import json
import MeCab
import re

# Initialize the Tagger
#tagger = MeCab.Tagger()

# Generate Hiragana and Katakana characters
hiragana = tuple(chr(i) for i in range(12353, 12436)) # \u3041 - \u3094
katakana = tuple(chr(i) for i in range(12450, 12532)) # \u30A2 - \u30F4
punctuation = tuple(chr(i) for i in range(65281, 65382))

# Combine both into one tuple
all_kana = hiragana + katakana + punctuation + ('　', 'ー', '・')

KANJI_RE = re.compile(r"[\u4E00-\u9FFF]")

def katakana_to_hiragana(text: str) -> str:
    return "".join(
        chr(ord(ch) - 0x60) if 0x30A1 <= ord(ch) <= 0x30F6 else ch
        for ch in text
    )

def get_node_reading(node) -> str:
    features = node.feature.split(",")
    print()
    if len(features) >= 8 and features[7] != "*":
        return katakana_to_hiragana(features[7])
    return node.surface

def has_kanji(text: str) -> bool:
    return bool(KANJI_RE.search(text))

def get_node_reading(node) -> str:
    features = node.feature.split(",")
    ## These depend on what dictionary is being used.
    if len(features) > 6 and features[6] != "*":
        return katakana_to_hiragana(features[6])
    return node.surface

def annotate_phrase(text: str) -> str:
    tagger = MeCab.Tagger()
    node = tagger.parseToNode(text)
    vocab = ()
    parts = []
    while node:
        surface = node.surface
        if surface:
            vocab += (surface,)
            if has_kanji(surface):
                reading = get_node_reading(node)
                parts.append(f"{surface}({reading})")
            else:
                parts.append(surface)
        node = node.next

    return {'reading':("".join(parts)),'vocab':vocab}

#print(annotate_phrase("私は学校へ行きます"))

with open("words-readings.json", "r", encoding="utf-16le") as f:
    readings = json.load(f)

with open("dump.json", "r", encoding="utf-16le") as f:
    dump = json.load(f)

vocab_dict = {}
## A micab phrase based word parser
for cd in dump:
    print(dump[cd]['nm'])
    # node = tagger.parseToNode(dump[cd]['nm'])
    # while node:
    #     # node.surface is the word; node.feature contains POS tags
    #     if node.surface:
    #         print(f"{node.surface}\t{node.feature}")
    #     node = node.next
    anottated = annotate_phrase(dump[cd]['nm'])
    if anottated['reading'] != dump[cd]['nm']:
        print(anottated['reading'])
        dump[cd]['kana'] = anottated['reading']
    cd_nm = dump[cd]['nm']
    for word in anottated['vocab']:
        # Skip punctuation words hopefully
        if len(word) == 1 and has_kanji(word) == False:
            continue
        if vocab_dict.get(word) is None:
            vocab_dict[word] = {
                'count': 0,
                'Examples': (cd_nm,)
            }
        else:
            vocab_dict[word]['count'] = vocab_dict[word]['count'] + 1
        if cd_nm not in vocab_dict[word]['Examples']:
            vocab_dict[word]['Examples'] += (cd_nm,)
    print()
    phrase = dump[cd]['de']
    anottated = annotate_phrase(phrase)
    if anottated['reading'] != phrase:
        #print(anottated['reading'])
        dump[cd]['furi_de'] = anottated['reading']
    for word in anottated['vocab']:
        if len(word) == 1 and has_kanji(word) == False:
            continue
        if vocab_dict.get(word) is None:
            vocab_dict[word] = {
                'count': 0,
                'Examples': (cd_nm,)
            }
        else:
            vocab_dict[word]['count'] = vocab_dict[word]['count'] + 1
        if len(vocab_dict[word]['Examples']) < 5:
            if cd_nm not in vocab_dict[word]['Examples']:
                vocab_dict[word]['Examples'] += (cd_nm,)

vocab_dict = sorted(vocab_dict.items(), key= lambda x: x[1]['count'], reverse=True)

with open("dump-withkana2.json", "w", encoding="utf-16") as outfile:
    json.dump(dump, outfile, ensure_ascii=False, indent=2)

with open("dump-vocab.json", "w", encoding="utf-16") as outfile:
    json.dump(vocab_dict, outfile, ensure_ascii=False, indent=2)