✨ 增加了拓扑排序

Author: Littlefean

061 拓扑排序/egg.py

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+"""
+背景，假如你在用python开发游戏的任务系统
+这个任务系统必须是无环的，否则就出bug了。
+"""
+
+# 拓扑图
+# 任务id：任务信息
+num2Task = {
+    1: {
+        "name": "开始冒险",
+        "details": "前往风起之地",
+    },
+    2: {
+        "name": "解救云隐村",
+        "details": "帮助云隐村解决危机",
+    },
+    3: {
+        "name": "破晓之星",
+        "details": "追踪星银之路",
+    },
+    4: {
+        "name": "征服风神",
+        "details": "挑战风神巅峰",
+    },
+    5: {
+        "name": "龙之末裔",
+        "details": "揭开龙的秘密",
+    },
+}
+
+graph = {
+    1: {2, 3},
+    2: {4},
+    3: {4},
+    4: {5},
+    5: {},
+}

061 拓扑排序/main.py

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+from graphlib import TopologicalSorter, CycleError
+
+
+def main():
+    # test0()
+    # test1()
+    test3()
+    ...
+
+
+def test0():
+    # 返回前驱为0的节点
+    ts = TopologicalSorter({
+        "D": {"B", "C"},
+        "C": {"A"},
+        "B": {"A"}
+    })
+    ts.prepare()  # 先让它准备一下，看看有没有环
+    print(ts.get_ready())  # 找到没有前驱的节点
+
+
+def test1():
+    graph = {"D": {"B", "C"}, "C": {"A"}, "B": {"A"}}
+    ts = TopologicalSorter(graph)
+    c = ts.static_order()
+    print(list(c)[::-1])
+
+
+def test2():
+    try:
+        ts2 = TopologicalSorter({
+            'a': {'b'},
+            'b': {'c'},
+            'c': {'d'},
+            'd': {'a'},
+        })
+        print(list(ts2.static_order()))
+    except CycleError:
+        ...
+
+
+def test3():
+    # 同样的图，换一个图的生成方式，用边生成
+    ts = TopologicalSorter()
+    ts.add('d', 'b')
+    ts.add('d', 'c')
+    ts.add('b', 'a')
+    ts.add('c', 'a')
+    print(list(ts.static_order()))
+    ...
+
+
+if __name__ == "__main__":
+    """
+    自创编译系统检测引入是否合理
+    工作流程管理
+    
+    在游戏项目中：
+    任务系统 关卡设计 任务进度解锁 效果触发 
+
+    """
+    main()

061 拓扑排序/test.py

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+from typing import *
+
+
+def main():
+    num2Task = {
+        1: {
+            "name": "构思",
+            "details": ...,
+        },
+        2: {
+            "name": "拍视频",
+            "details": ...,
+        },
+        3: {
+            "name": "找素材",
+            "details": ...,
+        },
+        4: {
+            "name": "剪辑",
+            "details": ...,
+        },
+        5: {
+            "name": "发b站",
+            "details": ...,
+        },
+    }
+    graph = {
+        1: {2, 3},
+        2: {4},
+        3: {4},
+        4: {5},
+        5: {},
+    }
+    graph = {
+        1: {2},
+        2: {3},
+        3: {1},
+    }
+    arr = f(graph)
+    if len(arr) < len(graph):
+        print("cycle")
+    print()
+
+
+def f(graph: Dict[int, Set[int]]) -> List[int]:
+    from collections import deque
+
+    count_dict = {n: 0 for n in graph}
+    for node, child_set in graph.items():
+        for child in child_set:
+            count_dict[child] += 1
+
+    q = deque()
+    for node, count in count_dict.items():
+        if count == 0:
+            q.append(node)
+
+    res = []
+    while q:
+        n = q.popleft()
+        res.append(n)
+        child_set = graph[n]
+        for child in child_set:
+            count_dict[child] -= 1
+            if count_dict[child] == 0:
+                q.append(child)
+    return res
+
+
+if __name__ == '__main__':
+    main()

061 拓扑排序/tradition.py

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+"""
+拓扑排序的传统实现
+
+"""
+
+
+def topological_sort(graph):
+    def dfs(node):
+        visited[node] = True
+        for child in graph[node]:
+            if not visited[child]:
+                dfs(child)
+        result.append(node)
+
+    # 初始化
+    visited = {node: False for node in graph}
+    result = []
+
+    # 遍历图中的每个节点
+    for node in graph:
+        if not visited[node]:
+            dfs(node)
+
+    # 结果是逆序的，反转得到拓扑排序
+    return result[::-1]
+
+
+def f(graph):
+    # 记录所有的入度量
+    from collections import deque
+    count_graph = {n: 0 for n in graph}
+    for k, child_set in graph.items():
+        for child in child_set:
+            count_graph[child] += 1
+    # 所有入度为0的节点入队列
+    q = deque()
+    for node, count in count_graph.items():
+        if count == 0:
+            q.append(node)
+    res = []
+    # 准备好开始队列了
+    while q:
+        n = q.popleft()
+        res.append(n)
+        child_set = graph[n]
+        for child in child_set:
+            count_graph[child] -= 1
+            if count_graph[child] == 0:
+                q.append(child)
+    return res
+
+
+def topological_sort_no_cycle(graph):
+    # 能检测出是否有环的情况
+    def dfs(node):
+        visited[node] = True
+        currently_visiting.add(node)
+
+        for child in graph[node]:
+            if not visited[child]:
+                if dfs(child):
+                    return True
+            elif child in currently_visiting:
+                # 如果在当前DFS路径上发现已经访问过的节点，说明存在环
+                return True
+
+        currently_visiting.remove(node)
+        result.append(node)
+        return False
+
+    # 初始化
+    visited = {node: False for node in graph}
+    result = []
+    currently_visiting = set()
+
+    # 遍历图中的每个节点
+    for node in graph:
+        if not visited[node]:
+            if dfs(node):
+                # 如果在DFS中发现环，返回空列表表示拓扑排序不可行
+                return []
+
+    # 结果是逆序的，反转得到拓扑排序
+    return result[::-1]
+
+
+def main():
+    # 示例用法
+    graph = {
+        1: {2, 3},
+        2: {4},
+        3: {4, 5},
+        4: {5},
+        5: {},
+    }
+    g = {
+        1: {2},
+        2: {3},
+        3: {4},
+        4: {5},
+        5: {1},
+    }
+
+    # result = topological_sort_no_cycle(graph)
+    # result = topological_sort(g)
+    result = f(graph)
+    print("Topological Sort:", result)
+
+
+if __name__ == '__main__':
+    main()