用python做出勤率的数据分析（图深度优先算法）

用python做出勤率的数据分析（图深度优先算法）procedure DFS-iterative(G v) is let S be a stack S.push(v) while S is not empty do v = S.pop() if v is not labeled as discovered then label v as discovered for all edges from v to w in G.adjacentEdges(v) do S.push(w)黄哥所写的代码，迭代实现。A non-recursive implementation of DFS with worst-case space complexity 。Output: All vertices reachabl

深度优先搜索算法（英语：Depth-First-Search，DFS）是一种用于遍历或搜索树或图的算法。沿着树的深度遍历树的节点，尽可能深的搜索树的分支。当节点v的所在边都己被探寻过，搜索将回溯到发现节点v的那条边的起始节点。这一过程一直进行到已发现从源节点可达的所有节点为止。如果还存在未被发现的节点，则选择其中一个作为源节点并重复以上过程，整个进程反复进行直到所有节点都被访问为止。属于盲目搜索。

深度优先搜索是图论中的经典算法，利用深度优先搜索算法可以产生目标图的相应拓扑排序表，利用拓扑排序表可以方便的解决很多相关的图论问题，如最大路径问题等等。因发明“深度优先搜索算法”，约翰·霍普克洛夫特与罗伯特·塔扬在1986年共同获得计算机领域的最高奖：图灵奖。

伪代码（Pseudocode）：

Input: A graph G and a vertex v of G

Output: All vertices reachable from v labeled as discovered

A recursive implementation of DFS:

procedure DFS(G v) is label v as discovered for all directed edges from v to w that are in G.adjacentEdges(v) do if vertex w is not labeled as discovered then recursively call DFS(G w)

The order in which the vertices are discovered by this algorithm is called the lexicographic order.

A non-recursive implementation of DFS with worst-case space complexity 。

procedure DFS-iterative(G v) is let S be a stack S.push(v) while S is not empty do v = S.pop() if v is not labeled as discovered then label v as discovered for all edges from v to w in G.adjacentEdges(v) do S.push(w)

黄哥所写的代码，迭代实现。

递归实现。

请看西瓜视频播放地址。