# coding: utf8

"""yiwa后台-语音、浏览器、数据库等处理"""

import time
from importlib import import_module
from jieba import lcut, lcut_for_search
from asr.stt import listening, wakeup, play_audio_file
from asr.awake import read_keywords
from nlp.comparison import match
from yiwa.browser import create as create_browser
from yiwa.db import DataConveyor
from yiwa.log import Log
from yiwa.rpi import dpms_on
from yiwa.settings import HOST, PORT, TIME, CappedFailAmount
from util.string import StringUtil

logger = Log().logger

ROOT = f"http://{HOST}:{PORT}"

if __name__ == "__main__":
    WAKEUP = False
    FAILURE = 0  # 指令匹配失败次数
    data_conveyor = DataConveyor()
    data_conveyor._init()
    keywords = read_keywords()
    browser = create_browser()
    browser.get(ROOT)


    def _todo(browser, action: str, param=""):
        """
        做action对应的动作
        :param browser: 浏览器对象
        :param action: 动作路径, 例如: apps.self_discipline.action.encourage
        :param param: 动作命令参数名, 例如: '放学写作业'
        :return: 无
        """
        # 解析action路径
        mothed_path = action.split(".")
        package_path = ".".join(mothed_path[:-1])  # 包
        mothed_name = mothed_path[-1]  # 方法
        # 执行action
        if package_path and mothed_name:
            try:
                package = import_module(package_path)  # 动态导入包
                todo = package.__getattribute__(mothed_name)  # 获取包中的方法
                if param:
                    todo(browser, param)
                else:
                    todo(browser)
            except Exception as e:
                logger.error(f"动态执行页面动作失败：{e}")


    def _command_filter(command):
        """过滤指令，缩小遍历范围"""
        # 相同指令
        same_commands = data_conveyor.filter_command(command)
        if same_commands:
            return same_commands

        # 分词匹配指令，有限的硬件资源环境不允许本地NLP
        all_commands = data_conveyor.all_command()

        def __filter_by_words(_words):
            """过滤分词，也可以采用jieba分词中的自定义字典实现"""
            actions = []
            for commands, action in all_commands:
                for _word in _words:
                    # 分词后匹配命令字符串
                    if _word in commands:
                        actions.append(action)
            return data_conveyor.filter_command_by_actions(set(actions))

        # 像似和模糊分词 https://cuiqingcai.com/5844.html
        cut_words = lcut_for_search(command)
        cut_all_words = lcut(command, cut_all=True)
        # 合并分词并过滤（匹配已有指令）
        _words = list(set(cut_words) | set(cut_all_words))
        like_commands = __filter_by_words(_words)
        return like_commands if like_commands else []


    def _exec():
        """执行指令"""
        access = False  # 是否成功执行并进入指令
        voice2text = listening()
        # 去除标点符号（也可以采用jieba分词中的去除停用词实现）
        voice2text = StringUtil.remove_punctuation(voice2text)
        logger.info(f"发出指令>>> {voice2text}")
        data_conveyor.stt(voice2text)
        if voice2text is None:
            data_conveyor.stt("我没听到声音")
            return access
        if StringUtil.same_word(voice2text):
            data_conveyor.stt("声音太小啦")
            return access
        for commands, action, appid in _command_filter(voice2text):
            found = False  # 指令是否已找到
            for command in commands.split(","):
                if match(voice2text, command):
                    play_audio_file()
                    logger.info(f"指令命中: {command}")
                    data_conveyor.access(command)
                    if action.startswith("/"):
                        # 更新当前所在一级目录
                        data_conveyor.update_cur_appid(appid)
                        # 页面访问
                        browser.get(ROOT + action)
                    else:
                        # 页面动作，部分动作带有动态参数
                        if ":" in action:
                            # 带参数
                            _todo(browser, action.split(":")[0], command)
                        else:
                            # 不带参数
                            _todo(browser, action)
                    data_conveyor.hot(action)  # +指令热度
                    found = True
                    break
            if found:
                access = True
                break
        else:
            logger.info("~_~ 指令不匹配")
            data_conveyor.info("~_~ 指令不匹配")
        return access


    while True:
        try:
            if WAKEUP:
                FAILURE = 0 if _exec() else (FAILURE + 1)
            else:
                word, up = wakeup(keywords)
                data_conveyor.stt(word)
                if up:
                    WAKEUP = True
                    logger.info("^_^ 唤醒成功")
                    dpms_on()
                    data_conveyor.wakeup()
                    FAILURE = 0 if _exec() else (FAILURE + 1)
                else:
                    data_conveyor.stt("")
            # 达到匹配上限次数则睡眠
            if FAILURE >= CappedFailAmount:
                logger.info("睡眠待命")
                data_conveyor.sleep()
                WAKEUP = False
                FAILURE = 0
        except Exception as e:
            logger.error(f"接收语音错误，{e}")
            data_conveyor.error()

        time.sleep(TIME)
    browser.close()