import json
import os
import random

import numpy as np
from paddle.io import Dataset

from .imaug import create_operators, transform


class PubTabDataSet(Dataset):
    def __init__(self, config, mode, logger, seed=None):
        super(PubTabDataSet, self).__init__()
        self.logger = logger

        global_config = config["Global"]
        dataset_config = config[mode]["dataset"]
        loader_config = config[mode]["loader"]

        label_file_path = dataset_config.pop("label_file_path")

        self.data_dir = dataset_config["data_dir"]
        self.do_shuffle = loader_config["shuffle"]
        self.do_hard_select = False
        if "hard_select" in loader_config:
            self.do_hard_select = loader_config["hard_select"]
            self.hard_prob = loader_config["hard_prob"]
        if self.do_hard_select:
            self.img_select_prob = self.load_hard_select_prob()
        self.table_select_type = None
        if "table_select_type" in loader_config:
            self.table_select_type = loader_config["table_select_type"]
            self.table_select_prob = loader_config["table_select_prob"]

        self.seed = seed
        logger.info("Initialize indexs of datasets:%s" % label_file_path)
        with open(label_file_path, "rb") as f:
            self.data_lines = f.readlines()
        self.data_idx_order_list = list(range(len(self.data_lines)))
        if mode.lower() == "train":
            self.shuffle_data_random()
        self.ops = create_operators(dataset_config["transforms"], global_config)

        ratio_list = dataset_config.get("ratio_list", [1.0])
        self.need_reset = True in [x < 1 for x in ratio_list]

    def shuffle_data_random(self):
        if self.do_shuffle:
            random.seed(self.seed)
            random.shuffle(self.data_lines)
        return

    def __getitem__(self, idx):
        try:
            data_line = self.data_lines[idx]
            data_line = data_line.decode("utf-8").strip("\n")
            info = json.loads(data_line)
            file_name = info["filename"]
            select_flag = True
            if self.do_hard_select:
                prob = self.img_select_prob[file_name]
                if prob < random.uniform(0, 1):
                    select_flag = False

            if self.table_select_type:
                structure = info["html"]["structure"]["tokens"].copy()
                structure_str = "".join(structure)
                table_type = "simple"
                if "colspan" in structure_str or "rowspan" in structure_str:
                    table_type = "complex"
                if table_type == "complex":
                    if self.table_select_prob < random.uniform(0, 1):
                        select_flag = False

            if select_flag:
                cells = info["html"]["cells"].copy()
                structure = info["html"]["structure"].copy()
                img_path = os.path.join(self.data_dir, file_name)
                data = {"img_path": img_path, "cells": cells, "structure": structure}
                if not os.path.exists(img_path):
                    raise Exception("{} does not exist!".format(img_path))
                with open(data["img_path"], "rb") as f:
                    img = f.read()
                    data["image"] = img
                outs = transform(data, self.ops)
            else:
                outs = None
        except Exception as e:
            self.logger.error(
                "When parsing line {}, error happened with msg: {}".format(data_line, e)
            )
            outs = None
        if outs is None:
            return self.__getitem__(np.random.randint(self.__len__()))
        return outs

    def __len__(self):
        return len(self.data_idx_order_list)