修复了大量存在的问题，增加了假鸭子类型等等机制

lib/core/DifferenceCalculation.py

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 def LevenshteinDistance(s1: str, s2: str) -> int:
     """
     计算两个字符串的 Levenshtein 距离（编辑距离）
@@ -6,13 +8,17 @@ def LevenshteinDistance(s1: str, s2: str) -> int:
     :return: 最少编辑操作次数（差异程度）
     """
     # 创建二维动态规划表，dp[i][j] 表示 s1[:i] 到 s2[:j] 的编辑距离
+    m: int
+    n: int
     m, n = len(s1), len(s2)
-    dp = [[0] * (n + 1) for _ in range(m + 1)]
+    dp: list[list[int]] = [[0] * (n + 1) for _ in range(m + 1)]
 
     # 初始化：空字符串到 s1[:i] 需要 i 次删除操作
+    i: int
     for i in range(m + 1):
         dp[i][0] = i
     # 初始化：空字符串到 s2[:j] 需要 j 次插入操作
+    j: int
     for j in range(n + 1):
         dp[0][j] = j
 
@@ -39,11 +45,15 @@ def LongestCommonSubsequence(s1: str, s2: str) -> tuple[list[tuple[int, int]], s
     :param s2: 目标字符串
     :return: (LCS 位置列表 [(S1Idx, S2Idx)], LCS 字符串)
     """
+    m: int
+    n: int
     m, n = len(s1), len(s2)
     # dp[i][j] 表示 s1[:i] 和 s2[:j] 的 LCS 长度
-    dp = [[0] * (n + 1) for _ in range(m + 1)]
+    dp: list[list[int]] = [[0] * (n + 1) for _ in range(m + 1)]
 
     # 填充 LCS 长度表
+    i: int
+    j: int
     for i in range(1, m + 1):
         for j in range(1, n + 1):
             if s1[i-1] == s2[j-1]:
@@ -52,8 +62,8 @@ def LongestCommonSubsequence(s1: str, s2: str) -> tuple[list[tuple[int, int]], s
                 dp[i][j] = max(dp[i-1][j], dp[i][j-1])
 
     # 回溯找 LCS 的具体字符和位置
-    LcsChars = []
-    LcsPositions = []
+    LcsChars: list[str] = []
+    LcsPositions: list[tuple[int, int]] = []
     i, j = m, n
     while i > 0 and j > 0:
         if s1[i-1] == s2[j-1]:
@@ -72,7 +82,7 @@ def LongestCommonSubsequence(s1: str, s2: str) -> tuple[list[tuple[int, int]], s
     return LcsPositions, ''.join(LcsChars)
 
 
-def GetStringDiff(s1: str, s2: str) -> dict:
+def GetStringDiff(s1: str, s2: str) -> dict[str, int | float | str | dict[str, list[tuple[int, str] | tuple[int, str, str]]]]:
     """
     完整对比两个字符串，返回差异详情
     :param s1: 原始字符串
@@ -80,20 +90,24 @@ def GetStringDiff(s1: str, s2: str) -> dict:
     :return: 差异字典（包含编辑距离、LCS、差异位置/内容）
     """
     # 1. 计算编辑距离（差异程度）
-    EditDist = LevenshteinDistance(s1, s2)
+    EditDist: int = LevenshteinDistance(s1, s2)
     # 2. 计算 LCS（公共部分）
+    LcsPos: list[tuple[int, int]]
+    LcsStr: str
     LcsPos, LcsStr = LongestCommonSubsequence(s1, s2)
 
     # 3. 定位差异位置和内容
-    DiffDetails = {
+    DiffDetails: dict[str, list] = {
         "delete": [],  # s1 中需要删除的字符 (索引, 字符)
         "insert": [],  # s2 中需要插入的字符 (索引, 字符)
         "replace": []  # s1 中需要替换的字符 (s1索引, 原字符, 目标字符)
     }
 
     # 生成 s1 和 s2 的差异标记
-    S1Idx = 0
-    S2Idx = 0
+    S1Idx: int = 0
+    S2Idx: int = 0
+    LcsS1Idx: int
+    LcsS2Idx: int
     for (LcsS1Idx, LcsS2Idx) in LcsPos:
         # 处理 s1 中需要删除的字符（LCS 前的非公共部分）
         while S1Idx < LcsS1Idx:
@@ -116,7 +130,13 @@ def GetStringDiff(s1: str, s2: str) -> dict:
         S2Idx += 1
 
     # 优化：将连续的删除+插入合并为替换（更符合直观）
-    ReplaceCandidates = list(zip(DiffDetails["delete"], DiffDetails["insert"]))
+    ReplaceCandidates: list[tuple[tuple[int, str], tuple[int, str]]] = list(zip(DiffDetails["delete"], DiffDetails["insert"]))
+    DelItem: tuple[int, str]
+    InsItem: tuple[int, str]
+    DelIdx: int
+    DelChar: str
+    InsIdx: int
+    InsChar: str
     for (DelItem, InsItem) in ReplaceCandidates:
         DelIdx, DelChar = DelItem
         InsIdx, InsChar = InsItem
@@ -136,9 +156,9 @@ def GetStringDiff(s1: str, s2: str) -> dict:
 # 测试用例
 if __name__ == "__main__":
     # 示例1：轻微差异（替换+插入）
-    s1 = "Hello World!"
-    s2 = "Hello Python!"
-    DiffResult = GetStringDiff(s1, s2)
+    s1: str = "Hello World!"
+    s2: str = "Hello Python!"
+    DiffResult: dict = GetStringDiff(s1, s2)
     print("=== 示例1：轻微差异 ===")
     print(f"编辑距离：{DiffResult['EditDistance']}")
     print(f"相似度：{DiffResult['similarity']:.2f}")
@@ -146,9 +166,9 @@ if __name__ == "__main__":
     print(f"差异详情：{DiffResult['DiffDetails']}")
 
     # 示例2：完全不同
-    s3 = "abc123"
-    s4 = "xyz789"
-    DiffResult2 = GetStringDiff(s3, s4)
+    s3: str = "abc123"
+    s4: str = "xyz789"
+    DiffResult2: dict = GetStringDiff(s3, s4)
     print("\n=== 示例2：完全不同 ===")
     print(f"编辑距离：{DiffResult2['EditDistance']}")
     print(f"相似度：{DiffResult2['similarity']:.2f}")
@@ -156,9 +176,9 @@ if __name__ == "__main__":
     print(f"差异详情：{DiffResult2['DiffDetails']}")
 
     # 示例3：内容一致
-    s5 = "TestString"
-    s6 = "TestString"
-    DiffResult3 = GetStringDiff(s5, s6)
+    s5: str = "TestString"
+    s6: str = "TestString"
+    DiffResult3: dict = GetStringDiff(s5, s6)
     print("\n=== 示例3：内容一致 ===")
     print(f"编辑距离：{DiffResult3['EditDistance']}")
     print(f"相似度：{DiffResult3['similarity']:.2f}")