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feat: Traditional Chinese version (#1163)
* First commit * Update mkdocs.yml * Translate all the docs to traditional Chinese * Translate the code files. * Translate the docker file * Fix mkdocs.yml * Translate all the figures from SC to TC * 二叉搜尋樹 -> 二元搜尋樹 * Update terminology. * Update terminology * 构造函数/构造方法 -> 建構子 异或 -> 互斥或 * 擴充套件 -> 擴展 * constant - 常量 - 常數 * 類 -> 類別 * AVL -> AVL 樹 * 數組 -> 陣列 * 係統 -> 系統 斐波那契數列 -> 費波那契數列 運算元量 -> 運算量 引數 -> 參數 * 聯絡 -> 關聯 * 麵試 -> 面試 * 面向物件 -> 物件導向 歸併排序 -> 合併排序 范式 -> 範式 * Fix 算法 -> 演算法 * 錶示 -> 表示 反碼 -> 一補數 補碼 -> 二補數 列列尾部 -> 佇列尾部 區域性性 -> 區域性 一摞 -> 一疊 * Synchronize with main branch * 賬號 -> 帳號 推匯 -> 推導 * Sync with main branch * First commit * Update mkdocs.yml * Translate all the docs to traditional Chinese * Translate the code files. * Translate the docker file * Fix mkdocs.yml * Translate all the figures from SC to TC * 二叉搜尋樹 -> 二元搜尋樹 * Update terminology * 构造函数/构造方法 -> 建構子 异或 -> 互斥或 * 擴充套件 -> 擴展 * constant - 常量 - 常數 * 類 -> 類別 * AVL -> AVL 樹 * 數組 -> 陣列 * 係統 -> 系統 斐波那契數列 -> 費波那契數列 運算元量 -> 運算量 引數 -> 參數 * 聯絡 -> 關聯 * 麵試 -> 面試 * 面向物件 -> 物件導向 歸併排序 -> 合併排序 范式 -> 範式 * Fix 算法 -> 演算法 * 錶示 -> 表示 反碼 -> 一補數 補碼 -> 二補數 列列尾部 -> 佇列尾部 區域性性 -> 區域性 一摞 -> 一疊 * Synchronize with main branch * 賬號 -> 帳號 推匯 -> 推導 * Sync with main branch * Update terminology.md * 操作数量(num. of operations)-> 操作數量 * 字首和->前綴和 * Update figures * 歸 -> 迴 記憶體洩漏 -> 記憶體流失 * Fix the bug of the file filter * 支援 -> 支持 Add zh-Hant/README.md * Add the zh-Hant chapter covers. Bug fixes. * 外掛 -> 擴充功能 * Add the landing page for zh-Hant version * Unify the font of the chapter covers for the zh, en, and zh-Hant version * Move zh-Hant/ to zh-hant/ * Translate terminology.md to traditional Chinese
This commit is contained in:
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"""
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File: binary_search.py
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Created Time: 2022-11-26
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Author: timi (xisunyy@163.com)
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"""
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def binary_search(nums: list[int], target: int) -> int:
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"""二分搜尋(雙閉區間)"""
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# 初始化雙閉區間 [0, n-1] ,即 i, j 分別指向陣列首元素、尾元素
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i, j = 0, len(nums) - 1
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# 迴圈,當搜尋區間為空時跳出(當 i > j 時為空)
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while i <= j:
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# 理論上 Python 的數字可以無限大(取決於記憶體大小),無須考慮大數越界問題
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m = (i + j) // 2 # 計算中點索引 m
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if nums[m] < target:
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i = m + 1 # 此情況說明 target 在區間 [m+1, j] 中
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elif nums[m] > target:
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j = m - 1 # 此情況說明 target 在區間 [i, m-1] 中
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else:
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return m # 找到目標元素,返回其索引
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return -1 # 未找到目標元素,返回 -1
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def binary_search_lcro(nums: list[int], target: int) -> int:
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"""二分搜尋(左閉右開區間)"""
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# 初始化左閉右開區間 [0, n) ,即 i, j 分別指向陣列首元素、尾元素+1
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i, j = 0, len(nums)
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# 迴圈,當搜尋區間為空時跳出(當 i = j 時為空)
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while i < j:
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m = (i + j) // 2 # 計算中點索引 m
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if nums[m] < target:
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i = m + 1 # 此情況說明 target 在區間 [m+1, j) 中
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elif nums[m] > target:
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j = m # 此情況說明 target 在區間 [i, m) 中
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else:
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return m # 找到目標元素,返回其索引
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return -1 # 未找到目標元素,返回 -1
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"""Driver Code"""
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if __name__ == "__main__":
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target = 6
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nums = [1, 3, 6, 8, 12, 15, 23, 26, 31, 35]
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# 二分搜尋(雙閉區間)
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index = binary_search(nums, target)
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print("目標元素 6 的索引 = ", index)
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# 二分搜尋(左閉右開區間)
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index = binary_search_lcro(nums, target)
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print("目標元素 6 的索引 = ", index)
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"""
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File: binary_search_edge.py
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Created Time: 2023-08-04
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Author: krahets (krahets@163.com)
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"""
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import sys
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from pathlib import Path
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sys.path.append(str(Path(__file__).parent.parent))
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from binary_search_insertion import binary_search_insertion
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def binary_search_left_edge(nums: list[int], target: int) -> int:
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"""二分搜尋最左一個 target"""
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# 等價於查詢 target 的插入點
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i = binary_search_insertion(nums, target)
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# 未找到 target ,返回 -1
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if i == len(nums) or nums[i] != target:
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return -1
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# 找到 target ,返回索引 i
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return i
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def binary_search_right_edge(nums: list[int], target: int) -> int:
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"""二分搜尋最右一個 target"""
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# 轉化為查詢最左一個 target + 1
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i = binary_search_insertion(nums, target + 1)
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# j 指向最右一個 target ,i 指向首個大於 target 的元素
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j = i - 1
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# 未找到 target ,返回 -1
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if j == -1 or nums[j] != target:
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return -1
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# 找到 target ,返回索引 j
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return j
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"""Driver Code"""
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if __name__ == "__main__":
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# 包含重複元素的陣列
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nums = [1, 3, 6, 6, 6, 6, 6, 10, 12, 15]
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print(f"\n陣列 nums = {nums}")
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# 二分搜尋左邊界和右邊界
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for target in [6, 7]:
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index = binary_search_left_edge(nums, target)
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print(f"最左一個元素 {target} 的索引為 {index}")
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index = binary_search_right_edge(nums, target)
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print(f"最右一個元素 {target} 的索引為 {index}")
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@@ -0,0 +1,54 @@
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"""
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File: binary_search_insertion.py
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Created Time: 2023-08-04
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Author: krahets (krahets@163.com)
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"""
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def binary_search_insertion_simple(nums: list[int], target: int) -> int:
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"""二分搜尋插入點(無重複元素)"""
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i, j = 0, len(nums) - 1 # 初始化雙閉區間 [0, n-1]
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while i <= j:
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m = (i + j) // 2 # 計算中點索引 m
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if nums[m] < target:
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i = m + 1 # target 在區間 [m+1, j] 中
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elif nums[m] > target:
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j = m - 1 # target 在區間 [i, m-1] 中
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else:
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return m # 找到 target ,返回插入點 m
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# 未找到 target ,返回插入點 i
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return i
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def binary_search_insertion(nums: list[int], target: int) -> int:
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"""二分搜尋插入點(存在重複元素)"""
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i, j = 0, len(nums) - 1 # 初始化雙閉區間 [0, n-1]
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while i <= j:
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m = (i + j) // 2 # 計算中點索引 m
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if nums[m] < target:
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i = m + 1 # target 在區間 [m+1, j] 中
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elif nums[m] > target:
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j = m - 1 # target 在區間 [i, m-1] 中
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else:
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j = m - 1 # 首個小於 target 的元素在區間 [i, m-1] 中
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# 返回插入點 i
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return i
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"""Driver Code"""
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if __name__ == "__main__":
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# 無重複元素的陣列
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nums = [1, 3, 6, 8, 12, 15, 23, 26, 31, 35]
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print(f"\n陣列 nums = {nums}")
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# 二分搜尋插入點
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for target in [6, 9]:
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index = binary_search_insertion_simple(nums, target)
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print(f"元素 {target} 的插入點的索引為 {index}")
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# 包含重複元素的陣列
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nums = [1, 3, 6, 6, 6, 6, 6, 10, 12, 15]
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print(f"\n陣列 nums = {nums}")
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# 二分搜尋插入點
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for target in [2, 6, 20]:
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index = binary_search_insertion(nums, target)
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print(f"元素 {target} 的插入點的索引為 {index}")
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@@ -0,0 +1,51 @@
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"""
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File: hashing_search.py
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Created Time: 2022-11-26
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Author: timi (xisunyy@163.com)
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"""
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import sys
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from pathlib import Path
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sys.path.append(str(Path(__file__).parent.parent))
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from modules import ListNode, list_to_linked_list
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def hashing_search_array(hmap: dict[int, int], target: int) -> int:
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"""雜湊查詢(陣列)"""
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# 雜湊表的 key: 目標元素,value: 索引
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# 若雜湊表中無此 key ,返回 -1
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return hmap.get(target, -1)
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def hashing_search_linkedlist(
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hmap: dict[int, ListNode], target: int
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) -> ListNode | None:
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"""雜湊查詢(鏈結串列)"""
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# 雜湊表的 key: 目標元素,value: 節點物件
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# 若雜湊表中無此 key ,返回 None
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return hmap.get(target, None)
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"""Driver Code"""
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if __name__ == "__main__":
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target = 3
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# 雜湊查詢(陣列)
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nums = [1, 5, 3, 2, 4, 7, 5, 9, 10, 8]
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# 初始化雜湊表
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map0 = dict[int, int]()
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for i in range(len(nums)):
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map0[nums[i]] = i # key: 元素,value: 索引
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index: int = hashing_search_array(map0, target)
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print("目標元素 3 的索引 =", index)
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# 雜湊查詢(鏈結串列)
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head: ListNode = list_to_linked_list(nums)
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# 初始化雜湊表
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map1 = dict[int, ListNode]()
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while head:
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map1[head.val] = head # key: 節點值,value: 節點
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head = head.next
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node: ListNode = hashing_search_linkedlist(map1, target)
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print("目標節點值 3 的對應節點物件為", node)
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"""
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File: linear_search.py
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Created Time: 2022-11-26
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Author: timi (xisunyy@163.com)
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"""
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import sys
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from pathlib import Path
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sys.path.append(str(Path(__file__).parent.parent))
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from modules import ListNode, list_to_linked_list
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def linear_search_array(nums: list[int], target: int) -> int:
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"""線性查詢(陣列)"""
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# 走訪陣列
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for i in range(len(nums)):
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if nums[i] == target: # 找到目標元素,返回其索引
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return i
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return -1 # 未找到目標元素,返回 -1
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def linear_search_linkedlist(head: ListNode, target: int) -> ListNode | None:
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"""線性查詢(鏈結串列)"""
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# 走訪鏈結串列
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while head:
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if head.val == target: # 找到目標節點,返回之
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return head
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head = head.next
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return None # 未找到目標節點,返回 None
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"""Driver Code"""
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if __name__ == "__main__":
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target = 3
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# 在陣列中執行線性查詢
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nums = [1, 5, 3, 2, 4, 7, 5, 9, 10, 8]
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index: int = linear_search_array(nums, target)
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print("目標元素 3 的索引 =", index)
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# 在鏈結串列中執行線性查詢
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head: ListNode = list_to_linked_list(nums)
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node: ListNode | None = linear_search_linkedlist(head, target)
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print("目標節點值 3 的對應節點物件為", node)
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@@ -0,0 +1,42 @@
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"""
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File: two_sum.py
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Created Time: 2022-11-25
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Author: krahets (krahets@163.com)
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"""
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def two_sum_brute_force(nums: list[int], target: int) -> list[int]:
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"""方法一:暴力列舉"""
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# 兩層迴圈,時間複雜度為 O(n^2)
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for i in range(len(nums) - 1):
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for j in range(i + 1, len(nums)):
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if nums[i] + nums[j] == target:
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return [i, j]
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return []
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def two_sum_hash_table(nums: list[int], target: int) -> list[int]:
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"""方法二:輔助雜湊表"""
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# 輔助雜湊表,空間複雜度為 O(n)
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dic = {}
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# 單層迴圈,時間複雜度為 O(n)
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for i in range(len(nums)):
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if target - nums[i] in dic:
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return [dic[target - nums[i]], i]
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dic[nums[i]] = i
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return []
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"""Driver Code"""
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if __name__ == "__main__":
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# ======= Test Case =======
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nums = [2, 7, 11, 15]
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target = 13
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# ====== Driver Code ======
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# 方法一
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res: list[int] = two_sum_brute_force(nums, target)
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print("方法一 res =", res)
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# 方法二
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res: list[int] = two_sum_hash_table(nums, target)
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print("方法二 res =", res)
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