from csc148_queue import Queue


class Tree:
    """
    A bare-bones Tree ADT that identifies the root with the entire tree.
    """

    def __init__(self, value=None, children=None):
        """
        Create Tree self with content value and 0 or more children

        @param Tree self: this tree
        @param object value: value contained in this tree
        @param list[Tree] children: possibly-empty list of children
        @rtype: None
        """
        self.value = value
        # copy children if not None
        self.children = children.copy() if children else []

    def __repr__(self):
        """
        Return representation of Tree (self) as string that
        can be evaluated into an equivalent Tree.

        @param Tree self: this tree
        @rtype: str

        >>> t1 = Tree(5)
        >>> t1
        Tree(5)
        >>> t2 = Tree(7, [t1])
        >>> t2
        Tree(7, [Tree(5)])
        """
        # Our __repr__ is recursive, because it can also be called
        # via repr...!
        return ('Tree({}, {})'.format(repr(self.value), repr(self.children))
                if self.children
                else 'Tree({})'.format(repr(self.value)))

    def __eq__(self, other):
        """
        Return whether this Tree is equivalent to other.

        @param Tree self: this tree
        @param object|Tree other: object to compare to self
        @rtype: bool

        >>> t1 = Tree(5)
        >>> t2 = Tree(5, [])
        >>> t1 == t2
        True
        >>> t3 = Tree(5, [t1])
        >>> t2 == t3
        False
        """
        return (type(self) is type(other) and
                self.value == other.value and
                self.children == other.children)

    def __str__(self, indent=0):
        """
        Produce a user-friendly string representation of Tree self,
        indenting each level as a visual clue.

        @param Tree self: this tree
        @param int indent: amount to indent each level of tree
        @rtype: str

        >>> t = Tree(17)
        >>> print(t)
        17
        >>> t1 = Tree(19, [t, Tree(23)])
        >>> print(t1)
        19
           17
           23
        >>> t3 = Tree(29, [Tree(31), t1])
        >>> print(t3)
        29
           31
           19
              17
              23
        """
        root_str = indent * " " + str(self.value)
        return '\n'.join([root_str] +
                         [c.__str__(indent + 3) for c in self.children])

    def __contains__(self, v):
        """
        Return whether Tree self contains v.

        @param Tree self: this tree
        @param object v: value to search this tree for

        >>> t = Tree(17)
        >>> t.__contains__(17)
        True
        >>> t = descendants_from_list(Tree(19), [1, 2, 3, 4, 5, 6, 7], 3)
        >>> t.__contains__(5)
        True
        >>> t.__contains__(18)
        False
        """
        if not self.children:
            # self is a leaf
            return self.value == v
        else:
            # self is an interior node
            # this else block would probably also work for
            # the base case!
            return ((self.value == v) or
                    (any([v in n for n in self.children])))


def leaf_count(t):
    """
    Return the number of leaves in Tree t.

    @param Tree t: tree to count the leaves of
    @rtype: int

    >>> t = Tree(7)
    >>> leaf_count(t)
    1
    >>> t = descendants_from_list(Tree(7), [0, 1, 3, 5, 7, 9, 11, 13], 3)
    >>> leaf_count(t)
    6
    """
    if len(t.children) == 0:
        return 1
    else:
        return sum([leaf_count(child) for child in t.children])


def preorder_visit(t, act):
    """
    Visit each node of Tree t in preorder, and act on the nodes
    as they are visited.

    @param Tree t: tree to visit in preorder
    @param (Tree)->Any act: function to carry out on visited Tree node
    @rtype: None

    >>> t = descendants_from_list(Tree(0), [1, 2, 3, 4, 5, 6, 7], 3)
    >>> def act(node): print(node.value)
    >>> preorder_visit(t, act)
    0
    1
    4
    5
    6
    2
    7
    3
    """
    act(t)
    for x in t.children:
        preorder_visit(x, act)


def postorder_visit(t, act):
    """
    Visit each node of t in postorder, and act on it when it is visited.

    @param Tree t: tree to be visited in postorder
    @param (Tree)->Any act: function to do to each node
    @rtype: None

    >>> t = descendants_from_list(Tree(0), [1, 2, 3, 4, 5, 6, 7], 3)
    >>> def act(node): print(node.value)
    >>> postorder_visit(t, act)
    4
    5
    6
    1
    7
    2
    3
    0
    """
    for x in t.children:
        postorder_visit(x, act)
    act(t)


def levelorder_visit(t, act):
    """
    Visit every node in Tree t in level order and act on the node
    as you visit it.

    @param Tree t: tree to visit in level order
    @param (Tree)->Any act: function to execute during visit

    >>> t = descendants_from_list(Tree(0), [1, 2, 3, 4, 5, 6, 7], 3)
    >>> def act(node): print(node.value)
    >>> levelorder_visit(t, act)
    0
    1
    2
    3
    4
    5
    6
    7
    """
    to_process = Queue()
    to_process.add(t)
    while not to_process.is_empty():
        next_tree = to_process.remove()
        act(next_tree)
        for c in next_tree.children:
            to_process.add(c)


def visit_level(t, n, act):
    """
    Visit, and act on, the nodes at level n (depth n) of t, 
    and return the number of nodes visited.

    @param Tree n: tree to visit
    @param int n: level to visit
    @param (Tree)->object act: function to carry out on visitees
    @rtype: int

    >>> t = descendants_from_list(Tree(0), [1, 2, 3, 4, 5, 6, 7, 8, 9], 3)
    >>> def f(n): print(n.value)
    >>> visit_level(t, 0, f)
    0
    1
    >>> visit_level(t, 2, f)
    4
    5
    6
    7
    8
    9
    6
    """
    if n == 0:
        act(t)
        return 1
    else:
        # hmmm, a mixture of side-effect and return value
        return sum([visit_level(c, n-1, act) for c in t.children])


def descendants_from_list(t, list_, arity):
    """
    Populate Tree t's descendants from list_, filling them
    in in level order, with up to arity children per node.
    Then return t.

    @param Tree t: tree to populate from list_
    @param list list_: list of values to populate from
    @param int arity: maximum branching factor
    @rtype: Tree

    >>> descendants_from_list(Tree(0), [1, 2, 3, 4], 2)
    Tree(0, [Tree(1, [Tree(3), Tree(4)]), Tree(2)])
    """
    q = Queue()
    q.add(t)
    list_ = list_.copy()
    while not q.is_empty():  # unlikely to happen
        new_t = q.remove()
        for i in range(0, arity):
            if len(list_) == 0:
                return t  # our work here is done
            else:
                new_t_child = Tree(list_.pop(0))
                new_t.children.append(new_t_child)
                q.add(new_t_child)
    return t


if __name__ == '__main__':
    import doctest

    doctest.testmod()