool],
+    diags1: list[bool],
+    diags2: list[bool],
+):
+    """Backtracking algorithm: n queens"""
+    # When all rows are placed, record the solution
+    if row == n:
+        res.append([list(row) for row in state])
+        return
+    # Traverse all columns
+    for col in range(n):
+        # Calculate the main and minor diagonals corresponding to the cell
+        diag1 = row - col + n - 1
+        diag2 = row + col
+        # Pruning: do not allow queens on the column, main diagonal, or minor diagonal of the cell
+        if not cols[col] and not diags1[diag1] and not diags2[diag2]:
+            # Attempt: place the queen in the cell
+            state[row][col] = "Q"
+            cols[col] = diags1[diag1] = diags2[diag2] = True
+            # Place the next row
+            backtrack(row + 1, n, state, res, cols, diags1, diags2)
+            # Retract: restore the cell to an empty spot
+            state[row][col] = "#"
+            cols[col] = diags1[diag1] = diags2[diag2] = False
+
+
+def n_queens(n: int) -> list[list[list[str]]]:
+    """Solve n queens"""
+    # Initialize an n*n size chessboard, where 'Q' represents the queen and '#' represents an empty spot
+    state = [["#" for _ in range(n)] for _ in range(n)]
+    cols = [False] * n  # Record columns with queens
+    diags1 = [False] * (2 * n - 1)  # Record main diagonals with queens
+    diags2 = [False] * (2 * n - 1)  # Record minor diagonals with queens
+    res = []
+    backtrack(0, n, state, res, cols, diags1, diags2)
+
+    return res
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    n = 4
+    res = n_queens(n)
+
+    print(f"Input chessboard dimensions as {n}")
+    print(f"The total number of queen placement solutions is {len(res)}")
+    for state in res:
+        print("--------------------")
+        for row in state:
+            print(row)

en/codes/python/chapter_backtracking/permutations_i.py

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+"""
+File: permutations_i.py
+Created Time: 2023-04-15
+Author: krahets (krahets@163.com)
+"""
+
+
+def backtrack(
+    state: list[int], choices: list[int], selected: list[bool], res: list[list[int]]
+):
+    """Backtracking algorithm: Permutation I"""
+    # When the state length equals the number of elements, record the solution
+    if len(state) == len(choices):
+        res.append(list(state))
+        return
+    # Traverse all choices
+    for i, choice in enumerate(choices):
+        # Pruning: do not allow repeated selection of elements
+        if not selected[i]:
+            # Attempt: make a choice, update the state
+            selected[i] = True
+            state.append(choice)
+            # Proceed to the next round of selection
+            backtrack(state, choices, selected, res)
+            # Retract: undo the choice, restore to the previous state
+            selected[i] = False
+            state.pop()
+
+
+def permutations_i(nums: list[int]) -> list[list[int]]:
+    """Permutation I"""
+    res = []
+    backtrack(state=[], choices=nums, selected=[False] * len(nums), res=res)
+    return res
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    nums = [1, 2, 3]
+
+    res = permutations_i(nums)
+
+    print(f"Input array nums = {nums}")
+    print(f"All permutations res = {res}")

en/codes/python/chapter_backtracking/permutations_ii.py

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+"""
+File: permutations_ii.py
+Created Time: 2023-04-15
+Author: krahets (krahets@163.com)
+"""
+
+
+def backtrack(
+    state: list[int], choices: list[int], selected: list[bool], res: list[list[int]]
+):
+    """Backtracking algorithm: Permutation II"""
+    # When the state length equals the number of elements, record the solution
+    if len(state) == len(choices):
+        res.append(list(state))
+        return
+    # Traverse all choices
+    duplicated = set[int]()
+    for i, choice in enumerate(choices):
+        # Pruning: do not allow repeated selection of elements and do not allow repeated selection of equal elements
+        if not selected[i] and choice not in duplicated:
+            # Attempt: make a choice, update the state
+            duplicated.add(choice)  # Record selected element values
+            selected[i] = True
+            state.append(choice)
+            # Proceed to the next round of selection
+            backtrack(state, choices, selected, res)
+            # Retract: undo the choice, restore to the previous state
+            selected[i] = False
+            state.pop()
+
+
+def permutations_ii(nums: list[int]) -> list[list[int]]:
+    """Permutation II"""
+    res = []
+    backtrack(state=[], choices=nums, selected=[False] * len(nums), res=res)
+    return res
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    nums = [1, 2, 2]
+
+    res = permutations_ii(nums)
+
+    print(f"Input array nums = {nums}")
+    print(f"All permutations res = {res}")

en/codes/python/chapter_backtracking/preorder_traversal_i_compact.py

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+"""
+File: preorder_traversal_i_compact.py
+Created Time: 2023-04-15
+Author: krahets (krahets@163.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import TreeNode, print_tree, list_to_tree
+
+
+def pre_order(root: TreeNode):
+    """Pre-order traversal: Example one"""
+    if root is None:
+        return
+    if root.val == 7:
+        # Record solution
+        res.append(root)
+    pre_order(root.left)
+    pre_order(root.right)
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    root = list_to_tree([1, 7, 3, 4, 5, 6, 7])
+    print("\nInitialize binary tree")
+    print_tree(root)
+
+    # Pre-order traversal
+    res = list[TreeNode]()
+    pre_order(root)
+
+    print("\nOutput all nodes with value 7")
+    print([node.val for node in res])

en/codes/python/chapter_backtracking/preorder_traversal_ii_compact.py

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+"""
+File: preorder_traversal_ii_compact.py
+Created Time: 2023-04-15
+Author: krahets (krahets@163.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import TreeNode, print_tree, list_to_tree
+
+
+def pre_order(root: TreeNode):
+    """Pre-order traversal: Example two"""
+    if root is None:
+        return
+    # Attempt
+    path.append(root)
+    if root.val == 7:
+        # Record solution
+        res.append(list(path))
+    pre_order(root.left)
+    pre_order(root.right)
+    # Retract
+    path.pop()
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    root = list_to_tree([1, 7, 3, 4, 5, 6, 7])
+    print("\nInitialize binary tree")
+    print_tree(root)
+
+    # Pre-order traversal
+    path = list[TreeNode]()
+    res = list[list[TreeNode]]()
+    pre_order(root)
+
+    print("\nOutput all root-to-node 7 paths")
+    for path in res:
+        print([node.val for node in path])

en/codes/python/chapter_backtracking/preorder_traversal_iii_compact.py

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+"""
+File: preorder_traversal_iii_compact.py
+Created Time: 2023-04-15
+Author: krahets (krahets@163.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import TreeNode, print_tree, list_to_tree
+
+
+def pre_order(root: TreeNode):
+    """Pre-order traversal: Example three"""
+    # Pruning
+    if root is None or root.val == 3:
+        return
+    # Attempt
+    path.append(root)
+    if root.val == 7:
+        # Record solution
+        res.append(list(path))
+    pre_order(root.left)
+    pre_order(root.right)
+    # Retract
+    path.pop()
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    root = list_to_tree([1, 7, 3, 4, 5, 6, 7])
+    print("\nInitialize binary tree")
+    print_tree(root)
+
+    # Pre-order traversal
+    path = list[TreeNode]()
+    res = list[list[TreeNode]]()
+    pre_order(root)
+
+    print("\nOutput all root-to-node 7 paths, not including nodes with value 3")
+    for path in res:
+        print([node.val for node in path])

en/codes/python/chapter_backtracking/preorder_traversal_iii_template.py

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+"""
+File: preorder_traversal_iii_template.py
+Created Time: 2023-04-15
+Author: krahets (krahets@163.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import TreeNode, print_tree, list_to_tree
+
+
+def is_solution(state: list[TreeNode]) -> bool:
+    """Determine if the current state is a solution"""
+    return state and state[-1].val == 7
+
+
+def record_solution(state: list[TreeNode], res: list[list[TreeNode]]):
+    """Record solution"""
+    res.append(list(state))
+
+
+def is_valid(state: list[TreeNode], choice: TreeNode) -> bool:
+    """Determine if the choice is legal under the current state"""
+    return choice is not None and choice.val != 3
+
+
+def make_choice(state: list[TreeNode], choice: TreeNode):
+    """Update state"""
+    state.append(choice)
+
+
+def undo_choice(state: list[TreeNode], choice: TreeNode):
+    """Restore state"""
+    state.pop()
+
+
+def backtrack(
+    state: list[TreeNode], choices: list[TreeNode], res: list[list[TreeNode]]
+):
+    """Backtracking algorithm: Example three"""
+    # Check if it's a solution
+    if is_solution(state):
+        # Record solution
+        record_solution(state, res)
+    # Traverse all choices
+    for choice in choices:
+        # Pruning: check if the choice is legal
+        if is_valid(state, choice):
+            # Attempt: make a choice, update the state
+            make_choice(state, choice)
+            # Proceed to the next round of selection
+            backtrack(state, [choice.left, choice.right], res)
+            # Retract: undo the choice, restore to the previous state
+            undo_choice(state, choice)
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    root = list_to_tree([1, 7, 3, 4, 5, 6, 7])
+    print("\nInitialize binary tree")
+    print_tree(root)
+
+    # Backtracking algorithm
+    res = []
+    backtrack(state=[], choices=[root], res=res)
+
+    print("\nOutput all root-to-node 7 paths, requiring paths not to include nodes with value 3")
+    for path in res:
+        print([node.val for node in path])

en/codes/python/chapter_backtracking/subset_sum_i.py

@@ -0,0 +1,48 @@
+"""
+File: subset_sum_i.py
+Created Time: 2023-06-17
+Author: krahets (krahets@163.com)
+"""
+
+
+def backtrack(
+    state: list[int], target: int, choices: list[int], start: int, res: list[list[int]]
+):
+    """Backtracking algorithm: Subset Sum I"""
+    # When the subset sum equals target, record the solution
+    if target == 0:
+        res.append(list(state))
+        return
+    # Traverse all choices
+    # Pruning two: start traversing from start to avoid generating duplicate subsets
+    for i in range(start, len(choices)):
+        # Pruning one: if the subset sum exceeds target, end the loop immediately
+        # This is because the array is sorted, and later elements are larger, so the subset sum will definitely exceed target
+        if target - choices[i] < 0:
+            break
+        # Attempt: make a choice, update target, start
+        state.append(choices[i])
+        # Proceed to the next round of selection
+        backtrack(state, target - choices[i], choices, i, res)
+        # Retract: undo the choice, restore to the previous state
+        state.pop()
+
+
+def subset_sum_i(nums: list[int], target: int) -> list[list[int]]:
+    """Solve Subset Sum I"""
+    state = []  # State (subset)
+    nums.sort()  # Sort nums
+    start = 0  # Start point for traversal
+    res = []  # Result list (subset list)
+    backtrack(state, target, nums, start, res)
+    return res
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    nums = [3, 4, 5]
+    target = 9
+    res = subset_sum_i(nums, target)
+
+    print(f"Input array nums = {nums}, target = {target}")
+    print(f"All subsets equal to {target} res = {res}")

en/codes/python/chapter_backtracking/subset_sum_i_naive.py

@@ -0,0 +1,50 @@
+"""
+File: subset_sum_i_naive.py
+Created Time: 2023-06-17
+Author: krahets (krahets@163.com)
+"""
+
+
+def backtrack(
+    state: list[int],
+    target: int,
+    total: int,
+    choices: list[int],
+    res: list[list[int]],
+):
+    """Backtracking algorithm: Subset Sum I"""
+    # When the subset sum equals target, record the solution
+    if total == target:
+        res.append(list(state))
+        return
+    # Traverse all choices
+    for i in range(len(choices)):
+        # Pruning: if the subset sum exceeds target, skip that choice
+        if total + choices[i] > target:
+            continue
+        # Attempt: make a choice, update elements and total
+        state.append(choices[i])
+        # Proceed to the next round of selection
+        backtrack(state, target, total + choices[i], choices, res)
+        # Retract: undo the choice, restore to the previous state
+        state.pop()
+
+
+def subset_sum_i_naive(nums: list[int], target: int) -> list[list[int]]:
+    """Solve Subset Sum I (including duplicate subsets)"""
+    state = []  # State (subset)
+    total = 0  # Subset sum
+    res = []  # Result list (subset list)
+    backtrack(state, target, total, nums, res)
+    return res
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    nums = [3, 4, 5]
+    target = 9
+    res = subset_sum_i_naive(nums, target)
+
+    print(f"Input array nums = {nums}, target = {target}")
+    print(f"All subsets equal to {target} res = {res}")
+    print(f"Please note that the result of this method includes duplicate sets")

en/codes/python/chapter_backtracking/subset_sum_ii.py

@@ -0,0 +1,52 @@
+"""
+File: subset_sum_ii.py
+Created Time: 2023-06-17
+Author: krahets (krahets@163.com)
+"""
+
+
+def backtrack(
+    state: list[int], target: int, choices: list[int], start: int, res: list[list[int]]
+):
+    """Backtracking algorithm: Subset Sum II"""
+    # When the subset sum equals target, record the solution
+    if target == 0:
+        res.append(list(state))
+        return
+    # Traverse all choices
+    # Pruning two: start traversing from start to avoid generating duplicate subsets
+    # Pruning three: start traversing from start to avoid repeatedly selecting the same element
+    for i in range(start, len(choices)):
+        # Pruning one: if the subset sum exceeds target, end the loop immediately
+        # This is because the array is sorted, and later elements are larger, so the subset sum will definitely exceed target
+        if target - choices[i] < 0:
+            break
+        # Pruning four: if the element equals the left element, it indicates that the search branch is repeated, skip it
+        if i > start and choices[i] == choices[i - 1]:
+            continue
+        # Attempt: make a choice, update target, start
+        state.append(choices[i])
+        # Proceed to the next round of selection
+        backtrack(state, target - choices[i], choices, i + 1, res)
+        # Retract: undo the choice, restore to the previous state
+        state.pop()
+
+
+def subset_sum_ii(nums: list[int], target: int) -> list[list[int]]:
+    """Solve Subset Sum II"""
+    state = []  # State (subset)
+    nums.sort()  # Sort nums
+    start = 0  # Start point for traversal
+    res = []  # Result list (subset list)
+    backtrack(state, target, nums, start, res)
+    return res
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    nums = [4, 4, 5]
+    target = 9
+    res = subset_sum_ii(nums, target)
+
+    print(f"Input array nums = {nums}, target = {target}")
+    print(f"All subsets equal to {target} res = {res}")

en/codes/python/chapter_computational_complexity/iteration.py

@@ -0,0 +1,65 @@
+"""
+File: iteration.py
+Created Time: 2023-08-24
+Author: krahets (krahets@163.com)
+"""
+
+
+def for_loop(n: int) -> int:
+    """for loop"""
+    res = 0
+    # Loop sum 1, 2, ..., n-1, n
+    for i in range(1, n + 1):
+        res += i
+    return res
+
+
+def while_loop(n: int) -> int:
+    """while loop"""
+    res = 0
+    i = 1  # Initialize condition variable
+    # Loop sum 1, 2, ..., n-1, n
+    while i <= n:
+        res += i
+        i += 1  # Update condition variable
+    return res
+
+
+def while_loop_ii(n: int) -> int:
+    """while loop (two updates)"""
+    res = 0
+    i = 1  # Initialize condition variable
+    # Loop sum 1, 4, 10, ...
+    while i <= n:
+        res += i
+        # Update condition variable
+        i += 1
+        i *= 2
+    return res
+
+
+def nested_for_loop(n: int) -> str:
+    """Double for loop"""
+    res = ""
+    # Loop i = 1, 2, ..., n-1, n
+    for i in range(1, n + 1):
+        # Loop j = 1, 2, ..., n-1, n
+        for j in range(1, n + 1):
+            res += f"({i}, {j}), "
+    return res
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    n = 5
+    res = for_loop(n)
+    print(f"\nfor loop sum result res = {res}")
+
+    res = while_loop(n)
+    print(f"\nwhile loop sum result res = {res}")
+
+    res = while_loop_ii(n)
+    print(f"\nwhile loop (two updates) sum result res = {res}")
+
+    res = nested_for_loop(n)
+    print(f"\nDouble for loop traversal result {res}")

en/codes/python/chapter_computational_complexity/recursion.py

@@ -0,0 +1,69 @@
+"""
+File: recursion.py
+Created Time: 2023-08-24
+Author: krahets (krahets@163.com)
+"""
+
+
+def recur(n: int) -> int:
+    """Recursion"""
+    # Termination condition
+    if n == 1:
+        return 1
+    # Recursive: recursive call
+    res = recur(n - 1)
+    # Return: return result
+    return n + res
+
+
+def for_loop_recur(n: int) -> int:
+    """Simulate recursion with iteration"""
+    # Use an explicit stack to simulate the system call stack
+    stack = []
+    res = 0
+    # Recursive: recursive call
+    for i in range(n, 0, -1):
+        # Simulate "recursive" by "pushing onto the stack"
+        stack.append(i)
+    # Return: return result
+    while stack:
+        # Simulate "return" by "popping from the stack"
+        res += stack.pop()
+    # res = 1+2+3+...+n
+    return res
+
+
+def tail_recur(n, res):
+    """Tail recursion"""
+    # Termination condition
+    if n == 0:
+        return res
+    # Tail recursive call
+    return tail_recur(n - 1, res + n)
+
+
+def fib(n: int) -> int:
+    """Fibonacci sequence: Recursion"""
+    # Termination condition f(1) = 0, f(2) = 1
+    if n == 1 or n == 2:
+        return n - 1
+    # Recursive call f(n) = f(n-1) + f(n-2)
+    res = fib(n - 1) + fib(n - 2)
+    # Return result f(n)
+    return res
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    n = 5
+    res = recur(n)
+    print(f"\nRecursive function sum result res = {res}")
+
+    res = for_loop_recur(n)
+    print(f"\nSimulate recursion with iteration sum result res = {res}")
+
+    res = tail_recur(n, 0)
+    print(f"\nTail recursive function sum result res = {res}")
+
+    res = fib(n)
+    print(f"\nThe n th term of the Fibonacci sequence is {res}")

en/codes/python/chapter_computational_complexity/space_complexity.py

@@ -0,0 +1,90 @@
+"""
+File: space_complexity.py
+Created Time: 2022-11-25
+Author: krahets (krahets@163.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import ListNode, TreeNode, print_tree
+
+
+def function() -> int:
+    """Function"""
+    # Perform some operations
+    return 0
+
+
+def constant(n: int):
+    """Constant complexity"""
+    # Constants, variables, objects occupy O(1) space
+    a = 0
+    nums = [0] * 10000
+    node = ListNode(0)
+    # Variables in a loop occupy O(1) space
+    for _ in range(n):
+        c = 0
+    # Functions in a loop occupy O(1) space
+    for _ in range(n):
+        function()
+
+
+def linear(n: int):
+    """Linear complexity"""
+    # A list of length n occupies O(n) space
+    nums = [0] * n
+    # A hash table of length n occupies O(n) space
+    hmap = dict[int, str]()
+    for i in range(n):
+        hmap[i] = str(i)
+
+
+def linear_recur(n: int):
+    """Linear complexity (recursive implementation)"""
+    print("Recursive n =", n)
+    if n == 1:
+        return
+    linear_recur(n - 1)
+
+
+def quadratic(n: int):
+    """Quadratic complexity"""
+    # A two-dimensional list occupies O(n^2) space
+    num_matrix = [[0] * n for _ in range(n)]
+
+
+def quadratic_recur(n: int) -> int:
+    """Quadratic complexity (recursive implementation)"""
+    if n <= 0:
+        return 0
+    # Array nums length = n, n-1, ..., 2, 1
+    nums = [0] * n
+    return quadratic_recur(n - 1)
+
+
+def build_tree(n: int) -> TreeNode | None:
+    """Exponential complexity (building a full binary tree)"""
+    if n == 0:
+        return None
+    root = TreeNode(0)
+    root.left = build_tree(n - 1)
+    root.right = build_tree(n - 1)
+    return root
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    n = 5
+    # Constant complexity
+    constant(n)
+    # Linear complexity
+    linear(n)
+    linear_recur(n)
+    # Quadratic complexity
+    quadratic(n)
+    quadratic_recur(n)
+    # Exponential complexity
+    root = build_tree(n)
+    print_tree(root)

en/codes/python/chapter_computational_complexity/time_complexity.py

@@ -0,0 +1,151 @@
+"""
+File: time_complexity.py
+Created Time: 2022-11-25
+Author: krahets (krahets@163.com)
+"""
+
+
+def constant(n: int) -> int:
+    """Constant complexity"""
+    count = 0
+    size = 100000
+    for _ in range(size):
+        count += 1
+    return count
+
+
+def linear(n: int) -> int:
+    """Linear complexity"""
+    count = 0
+    for _ in range(n):
+        count += 1
+    return count
+
+
+def array_traversal(nums: list[int]) -> int:
+    """Linear complexity (traversing an array)"""
+    count = 0
+    # Loop count is proportional to the length of the array
+    for num in nums:
+        count += 1
+    return count
+
+
+def quadratic(n: int) -> int:
+    """Quadratic complexity"""
+    count = 0
+    # Loop count is squared in relation to the data size n
+    for i in range(n):
+        for j in range(n):
+            count += 1
+    return count
+
+
+def bubble_sort(nums: list[int]) -> int:
+    """Quadratic complexity (bubble sort)"""
+    count = 0  # Counter
+    # Outer loop: unsorted range is [0, i]
+    for i in range(len(nums) - 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]
+                tmp: int = nums[j]
+                nums[j] = nums[j + 1]
+                nums[j + 1] = tmp
+                count += 3  # Element swap includes 3 individual operations
+    return count
+
+
+def exponential(n: int) -> int:
+    """Exponential complexity (loop implementation)"""
+    count = 0
+    base = 1
+    # Cells split into two every round, forming the sequence 1, 2, 4, 8, ..., 2^(n-1)
+    for _ in range(n):
+        for _ in range(base):
+            count += 1
+        base *= 2
+    # count = 1 + 2 + 4 + 8 + .. + 2^(n-1) = 2^n - 1
+    return count
+
+
+def exp_recur(n: int) -> int:
+    """Exponential complexity (recursive implementation)"""
+    if n == 1:
+        return 1
+    return exp_recur(n - 1) + exp_recur(n - 1) + 1
+
+
+def logarithmic(n: int) -> int:
+    """Logarithmic complexity (loop implementation)"""
+    count = 0
+    while n > 1:
+        n = n / 2
+        count += 1
+    return count
+
+
+def log_recur(n: int) -> int:
+    """Logarithmic complexity (recursive implementation)"""
+    if n <= 1:
+        return 0
+    return log_recur(n / 2) + 1
+
+
+def linear_log_recur(n: int) -> int:
+    """Linear logarithmic complexity"""
+    if n <= 1:
+        return 1
+    count: int = linear_log_recur(n // 2) + linear_log_recur(n // 2)
+    for _ in range(n):
+        count += 1
+    return count
+
+
+def factorial_recur(n: int) -> int:
+    """Factorial complexity (recursive implementation)"""
+    if n == 0:
+        return 1
+    count = 0
+    # From 1 split into n
+    for _ in range(n):
+        count += factorial_recur(n - 1)
+    return count
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Can modify n to experience the trend of operation count changes under various complexities
+    n = 8
+    print("Input data size n =", n)
+
+    count: int = constant(n)
+    print("Constant complexity operation count =", count)
+
+    count: int = linear(n)
+    print("Linear complexity operation count =", count)
+    count: int = array_traversal([0] * n)
+    print("Linear complexity (traversing an array) operation count =", count)
+
+    count: int = quadratic(n)
+    print("Quadratic complexity operation count =", count)
+    nums = [i for i in range(n, 0, -1)]  # [n, n-1, ..., 2, 1]
+    count: int = bubble_sort(nums)
+    print("Quadratic complexity (bubble sort) operation count =", count)
+
+    count: int = exponential(n)
+    print("Exponential complexity (loop implementation) operation count =", count)
+    count: int = exp_recur(n)
+    print("Exponential complexity (recursive implementation) operation count =", count)
+
+    count: int = logarithmic(n)
+    print("Logarithmic complexity (loop implementation) operation count =", count)
+    count: int = log_recur(n)
+    print("Logarithmic complexity (recursive implementation) operation count =", count)
+
+    count: int = linear_log_recur(n)
+    print("Linear logarithmic complexity (recursive implementation) operation count =", count)
+
+    count: int = factorial_recur(n)
+    print("Factorial complexity (recursive implementation) operation count =", count)

en/codes/python/chapter_computational_complexity/worst_best_time_complexity.py

@@ -0,0 +1,36 @@
+"""
+File: worst_best_time_complexity.py
+Created Time: 2022-11-25
+Author: krahets (krahets@163.com)
+"""
+
+import random
+
+
+def random_numbers(n: int) -> list[int]:
+    """Generate an array with elements: 1, 2, ..., n, order shuffled"""
+    # Generate array nums =: 1, 2, 3, ..., n
+    nums = [i for i in range(1, n + 1)]
+    # Randomly shuffle array elements
+    random.shuffle(nums)
+    return nums
+
+
+def find_one(nums: list[int]) -> int:
+    """Find the index of number 1 in array nums"""
+    for i in range(len(nums)):
+        # When element 1 is at the start of the array, achieve best time complexity O(1)
+        # When element 1 is at the end of the array, achieve worst time complexity O(n)
+        if nums[i] == 1:
+            return i
+    return -1
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    for i in range(10):
+        n = 100
+        nums: list[int] = random_numbers(n)
+        index: int = find_one(nums)
+        print("\nThe array [ 1, 2, ..., n ] after being shuffled =", nums)
+        print("Index of number 1 =", index)

en/codes/python/chapter_divide_and_conquer/binary_search_recur.py

@@ -0,0 +1,40 @@
+"""
+File: binary_search_recur.py
+Created Time: 2023-07-17
+Author: krahets (krahets@163.com)
+"""
+
+
+def dfs(nums: list[int], target: int, i: int, j: int) -> int:
+    """Binary search: problem f(i, j)"""
+    # If the interval is empty, indicating no target element, return -1
+    if i > j:
+        return -1
+    # Calculate midpoint index m
+    m = (i + j) // 2
+    if nums[m] < target:
+        # Recursive subproblem f(m+1, j)
+        return dfs(nums, target, m + 1, j)
+    elif nums[m] > target:
+        # Recursive subproblem f(i, m-1)
+        return dfs(nums, target, i, m - 1)
+    else:
+        # Found the target element, thus return its index
+        return m
+
+
+def binary_search(nums: list[int], target: int) -> int:
+    """Binary search"""
+    n = len(nums)
+    # Solve problem f(0, n-1)
+    return dfs(nums, target, 0, n - 1)
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    target = 6
+    nums = [1, 3, 6, 8, 12, 15, 23, 26, 31, 35]
+
+    # Binary search (double closed interval)
+    index = binary_search(nums, target)
+    print("Index of target element 6 =", index)

en/codes/python/chapter_divide_and_conquer/build_tree.py

@@ -0,0 +1,54 @@
+"""
+File: build_tree.py
+Created Time: 2023-07-15
+Author: krahets (krahets@163.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import TreeNode, print_tree
+
+
+def dfs(
+    preorder: list[int],
+    inorder_map: dict[int, int],
+    i: int,
+    l: int,
+    r: int,
+) -> TreeNode | None:
+    """Build binary tree: Divide and conquer"""
+    # Terminate when subtree interval is empty
+    if r - l < 0:
+        return None
+    # Initialize root node
+    root = TreeNode(preorder[i])
+    # Query m to divide left and right subtrees
+    m = inorder_map[preorder[i]]
+    # Subproblem: build left subtree
+    root.left = dfs(preorder, inorder_map, i + 1, l, m - 1)
+    # Subproblem: build right subtree
+    root.right = dfs(preorder, inorder_map, i + 1 + m - l, m + 1, r)
+    # Return root node
+    return root
+
+
+def build_tree(preorder: list[int], inorder: list[int]) -> TreeNode | None:
+    """Build binary tree"""
+    # Initialize hash table, storing in-order elements to indices mapping
+    inorder_map = {val: i for i, val in enumerate(inorder)}
+    root = dfs(preorder, inorder_map, 0, 0, len(inorder) - 1)
+    return root
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    preorder = [3, 9, 2, 1, 7]
+    inorder = [9, 3, 1, 2, 7]
+    print(f"Pre-order traversal = {preorder}")
+    print(f"In-order traversal = {inorder}")
+
+    root = build_tree(preorder, inorder)
+    print("The built binary tree is:")
+    print_tree(root)

en/codes/python/chapter_divide_and_conquer/hanota.py

@@ -0,0 +1,53 @@
+"""
+File: hanota.py
+Created Time: 2023-07-16
+Author: krahets (krahets@163.com)
+"""
+
+
+def move(src: list[int], tar: list[int]):
+    """Move a disc"""
+    # Take out a disc from the top of src
+    pan = src.pop()
+    # Place the disc on top of tar
+    tar.append(pan)
+
+
+def dfs(i: int, src: list[int], buf: list[int], tar: list[int]):
+    """Solve the Tower of Hanoi problem f(i)"""
+    # If only one disc remains on src, move it to tar
+    if i == 1:
+        move(src, tar)
+        return
+    # Subproblem f(i-1): move the top i-1 discs from src with the help of tar to buf
+    dfs(i - 1, src, tar, buf)
+    # Subproblem f(1): move the remaining one disc from src to tar
+    move(src, tar)
+    # Subproblem f(i-1): move the top i-1 discs from buf with the help of src to tar
+    dfs(i - 1, buf, src, tar)
+
+
+def solve_hanota(A: list[int], B: list[int], C: list[int]):
+    """Solve the Tower of Hanoi problem"""
+    n = len(A)
+    # Move the top n discs from A with the help of B to C
+    dfs(n, A, B, C)
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # The tail of the list is the top of the pillar
+    A = [5, 4, 3, 2, 1]
+    B = []
+    C = []
+    print("Initial state:")
+    print(f"A = {A}")
+    print(f"B = {B}")
+    print(f"C = {C}")
+
+    solve_hanota(A, B, C)
+
+    print("After the discs are moved:")
+    print(f"A = {A}")
+    print(f"B = {B}")
+    print(f"C = {C}")

en/codes/python/chapter_dynamic_programming/climbing_stairs_backtrack.py

@@ -0,0 +1,37 @@
+"""
+File: climbing_stairs_backtrack.py
+Created Time: 2023-06-30
+Author: krahets (krahets@163.com)
+"""
+
+
+def backtrack(choices: list[int], state: int, n: int, res: list[int]) -> int:
+    """Backtracking"""
+    # When climbing to the nth step, add 1 to the number of solutions
+    if state == n:
+        res[0] += 1
+    # Traverse all choices
+    for choice in choices:
+        # Pruning: do not allow climbing beyond the nth step
+        if state + choice > n:
+            continue
+        # Attempt: make a choice, update the state
+        backtrack(choices, state + choice, n, res)
+        # Retract
+
+
+def climbing_stairs_backtrack(n: int) -> int:
+    """Climbing stairs: Backtracking"""
+    choices = [1, 2]  # Can choose to climb up 1 step or 2 steps
+    state = 0  # Start climbing from the 0th step
+    res = [0]  # Use res[0] to record the number of solutions
+    backtrack(choices, state, n, res)
+    return res[0]
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    n = 9
+
+    res = climbing_stairs_backtrack(n)
+    print(f"Climb {n} steps, there are {res} solutions in total")

en/codes/python/chapter_dynamic_programming/climbing_stairs_constraint_dp.py

@@ -0,0 +1,29 @@
+"""
+File: climbing_stairs_constraint_dp.py
+Created Time: 2023-06-30
+Author: krahets (krahets@163.com)
+"""
+
+
+def climbing_stairs_constraint_dp(n: int) -> int:
+    """Constrained climbing stairs: Dynamic programming"""
+    if n == 1 or n == 2:
+        return 1
+    # Initialize dp table, used to store subproblem solutions
+    dp = [[0] * 3 for _ in range(n + 1)]
+    # Initial state: preset the smallest subproblem solution
+    dp[1][1], dp[1][2] = 1, 0
+    dp[2][1], dp[2][2] = 0, 1
+    # State transition: gradually solve larger subproblems from smaller ones
+    for i in range(3, n + 1):
+        dp[i][1] = dp[i - 1][2]
+        dp[i][2] = dp[i - 2][1] + dp[i - 2][2]
+    return dp[n][1] + dp[n][2]
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    n = 9
+
+    res = climbing_stairs_constraint_dp(n)
+    print(f"Climb {n} steps, there are {res} solutions in total")

en/codes/python/chapter_dynamic_programming/climbing_stairs_dfs.py

@@ -0,0 +1,28 @@
+"""
+File: climbing_stairs_dfs.py
+Created Time: 2023-06-30
+Author: krahets (krahets@163.com)
+"""
+
+
+def dfs(i: int) -> int:
+    """Search"""
+    # Known dp[1] and dp[2], return them
+    if i == 1 or i == 2:
+        return i
+    # dp[i] = dp[i-1] + dp[i-2]
+    count = dfs(i - 1) + dfs(i - 2)
+    return count
+
+
+def climbing_stairs_dfs(n: int) -> int:
+    """Climbing stairs: Search"""
+    return dfs(n)
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    n = 9
+
+    res = climbing_stairs_dfs(n)
+    print(f"Climb {n} steps, there are {res} solutions in total")

en/codes/python/chapter_dynamic_programming/climbing_stairs_dfs_mem.py

@@ -0,0 +1,35 @@
+"""
+File: climbing_stairs_dfs_mem.py
+Created Time: 2023-06-30
+Author: krahets (krahets@163.com)
+"""
+
+
+def dfs(i: int, mem: list[int]) -> int:
+    """Memoized search"""
+    # Known dp[1] and dp[2], return them
+    if i == 1 or i == 2:
+        return i
+    # If there is a record for dp[i], return it
+    if mem[i] != -1:
+        return mem[i]
+    # dp[i] = dp[i-1] + dp[i-2]
+    count = dfs(i - 1, mem) + dfs(i - 2, mem)
+    # Record dp[i]
+    mem[i] = count
+    return count
+
+
+def climbing_stairs_dfs_mem(n: int) -> int:
+    """Climbing stairs: Memoized search"""
+    # mem[i] records the total number of solutions for climbing to the ith step, -1 means no record
+    mem = [-1] * (n + 1)
+    return dfs(n, mem)
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    n = 9
+
+    res = climbing_stairs_dfs_mem(n)
+    print(f"Climb {n} steps, there are {res} solutions in total")

en/codes/python/chapter_dynamic_programming/climbing_stairs_dp.py

@@ -0,0 +1,40 @@
+"""
+File: climbing_stairs_dp.py
+Created Time: 2023-06-30
+Author: krahets (krahets@163.com)
+"""
+
+
+def climbing_stairs_dp(n: int) -> int:
+    """Climbing stairs: Dynamic programming"""
+    if n == 1 or n == 2:
+        return n
+    # Initialize dp table, used to store subproblem solutions
+    dp = [0] * (n + 1)
+    # Initial state: preset the smallest subproblem solution
+    dp[1], dp[2] = 1, 2
+    # State transition: gradually solve larger subproblems from smaller ones
+    for i in range(3, n + 1):
+        dp[i] = dp[i - 1] + dp[i - 2]
+    return dp[n]
+
+
+def climbing_stairs_dp_comp(n: int) -> int:
+    """Climbing stairs: Space-optimized dynamic programming"""
+    if n == 1 or n == 2:
+        return n
+    a, b = 1, 2
+    for _ in range(3, n + 1):
+        a, b = b, a + b
+    return b
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    n = 9
+
+    res = climbing_stairs_dp(n)
+    print(f"Climb {n} steps, there are {res} solutions in total")
+
+    res = climbing_stairs_dp_comp(n)
+    print(f"Climb {n} steps, there are {res} solutions in total")

en/codes/python/chapter_dynamic_programming/coin_change.py

@@ -0,0 +1,60 @@
+"""
+File: coin_change.py
+Created Time: 2023-07-10
+Author: krahets (krahets@163.com)
+"""
+
+
+def coin_change_dp(coins: list[int], amt: int) -> int:
+    """Coin change: Dynamic programming"""
+    n = len(coins)
+    MAX = amt + 1
+    # Initialize dp table
+    dp = [[0] * (amt + 1) for _ in range(n + 1)]
+    # State transition: first row and first column
+    for a in range(1, amt + 1):
+        dp[0][a] = MAX
+    # State transition: the rest of the rows and columns
+    for i in range(1, n + 1):
+        for a in range(1, amt + 1):
+            if coins[i - 1] > a:
+                # If exceeding the target amount, do not choose coin i
+                dp[i][a] = dp[i - 1][a]
+            else:
+                # The smaller value between not choosing and choosing coin i
+                dp[i][a] = min(dp[i - 1][a], dp[i][a - coins[i - 1]] + 1)
+    return dp[n][amt] if dp[n][amt] != MAX else -1
+
+
+def coin_change_dp_comp(coins: list[int], amt: int) -> int:
+    """Coin change: Space-optimized dynamic programming"""
+    n = len(coins)
+    MAX = amt + 1
+    # Initialize dp table
+    dp = [MAX] * (amt + 1)
+    dp[0] = 0
+    # State transition
+    for i in range(1, n + 1):
+        # Traverse in order
+        for a in range(1, amt + 1):
+            if coins[i - 1] > a:
+                # If exceeding the target amount, do not choose coin i
+                dp[a] = dp[a]
+            else:
+                # The smaller value between not choosing and choosing coin i
+                dp[a] = min(dp[a], dp[a - coins[i - 1]] + 1)
+    return dp[amt] if dp[amt] != MAX else -1
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    coins = [1, 2, 5]
+    amt = 4
+
+    # Dynamic programming
+    res = coin_change_dp(coins, amt)
+    print(f"Minimum number of coins required to reach the target amount = {res}")
+
+    # Space-optimized dynamic programming
+    res = coin_change_dp_comp(coins, amt)
+    print(f"Minimum number of coins required to reach the target amount = {res}")

en/codes/python/chapter_dynamic_programming/coin_change_ii.py

@@ -0,0 +1,58 @@
+"""
+File: coin_change_ii.py
+Created Time: 2023-07-10
+Author: krahets (krahets@163.com)
+"""
+
+
+def coin_change_ii_dp(coins: list[int], amt: int) -> int:
+    """Coin change II: Dynamic programming"""
+    n = len(coins)
+    # Initialize dp table
+    dp = [[0] * (amt + 1) for _ in range(n + 1)]
+    # Initialize first column
+    for i in range(n + 1):
+        dp[i][0] = 1
+    # State transition
+    for i in range(1, n + 1):
+        for a in range(1, amt + 1):
+            if coins[i - 1] > a:
+                # If exceeding the target amount, do not choose coin i
+                dp[i][a] = dp[i - 1][a]
+            else:
+                # The sum of the two options of not choosing and choosing coin i
+                dp[i][a] = dp[i - 1][a] + dp[i][a - coins[i - 1]]
+    return dp[n][amt]
+
+
+def coin_change_ii_dp_comp(coins: list[int], amt: int) -> int:
+    """Coin change II: Space-optimized dynamic programming"""
+    n = len(coins)
+    # Initialize dp table
+    dp = [0] * (amt + 1)
+    dp[0] = 1
+    # State transition
+    for i in range(1, n + 1):
+        # Traverse in order
+        for a in range(1, amt + 1):
+            if coins[i - 1] > a:
+                # If exceeding the target amount, do not choose coin i
+                dp[a] = dp[a]
+            else:
+                # The sum of the two options of not choosing and choosing coin i
+                dp[a] = dp[a] + dp[a - coins[i - 1]]
+    return dp[amt]
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    coins = [1, 2, 5]
+    amt = 5
+
+    # Dynamic programming
+    res = coin_change_ii_dp(coins, amt)
+    print(f"The number of coin combinations to make up the target amount is {res}")
+
+    # Space-optimized dynamic programming
+    res = coin_change_ii_dp_comp(coins, amt)
+    print(f"The number of coin combinations to make up the target amount is {res}")

en/codes/python/chapter_dynamic_programming/edit_distance.py

@@ -0,0 +1,123 @@
+"""
+File: edit_distancde.py
+Created Time: 2023-07-04
+Author: krahets (krahets@163.com)
+"""
+
+
+def edit_distance_dfs(s: str, t: str, i: int, j: int) -> int:
+    """Edit distance: Brute force search"""
+    # If both s and t are empty, return 0
+    if i == 0 and j == 0:
+        return 0
+    # If s is empty, return the length of t
+    if i == 0:
+        return j
+    # If t is empty, return the length of s
+    if j == 0:
+        return i
+    # If the two characters are equal, skip these two characters
+    if s[i - 1] == t[j - 1]:
+        return edit_distance_dfs(s, t, i - 1, j - 1)
+    # The minimum number of edits = the minimum number of edits from three operations (insert, remove, replace) + 1
+    insert = edit_distance_dfs(s, t, i, j - 1)
+    delete = edit_distance_dfs(s, t, i - 1, j)
+    replace = edit_distance_dfs(s, t, i - 1, j - 1)
+    # Return the minimum number of edits
+    return min(insert, delete, replace) + 1
+
+
+def edit_distance_dfs_mem(s: str, t: str, mem: list[list[int]], i: int, j: int) -> int:
+    """Edit distance: Memoized search"""
+    # If both s and t are empty, return 0
+    if i == 0 and j == 0:
+        return 0
+    # If s is empty, return the length of t
+    if i == 0:
+        return j
+    # If t is empty, return the length of s
+    if j == 0:
+        return i
+    # If there is a record, return it
+    if mem[i][j] != -1:
+        return mem[i][j]
+    # If the two characters are equal, skip these two characters
+    if s[i - 1] == t[j - 1]:
+        return edit_distance_dfs_mem(s, t, mem, i - 1, j - 1)
+    # The minimum number of edits = the minimum number of edits from three operations (insert, remove, replace) + 1
+    insert = edit_distance_dfs_mem(s, t, mem, i, j - 1)
+    delete = edit_distance_dfs_mem(s, t, mem, i - 1, j)
+    replace = edit_distance_dfs_mem(s, t, mem, i - 1, j - 1)
+    # Record and return the minimum number of edits
+    mem[i][j] = min(insert, delete, replace) + 1
+    return mem[i][j]
+
+
+def edit_distance_dp(s: str, t: str) -> int:
+    """Edit distance: Dynamic programming"""
+    n, m = len(s), len(t)
+    dp = [[0] * (m + 1) for _ in range(n + 1)]
+    # State transition: first row and first column
+    for i in range(1, n + 1):
+        dp[i][0] = i
+    for j in range(1, m + 1):
+        dp[0][j] = j
+    # State transition: the rest of the rows and columns
+    for i in range(1, n + 1):
+        for j in range(1, m + 1):
+            if s[i - 1] == t[j - 1]:
+                # If the two characters are equal, skip these two characters
+                dp[i][j] = dp[i - 1][j - 1]
+            else:
+                # The minimum number of edits = the minimum number of edits from three operations (insert, remove, replace) + 1
+                dp[i][j] = min(dp[i][j - 1], dp[i - 1][j], dp[i - 1][j - 1]) + 1
+    return dp[n][m]
+
+
+def edit_distance_dp_comp(s: str, t: str) -> int:
+    """Edit distance: Space-optimized dynamic programming"""
+    n, m = len(s), len(t)
+    dp = [0] * (m + 1)
+    # State transition: first row
+    for j in range(1, m + 1):
+        dp[j] = j
+    # State transition: the rest of the rows
+    for i in range(1, n + 1):
+        # State transition: first column
+        leftup = dp[0]  # Temporarily store dp[i-1, j-1]
+        dp[0] += 1
+        # State transition: the rest of the columns
+        for j in range(1, m + 1):
+            temp = dp[j]
+            if s[i - 1] == t[j - 1]:
+                # If the two characters are equal, skip these two characters
+                dp[j] = leftup
+            else:
+                # The minimum number of edits = the minimum number of edits from three operations (insert, remove, replace) + 1
+                dp[j] = min(dp[j - 1], dp[j], leftup) + 1
+            leftup = temp  # Update for the next round of dp[i-1, j-1]
+    return dp[m]
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    s = "bag"
+    t = "pack"
+    n, m = len(s), len(t)
+
+    # Brute force search
+    res = edit_distance_dfs(s, t, n, m)
+    print(f"To change {s} to {t}, the minimum number of edits required is {res}")
+
+    # Memoized search
+    mem = [[-1] * (m + 1) for _ in range(n + 1)]
+    res = edit_distance_dfs_mem(s, t, mem, n, m)
+    print(f"To change {s} to {t}, the minimum number of edits required is {res}")
+
+    # Dynamic programming
+    res = edit_distance_dp(s, t)
+    print(f"To change {s} to {t}, the minimum number of edits required is {res}")
+
+    # Space-optimized dynamic programming
+    res = edit_distance_dp_comp(s, t)
+    print(f"To change {s} to {t}, the minimum number of edits required is {res}")

en/codes/python/chapter_dynamic_programming/knapsack.py

@@ -0,0 +1,101 @@
+"""
+File: knapsack.py
+Created Time: 2023-07-03
+Author: krahets (krahets@163.com)
+"""
+
+
+def knapsack_dfs(wgt: list[int], val: list[int], i: int, c: int) -> int:
+    """0-1 Knapsack: Brute force search"""
+    # If all items have been chosen or the knapsack has no remaining capacity, return value 0
+    if i == 0 or c == 0:
+        return 0
+    # If exceeding the knapsack capacity, can only choose not to put it in the knapsack
+    if wgt[i - 1] > c:
+        return knapsack_dfs(wgt, val, i - 1, c)
+    # Calculate the maximum value of not putting in and putting in item i
+    no = knapsack_dfs(wgt, val, i - 1, c)
+    yes = knapsack_dfs(wgt, val, i - 1, c - wgt[i - 1]) + val[i - 1]
+    # Return the greater value of the two options
+    return max(no, yes)
+
+
+def knapsack_dfs_mem(
+    wgt: list[int], val: list[int], mem: list[list[int]], i: int, c: int
+) -> int:
+    """0-1 Knapsack: Memoized search"""
+    # If all items have been chosen or the knapsack has no remaining capacity, return value 0
+    if i == 0 or c == 0:
+        return 0
+    # If there is a record, return it
+    if mem[i][c] != -1:
+        return mem[i][c]
+    # If exceeding the knapsack capacity, can only choose not to put it in the knapsack
+    if wgt[i - 1] > c:
+        return knapsack_dfs_mem(wgt, val, mem, i - 1, c)
+    # Calculate the maximum value of not putting in and putting in item i
+    no = knapsack_dfs_mem(wgt, val, mem, i - 1, c)
+    yes = knapsack_dfs_mem(wgt, val, mem, i - 1, c - wgt[i - 1]) + val[i - 1]
+    # Record and return the greater value of the two options
+    mem[i][c] = max(no, yes)
+    return mem[i][c]
+
+
+def knapsack_dp(wgt: list[int], val: list[int], cap: int) -> int:
+    """0-1 Knapsack: Dynamic programming"""
+    n = len(wgt)
+    # Initialize dp table
+    dp = [[0] * (cap + 1) for _ in range(n + 1)]
+    # State transition
+    for i in range(1, n + 1):
+        for c in range(1, cap + 1):
+            if wgt[i - 1] > c:
+                # If exceeding the knapsack capacity, do not choose item i
+                dp[i][c] = dp[i - 1][c]
+            else:
+                # The greater value between not choosing and choosing item i
+                dp[i][c] = max(dp[i - 1][c], dp[i - 1][c - wgt[i - 1]] + val[i - 1])
+    return dp[n][cap]
+
+
+def knapsack_dp_comp(wgt: list[int], val: list[int], cap: int) -> int:
+    """0-1 Knapsack: Space-optimized dynamic programming"""
+    n = len(wgt)
+    # Initialize dp table
+    dp = [0] * (cap + 1)
+    # State transition
+    for i in range(1, n + 1):
+        # Traverse in reverse order
+        for c in range(cap, 0, -1):
+            if wgt[i - 1] > c:
+                # If exceeding the knapsack capacity, do not choose item i
+                dp[c] = dp[c]
+            else:
+                # The greater value between not choosing and choosing item i
+                dp[c] = max(dp[c], dp[c - wgt[i - 1]] + val[i - 1])
+    return dp[cap]
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    wgt = [10, 20, 30, 40, 50]
+    val = [50, 120, 150, 210, 240]
+    cap = 50
+    n = len(wgt)
+
+    # Brute force search
+    res = knapsack_dfs(wgt, val, n, cap)
+    print(f"The maximum item value without exceeding knapsack capacity is {res}")
+
+    # Memoized search
+    mem = [[-1] * (cap + 1) for _ in range(n + 1)]
+    res = knapsack_dfs_mem(wgt, val, mem, n, cap)
+    print(f"The maximum item value without exceeding knapsack capacity is {res}")
+
+    # Dynamic programming
+    res = knapsack_dp(wgt, val, cap)
+    print(f"The maximum item value without exceeding knapsack capacity is {res}")
+
+    # Space-optimized dynamic programming
+    res = knapsack_dp_comp(wgt, val, cap)
+    print(f"The maximum item value without exceeding knapsack capacity is {res}")

en/codes/python/chapter_dynamic_programming/min_cost_climbing_stairs_dp.py

@@ -0,0 +1,43 @@
+"""
+File: min_cost_climbing_stairs_dp.py
+Created Time: 2023-06-30
+Author: krahets (krahets@163.com)
+"""
+
+
+def min_cost_climbing_stairs_dp(cost: list[int]) -> int:
+    """Climbing stairs with minimum cost: Dynamic programming"""
+    n = len(cost) - 1
+    if n == 1 or n == 2:
+        return cost[n]
+    # Initialize dp table, used to store subproblem solutions
+    dp = [0] * (n + 1)
+    # Initial state: preset the smallest subproblem solution
+    dp[1], dp[2] = cost[1], cost[2]
+    # State transition: gradually solve larger subproblems from smaller ones
+    for i in range(3, n + 1):
+        dp[i] = min(dp[i - 1], dp[i - 2]) + cost[i]
+    return dp[n]
+
+
+def min_cost_climbing_stairs_dp_comp(cost: list[int]) -> int:
+    """Climbing stairs with minimum cost: Space-optimized dynamic programming"""
+    n = len(cost) - 1
+    if n == 1 or n == 2:
+        return cost[n]
+    a, b = cost[1], cost[2]
+    for i in range(3, n + 1):
+        a, b = b, min(a, b) + cost[i]
+    return b
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    cost = [0, 1, 10, 1, 1, 1, 10, 1, 1, 10, 1]
+    print(f"Enter the list of stair costs as {cost}")
+
+    res = min_cost_climbing_stairs_dp(cost)
+    print(f"Minimum cost to climb the stairs {res}")
+
+    res = min_cost_climbing_stairs_dp_comp(cost)
+    print(f"Minimum cost to climb the stairs {res}")

en/codes/python/chapter_dynamic_programming/min_path_sum.py

@@ -0,0 +1,104 @@
+"""
+File: min_path_sum.py
+Created Time: 2023-07-04
+Author: krahets (krahets@163.com)
+"""
+
+from math import inf
+
+
+def min_path_sum_dfs(grid: list[list[int]], i: int, j: int) -> int:
+    """Minimum path sum: Brute force search"""
+    # If it's the top-left cell, terminate the search
+    if i == 0 and j == 0:
+        return grid[0][0]
+    # If the row or column index is out of bounds, return a +∞ cost
+    if i < 0 or j < 0:
+        return inf
+    # Calculate the minimum path cost from the top-left to (i-1, j) and (i, j-1)
+    up = min_path_sum_dfs(grid, i - 1, j)
+    left = min_path_sum_dfs(grid, i, j - 1)
+    # Return the minimum path cost from the top-left to (i, j)
+    return min(left, up) + grid[i][j]
+
+
+def min_path_sum_dfs_mem(
+    grid: list[list[int]], mem: list[list[int]], i: int, j: int
+) -> int:
+    """Minimum path sum: Memoized search"""
+    # If it's the top-left cell, terminate the search
+    if i == 0 and j == 0:
+        return grid[0][0]
+    # If the row or column index is out of bounds, return a +∞ cost
+    if i < 0 or j < 0:
+        return inf
+    # If there is a record, return it
+    if mem[i][j] != -1:
+        return mem[i][j]
+    # The minimum path cost from the left and top cells
+    up = min_path_sum_dfs_mem(grid, mem, i - 1, j)
+    left = min_path_sum_dfs_mem(grid, mem, i, j - 1)
+    # Record and return the minimum path cost from the top-left to (i, j)
+    mem[i][j] = min(left, up) + grid[i][j]
+    return mem[i][j]
+
+
+def min_path_sum_dp(grid: list[list[int]]) -> int:
+    """Minimum path sum: Dynamic programming"""
+    n, m = len(grid), len(grid[0])
+    # Initialize dp table
+    dp = [[0] * m for _ in range(n)]
+    dp[0][0] = grid[0][0]
+    # State transition: first row
+    for j in range(1, m):
+        dp[0][j] = dp[0][j - 1] + grid[0][j]
+    # State transition: first column
+    for i in range(1, n):
+        dp[i][0] = dp[i - 1][0] + grid[i][0]
+    # State transition: the rest of the rows and columns
+    for i in range(1, n):
+        for j in range(1, m):
+            dp[i][j] = min(dp[i][j - 1], dp[i - 1][j]) + grid[i][j]
+    return dp[n - 1][m - 1]
+
+
+def min_path_sum_dp_comp(grid: list[list[int]]) -> int:
+    """Minimum path sum: Space-optimized dynamic programming"""
+    n, m = len(grid), len(grid[0])
+    # Initialize dp table
+    dp = [0] * m
+    # State transition: first row
+    dp[0] = grid[0][0]
+    for j in range(1, m):
+        dp[j] = dp[j - 1] + grid[0][j]
+    # State transition: the rest of the rows
+    for i in range(1, n):
+        # State transition: first column
+        dp[0] = dp[0] + grid[i][0]
+        # State transition: the rest of the columns
+        for j in range(1, m):
+            dp[j] = min(dp[j - 1], dp[j]) + grid[i][j]
+    return dp[m - 1]
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    grid = [[1, 3, 1, 5], [2, 2, 4, 2], [5, 3, 2, 1], [4, 3, 5, 2]]
+    n, m = len(grid), len(grid[0])
+
+    # Brute force search
+    res = min_path_sum_dfs(grid, n - 1, m - 1)
+    print(f"The minimum path sum from the top-left to the bottom-right corner is {res}")
+
+    # Memoized search
+    mem = [[-1] * m for _ in range(n)]
+    res = min_path_sum_dfs_mem(grid, mem, n - 1, m - 1)
+    print(f"The minimum path sum from the top-left to the bottom-right corner is {res}")
+
+    # Dynamic programming
+    res = min_path_sum_dp(grid)
+    print(f"The minimum path sum from the top-left to the bottom-right corner is {res}")
+
+    # Space-optimized dynamic programming
+    res = min_path_sum_dp_comp(grid)
+    print(f"The minimum path sum from the top-left to the bottom-right corner is {res}")

en/codes/python/chapter_dynamic_programming/unbounded_knapsack.py

@@ -0,0 +1,55 @@
+"""
+File: unbounded_knapsack.py
+Created Time: 2023-07-10
+Author: krahets (krahets@163.com)
+"""
+
+
+def unbounded_knapsack_dp(wgt: list[int], val: list[int], cap: int) -> int:
+    """Complete knapsack: Dynamic programming"""
+    n = len(wgt)
+    # Initialize dp table
+    dp = [[0] * (cap + 1) for _ in range(n + 1)]
+    # State transition
+    for i in range(1, n + 1):
+        for c in range(1, cap + 1):
+            if wgt[i - 1] > c:
+                # If exceeding the knapsack capacity, do not choose item i
+                dp[i][c] = dp[i - 1][c]
+            else:
+                # The greater value between not choosing and choosing item i
+                dp[i][c] = max(dp[i - 1][c], dp[i][c - wgt[i - 1]] + val[i - 1])
+    return dp[n][cap]
+
+
+def unbounded_knapsack_dp_comp(wgt: list[int], val: list[int], cap: int) -> int:
+    """Complete knapsack: Space-optimized dynamic programming"""
+    n = len(wgt)
+    # Initialize dp table
+    dp = [0] * (cap + 1)
+    # State transition
+    for i in range(1, n + 1):
+        # Traverse in order
+        for c in range(1, cap + 1):
+            if wgt[i - 1] > c:
+                # If exceeding the knapsack capacity, do not choose item i
+                dp[c] = dp[c]
+            else:
+                # The greater value between not choosing and choosing item i
+                dp[c] = max(dp[c], dp[c - wgt[i - 1]] + val[i - 1])
+    return dp[cap]
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    wgt = [1, 2, 3]
+    val = [5, 11, 15]
+    cap = 4
+
+    # Dynamic programming
+    res = unbounded_knapsack_dp(wgt, val, cap)
+    print(f"The maximum item value without exceeding knapsack capacity is {res}")
+
+    # Space-optimized dynamic programming
+    res = unbounded_knapsack_dp_comp(wgt, val, cap)
+    print(f"The maximum item value without exceeding knapsack capacity is {res}")

en/codes/python/chapter_graph/graph_adjacency_list.py

@@ -0,0 +1,111 @@
+"""
+File: graph_adjacency_list.py
+Created Time: 2023-02-23
+Author: krahets (krahets@163.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import Vertex, vals_to_vets
+
+
+class GraphAdjList:
+    """Undirected graph class based on adjacency list"""
+
+    def __init__(self, edges: list[list[Vertex]]):
+        """Constructor"""
+        # Adjacency list, key: vertex, value: all adjacent vertices of that vertex
+        self.adj_list = dict[Vertex, list[Vertex]]()
+        # Add all vertices and edges
+        for edge in edges:
+            self.add_vertex(edge[0])
+            self.add_vertex(edge[1])
+            self.add_edge(edge[0], edge[1])
+
+    def size(self) -> int:
+        """Get the number of vertices"""
+        return len(self.adj_list)
+
+    def add_edge(self, vet1: Vertex, vet2: Vertex):
+        """Add edge"""
+        if vet1 not in self.adj_list or vet2 not in self.adj_list or vet1 == vet2:
+            raise ValueError()
+        # Add edge vet1 - vet2
+        self.adj_list[vet1].append(vet2)
+        self.adj_list[vet2].append(vet1)
+
+    def remove_edge(self, vet1: Vertex, vet2: Vertex):
+        """Remove edge"""
+        if vet1 not in self.adj_list or vet2 not in self.adj_list or vet1 == vet2:
+            raise ValueError()
+        # Remove edge vet1 - vet2
+        self.adj_list[vet1].remove(vet2)
+        self.adj_list[vet2].remove(vet1)
+
+    def add_vertex(self, vet: Vertex):
+        """Add vertex"""
+        if vet in self.adj_list:
+            return
+        # Add a new linked list to the adjacency list
+        self.adj_list[vet] = []
+
+    def remove_vertex(self, vet: Vertex):
+        """Remove vertex"""
+        if vet not in self.adj_list:
+            raise ValueError()
+        # Remove the vertex vet's corresponding linked list from the adjacency list
+        self.adj_list.pop(vet)
+        # Traverse other vertices' linked lists, removing all edges containing vet
+        for vertex in self.adj_list:
+            if vet in self.adj_list[vertex]:
+                self.adj_list[vertex].remove(vet)
+
+    def print(self):
+        """Print the adjacency list"""
+        print("Adjacency list =")
+        for vertex in self.adj_list:
+            tmp = [v.val for v in self.adj_list[vertex]]
+            print(f"{vertex.val}: {tmp},")
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize undirected graph
+    v = vals_to_vets([1, 3, 2, 5, 4])
+    edges = [
+        [v[0], v[1]],
+        [v[0], v[3]],
+        [v[1], v[2]],
+        [v[2], v[3]],
+        [v[2], v[4]],
+        [v[3], v[4]],
+    ]
+    graph = GraphAdjList(edges)
+    print("\nAfter initialization, the graph is")
+    graph.print()
+
+    # Add edge
+    # Vertices 1, 2 i.e., v[0], v[2]
+    graph.add_edge(v[0], v[2])
+    print("\nAfter adding edge 1-2, the graph is")
+    graph.print()
+
+    # Remove edge
+    # Vertices 1, 3 i.e., v[0], v[1]
+    graph.remove_edge(v[0], v[1])
+    print("\nAfter removing edge 1-3, the graph is")
+    graph.print()
+
+    # Add vertex
+    v5 = Vertex(6)
+    graph.add_vertex(v5)
+    print("\nAfter adding vertex 6, the graph is")
+    graph.print()
+
+    # Remove vertex
+    # Vertex 3 i.e., v[1]
+    graph.remove_vertex(v[1])
+    print("\nAfter removing vertex 3, the graph is")
+    graph.print()

en/codes/python/chapter_graph/graph_adjacency_matrix.py

@@ -0,0 +1,116 @@
+"""
+File: graph_adjacency_matrix.py
+Created Time: 2023-02-23
+Author: krahets (krahets@163.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import Vertex, print_matrix
+
+
+class GraphAdjMat:
+    """Undirected graph class based on adjacency matrix"""
+
+    def __init__(self, vertices: list[int], edges: list[list[int]]):
+        """Constructor"""
+        # Vertex list, elements represent "vertex value", index represents "vertex index"
+        self.vertices: list[int] = []
+        # Adjacency matrix, row and column indices correspond to "vertex index"
+        self.adj_mat: list[list[int]] = []
+        # Add vertex
+        for val in vertices:
+            self.add_vertex(val)
+        # Add edge
+        # Please note, edges elements represent vertex indices, corresponding to vertices elements indices
+        for e in edges:
+            self.add_edge(e[0], e[1])
+
+    def size(self) -> int:
+        """Get the number of vertices"""
+        return len(self.vertices)
+
+    def add_vertex(self, val: int):
+        """Add vertex"""
+        n = self.size()
+        # Add new vertex value to the vertex list
+        self.vertices.append(val)
+        # Add a row to the adjacency matrix
+        new_row = [0] * n
+        self.adj_mat.append(new_row)
+        # Add a column to the adjacency matrix
+        for row in self.adj_mat:
+            row.append(0)
+
+    def remove_vertex(self, index: int):
+        """Remove vertex"""
+        if index >= self.size():
+            raise IndexError()
+        # Remove vertex at `index` from the vertex list
+        self.vertices.pop(index)
+        # Remove the row at `index` from the adjacency matrix
+        self.adj_mat.pop(index)
+        # Remove the column at `index` from the adjacency matrix
+        for row in self.adj_mat:
+            row.pop(index)
+
+    def add_edge(self, i: int, j: int):
+        """Add edge"""
+        # Parameters i, j correspond to vertices element indices
+        # Handle index out of bounds and equality
+        if i < 0 or j < 0 or i >= self.size() or j >= self.size() or i == j:
+            raise IndexError()
+        # In an undirected graph, the adjacency matrix is symmetric about the main diagonal, i.e., satisfies (i, j) == (j, i)
+        self.adj_mat[i][j] = 1
+        self.adj_mat[j][i] = 1
+
+    def remove_edge(self, i: int, j: int):
+        """Remove edge"""
+        # Parameters i, j correspond to vertices element indices
+        # Handle index out of bounds and equality
+        if i < 0 or j < 0 or i >= self.size() or j >= self.size() or i == j:
+            raise IndexError()
+        self.adj_mat[i][j] = 0
+        self.adj_mat[j][i] = 0
+
+    def print(self):
+        """Print adjacency matrix"""
+        print("Vertex list =", self.vertices)
+        print("Adjacency matrix =")
+        print_matrix(self.adj_mat)
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize undirected graph
+    # Please note, edges elements represent vertex indices, corresponding to vertices elements indices
+    vertices = [1, 3, 2, 5, 4]
+    edges = [[0, 1], [0, 3], [1, 2], [2, 3], [2, 4], [3, 4]]
+    graph = GraphAdjMat(vertices, edges)
+    print("\nAfter initialization, the graph is")
+    graph.print()
+
+    # Add edge
+    # Indices of vertices 1, 2 are 0, 2 respectively
+    graph.add_edge(0, 2)
+    print("\nAfter adding edge 1-2, the graph is")
+    graph.print()
+
+    # Remove edge
+    # Indices of vertices 1, 3 are 0, 1 respectively
+    graph.remove_edge(0, 1)
+    print("\nAfter removing edge 1-3, the graph is")
+    graph.print()
+
+    # Add vertex
+    graph.add_vertex(6)
+    print("\nAfter adding vertex 6, the graph is")
+    graph.print()
+
+    # Remove vertex
+    # Index of vertex 3 is 1
+    graph.remove_vertex(1)
+    print("\nAfter removing vertex 3, the graph is")
+    graph.print()

en/codes/python/chapter_graph/graph_bfs.py

@@ -0,0 +1,64 @@
+"""
+File: graph_bfs.py
+Created Time: 2023-02-23
+Author: krahets (krahets@163.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import Vertex, vals_to_vets, vets_to_vals
+from collections import deque
+from graph_adjacency_list import GraphAdjList
+
+
+def graph_bfs(graph: GraphAdjList, start_vet: Vertex) -> list[Vertex]:
+    """Breadth-first traversal"""
+    # Use adjacency list to represent the graph, to obtain all adjacent vertices of a specified vertex
+    # Vertex traversal sequence
+    res = []
+    # Hash set, used to record visited vertices
+    visited = set[Vertex]([start_vet])
+    # Queue used to implement BFS
+    que = deque[Vertex]([start_vet])
+    # Starting from vertex vet, loop until all vertices are visited
+    while len(que) > 0:
+        vet = que.popleft()  # Dequeue the vertex at the head of the queue
+        res.append(vet)  # Record visited vertex
+        # Traverse all adjacent vertices of that vertex
+        for adj_vet in graph.adj_list[vet]:
+            if adj_vet in visited:
+                continue  # Skip already visited vertices
+            que.append(adj_vet)  # Only enqueue unvisited vertices
+            visited.add(adj_vet)  # Mark the vertex as visited
+    # Return the vertex traversal sequence
+    return res
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize undirected graph
+    v = vals_to_vets([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
+    edges = [
+        [v[0], v[1]],
+        [v[0], v[3]],
+        [v[1], v[2]],
+        [v[1], v[4]],
+        [v[2], v[5]],
+        [v[3], v[4]],
+        [v[3], v[6]],
+        [v[4], v[5]],
+        [v[4], v[7]],
+        [v[5], v[8]],
+        [v[6], v[7]],
+        [v[7], v[8]],
+    ]
+    graph = GraphAdjList(edges)
+    print("\nAfter initialization, the graph is")
+    graph.print()
+
+    # Breadth-first traversal
+    res = graph_bfs(graph, v[0])
+    print("\nBreadth-first traversal (BFS) vertex sequence is")
+    print(vets_to_vals(res))

en/codes/python/chapter_graph/graph_dfs.py

@@ -0,0 +1,57 @@
+"""
+File: graph_dfs.py
+Created Time: 2023-02-23
+Author: krahets (krahets@163.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import Vertex, vets_to_vals, vals_to_vets
+from graph_adjacency_list import GraphAdjList
+
+
+def dfs(graph: GraphAdjList, visited: set[Vertex], res: list[Vertex], vet: Vertex):
+    """Depth-first traversal helper function"""
+    res.append(vet)  # Record visited vertex
+    visited.add(vet)  # Mark the vertex as visited
+    # Traverse all adjacent vertices of that vertex
+    for adjVet in graph.adj_list[vet]:
+        if adjVet in visited:
+            continue  # Skip already visited vertices
+        # Recursively visit adjacent vertices
+        dfs(graph, visited, res, adjVet)
+
+
+def graph_dfs(graph: GraphAdjList, start_vet: Vertex) -> list[Vertex]:
+    """Depth-first traversal"""
+    # Use adjacency list to represent the graph, to obtain all adjacent vertices of a specified vertex
+    # Vertex traversal sequence
+    res = []
+    # Hash set, used to record visited vertices
+    visited = set[Vertex]()
+    dfs(graph, visited, res, start_vet)
+    return res
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize undirected graph
+    v = vals_to_vets([0, 1, 2, 3, 4, 5, 6])
+    edges = [
+        [v[0], v[1]],
+        [v[0], v[3]],
+        [v[1], v[2]],
+        [v[2], v[5]],
+        [v[4], v[5]],
+        [v[5], v[6]],
+    ]
+    graph = GraphAdjList(edges)
+    print("\nAfter initialization, the graph is")
+    graph.print()
+
+    # Depth-first traversal
+    res = graph_dfs(graph, v[0])
+    print("\nDepth-first traversal (DFS) vertex sequence is")
+    print(vets_to_vals(res))

en/codes/python/chapter_greedy/coin_change_greedy.py

@@ -0,0 +1,48 @@
+"""
+File: coin_change_greedy.py
+Created Time: 2023-07-18
+Author: krahets (krahets@163.com)
+"""
+
+
+def coin_change_greedy(coins: list[int], amt: int) -> int:
+    """Coin change: Greedy"""
+    # Assume coins list is ordered
+    i = len(coins) - 1
+    count = 0
+    # Loop for greedy selection until no remaining amount
+    while amt > 0:
+        # Find the smallest coin close to and less than the remaining amount
+        while i > 0 and coins[i] > amt:
+            i -= 1
+        # Choose coins[i]
+        amt -= coins[i]
+        count += 1
+    # If no feasible solution is found, return -1
+    return count if amt == 0 else -1
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Greedy: can ensure finding a global optimal solution
+    coins = [1, 5, 10, 20, 50, 100]
+    amt = 186
+    res = coin_change_greedy(coins, amt)
+    print(f"\ncoins = {coins}, amt = {amt}")
+    print(f"The minimum number of coins needed to make up {amt} is {res}")
+
+    # Greedy: cannot ensure finding a global optimal solution
+    coins = [1, 20, 50]
+    amt = 60
+    res = coin_change_greedy(coins, amt)
+    print(f"\ncoins = {coins}, amt = {amt}")
+    print(f"The minimum number of coins needed to make up {amt} is {res}")
+    print(f"In reality, the minimum number needed is 3, i.e., 20 + 20 + 20")
+
+    # Greedy: cannot ensure finding a global optimal solution
+    coins = [1, 49, 50]
+    amt = 98
+    res = coin_change_greedy(coins, amt)
+    print(f"\ncoins = {coins}, amt = {amt}")
+    print(f"The minimum number of coins needed to make up {amt} is {res}")
+    print(f"In reality, the minimum number needed is 2, i.e., 49 + 49")

en/codes/python/chapter_greedy/fractional_knapsack.py

@@ -0,0 +1,46 @@
+"""
+File: fractional_knapsack.py
+Created Time: 2023-07-19
+Author: krahets (krahets@163.com)
+"""
+
+
+class Item:
+    """Item"""
+
+    def __init__(self, w: int, v: int):
+        self.w = w  # Item weight
+        self.v = v  # Item value
+
+
+def fractional_knapsack(wgt: list[int], val: list[int], cap: int) -> int:
+    """Fractional knapsack: Greedy"""
+    # Create an item list, containing two properties: weight, value
+    items = [Item(w, v) for w, v in zip(wgt, val)]
+    # Sort by unit value item.v / item.w from high to low
+    items.sort(key=lambda item: item.v / item.w, reverse=True)
+    # Loop for greedy selection
+    res = 0
+    for item in items:
+        if item.w <= cap:
+            # If the remaining capacity is sufficient, put the entire item into the knapsack
+            res += item.v
+            cap -= item.w
+        else:
+            # If the remaining capacity is insufficient, put part of the item into the knapsack
+            res += (item.v / item.w) * cap
+            # No remaining capacity left, thus break the loop
+            break
+    return res
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    wgt = [10, 20, 30, 40, 50]
+    val = [50, 120, 150, 210, 240]
+    cap = 50
+    n = len(wgt)
+
+    # Greedy algorithm
+    res = fractional_knapsack(wgt, val, cap)
+    print(f"The maximum item value without exceeding knapsack capacity is {res}")

en/codes/python/chapter_greedy/max_capacity.py

@@ -0,0 +1,33 @@
+"""
+File: max_capacity.py
+Created Time: 2023-07-21
+Author: krahets (krahets@163.com)
+"""
+
+
+def max_capacity(ht: list[int]) -> int:
+    """Maximum capacity: Greedy"""
+    # Initialize i, j, making them split the array at both ends
+    i, j = 0, len(ht) - 1
+    # Initial maximum capacity is 0
+    res = 0
+    # Loop for greedy selection until the two boards meet
+    while i < j:
+        # Update maximum capacity
+        cap = min(ht[i], ht[j]) * (j - i)
+        res = max(res, cap)
+        # Move the shorter board inward
+        if ht[i] < ht[j]:
+            i += 1
+        else:
+            j -= 1
+    return res
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    ht = [3, 8, 5, 2, 7, 7, 3, 4]
+
+    # Greedy algorithm
+    res = max_capacity(ht)
+    print(f"Maximum capacity is {res}")

en/codes/python/chapter_greedy/max_product_cutting.py

@@ -0,0 +1,33 @@
+"""
+File: max_product_cutting.py
+Created Time: 2023-07-21
+Author: krahets (krahets@163.com)
+"""
+
+import math
+
+
+def max_product_cutting(n: int) -> int:
+    """Maximum product of cutting: Greedy"""
+    # When n <= 3, must cut out a 1
+    if n <= 3:
+        return 1 * (n - 1)
+    # Greedy cut out 3s, a is the number of 3s, b is the remainder
+    a, b = n // 3, n % 3
+    if b == 1:
+        # When the remainder is 1, convert a pair of 1 * 3 into 2 * 2
+        return int(math.pow(3, a - 1)) * 2 * 2
+    if b == 2:
+        # When the remainder is 2, do nothing
+        return int(math.pow(3, a)) * 2
+    # When the remainder is 0, do nothing
+    return int(math.pow(3, a))
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    n = 58
+
+    # Greedy algorithm
+    res = max_product_cutting(n)
+    print(f"Maximum product of cutting is {res}")

en/codes/python/chapter_hashing/array_hash_map.py

@@ -0,0 +1,117 @@
+"""
+File: array_hash_map.py
+Created Time: 2022-12-14
+Author: msk397 (machangxinq@gmail.com)
+"""
+
+
+class Pair:
+    """Key-value pair"""
+
+    def __init__(self, key: int, val: str):
+        self.key = key
+        self.val = val
+
+
+class ArrayHashMap:
+    """Hash table based on array implementation"""
+
+    def __init__(self):
+        """Constructor"""
+        # Initialize an array, containing 100 buckets
+        self.buckets: list[Pair | None] = [None] * 100
+
+    def hash_func(self, key: int) -> int:
+        """Hash function"""
+        index = key % 100
+        return index
+
+    def get(self, key: int) -> str:
+        """Query operation"""
+        index: int = self.hash_func(key)
+        pair: Pair = self.buckets[index]
+        if pair is None:
+            return None
+        return pair.val
+
+    def put(self, key: int, val: str):
+        """Add operation"""
+        pair = Pair(key, val)
+        index: int = self.hash_func(key)
+        self.buckets[index] = pair
+
+    def remove(self, key: int):
+        """Remove operation"""
+        index: int = self.hash_func(key)
+        # Set to None, representing removal
+        self.buckets[index] = None
+
+    def entry_set(self) -> list[Pair]:
+        """Get all key-value pairs"""
+        result: list[Pair] = []
+        for pair in self.buckets:
+            if pair is not None:
+                result.append(pair)
+        return result
+
+    def key_set(self) -> list[int]:
+        """Get all keys"""
+        result = []
+        for pair in self.buckets:
+            if pair is not None:
+                result.append(pair.key)
+        return result
+
+    def value_set(self) -> list[str]:
+        """Get all values"""
+        result = []
+        for pair in self.buckets:
+            if pair is not None:
+                result.append(pair.val)
+        return result
+
+    def print(self):
+        """Print hash table"""
+        for pair in self.buckets:
+            if pair is not None:
+                print(pair.key, "->", pair.val)
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize hash table
+    hmap = ArrayHashMap()
+
+    # Add operation
+    # Add key-value pair (key, value) to the hash table
+    hmap.put(12836, "Ha")
+    hmap.put(15937, "Luo")
+    hmap.put(16750, "Suan")
+    hmap.put(13276, "Fa")
+    hmap.put(10583, "Ya")
+    print("\nAfter adding, the hash table is\nKey -> Value")
+    hmap.print()
+
+    # Query operation
+    # Enter key to the hash table, get value
+    name = hmap.get(15937)
+    print("\nEnter student ID 15937, found name " + name)
+
+    # Remove operation
+    # Remove key-value pair (key, value) from the hash table
+    hmap.remove(10583)
+    print("\nAfter removing 10583, the hash table is\nKey -> Value")
+    hmap.print()
+
+    # Traverse hash table
+    print("\nTraverse key-value pairs Key->Value")
+    for pair in hmap.entry_set():
+        print(pair.key, "->", pair.val)
+
+    print("\nIndividually traverse keys Key")
+    for key in hmap.key_set():
+        print(key)
+
+    print("\nIndividually traverse values Value")
+    for val in hmap.value_set():
+        print(val)

en/codes/python/chapter_hashing/built_in_hash.py

@@ -0,0 +1,37 @@
+"""
+File: built_in_hash.py
+Created Time: 2023-06-15
+Author: krahets (krahets@163.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import ListNode
+
+"""Driver Code"""
+if __name__ == "__main__":
+    num = 3
+    hash_num = hash(num)
+    print(f"Integer {num}'s hash value is {hash_num}")
+
+    bol = True
+    hash_bol = hash(bol)
+    print(f"Boolean {bol}'s hash value is {hash_bol}")
+
+    dec = 3.14159
+    hash_dec = hash(dec)
+    print(f"Decimal {dec}'s hash value is {hash_dec}")
+
+    str = "Hello algorithm"
+    hash_str = hash(str)
+    print(f"String {str}'s hash value is {hash_str}")
+
+    tup = (12836, "Ha")
+    hash_tup = hash(tup)
+    print(f"Tuple {tup}'s hash value is {hash(hash_tup)}")
+
+    obj = ListNode(0)
+    hash_obj = hash(obj)
+    print(f"Node object {obj}'s hash value is {hash_obj}")

en/codes/python/chapter_hashing/hash_map.py

@@ -0,0 +1,50 @@
+"""
+File: hash_map.py
+Created Time: 2022-12-14
+Author: msk397 (machangxinq@gmail.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import print_dict
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize hash table
+    hmap = dict[int, str]()
+
+    # Add operation
+    # Add key-value pair (key, value) to the hash table
+    hmap[12836] = "Ha"
+    hmap[15937] = "Luo"
+    hmap[16750] = "Suan"
+    hmap[13276] = "Fa"
+    hmap[10583] = "Ya"
+    print("\nAfter adding, the hash table is\nKey -> Value")
+    print_dict(hmap)
+
+    # Query operation
+    # Enter key to the hash table, get value
+    name: str = hmap[15937]
+    print("\nEnter student ID 15937, found name " + name)
+
+    # Remove operation
+    # Remove key-value pair (key, value) from the hash table
+    hmap.pop(10583)
+    print("\nAfter removing 10583, the hash table is\nKey -> Value")
+    print_dict(hmap)
+
+    # Traverse hash table
+    print("\nTraverse key-value pairs Key->Value")
+    for key, value in hmap.items():
+        print(key, "->", value)
+
+    print("\nIndividually traverse keys Key")
+    for key in hmap.keys():
+        print(key)
+
+    print("\nIndividually traverse values Value")
+    for val in hmap.values():
+        print(val)

en/codes/python/chapter_hashing/hash_map_chaining.py

@@ -0,0 +1,118 @@
+"""
+File: hash_map_chaining.py
+Created Time: 2023-06-13
+Author: krahets (krahets@163.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from chapter_hashing.array_hash_map import Pair
+
+
+class HashMapChaining:
+    """Chained address hash table"""
+
+    def __init__(self):
+        """Constructor"""
+        self.size = 0  # Number of key-value pairs
+        self.capacity = 4  # Hash table capacity
+        self.load_thres = 2.0 / 3.0  # Load factor threshold for triggering expansion
+        self.extend_ratio = 2  # Expansion multiplier
+        self.buckets = [[] for _ in range(self.capacity)]  # Bucket array
+
+    def hash_func(self, key: int) -> int:
+        """Hash function"""
+        return key % self.capacity
+
+    def load_factor(self) -> float:
+        """Load factor"""
+        return self.size / self.capacity
+
+    def get(self, key: int) -> str | None:
+        """Query operation"""
+        index = self.hash_func(key)
+        bucket = self.buckets[index]
+        # Traverse the bucket, if the key is found, return the corresponding val
+        for pair in bucket:
+            if pair.key == key:
+                return pair.val
+        # If the key is not found, return None
+        return None
+
+    def put(self, key: int, val: str):
+        """Add operation"""
+        # When the load factor exceeds the threshold, perform expansion
+        if self.load_factor() > self.load_thres:
+            self.extend()
+        index = self.hash_func(key)
+        bucket = self.buckets[index]
+        # Traverse the bucket, if the specified key is encountered, update the corresponding val and return
+        for pair in bucket:
+            if pair.key == key:
+                pair.val = val
+                return
+        # If the key is not found, add the key-value pair to the end
+        pair = Pair(key, val)
+        bucket.append(pair)
+        self.size += 1
+
+    def remove(self, key: int):
+        """Remove operation"""
+        index = self.hash_func(key)
+        bucket = self.buckets[index]
+        # Traverse the bucket, remove the key-value pair from it
+        for pair in bucket:
+            if pair.key == key:
+                bucket.remove(pair)
+                self.size -= 1
+                break
+
+    def extend(self):
+        """Extend hash table"""
+        # Temporarily store the original hash table
+        buckets = self.buckets
+        # Initialize the extended new hash table
+        self.capacity *= self.extend_ratio
+        self.buckets = [[] for _ in range(self.capacity)]
+        self.size = 0
+        # Move key-value pairs from the original hash table to the new hash table
+        for bucket in buckets:
+            for pair in bucket:
+                self.put(pair.key, pair.val)
+
+    def print(self):
+        """Print hash table"""
+        for bucket in self.buckets:
+            res = []
+            for pair in bucket:
+                res.append(str(pair.key) + " -> " + pair.val)
+            print(res)
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize hash table
+    hashmap = HashMapChaining()
+
+    # Add operation
+    # Add key-value pair (key, value) to the hash table
+    hashmap.put(12836, "Ha")
+    hashmap.put(15937, "Luo")
+    hashmap.put(16750, "Suan")
+    hashmap.put(13276, "Fa")
+    hashmap.put(10583, "Ya")
+    print("\nAfter adding, the hash table is\n[Key1 -> Value1, Key2 -> Value2, ...]")
+    hashmap.print()
+
+    # Query operation
+    # Enter key to the hash table, get value
+    name = hashmap.get(13276)
+    print("\nEnter student ID 13276, found name " + name)
+
+    # Remove operation
+    # Remove key-value pair (key, value) from the hash table
+    hashmap.remove(12836)
+    print("\nAfter removing 12836, the hash table is\n[Key1 -> Value1, Key2 -> Value2, ...]")
+    hashmap.print()

en/codes/python/chapter_hashing/hash_map_open_addressing.py

@@ -0,0 +1,138 @@
+"""
+File: hash_map_open_addressing.py
+Created Time: 2023-06-13
+Author: krahets (krahets@163.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from chapter_hashing.array_hash_map import Pair
+
+
+class HashMapOpenAddressing:
+    """Open addressing hash table"""
+
+    def __init__(self):
+        """Constructor"""
+        self.size = 0  # Number of key-value pairs
+        self.capacity = 4  # Hash table capacity
+        self.load_thres = 2.0 / 3.0  # Load factor threshold for triggering expansion
+        self.extend_ratio = 2  # Expansion multiplier
+        self.buckets: list[Pair | None] = [None] * self.capacity  # Bucket array
+        self.TOMBSTONE = Pair(-1, "-1")  # Removal mark
+
+    def hash_func(self, key: int) -> int:
+        """Hash function"""
+        return key % self.capacity
+
+    def load_factor(self) -> float:
+        """Load factor"""
+        return self.size / self.capacity
+
+    def find_bucket(self, key: int) -> int:
+        """Search for the bucket index corresponding to key"""
+        index = self.hash_func(key)
+        first_tombstone = -1
+        # Linear probing, break when encountering an empty bucket
+        while self.buckets[index] is not None:
+            # If the key is encountered, return the corresponding bucket index
+            if self.buckets[index].key == key:
+                # If a removal mark was encountered earlier, move the key-value pair to that index
+                if first_tombstone != -1:
+                    self.buckets[first_tombstone] = self.buckets[index]
+                    self.buckets[index] = self.TOMBSTONE
+                    return first_tombstone  # Return the moved bucket index
+                return index  # Return bucket index
+            # Record the first encountered removal mark
+            if first_tombstone == -1 and self.buckets[index] is self.TOMBSTONE:
+                first_tombstone = index
+            # Calculate the bucket index, return to the head if exceeding the tail
+            index = (index + 1) % self.capacity
+        # If the key does not exist, return the index of the insertion point
+        return index if first_tombstone == -1 else first_tombstone
+
+    def get(self, key: int) -> str:
+        """Query operation"""
+        # Search for the bucket index corresponding to key
+        index = self.find_bucket(key)
+        # If the key-value pair is found, return the corresponding val
+        if self.buckets[index] not in [None, self.TOMBSTONE]:
+            return self.buckets[index].val
+        # If the key-value pair does not exist, return None
+        return None
+
+    def put(self, key: int, val: str):
+        """Add operation"""
+        # When the load factor exceeds the threshold, perform expansion
+        if self.load_factor() > self.load_thres:
+            self.extend()
+        # Search for the bucket index corresponding to key
+        index = self.find_bucket(key)
+        # If the key-value pair is found, overwrite val and return
+        if self.buckets[index] not in [None, self.TOMBSTONE]:
+            self.buckets[index].val = val
+            return
+        # If the key-value pair does not exist, add the key-value pair
+        self.buckets[index] = Pair(key, val)
+        self.size += 1
+
+    def remove(self, key: int):
+        """Remove operation"""
+        # Search for the bucket index corresponding to key
+        index = self.find_bucket(key)
+        # If the key-value pair is found, cover it with a removal mark
+        if self.buckets[index] not in [None, self.TOMBSTONE]:
+            self.buckets[index] = self.TOMBSTONE
+            self.size -= 1
+
+    def extend(self):
+        """Extend hash table"""
+        # Temporarily store the original hash table
+        buckets_tmp = self.buckets
+        # Initialize the extended new hash table
+        self.capacity *= self.extend_ratio
+        self.buckets = [None] * self.capacity
+        self.size = 0
+        # Move key-value pairs from the original hash table to the new hash table
+        for pair in buckets_tmp:
+            if pair not in [None, self.TOMBSTONE]:
+                self.put(pair.key, pair.val)
+
+    def print(self):
+        """Print hash table"""
+        for pair in self.buckets:
+            if pair is None:
+                print("None")
+            elif pair is self.TOMBSTONE:
+                print("TOMBSTONE")
+            else:
+                print(pair.key, "->", pair.val)
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize hash table
+    hashmap = HashMapOpenAddressing()
+
+    # Add operation
+    # Add key-value pair (key, val) to the hash table
+    hashmap.put(12836, "Ha")
+    hashmap.put(15937, "Luo")
+    hashmap.put(16750, "Suan")
+    hashmap.put(13276, "Fa")
+    hashmap.put(10583, "Ya")
+    print("\nAfter adding, the hash table is\nKey -> Value")
+    hashmap.print()
+
+    # Query operation
+    # Enter key to the hash table, get value val
+    name = hashmap.get(13276)
+    print("\nEnter student ID 13276, found name " + name)
+
+    # Remove operation
+    # Remove key-value pair (key, val) from the hash table
+    hashmap.remove(16750)
+    print("\nAfter removing 16750, the hash table is\nKey -> Value")
+    hashmap.print()

en/codes/python/chapter_hashing/simple_hash.py

@@ -0,0 +1,58 @@
+"""
+File: simple_hash.py
+Created Time: 2023-06-15
+Author: krahets (krahets@163.com)
+"""
+
+
+def add_hash(key: str) -> int:
+    """Additive hash"""
+    hash = 0
+    modulus = 1000000007
+    for c in key:
+        hash += ord(c)
+    return hash % modulus
+
+
+def mul_hash(key: str) -> int:
+    """Multiplicative hash"""
+    hash = 0
+    modulus = 1000000007
+    for c in key:
+        hash = 31 * hash + ord(c)
+    return hash % modulus
+
+
+def xor_hash(key: str) -> int:
+    """XOR hash"""
+    hash = 0
+    modulus = 1000000007
+    for c in key:
+        hash ^= ord(c)
+    return hash % modulus
+
+
+def rot_hash(key: str) -> int:
+    """Rotational hash"""
+    hash = 0
+    modulus = 1000000007
+    for c in key:
+        hash = (hash << 4) ^ (hash >> 28) ^ ord(c)
+    return hash % modulus
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    key = "Hello algorithm"
+
+    hash = add_hash(key)
+    print(f"Additive hash value is {hash}")
+
+    hash = mul_hash(key)
+    print(f"Multiplicative hash value is {hash}")
+
+    hash = xor_hash(key)
+    print(f"XOR hash value is {hash}")
+
+    hash = rot_hash(key)
+    print(f"Rotational hash value is {hash}")

en/codes/python/chapter_heap/heap.py

@@ -0,0 +1,71 @@
+"""
+File: heap.py
+Created Time: 2023-02-23
+Author: krahets (krahets@163.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import print_heap
+
+import heapq
+
+
+def test_push(heap: list, val: int, flag: int = 1):
+    heapq.heappush(heap, flag * val)  # Push the element into heap
+    print(f"\nElement {val} after pushed into heap")
+    print_heap([flag * val for val in heap])
+
+
+def test_pop(heap: list, flag: int = 1):
+    val = flag * heapq.heappop(heap)  # Pop the element at the heap top
+    print(f"\nHeap top element {val} after exiting heap")
+    print_heap([flag * val for val in heap])
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize min-heap
+    min_heap, flag = [], 1
+    # Initialize max-heap
+    max_heap, flag = [], -1
+
+    print("\nThe following test case is for max-heap")
+    # Python's heapq module implements min-heap by default
+    # Consider "negating the elements" before entering the heap, thus reversing the comparator to implement a max-heap
+    # In this example, flag = 1 corresponds to min-heap, flag = -1 corresponds to max-heap
+
+    # Push the element into heap
+    test_push(max_heap, 1, flag)
+    test_push(max_heap, 3, flag)
+    test_push(max_heap, 2, flag)
+    test_push(max_heap, 5, flag)
+    test_push(max_heap, 4, flag)
+
+    # Access heap top element
+    peek: int = flag * max_heap[0]
+    print(f"\nHeap top element is {peek}")
+
+    # Pop the element at the heap top
+    test_pop(max_heap, flag)
+    test_pop(max_heap, flag)
+    test_pop(max_heap, flag)
+    test_pop(max_heap, flag)
+    test_pop(max_heap, flag)
+
+    # Get heap size
+    size: int = len(max_heap)
+    print(f"\nNumber of heap elements is {size}")
+
+    # Determine if heap is empty
+    is_empty: bool = not max_heap
+    print(f"\nIs the heap empty {is_empty}")
+
+    # Enter list and build heap
+    # Time complexity is O(n), not O(nlogn)
+    min_heap = [1, 3, 2, 5, 4]
+    heapq.heapify(min_heap)
+    print("\nEnter list and build min-heap")
+    print_heap(min_heap)

en/codes/python/chapter_heap/my_heap.py

@@ -0,0 +1,137 @@
+"""
+File: my_heap.py
+Created Time: 2023-02-23
+Author: krahets (krahets@163.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import print_heap
+
+
+class MaxHeap:
+    """Max-heap"""
+
+    def __init__(self, nums: list[int]):
+        """Constructor, build heap based on input list"""
+        # Add all list elements into the heap
+        self.max_heap = nums
+        # Heapify all nodes except leaves
+        for i in range(self.parent(self.size() - 1), -1, -1):
+            self.sift_down(i)
+
+    def left(self, i: int) -> int:
+        """Get index of left child node"""
+        return 2 * i + 1
+
+    def right(self, i: int) -> int:
+        """Get index of right child node"""
+        return 2 * i + 2
+
+    def parent(self, i: int) -> int:
+        """Get index of parent node"""
+        return (i - 1) // 2  # Integer division down
+
+    def swap(self, i: int, j: int):
+        """Swap elements"""
+        self.max_heap[i], self.max_heap[j] = self.max_heap[j], self.max_heap[i]
+
+    def size(self) -> int:
+        """Get heap size"""
+        return len(self.max_heap)
+
+    def is_empty(self) -> bool:
+        """Determine if heap is empty"""
+        return self.size() == 0
+
+    def peek(self) -> int:
+        """Access heap top element"""
+        return self.max_heap[0]
+
+    def push(self, val: int):
+        """Push the element into heap"""
+        # Add node
+        self.max_heap.append(val)
+        # Heapify from bottom to top
+        self.sift_up(self.size() - 1)
+
+    def sift_up(self, i: int):
+        """Start heapifying node i, from bottom to top"""
+        while True:
+            # Get parent node of node i
+            p = self.parent(i)
+            # When "crossing the root node" or "node does not need repair", end heapification
+            if p < 0 or self.max_heap[i] <= self.max_heap[p]:
+                break
+            # Swap two nodes
+            self.swap(i, p)
+            # Loop upwards heapification
+            i = p
+
+    def pop(self) -> int:
+        """Element exits heap"""
+        # Empty handling
+        if self.is_empty():
+            raise IndexError("Heap is empty")
+        # Swap the root node with the rightmost leaf node (swap the first element with the last element)
+        self.swap(0, self.size() - 1)
+        # Remove node
+        val = self.max_heap.pop()
+        # Heapify from top to bottom
+        self.sift_down(0)
+        # Return heap top element
+        return val
+
+    def sift_down(self, i: int):
+        """Start heapifying node i, from top to bottom"""
+        while True:
+            # Determine the largest node among i, l, r, noted as ma
+            l, r, ma = self.left(i), self.right(i), i
+            if l < self.size() and self.max_heap[l] > self.max_heap[ma]:
+                ma = l
+            if r < self.size() and self.max_heap[r] > self.max_heap[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
+            self.swap(i, ma)
+            # Loop downwards heapification
+            i = ma
+
+    def print(self):
+        """Print heap (binary tree)"""
+        print_heap(self.max_heap)
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize max-heap
+    max_heap = MaxHeap([9, 8, 6, 6, 7, 5, 2, 1, 4, 3, 6, 2])
+    print("\nEnter list and build heap")
+    max_heap.print()
+
+    # Access heap top element
+    peek = max_heap.peek()
+    print(f"\nHeap top element is {peek}")
+
+    # Push the element into heap
+    val = 7
+    max_heap.push(val)
+    print(f"\nElement {val} after pushed into heap")
+    max_heap.print()
+
+    # Pop the element at the heap top
+    peek = max_heap.pop()
+    print(f"\nHeap top element {peek} after exiting heap")
+    max_heap.print()
+
+    # Get heap size
+    size = max_heap.size()
+    print(f"\nNumber of heap elements is {size}")
+
+    # Determine if heap is empty
+    is_empty = max_heap.is_empty()
+    print(f"\nIs the heap empty {is_empty}")

en/codes/python/chapter_heap/top_k.py

@@ -0,0 +1,39 @@
+"""
+File: top_k.py
+Created Time: 2023-06-10
+Author: krahets (krahets@163.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import print_heap
+
+import heapq
+
+
+def top_k_heap(nums: list[int], k: int) -> list[int]:
+    """Using heap to find the largest k elements in an array"""
+    # Initialize min-heap
+    heap = []
+    # Enter the first k elements of the array into the heap
+    for i in range(k):
+        heapq.heappush(heap, nums[i])
+    # From the k+1th element, keep the heap length as k
+    for i in range(k, len(nums)):
+        # If the current element is larger than the heap top element, remove the heap top element and enter the current element into the heap
+        if nums[i] > heap[0]:
+            heapq.heappop(heap)
+            heapq.heappush(heap, nums[i])
+    return heap
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    nums = [1, 7, 6, 3, 2]
+    k = 3
+
+    res = top_k_heap(nums, k)
+    print(f"The largest {k} elements are")
+    print_heap(res)

en/codes/python/chapter_searching/binary_search.py

@@ -0,0 +1,52 @@
+"""
+File: binary_search.py
+Created Time: 2022-11-26
+Author: timi (xisunyy@163.com)
+"""
+
+
+def binary_search(nums: list[int], target: int) -> int:
+    """Binary search (double closed interval)"""
+    # Initialize double closed interval [0, n-1], i.e., i, j point to the first element and last element of the array respectively
+    i, j = 0, len(nums) - 1
+    # Loop until the search interval is empty (when i > j, it is empty)
+    while i <= j:
+        # Theoretically, Python's numbers can be infinitely large (depending on memory size), so there is no need to consider large number overflow
+        m = (i + j) // 2  # Calculate midpoint index m
+        if nums[m] < target:
+            i = m + 1  # This situation indicates that target is in the interval [m+1, j]
+        elif nums[m] > target:
+            j = m - 1  # This situation indicates that target is in the interval [i, m-1]
+        else:
+            return m  # Found the target element, thus return its index
+    return -1  # Did not find the target element, thus return -1
+
+
+def binary_search_lcro(nums: list[int], target: int) -> int:
+    """Binary search (left closed right open interval)"""
+    # Initialize left closed right open interval [0, n), i.e., i, j point to the first element and the last element +1 of the array respectively
+    i, j = 0, len(nums)
+    # Loop until the search interval is empty (when i = j, it is empty)
+    while i < j:
+        m = (i + j) // 2  # Calculate midpoint index m
+        if nums[m] < target:
+            i = m + 1  # This situation indicates that target is in the interval [m+1, j)
+        elif nums[m] > target:
+            j = m  # This situation indicates that target is in the interval [i, m)
+        else:
+            return m  # Found the target element, thus return its index
+    return -1  # Did not find the target element, thus return -1
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    target = 6
+    nums = [1, 3, 6, 8, 12, 15, 23, 26, 31, 35]
+
+    # Binary search (double closed interval)
+    index = binary_search(nums, target)
+    print("Index of target element 6 =", index)
+
+    # Binary search (left closed right open interval)
+    index = binary_search_lcro(nums, target)
+    print("Index of target element 6 =", index)

en/codes/python/chapter_searching/binary_search_edge.py

@@ -0,0 +1,49 @@
+"""
+File: binary_search_edge.py
+Created Time: 2023-08-04
+Author: krahets (krahets@163.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from binary_search_insertion import binary_search_insertion
+
+
+def binary_search_left_edge(nums: list[int], target: int) -> int:
+    """Binary search for the leftmost target"""
+    # Equivalent to finding the insertion point of target
+    i = binary_search_insertion(nums, target)
+    # Did not find target, thus return -1
+    if i == len(nums) or nums[i] != target:
+        return -1
+    # Found target, return index i
+    return i
+
+
+def binary_search_right_edge(nums: list[int], target: int) -> int:
+    """Binary search for the rightmost target"""
+    # Convert to finding the leftmost target + 1
+    i = binary_search_insertion(nums, target + 1)
+    # j points to the rightmost target, i points to the first element greater than target
+    j = i - 1
+    # Did not find target, thus return -1
+    if j == -1 or nums[j] != target:
+        return -1
+    # Found target, return index j
+    return j
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Array with duplicate elements
+    nums = [1, 3, 6, 6, 6, 6, 6, 10, 12, 15]
+    print(f"\nArray nums = {nums}")
+
+    # Binary search for left and right boundaries
+    for target in [6, 7]:
+        index = binary_search_left_edge(nums, target)
+        print(f"The index of the leftmost element {target} is {index}")
+        index = binary_search_right_edge(nums, target)
+        print(f"The index of the rightmost element {target} is {index}")

en/codes/python/chapter_searching/binary_search_insertion.py

@@ -0,0 +1,54 @@
+"""
+File: binary_search_insertion.py
+Created Time: 2023-08-04
+Author: krahets (krahets@163.com)
+"""
+
+
+def binary_search_insertion_simple(nums: list[int], target: int) -> int:
+    """Binary search for insertion point (no duplicate elements)"""
+    i, j = 0, len(nums) - 1  # Initialize double closed interval [0, n-1]
+    while i <= j:
+        m = (i + j) // 2  # Calculate midpoint index m
+        if nums[m] < target:
+            i = m + 1  # Target is in interval [m+1, j]
+        elif nums[m] > target:
+            j = m - 1  # Target is in interval [i, m-1]
+        else:
+            return m  # Found target, return insertion point m
+    # Did not find target, return insertion point i
+    return i
+
+
+def binary_search_insertion(nums: list[int], target: int) -> int:
+    """Binary search for insertion point (with duplicate elements)"""
+    i, j = 0, len(nums) - 1  # Initialize double closed interval [0, n-1]
+    while i <= j:
+        m = (i + j) // 2  # Calculate midpoint index m
+        if nums[m] < target:
+            i = m + 1  # Target is in interval [m+1, j]
+        elif nums[m] > target:
+            j = m - 1  # Target is in interval [i, m-1]
+        else:
+            j = m - 1  # First element less than target is in interval [i, m-1]
+    # Return insertion point i
+    return i
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Array without duplicate elements
+    nums = [1, 3, 6, 8, 12, 15, 23, 26, 31, 35]
+    print(f"\nArray nums = {nums}")
+    # Binary search for insertion point
+    for target in [6, 9]:
+        index = binary_search_insertion_simple(nums, target)
+        print(f"Element {target}'s insertion point index is {index}")
+
+    # Array with duplicate elements
+    nums = [1, 3, 6, 6, 6, 6, 6, 10, 12, 15]
+    print(f"\nArray nums = {nums}")
+    # Binary search for insertion point
+    for target in [2, 6, 20]:
+        index = binary_search_insertion(nums, target)
+        print(f"Element {target}'s insertion point index is {index}")

en/codes/python/chapter_searching/hashing_search.py

@@ -0,0 +1,51 @@
+"""
+File: hashing_search.py
+Created Time: 2022-11-26
+Author: timi (xisunyy@163.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import ListNode, list_to_linked_list
+
+
+def hashing_search_array(hmap: dict[int, int], target: int) -> int:
+    """Hash search (array)"""
+    # Hash table's key: target element, value: index
+    # If the hash table does not contain this key, return -1
+    return hmap.get(target, -1)
+
+
+def hashing_search_linkedlist(
+    hmap: dict[int, ListNode], target: int
+) -> ListNode | None:
+    """Hash search (linked list)"""
+    # Hash table's key: target element, value: node object
+    # If the hash table does not contain this key, return None
+    return hmap.get(target, None)
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    target = 3
+
+    # Hash search (array)
+    nums = [1, 5, 3, 2, 4, 7, 5, 9, 10, 8]
+    # Initialize hash table
+    map0 = dict[int, int]()
+    for i in range(len(nums)):
+        map0[nums[i]] = i  # key: element, value: index
+    index: int = hashing_search_array(map0, target)
+    print("Index of target element 3 =", index)
+
+    # Hash search (linked list)
+    head: ListNode = list_to_linked_list(nums)
+    # Initialize hash table
+    map1 = dict[int, ListNode]()
+    while head:
+        map1[head.val] = head  # key: node value, value: node
+        head = head.next
+    node: ListNode = hashing_search_linkedlist(map1, target)
+    print("Target node value 3's corresponding node object is", node)

en/codes/python/chapter_searching/linear_search.py

@@ -0,0 +1,45 @@
+"""
+File: linear_search.py
+Created Time: 2022-11-26
+Author: timi (xisunyy@163.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import ListNode, list_to_linked_list
+
+
+def linear_search_array(nums: list[int], target: int) -> int:
+    """Linear search (array)"""
+    # Traverse array
+    for i in range(len(nums)):
+        if nums[i] == target:  # Found the target element, thus return its index
+            return i
+    return -1  # Did not find the target element, thus return -1
+
+
+def linear_search_linkedlist(head: ListNode, target: int) -> ListNode | None:
+    """Linear search (linked list)"""
+    # Traverse the list
+    while head:
+        if head.val == target:  # Found the target node, return it
+            return head
+        head = head.next
+    return None  # Did not find the target node, thus return None
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    target = 3
+
+    # Perform linear search in array
+    nums = [1, 5, 3, 2, 4, 7, 5, 9, 10, 8]
+    index: int = linear_search_array(nums, target)
+    print("Index of target element 3 =", index)
+
+    # Perform linear search in linked list
+    head: ListNode = list_to_linked_list(nums)
+    node: ListNode | None = linear_search_linkedlist(head, target)
+    print("Target node value 3's corresponding node object is", node)

en/codes/python/chapter_searching/two_sum.py

@@ -0,0 +1,42 @@
+"""
+File: two_sum.py
+Created Time: 2022-11-25
+Author: krahets (krahets@163.com)
+"""
+
+
+def two_sum_brute_force(nums: list[int], target: int) -> list[int]:
+    """Method one: Brute force enumeration"""
+    # Two-layer loop, time complexity is O(n^2)
+    for i in range(len(nums) - 1):
+        for j in range(i + 1, len(nums)):
+            if nums[i] + nums[j] == target:
+                return [i, j]
+    return []
+
+
+def two_sum_hash_table(nums: list[int], target: int) -> list[int]:
+    """Method two: Auxiliary hash table"""
+    # Auxiliary hash table, space complexity is O(n)
+    dic = {}
+    # Single-layer loop, time complexity is O(n)
+    for i in range(len(nums)):
+        if target - nums[i] in dic:
+            return [dic[target - nums[i]], i]
+        dic[nums[i]] = i
+    return []
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # ======= Test Case =======
+    nums = [2, 7, 11, 15]
+    target = 13
+
+    # ====== Driver Code ======
+    # Method one
+    res: list[int] = two_sum_brute_force(nums, target)
+    print("Method one res =", res)
+    # Method two
+    res: list[int] = two_sum_hash_table(nums, target)
+    print("Method two res =", res)

en/codes/python/chapter_sorting/bubble_sort.py

@@ -0,0 +1,44 @@
+"""
+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

@@ -0,0 +1,69 @@
+"""
+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)

en/codes/python/chapter_stack_and_queue/array_deque.py

@@ -0,0 +1,129 @@
+"""
+File: array_deque.py
+Created Time: 2023-03-01
+Author: krahets (krahets@163.com)
+"""
+
+
+class ArrayDeque:
+    """Double-ended queue class based on circular array"""
+
+    def __init__(self, capacity: int):
+        """Constructor"""
+        self._nums: list[int] = [0] * capacity
+        self._front: int = 0
+        self._size: int = 0
+
+    def capacity(self) -> int:
+        """Get the capacity of the double-ended queue"""
+        return len(self._nums)
+
+    def size(self) -> int:
+        """Get the length of the double-ended queue"""
+        return self._size
+
+    def is_empty(self) -> bool:
+        """Determine if the double-ended queue is empty"""
+        return self._size == 0
+
+    def index(self, i: int) -> int:
+        """Calculate circular array index"""
+        # Implement circular array by modulo operation
+        # When i exceeds the tail of the array, return to the head
+        # When i exceeds the head of the array, return to the tail
+        return (i + self.capacity()) % self.capacity()
+
+    def push_first(self, num: int):
+        """Front enqueue"""
+        if self._size == self.capacity():
+            print("Double-ended queue is full")
+            return
+        # Move the front pointer one position to the left
+        # Implement front crossing the head of the array to return to the tail by modulo operation
+        self._front = self.index(self._front - 1)
+        # Add num to the front
+        self._nums[self._front] = num
+        self._size += 1
+
+    def push_last(self, num: int):
+        """Rear enqueue"""
+        if self._size == self.capacity():
+            print("Double-ended queue is full")
+            return
+        # Calculate rear pointer, pointing to rear index + 1
+        rear = self.index(self._front + self._size)
+        # Add num to the rear
+        self._nums[rear] = num
+        self._size += 1
+
+    def pop_first(self) -> int:
+        """Front dequeue"""
+        num = self.peek_first()
+        # Move front pointer one position backward
+        self._front = self.index(self._front + 1)
+        self._size -= 1
+        return num
+
+    def pop_last(self) -> int:
+        """Rear dequeue"""
+        num = self.peek_last()
+        self._size -= 1
+        return num
+
+    def peek_first(self) -> int:
+        """Access front element"""
+        if self.is_empty():
+            raise IndexError("Double-ended queue is empty")
+        return self._nums[self._front]
+
+    def peek_last(self) -> int:
+        """Access rear element"""
+        if self.is_empty():
+            raise IndexError("Double-ended queue is empty")
+        # Calculate rear element index
+        last = self.index(self._front + self._size - 1)
+        return self._nums[last]
+
+    def to_array(self) -> list[int]:
+        """Return array for printing"""
+        # Only convert elements within valid length range
+        res = []
+        for i in range(self._size):
+            res.append(self._nums[self.index(self._front + i)])
+        return res
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize double-ended queue
+    deque = ArrayDeque(10)
+    deque.push_last(3)
+    deque.push_last(2)
+    deque.push_last(5)
+    print("Double-ended queue deque =", deque.to_array())
+
+    # Access element
+    peek_first: int = deque.peek_first()
+    print("Front element peek_first =", peek_first)
+    peek_last: int = deque.peek_last()
+    print("Rear element peek_last =", peek_last)
+
+    # Element enqueue
+    deque.push_last(4)
+    print("Element 4 rear enqueued, deque =", deque.to_array())
+    deque.push_first(1)
+    print("Element 1 front enqueued, deque =", deque.to_array())
+
+    # Element dequeue
+    pop_last: int = deque.pop_last()
+    print("Rear dequeued element =", pop_last, ", deque after rear dequeue =", deque.to_array())
+    pop_first: int = deque.pop_first()
+    print("Front dequeued element =", pop_first, ", deque after front dequeue =", deque.to_array())
+
+    # Get the length of the double-ended queue
+    size: int = deque.size()
+    print("Double-ended queue length size =", size)
+
+    # Determine if the double-ended queue is empty
+    is_empty: bool = deque.is_empty()
+    print("Is the double-ended queue empty =", is_empty)

en/codes/python/chapter_stack_and_queue/array_queue.py

@@ -0,0 +1,98 @@
+"""
+File: array_queue.py
+Created Time: 2022-12-01
+Author: Peng Chen (pengchzn@gmail.com)
+"""
+
+
+class ArrayQueue:
+    """Queue class based on circular array"""
+
+    def __init__(self, size: int):
+        """Constructor"""
+        self._nums: list[int] = [0] * size  # Array for storing queue elements
+        self._front: int = 0  # Front pointer, pointing to the front element
+        self._size: int = 0  # Queue length
+
+    def capacity(self) -> int:
+        """Get the capacity of the queue"""
+        return len(self._nums)
+
+    def size(self) -> int:
+        """Get the length of the queue"""
+        return self._size
+
+    def is_empty(self) -> bool:
+        """Determine if the queue is empty"""
+        return self._size == 0
+
+    def push(self, num: int):
+        """Enqueue"""
+        if self._size == self.capacity():
+            raise IndexError("Queue is full")
+        # Calculate rear pointer, pointing to rear index + 1
+        # Use modulo operation to wrap the rear pointer from the end of the array back to the start
+        rear: int = (self._front + self._size) % self.capacity()
+        # Add num to the rear
+        self._nums[rear] = num
+        self._size += 1
+
+    def pop(self) -> int:
+        """Dequeue"""
+        num: int = self.peek()
+        # Move front pointer one position backward, returning to the head of the array if it exceeds the tail
+        self._front = (self._front + 1) % self.capacity()
+        self._size -= 1
+        return num
+
+    def peek(self) -> int:
+        """Access front element"""
+        if self.is_empty():
+            raise IndexError("Queue is empty")
+        return self._nums[self._front]
+
+    def to_list(self) -> list[int]:
+        """Return array for printing"""
+        res = [0] * self.size()
+        j: int = self._front
+        for i in range(self.size()):
+            res[i] = self._nums[(j % self.capacity())]
+            j += 1
+        return res
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize queue
+    queue = ArrayQueue(10)
+
+    # Element enqueue
+    queue.push(1)
+    queue.push(3)
+    queue.push(2)
+    queue.push(5)
+    queue.push(4)
+    print("Queue queue =", queue.to_list())
+
+    # Access front element
+    peek: int = queue.peek()
+    print("Front element peek =", peek)
+
+    # Element dequeue
+    pop: int = queue.pop()
+    print("Dequeued element pop =", pop)
+    print("Queue after dequeue =", queue.to_list())
+
+    # Get the length of the queue
+    size: int = queue.size()
+    print("Queue length size =", size)
+
+    # Determine if the queue is empty
+    is_empty: bool = queue.is_empty()
+    print("Is the queue empty =", is_empty)
+
+    # Test circular array
+    for i in range(10):
+        queue.push(i)
+        queue.pop()
+        print("In the ", i, "th round of enqueue + dequeue, queue = ", queue.to_list())

en/codes/python/chapter_stack_and_queue/array_stack.py

@@ -0,0 +1,72 @@
+"""
+File: array_stack.py
+Created Time: 2022-11-29
+Author: Peng Chen (pengchzn@gmail.com)
+"""
+
+
+class ArrayStack:
+    """Stack class based on array"""
+
+    def __init__(self):
+        """Constructor"""
+        self._stack: list[int] = []
+
+    def size(self) -> int:
+        """Get the length of the stack"""
+        return len(self._stack)
+
+    def is_empty(self) -> bool:
+        """Determine if the stack is empty"""
+        return self.size() == 0
+
+    def push(self, item: int):
+        """Push"""
+        self._stack.append(item)
+
+    def pop(self) -> int:
+        """Pop"""
+        if self.is_empty():
+            raise IndexError("Stack is empty")
+        return self._stack.pop()
+
+    def peek(self) -> int:
+        """Access stack top element"""
+        if self.is_empty():
+            raise IndexError("Stack is empty")
+        return self._stack[-1]
+
+    def to_list(self) -> list[int]:
+        """Return array for printing"""
+        return self._stack
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize stack
+    stack = ArrayStack()
+
+    # Element push
+    stack.push(1)
+    stack.push(3)
+    stack.push(2)
+    stack.push(5)
+    stack.push(4)
+    print("Stack stack =", stack.to_list())
+
+    # Access stack top element
+    peek: int = stack.peek()
+    print("Stack top element peek =", peek)
+
+    # Element pop
+    pop: int = stack.pop()
+    print("Popped element pop =", pop)
+    print("Stack after pop =", stack.to_list())
+
+    # Get the length of the stack
+    size: int = stack.size()
+    print("Stack length size =", size)
+
+    # Determine if it's empty
+    is_empty: bool = stack.is_empty()
+    print("Is the stack empty =", is_empty)

en/codes/python/chapter_stack_and_queue/deque.py

@@ -0,0 +1,42 @@
+"""
+File: deque.py
+Created Time: 2022-11-29
+Author: Peng Chen (pengchzn@gmail.com)
+"""
+
+from collections import deque
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize double-ended queue
+    deq: deque[int] = deque()
+
+    # Element enqueue
+    deq.append(2)  # Add to rear
+    deq.append(5)
+    deq.append(4)
+    deq.appendleft(3)  # Add to front
+    deq.appendleft(1)
+    print("Double-ended queue deque =", deq)
+
+    # Access element
+    front: int = deq[0]  # Front element
+    print("Front element front =", front)
+    rear: int = deq[-1]  # Rear element
+    print("Rear element rear =", rear)
+
+    # Element dequeue
+    pop_front: int = deq.popleft()  # Front element dequeue
+    print("Front dequeued element  pop_front =", pop_front)
+    print("Deque after front dequeue =", deq)
+    pop_rear: int = deq.pop()  # Rear element dequeue
+    print("Rear dequeued element  pop_rear =", pop_rear)
+    print("Deque after rear dequeue =", deq)
+
+    # Get the length of the double-ended queue
+    size: int = len(deq)
+    print("Double-ended queue length size =", size)
+
+    # Determine if the double-ended queue is empty
+    is_empty: bool = len(deq) == 0
+    print("Is the double-ended queue empty =", is_empty)

en/codes/python/chapter_stack_and_queue/linkedlist_deque.py

@@ -0,0 +1,151 @@
+"""
+File: linkedlist_deque.py
+Created Time: 2023-03-01
+Author: krahets (krahets@163.com)
+"""
+
+
+class ListNode:
+    """Double-linked list node"""
+
+    def __init__(self, val: int):
+        """Constructor"""
+        self.val: int = val
+        self.next: ListNode | None = None  # Reference to the next node
+        self.prev: ListNode | None = None  # Reference to predecessor node
+
+
+class LinkedListDeque:
+    """Double-ended queue class based on double-linked list"""
+
+    def __init__(self):
+        """Constructor"""
+        self._front: ListNode | None = None  # Head node front
+        self._rear: ListNode | None = None  # Tail node rear
+        self._size: int = 0  # Length of the double-ended queue
+
+    def size(self) -> int:
+        """Get the length of the double-ended queue"""
+        return self._size
+
+    def is_empty(self) -> bool:
+        """Determine if the double-ended queue is empty"""
+        return self._size == 0
+
+    def push(self, num: int, is_front: bool):
+        """Enqueue operation"""
+        node = ListNode(num)
+        # If the list is empty, make front and rear both point to node
+        if self.is_empty():
+            self._front = self._rear = node
+        # Front enqueue operation
+        elif is_front:
+            # Add node to the head of the list
+            self._front.prev = node
+            node.next = self._front
+            self._front = node  # Update head node
+        # Rear enqueue operation
+        else:
+            # Add node to the tail of the list
+            self._rear.next = node
+            node.prev = self._rear
+            self._rear = node  # Update tail node
+        self._size += 1  # Update queue length
+
+    def push_first(self, num: int):
+        """Front enqueue"""
+        self.push(num, True)
+
+    def push_last(self, num: int):
+        """Rear enqueue"""
+        self.push(num, False)
+
+    def pop(self, is_front: bool) -> int:
+        """Dequeue operation"""
+        if self.is_empty():
+            raise IndexError("Double-ended queue is empty")
+        # Front dequeue operation
+        if is_front:
+            val: int = self._front.val  # Temporarily store the head node value
+            # Remove head node
+            fnext: ListNode | None = self._front.next
+            if fnext != None:
+                fnext.prev = None
+                self._front.next = None
+            self._front = fnext  # Update head node
+        # Rear dequeue operation
+        else:
+            val: int = self._rear.val  # Temporarily store the tail node value
+            # Remove tail node
+            rprev: ListNode | None = self._rear.prev
+            if rprev != None:
+                rprev.next = None
+                self._rear.prev = None
+            self._rear = rprev  # Update tail node
+        self._size -= 1  # Update queue length
+        return val
+
+    def pop_first(self) -> int:
+        """Front dequeue"""
+        return self.pop(True)
+
+    def pop_last(self) -> int:
+        """Rear dequeue"""
+        return self.pop(False)
+
+    def peek_first(self) -> int:
+        """Access front element"""
+        if self.is_empty():
+            raise IndexError("Double-ended queue is empty")
+        return self._front.val
+
+    def peek_last(self) -> int:
+        """Access rear element"""
+        if self.is_empty():
+            raise IndexError("Double-ended queue is empty")
+        return self._rear.val
+
+    def to_array(self) -> list[int]:
+        """Return array for printing"""
+        node = self._front
+        res = [0] * self.size()
+        for i in range(self.size()):
+            res[i] = node.val
+            node = node.next
+        return res
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize double-ended queue
+    deque = LinkedListDeque()
+    deque.push_last(3)
+    deque.push_last(2)
+    deque.push_last(5)
+    print("Double-ended queue deque =", deque.to_array())
+
+    # Access element
+    peek_first: int = deque.peek_first()
+    print("Front element peek_first =", peek_first)
+    peek_last: int = deque.peek_last()
+    print("Rear element peek_last =", peek_last)
+
+    # Element enqueue
+    deque.push_last(4)
+    print("Element 4 rear enqueued, deque =", deque.to_array())
+    deque.push_first(1)
+    print("Element 1 front enqueued, deque =", deque.to_array())
+
+    # Element dequeue
+    pop_last: int = deque.pop_last()
+    print("Rear dequeued element =", pop_last, ", deque after rear dequeue =", deque.to_array())
+    pop_first: int = deque.pop_first()
+    print("Front dequeued element =", pop_first, ", deque after front dequeue =", deque.to_array())
+
+    # Get the length of the double-ended queue
+    size: int = deque.size()
+    print("Double-ended queue length size =", size)
+
+    # Determine if the double-ended queue is empty
+    is_empty: bool = deque.is_empty()
+    print("Is the double-ended queue empty =", is_empty)

en/codes/python/chapter_stack_and_queue/linkedlist_queue.py

@@ -0,0 +1,97 @@
+"""
+File: linkedlist_queue.py
+Created Time: 2022-12-01
+Author: Peng Chen (pengchzn@gmail.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import ListNode
+
+
+class LinkedListQueue:
+    """Queue class based on linked list"""
+
+    def __init__(self):
+        """Constructor"""
+        self._front: ListNode | None = None  # Head node front
+        self._rear: ListNode | None = None  # Tail node rear
+        self._size: int = 0
+
+    def size(self) -> int:
+        """Get the length of the queue"""
+        return self._size
+
+    def is_empty(self) -> bool:
+        """Determine if the queue is empty"""
+        return self._size == 0
+
+    def push(self, num: int):
+        """Enqueue"""
+        # Add num behind the tail node
+        node = ListNode(num)
+        # If the queue is empty, make the head and tail nodes both point to that node
+        if self._front is None:
+            self._front = node
+            self._rear = node
+        # If the queue is not empty, add that node behind the tail node
+        else:
+            self._rear.next = node
+            self._rear = node
+        self._size += 1
+
+    def pop(self) -> int:
+        """Dequeue"""
+        num = self.peek()
+        # Remove head node
+        self._front = self._front.next
+        self._size -= 1
+        return num
+
+    def peek(self) -> int:
+        """Access front element"""
+        if self.is_empty():
+            raise IndexError("Queue is empty")
+        return self._front.val
+
+    def to_list(self) -> list[int]:
+        """Convert to a list for printing"""
+        queue = []
+        temp = self._front
+        while temp:
+            queue.append(temp.val)
+            temp = temp.next
+        return queue
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize queue
+    queue = LinkedListQueue()
+
+    # Element enqueue
+    queue.push(1)
+    queue.push(3)
+    queue.push(2)
+    queue.push(5)
+    queue.push(4)
+    print("Queue queue =", queue.to_list())
+
+    # Access front element
+    peek: int = queue.peek()
+    print("Front element front =", peek)
+
+    # Element dequeue
+    pop_front: int = queue.pop()
+    print("Dequeued element pop =", pop_front)
+    print("Queue after dequeue =", queue.to_list())
+
+    # Get the length of the queue
+    size: int = queue.size()
+    print("Queue length size =", size)
+
+    # Determine if the queue is empty
+    is_empty: bool = queue.is_empty()
+    print("Is the queue empty =", is_empty)

en/codes/python/chapter_stack_and_queue/linkedlist_stack.py

@@ -0,0 +1,89 @@
+"""
+File: linkedlist_stack.py
+Created Time: 2022-11-29
+Author: Peng Chen (pengchzn@gmail.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import ListNode
+
+
+class LinkedListStack:
+    """Stack class based on linked list"""
+
+    def __init__(self):
+        """Constructor"""
+        self._peek: ListNode | None = None
+        self._size: int = 0
+
+    def size(self) -> int:
+        """Get the length of the stack"""
+        return self._size
+
+    def is_empty(self) -> bool:
+        """Determine if the stack is empty"""
+        return self._size == 0
+
+    def push(self, val: int):
+        """Push"""
+        node = ListNode(val)
+        node.next = self._peek
+        self._peek = node
+        self._size += 1
+
+    def pop(self) -> int:
+        """Pop"""
+        num = self.peek()
+        self._peek = self._peek.next
+        self._size -= 1
+        return num
+
+    def peek(self) -> int:
+        """Access stack top element"""
+        if self.is_empty():
+            raise IndexError("Stack is empty")
+        return self._peek.val
+
+    def to_list(self) -> list[int]:
+        """Convert to a list for printing"""
+        arr = []
+        node = self._peek
+        while node:
+            arr.append(node.val)
+            node = node.next
+        arr.reverse()
+        return arr
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize stack
+    stack = LinkedListStack()
+
+    # Element push
+    stack.push(1)
+    stack.push(3)
+    stack.push(2)
+    stack.push(5)
+    stack.push(4)
+    print("Stack stack =", stack.to_list())
+
+    # Access stack top element
+    peek: int = stack.peek()
+    print("Stack top element peek =", peek)
+
+    # Element pop
+    pop: int = stack.pop()
+    print("Popped element pop =", pop)
+    print("Stack after pop =", stack.to_list())
+
+    # Get the length of the stack
+    size: int = stack.size()
+    print("Stack length size =", size)
+
+    # Determine if it's empty
+    is_empty: bool = stack.is_empty()
+    print("Is the stack empty =", is_empty)

en/codes/python/chapter_stack_and_queue/queue.py

@@ -0,0 +1,39 @@
+"""
+File: queue.py
+Created Time: 2022-11-29
+Author: Peng Chen (pengchzn@gmail.com)
+"""
+
+from collections import deque
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize queue
+    # In Python, we generally consider the deque class as a queue
+    # Although queue.Queue() is a pure queue class, it's not very user-friendly
+    que: deque[int] = deque()
+
+    # Element enqueue
+    que.append(1)
+    que.append(3)
+    que.append(2)
+    que.append(5)
+    que.append(4)
+    print("Queue que =", que)
+
+    # Access front element
+    front: int = que[0]
+    print("Front element front =", front)
+
+    # Element dequeue
+    pop: int = que.popleft()
+    print("Dequeued element pop =", pop)
+    print("Queue after dequeue =", que)
+
+    # Get the length of the queue
+    size: int = len(que)
+    print("Queue length size =", size)
+
+    # Determine if the queue is empty
+    is_empty: bool = len(que) == 0
+    print("Is the queue empty =", is_empty)

en/codes/python/chapter_stack_and_queue/stack.py

@@ -0,0 +1,36 @@
+"""
+File: stack.py
+Created Time: 2022-11-29
+Author: Peng Chen (pengchzn@gmail.com)
+"""
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize stack
+    # Python does not have a built-in stack class, but you can use a list as a stack
+    stack: list[int] = []
+
+    # Element push
+    stack.append(1)
+    stack.append(3)
+    stack.append(2)
+    stack.append(5)
+    stack.append(4)
+    print("Stack stack =", stack)
+
+    # Access stack top element
+    peek: int = stack[-1]
+    print("Stack top element peek =", peek)
+
+    # Element pop
+    pop: int = stack.pop()
+    print("Popped element pop =", pop)
+    print("Stack after pop =", stack)
+
+    # Get the length of the stack
+    size: int = len(stack)
+    print("Stack length size =", size)
+
+    # Determine if it's empty
+    is_empty: bool = len(stack) == 0
+    print("Is the stack empty =", is_empty)

en/codes/python/chapter_tree/array_binary_tree.py

@@ -0,0 +1,119 @@
+"""
+File: array_binary_tree.py
+Created Time: 2023-07-19
+Author: krahets (krahets@163.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import TreeNode, list_to_tree, print_tree
+
+
+class ArrayBinaryTree:
+    """Array-based binary tree class"""
+
+    def __init__(self, arr: list[int | None]):
+        """Constructor"""
+        self._tree = list(arr)
+
+    def size(self):
+        """List capacity"""
+        return len(self._tree)
+
+    def val(self, i: int) -> int | None:
+        """Get the value of the node at index i"""
+        # If the index is out of bounds, return None, representing a vacancy
+        if i < 0 or i >= self.size():
+            return None
+        return self._tree[i]
+
+    def left(self, i: int) -> int | None:
+        """Get the index of the left child of the node at index i"""
+        return 2 * i + 1
+
+    def right(self, i: int) -> int | None:
+        """Get the index of the right child of the node at index i"""
+        return 2 * i + 2
+
+    def parent(self, i: int) -> int | None:
+        """Get the index of the parent of the node at index i"""
+        return (i - 1) // 2
+
+    def level_order(self) -> list[int]:
+        """Level-order traversal"""
+        self.res = []
+        # Traverse array
+        for i in range(self.size()):
+            if self.val(i) is not None:
+                self.res.append(self.val(i))
+        return self.res
+
+    def dfs(self, i: int, order: str):
+        """Depth-first traversal"""
+        if self.val(i) is None:
+            return
+        # Pre-order traversal
+        if order == "pre":
+            self.res.append(self.val(i))
+        self.dfs(self.left(i), order)
+        # In-order traversal
+        if order == "in":
+            self.res.append(self.val(i))
+        self.dfs(self.right(i), order)
+        # Post-order traversal
+        if order == "post":
+            self.res.append(self.val(i))
+
+    def pre_order(self) -> list[int]:
+        """Pre-order traversal"""
+        self.res = []
+        self.dfs(0, order="pre")
+        return self.res
+
+    def in_order(self) -> list[int]:
+        """In-order traversal"""
+        self.res = []
+        self.dfs(0, order="in")
+        return self.res
+
+    def post_order(self) -> list[int]:
+        """Post-order traversal"""
+        self.res = []
+        self.dfs(0, order="post")
+        return self.res
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize binary tree
+    # Use a specific function to convert an array into a binary tree
+    arr = [1, 2, 3, 4, None, 6, 7, 8, 9, None, None, 12, None, None, 15]
+    root = list_to_tree(arr)
+    print("\nInitialize binary tree\n")
+    print("Array representation of the binary tree:")
+    print(arr)
+    print("Linked list representation of the binary tree:")
+    print_tree(root)
+
+    # Array-based binary tree class
+    abt = ArrayBinaryTree(arr)
+
+    # Access node
+    i = 1
+    l, r, p = abt.left(i), abt.right(i), abt.parent(i)
+    print(f"\nCurrent node index is {i}, value is {abt.val(i)}")
+    print(f"Its left child node index is {l}, value is {abt.val(l)}")
+    print(f"Its right child node index is {r}, value is {abt.val(r)}")
+    print(f"Its parent node index is {p}, value is {abt.val(p)}")
+
+    # Traverse tree
+    res = abt.level_order()
+    print("\nLevel-order traversal is:", res)
+    res = abt.pre_order()
+    print("Pre-order traversal is:", res)
+    res = abt.in_order()
+    print("In-order traversal is:", res)
+    res = abt.post_order()
+    print("Post-order traversal is:", res)

en/codes/python/chapter_tree/avl_tree.py

@@ -0,0 +1,200 @@
+"""
+File: avl_tree.py
+Created Time: 2022-12-20
+Author: a16su (lpluls001@gmail.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import TreeNode, print_tree
+
+
+class AVLTree:
+    """AVL tree"""
+
+    def __init__(self):
+        """Constructor"""
+        self._root = None
+
+    def get_root(self) -> TreeNode | None:
+        """Get binary tree root node"""
+        return self._root
+
+    def height(self, node: TreeNode | None) -> int:
+        """Get node height"""
+        # Empty node height is -1, leaf node height is 0
+        if node is not None:
+            return node.height
+        return -1
+
+    def update_height(self, node: TreeNode | None):
+        """Update node height"""
+        # Node height equals the height of the tallest subtree + 1
+        node.height = max([self.height(node.left), self.height(node.right)]) + 1
+
+    def balance_factor(self, node: TreeNode | None) -> int:
+        """Get balance factor"""
+        # Empty node balance factor is 0
+        if node is None:
+            return 0
+        # Node balance factor = left subtree height - right subtree height
+        return self.height(node.left) - self.height(node.right)
+
+    def right_rotate(self, node: TreeNode | None) -> TreeNode | None:
+        """Right rotation operation"""
+        child = node.left
+        grand_child = child.right
+        # Rotate node to the right around child
+        child.right = node
+        node.left = grand_child
+        # Update node height
+        self.update_height(node)
+        self.update_height(child)
+        # Return the root of the subtree after rotation
+        return child
+
+    def left_rotate(self, node: TreeNode | None) -> TreeNode | None:
+        """Left rotation operation"""
+        child = node.right
+        grand_child = child.left
+        # Rotate node to the left around child
+        child.left = node
+        node.right = grand_child
+        # Update node height
+        self.update_height(node)
+        self.update_height(child)
+        # Return the root of the subtree after rotation
+        return child
+
+    def rotate(self, node: TreeNode | None) -> TreeNode | None:
+        """Perform rotation operation to restore balance to the subtree"""
+        # Get the balance factor of node
+        balance_factor = self.balance_factor(node)
+        # Left-leaning tree
+        if balance_factor > 1:
+            if self.balance_factor(node.left) >= 0:
+                # Right rotation
+                return self.right_rotate(node)
+            else:
+                # First left rotation then right rotation
+                node.left = self.left_rotate(node.left)
+                return self.right_rotate(node)
+        # Right-leaning tree
+        elif balance_factor < -1:
+            if self.balance_factor(node.right) <= 0:
+                # Left rotation
+                return self.left_rotate(node)
+            else:
+                # First right rotation then left rotation
+                node.right = self.right_rotate(node.right)
+                return self.left_rotate(node)
+        # Balanced tree, no rotation needed, return
+        return node
+
+    def insert(self, val):
+        """Insert node"""
+        self._root = self.insert_helper(self._root, val)
+
+    def insert_helper(self, node: TreeNode | None, val: int) -> TreeNode:
+        """Recursively insert node (helper method)"""
+        if node is None:
+            return TreeNode(val)
+        # 1. Find insertion position and insert node
+        if val < node.val:
+            node.left = self.insert_helper(node.left, val)
+        elif val > node.val:
+            node.right = self.insert_helper(node.right, val)
+        else:
+            # Do not insert duplicate nodes, return
+            return node
+        # Update node height
+        self.update_height(node)
+        # 2. Perform rotation operation to restore balance to the subtree
+        return self.rotate(node)
+
+    def remove(self, val: int):
+        """Remove node"""
+        self._root = self.remove_helper(self._root, val)
+
+    def remove_helper(self, node: TreeNode | None, val: int) -> TreeNode | None:
+        """Recursively remove node (helper method)"""
+        if node is None:
+            return None
+        # 1. Find and remove the node
+        if val < node.val:
+            node.left = self.remove_helper(node.left, val)
+        elif val > node.val:
+            node.right = self.remove_helper(node.right, val)
+        else:
+            if node.left is None or node.right is None:
+                child = node.left or node.right
+                # Number of child nodes = 0, remove node and return
+                if child is None:
+                    return None
+                # Number of child nodes = 1, remove node
+                else:
+                    node = child
+            else:
+                # Number of child nodes = 2, remove the next node in in-order traversal and replace the current node with it
+                temp = node.right
+                while temp.left is not None:
+                    temp = temp.left
+                node.right = self.remove_helper(node.right, temp.val)
+                node.val = temp.val
+        # Update node height
+        self.update_height(node)
+        # 2. Perform rotation operation to restore balance to the subtree
+        return self.rotate(node)
+
+    def search(self, val: int) -> TreeNode | None:
+        """Search node"""
+        cur = self._root
+        # Loop find, break after passing leaf nodes
+        while cur is not None:
+            # Target node is in cur's right subtree
+            if cur.val < val:
+                cur = cur.right
+            # Target node is in cur's left subtree
+            elif cur.val > val:
+                cur = cur.left
+            # Found target node, break loop
+            else:
+                break
+        # Return target node
+        return cur
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+
+    def test_insert(tree: AVLTree, val: int):
+        tree.insert(val)
+        print("\nInsert node {} after, AVL tree is".format(val))
+        print_tree(tree.get_root())
+
+    def test_remove(tree: AVLTree, val: int):
+        tree.remove(val)
+        print("\nRemove node {} after, AVL tree is".format(val))
+        print_tree(tree.get_root())
+
+    # Initialize empty AVL tree
+    avl_tree = AVLTree()
+
+    # Insert node
+    # Notice how the AVL tree maintains balance after inserting nodes
+    for val in [1, 2, 3, 4, 5, 8, 7, 9, 10, 6]:
+        test_insert(avl_tree, val)
+
+    # Insert duplicate node
+    test_insert(avl_tree, 7)
+
+    # Remove node
+    # Notice how the AVL tree maintains balance after removing nodes
+    test_remove(avl_tree, 8)  # Remove node with degree 0
+    test_remove(avl_tree, 5)  # Remove node with degree 1
+    test_remove(avl_tree, 4)  # Remove node with degree 2
+
+    result_node = avl_tree.search(7)
+    print("\nFound node object is {}, node value = {}".format(result_node, result_node.val))

en/codes/python/chapter_tree/binary_search_tree.py

@@ -0,0 +1,146 @@
+"""
+File: binary_search_tree.py
+Created Time: 2022-12-20
+Author: a16su (lpluls001@gmail.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import TreeNode, print_tree
+
+
+class BinarySearchTree:
+    """Binary search tree"""
+
+    def __init__(self):
+        """Constructor"""
+        # Initialize empty tree
+        self._root = None
+
+    def get_root(self) -> TreeNode | None:
+        """Get binary tree root node"""
+        return self._root
+
+    def search(self, num: int) -> TreeNode | None:
+        """Search node"""
+        cur = self._root
+        # Loop find, break after passing leaf nodes
+        while cur is not None:
+            # Target node is in cur's right subtree
+            if cur.val < num:
+                cur = cur.right
+            # Target node is in cur's left subtree
+            elif cur.val > num:
+                cur = cur.left
+            # Found target node, break loop
+            else:
+                break
+        return cur
+
+    def insert(self, num: int):
+        """Insert node"""
+        # If tree is empty, initialize root node
+        if self._root is None:
+            self._root = TreeNode(num)
+            return
+        # Loop find, break after passing leaf nodes
+        cur, pre = self._root, None
+        while cur is not None:
+            # Found duplicate node, thus return
+            if cur.val == num:
+                return
+            pre = cur
+            # Insertion position is in cur's right subtree
+            if cur.val < num:
+                cur = cur.right
+            # Insertion position is in cur's left subtree
+            else:
+                cur = cur.left
+        # Insert node
+        node = TreeNode(num)
+        if pre.val < num:
+            pre.right = node
+        else:
+            pre.left = node
+
+    def remove(self, num: int):
+        """Remove node"""
+        # If tree is empty, return
+        if self._root is None:
+            return
+        # Loop find, break after passing leaf nodes
+        cur, pre = self._root, None
+        while cur is not None:
+            # Found node to be removed, break loop
+            if cur.val == num:
+                break
+            pre = cur
+            # Node to be removed is in cur's right subtree
+            if cur.val < num:
+                cur = cur.right
+            # Node to be removed is in cur's left subtree
+            else:
+                cur = cur.left
+        # If no node to be removed, return
+        if cur is None:
+            return
+
+        # Number of child nodes = 0 or 1
+        if cur.left is None or cur.right is None:
+            # When the number of child nodes = 0/1, child = null/that child node
+            child = cur.left or cur.right
+            # Remove node cur
+            if cur != self._root:
+                if pre.left == cur:
+                    pre.left = child
+                else:
+                    pre.right = child
+            else:
+                # If the removed node is the root, reassign the root
+                self._root = child
+        # Number of child nodes = 2
+        else:
+            # Get the next node in in-order traversal of cur
+            tmp: TreeNode = cur.right
+            while tmp.left is not None:
+                tmp = tmp.left
+            # Recursively remove node tmp
+            self.remove(tmp.val)
+            # Replace cur with tmp
+            cur.val = tmp.val
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize binary search tree
+    bst = BinarySearchTree()
+    nums = [8, 4, 12, 2, 6, 10, 14, 1, 3, 5, 7, 9, 11, 13, 15]
+    # Note that different insertion orders can result in various tree structures. This particular sequence creates a perfect binary tree
+    for num in nums:
+        bst.insert(num)
+    print("\nInitialized binary tree is\n")
+    print_tree(bst.get_root())
+
+    # Search node
+    node = bst.search(7)
+    print("\nFound node object is: {}, node value = {}".format(node, node.val))
+
+    # Insert node
+    bst.insert(16)
+    print("\nAfter inserting node 16, the binary tree is\n")
+    print_tree(bst.get_root())
+
+    # Remove node
+    bst.remove(1)
+    print("\nAfter removing node 1, the binary tree is\n")
+    print_tree(bst.get_root())
+
+    bst.remove(2)
+    print("\nAfter removing node 2, the binary tree is\n")
+    print_tree(bst.get_root())
+
+    bst.remove(4)
+    print("\nAfter removing node 4, the binary tree is\n")
+    print_tree(bst.get_root())

en/codes/python/chapter_tree/binary_tree.py

@@ -0,0 +1,41 @@
+"""
+File: binary_tree.py
+Created Time: 2022-12-20
+Author: a16su (lpluls001@gmail.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import TreeNode, print_tree
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize binary tree
+    # Initialize node
+    n1 = TreeNode(val=1)
+    n2 = TreeNode(val=2)
+    n3 = TreeNode(val=3)
+    n4 = TreeNode(val=4)
+    n5 = TreeNode(val=5)
+    # Construct node references (pointers)
+    n1.left = n2
+    n1.right = n3
+    n2.left = n4
+    n2.right = n5
+    print("\nInitialize binary tree\n")
+    print_tree(n1)
+
+    # Insert and remove nodes
+    P = TreeNode(0)
+    # Insert node P between n1 -> n2
+    n1.left = P
+    P.left = n2
+    print("\nAfter inserting node P\n")
+    print_tree(n1)
+    # Remove node
+    n1.left = n2
+    print("\nAfter removing node P\n")
+    print_tree(n1)

en/codes/python/chapter_tree/binary_tree_bfs.py

@@ -0,0 +1,42 @@
+"""
+File: binary_tree_bfs.py
+Created Time: 2022-12-20
+Author: a16su (lpluls001@gmail.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import TreeNode, list_to_tree, print_tree
+from collections import deque
+
+
+def level_order(root: TreeNode | None) -> list[int]:
+    """Level-order traversal"""
+    # Initialize queue, add root node
+    queue: deque[TreeNode] = deque()
+    queue.append(root)
+    # Initialize a list to store the traversal sequence
+    res = []
+    while queue:
+        node: TreeNode = queue.popleft()  # Queue dequeues
+        res.append(node.val)  # Save node value
+        if node.left is not None:
+            queue.append(node.left)  # Left child node enqueues
+        if node.right is not None:
+            queue.append(node.right)  # Right child node enqueues
+    return res
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize binary tree
+    # Use a specific function to convert an array into a binary tree
+    root: TreeNode = list_to_tree(arr=[1, 2, 3, 4, 5, 6, 7])
+    print("\nInitialize binary tree\n")
+    print_tree(root)
+
+    # Level-order traversal
+    res: list[int] = level_order(root)
+    print("\nPrint sequence of nodes from level-order traversal = ", res)

en/codes/python/chapter_tree/binary_tree_dfs.py

@@ -0,0 +1,65 @@
+"""
+File: binary_tree_dfs.py
+Created Time: 2022-12-20
+Author: a16su (lpluls001@gmail.com)
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.append(str(Path(__file__).parent.parent))
+from modules import TreeNode, list_to_tree, print_tree
+
+
+def pre_order(root: TreeNode | None):
+    """Pre-order traversal"""
+    if root is None:
+        return
+    # Visit priority: root node -> left subtree -> right subtree
+    res.append(root.val)
+    pre_order(root=root.left)
+    pre_order(root=root.right)
+
+
+def in_order(root: TreeNode | None):
+    """In-order traversal"""
+    if root is None:
+        return
+    # Visit priority: left subtree -> root node -> right subtree
+    in_order(root=root.left)
+    res.append(root.val)
+    in_order(root=root.right)
+
+
+def post_order(root: TreeNode | None):
+    """Post-order traversal"""
+    if root is None:
+        return
+    # Visit priority: left subtree -> right subtree -> root node
+    post_order(root=root.left)
+    post_order(root=root.right)
+    res.append(root.val)
+
+
+"""Driver Code"""
+if __name__ == "__main__":
+    # Initialize binary tree
+    # Use a specific function to convert an array into a binary tree
+    root = list_to_tree(arr=[1, 2, 3, 4, 5, 6, 7])
+    print("\nInitialize binary tree\n")
+    print_tree(root)
+
+    # Pre-order traversal
+    res = []
+    pre_order(root)
+    print("\nPrint sequence of nodes from pre-order traversal = ", res)
+
+    # In-order traversal
+    res.clear()
+    in_order(root)
+    print("\nPrint sequence of nodes from in-order traversal = ", res)
+
+    # Post-order traversal
+    res.clear()
+    post_order(root)
+    print("\nPrint sequence of nodes from post-order traversal = ", res)

en/codes/python/modules/__init__.py

@@ -0,0 +1,19 @@
+# Follow the PEP 585 - Type Hinting Generics In Standard Collections
+# https://peps.python.org/pep-0585/
+from __future__ import annotations
+
+# Import common libs here to simplify the code by `from module import *`
+from .list_node import (
+    ListNode,
+    list_to_linked_list,
+    linked_list_to_list,
+)
+from .tree_node import TreeNode, list_to_tree, tree_to_list
+from .vertex import Vertex, vals_to_vets, vets_to_vals
+from .print_util import (
+    print_matrix,
+    print_linked_list,
+    print_tree,
+    print_dict,
+    print_heap,
+)

en/codes/python/modules/list_node.py

@@ -0,0 +1,32 @@
+"""
+File: list_node.py
+Created Time: 2021-12-11
+Author: krahets (krahets@163.com)
+"""
+
+
+class ListNode:
+    """LinkedList node class"""
+
+    def __init__(self, val: int):
+        self.val: int = val  # Node value
+        self.next: ListNode | None = None  # Reference to the next node
+
+
+def list_to_linked_list(arr: list[int]) -> ListNode | None:
+    """Deserialize a list into a linked list"""
+    dum = head = ListNode(0)
+    for a in arr:
+        node = ListNode(a)
+        head.next = node
+        head = head.next
+    return dum.next
+
+
+def linked_list_to_list(head: ListNode | None) -> list[int]:
+    """Serialize a linked list into a list"""
+    arr: list[int] = []
+    while head:
+        arr.append(head.val)
+        head = head.next
+    return arr

en/codes/python/modules/print_util.py

@@ -0,0 +1,81 @@
+"""
+File: print_util.py
+Created Time: 2021-12-11
+Author: krahets (krahets@163.com), msk397 (machangxinq@gmail.com)
+"""
+
+from .tree_node import TreeNode, list_to_tree
+from .list_node import ListNode, linked_list_to_list
+
+
+def print_matrix(mat: list[list[int]]):
+    """Print matrix"""
+    s = []
+    for arr in mat:
+        s.append("  " + str(arr))
+    print("[\n" + ",\n".join(s) + "\n]")
+
+
+def print_linked_list(head: ListNode | None):
+    """Print linked list"""
+    arr: list[int] = linked_list_to_list(head)
+    print(" -> ".join([str(a) for a in arr]))
+
+
+class Trunk:
+    def __init__(self, prev, string: str | None = None):
+        self.prev = prev
+        self.str = string
+
+
+def show_trunks(p: Trunk | None):
+    if p is None:
+        return
+    show_trunks(p.prev)
+    print(p.str, end="")
+
+
+def print_tree(
+    root: TreeNode | None, prev: Trunk | None = None, is_right: bool = False
+):
+    """
+    Print binary tree
+    This tree printer is borrowed from TECHIE DELIGHT
+    https://www.techiedelight.com/c-program-print-binary-tree/
+    """
+    if root is None:
+        return
+
+    prev_str = "    "
+    trunk = Trunk(prev, prev_str)
+    print_tree(root.right, trunk, True)
+
+    if prev is None:
+        trunk.str = "———"
+    elif is_right:
+        trunk.str = "/———"
+        prev_str = "   |"
+    else:
+        trunk.str = "\———"
+        prev.str = prev_str
+
+    show_trunks(trunk)
+    print(" " + str(root.val))
+    if prev:
+        prev.str = prev_str
+    trunk.str = "   |"
+    print_tree(root.left, trunk, False)
+
+
+def print_dict(hmap: dict):
+    """Print dictionary"""
+    for key, value in hmap.items():
+        print(key, "->", value)
+
+
+def print_heap(heap: list[int]):
+    """Print heap"""
+    print("Array representation of the heap:", heap)
+    print("Tree representation of the heap:")
+    root: TreeNode | None = list_to_tree(heap)
+    print_tree(root)

en/codes/python/modules/tree_node.py

@@ -0,0 +1,69 @@
+"""
+File: tree_node.py
+Created Time: 2021-12-11
+Author: krahets (krahets@163.com)
+"""
+
+from collections import deque
+
+
+class TreeNode:
+    """Binary tree node class"""
+
+    def __init__(self, val: int = 0):
+        self.val: int = val  # Node value
+        self.height: int = 0  # Node height
+        self.left: TreeNode | None = None  # Reference to the left child node
+        self.right: TreeNode | None = None  # Reference to the right child node
+
+    # For serialization encoding rules, refer to:
+    # https://www.hello-algo.com/chapter_tree/array_representation_of_tree/
+    # Array representation of the binary tree:
+    # [1, 2, 3, 4, None, 6, 7, 8, 9, None, None, 12, None, None, 15]
+    # Linked list representation of the binary tree:
+    #             /——— 15
+    #         /——— 7
+    #     /——— 3
+    #    |    \——— 6
+    #    |        \——— 12
+    # ——— 1
+    #     \——— 2
+    #        |    /——— 9
+    #         \——— 4
+    #             \——— 8
+
+
+def list_to_tree_dfs(arr: list[int], i: int) -> TreeNode | None:
+    """Deserialize a list into a binary tree: Recursively"""
+    # If the index is out of array bounds, or the corresponding element is None, return None
+    if i < 0 or i >= len(arr) or arr[i] is None:
+        return None
+    # Construct the current node
+    root = TreeNode(arr[i])
+    # Recursively construct left and right subtrees
+    root.left = list_to_tree_dfs(arr, 2 * i + 1)
+    root.right = list_to_tree_dfs(arr, 2 * i + 2)
+    return root
+
+
+def list_to_tree(arr: list[int]) -> TreeNode | None:
+    """Deserialize a list into a binary tree"""
+    return list_to_tree_dfs(arr, 0)
+
+
+def tree_to_list_dfs(root: TreeNode, i: int, res: list[int]) -> list[int]:
+    """Serialize a binary tree into a list: Recursively"""
+    if root is None:
+        return
+    if i >= len(res):
+        res += [None] * (i - len(res) + 1)
+    res[i] = root.val
+    tree_to_list_dfs(root.left, 2 * i + 1, res)
+    tree_to_list_dfs(root.right, 2 * i + 2, res)
+
+
+def tree_to_list(root: TreeNode | None) -> list[int]:
+    """Serialize a binary tree into a list"""
+    res = []
+    tree_to_list_dfs(root, 0, res)
+    return res

en/codes/python/modules/vertex.py

@@ -0,0 +1,20 @@
+# File: vertex.py
+# Created Time: 2023-02-23
+# Author: krahets (krahets@163.com)
+
+
+class Vertex:
+    """Vertex class"""
+
+    def __init__(self, val: int):
+        self.val = val
+
+
+def vals_to_vets(vals: list[int]) -> list["Vertex"]:
+    """Input a list of values vals, return a list of vertices vets"""
+    return [Vertex(val) for val in vals]
+
+
+def vets_to_vals(vets: list["Vertex"]) -> list[int]:
+    """Input a list of vertices vets, return a list of values vals"""
+    return [vet.val for vet in vets]

en/codes/python/test_all.py

@@ -0,0 +1,33 @@
+import os
+import glob
+import subprocess
+
+env = os.environ.copy()
+env["PYTHONIOENCODING"] = "utf-8"
+
+if __name__ == "__main__":
+    # find source code files
+    src_paths = sorted(glob.glob("en/codes/python/chapter_*/*.py"))
+    errors = []
+
+    # run python code
+    for src_path in src_paths:
+        process = subprocess.Popen(
+            ["python", src_path],
+            stdout=subprocess.PIPE,
+            stderr=subprocess.PIPE,
+            text=True,
+            env=env,
+            encoding='utf-8'
+        )
+        # Wait for the process to complete, and get the output and error messages
+        stdout, stderr = process.communicate()
+        # Check the exit status
+        exit_status = process.returncode
+        if exit_status != 0:
+            errors.append(stderr)
+
+    print(f"Tested {len(src_paths)} files")
+    print(f"Found exception in {len(errors)} files")
+    if len(errors) > 0:
+        raise RuntimeError("\n\n".join(errors))