from collections import defaultdict
from typing import List, Tuple

import numpy as np
from anytree import Node, RenderTree
import bs4
from anytree import PreOrderIter
from anytree.exporter import DotExporter


def nodenamefunc(node):
    return f"{node.name}|{node.prob}|{node.input_ids}"


class TokenDotExporter(DotExporter):
    def __init__(self, node, **kwargs):
        super().__init__(node, **kwargs)

    def __iter__(self):
        # prepare
        indent = " " * self.indent
        nodenamefunc = self.nodenamefunc or self._default_nodenamefunc
        nodeattrfunc = self.nodeattrfunc or self._default_nodeattrfunc
        edgeattrfunc = self.edgeattrfunc or self._default_edgeattrfunc
        edgetypefunc = self.edgetypefunc or self._default_edgetypefunc
        filter_ = self.filter_ or self._default_filter
        return self.__iter(indent, nodenamefunc, nodeattrfunc, edgeattrfunc, edgetypefunc, filter_)

    def __iter_nodes(self, indent, nodenamefunc, nodeattrfunc, filter_):
        for node in PreOrderIter(self.node, filter_=filter_, stop=self.stop, maxlevel=self.maxlevel):
            nodename = nodenamefunc(node)
            nodeattr = nodeattrfunc(node)
            nodeattr = " {%s}" % nodeattr if nodeattr is not None else ""
            yield '%s%s' % (DotExporter.esc(nodename), nodeattr)

    def __iter(self, indent, nodenamefunc, nodeattrfunc, edgeattrfunc, edgetypefunc, filter_):
        for node in self.__iter_nodes(indent, nodenamefunc, nodeattrfunc, filter_):
            yield node


class TokenIdNode(Node):
    def __init__(self, name, parent=None, children=None, **kwargs):
        super().__init__(name, parent, children, **kwargs)
        self.input_ids = kwargs.get('input_ids', [])
        self.prob = kwargs.get('prob', np.float32(0.0))


def split_tree(soup: bs4.BeautifulSoup, max_node_words=0) -> List[Tuple[bs4.element.Tag, List[str], bool]]:
    word_count = len(soup.get_text().split())
    if word_count > max_node_words:
        possible_trees = [(soup, [])]
        target_trees = []  # [(tag, path, is_leaf)]
        #  split the entire dom tee into subtrees, until the length of the subtree is less than max_node_words words
        #  find all possible trees
        while True:
            if len(possible_trees) == 0:
                break
            tree = possible_trees.pop(0)
            tag_children = defaultdict(int)
            bare_word_count = 0
            #  count child tags
            for child in tree[0].contents:
                if isinstance(child, bs4.element.Tag):
                    tag_children[child.name] += 1
            _tag_children = {k: 0 for k in tag_children.keys()}

            #  check if the tree can be split
            for child in tree[0].contents:
                if isinstance(child, bs4.element.Tag):
                    #  change child tag with duplicate names
                    if tag_children[child.name] > 1:
                        new_name = f"{child.name}{_tag_children[child.name]}"
                        new_tree = (child, tree[1] + [new_name])
                        _tag_children[child.name] += 1
                        child.name = new_name
                    else:
                        new_tree = (child, tree[1] + [child.name])
                    word_count = len(child.get_text().split())
                    #  add node with more than max_node_words words, and recursion depth is less than 64
                    if word_count > max_node_words and len(new_tree[1]) < 64:
                        possible_trees.append(new_tree)
                    else:
                        target_trees.append((new_tree[0], new_tree[1], True))
                else:
                    bare_word_count += len(str(child).split())

            #  add leaf node
            if len(tag_children) == 0:
                target_trees.append((tree[0], tree[1], True))
            #  add node with more than max_node_words bare words
            elif bare_word_count > max_node_words:
                target_trees.append((tree[0], tree[1], False))
    else:
        soup_children = [c for c in soup.contents if isinstance(c, bs4.element.Tag)]
        if len(soup_children) == 1:
            target_trees = [(soup_children[0], [soup_children[0].name], True)]
        else:
            # add an html tag to wrap all children
            new_soup = bs4.BeautifulSoup("", 'html.parser')
            new_tag = new_soup.new_tag("html")
            new_soup.append(new_tag)
            for child in soup_children:
                new_tag.append(child)
            target_trees = [(new_tag, ["html"], True)]
    return target_trees