# Algorithm from http://www.logarithmic.net/pfh/blog/01208083168
# License: public domain
# Authors: Dr. Paul Harrison / Dries Verdegem


def strongly_connected_components(graph):
    """
    Tarjan's Algorithm (named for its discoverer, Robert Tarjan) is a graph
    theory algorithm for finding the strongly connected components of a graph.

    Based on:
    http://en.wikipedia.org/wiki/Tarjan%27s_strongly_connected_components_algorithm
    """

    index_counter = [0]
    stack = []
    lowlinks = {}
    index = {}
    result = []

    def strongconnect(node):
        # set the depth index for this node to the smallest unused index
        index[node] = index_counter[0]
        lowlinks[node] = index_counter[0]
        index_counter[0] += 1
        stack.append(node)

        # Consider successors of `node`
        try:
            successors = graph[node]
        except KeyError:
            successors = []
        for successor in successors:
            if successor not in lowlinks:
                # Successor has not yet been visited; recurse on it
                strongconnect(successor)
                lowlinks[node] = min(lowlinks[node], lowlinks[successor])
            elif successor in stack:
                # the successor is in the stack and hence in the current
                # strongly connected component (SCC)
                lowlinks[node] = min(lowlinks[node], index[successor])

        # If 'node' is a root node, pop the stack and generate an SCC
        if lowlinks[node] == index[node]:
            connected_component = []

            while True:
                successor = stack.pop()
                connected_component.append(successor)
                if successor == node:
                    break
            component = tuple(connected_component)
            # storing the result
            result.append(component)

    for node in graph:
        if node not in lowlinks:
            strongconnect(node)

    return result