# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# TODO: Address all TODOs and remove all explanatory comments
"""桃園多國語系翻譯競賽: Translate dataset."""


import csv
import json
import os
import datasets

logger = datasets.logging.get_logger(__name__)


# TODO: Add BibTeX citation
# Find for instance the citation on arxiv or on the dataset repo/website
_CITATION = """\
@InProceedings{huggingface:dataset,
title = {A great new dataset},
author={huggingface, Inc.
},
year={2020}
}
"""

_DESCRIPTION = """\
Translation dataset based on the data from statmt.org.
Versions exist for different years using a combination of data
sources. The base `wmt` allows you to create a custom dataset by choosing
your own data/language pair. This can be done as follows:
```python
from datasets import inspect_dataset, load_dataset_builder
inspect_dataset("wmt16", "path/to/scripts")
builder = load_dataset_builder(
    "path/to/scripts/wmt_utils.py",
    language_pair=("fr", "de"),
    subsets={
        datasets.Split.TRAIN: ["commoncrawl_frde"],
        datasets.Split.VALIDATION: ["euelections_dev2019"],
    },
)
# Standard version
builder.download_and_prepare()
ds = builder.as_dataset()
# Streamable version
ds = builder.as_streaming_dataset()
```
"""

_LANGUAGE_PAIRS = [(lang, "zh_tw") for lang in ["en", "ja", "ko", "id", "vi", "th"]]

# TODO: Add a link to an official homepage for the dataset here
_HOMEPAGE = "https://huggingface.co/Heng666"

_LICENSE = "cc-by-2.0"

# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
_URL = "http://www.statmt.org/wmt16/translation-task.html"

class Ted2020TWMTConfig(datasets.BuilderConfig):
    """BuilderConfig for ted2020TW-mt"""

    def __init__(self, url=None, citation=None, description=None, language_pair=(None, None), **kwargs):
        """
        Args:
          url: The reference URL for the dataset.
          citation: The paper citation for the dataset.
          description: The description of the dataset.
          language_pair: pair of languages that will be used for translation. Should
                     contain 2 letter coded strings. For example: ("en", "de").
            configuration for the `datasets.features.text.TextEncoder` used for the
            `datasets.features.text.Translation` features.
          **kwargs: keyword arguments forwarded to super.
        """
        name = "%s-%s" % (language_pair[0], language_pair[1])
        if "name" in kwargs:  # Add name suffix for custom configs
            name += "." + kwargs.pop("name")

        super().__init__(name=name, description=description, **kwargs)

        self.url = url or "http://www.statmt.org"
        self.citation = citation
        self.language_pair = language_pair


class Ted2020TWMTDataset(datasets.GeneratorBasedBuilder):
    """TODO: Short description of my dataset."""

    VERSION = datasets.Version("1.0.0")

    BUILDER_CONFIG_CLASS = Ted2020TWMTConfig

    BUILDER_CONFIGS = [
        Ted2020TWMTConfig(  # pylint:disable=g-complex-comprehension
            description="桃園捷運 %s-%s translation task dataset." % (l1, l2),
            url=_URL,
            citation=_CITATION,
            language_pair=(l1, l2),
            version=datasets.Version("1.0.0"),
        )
        for l1, l2 in _LANGUAGE_PAIRS
    ]


    def _info(self):

      src, target = self.config.language_pair
      return datasets.DatasetInfo(
          description=_DESCRIPTION,
          features=datasets.Features(
            {
              "translation": datasets.features.Translation(languages=self.config.language_pair)
            }
          ),
          homepage=_HOMEPAGE,
          citation=_CITATION,
          license=_LICENSE
      )

    def _split_generators(self, dl_manager):

        lang_pair = self.config.language_pair

        # 將語言對轉換成適合檔案命名的格式，例如 'vi-zh_tw'
        lang_pair_str = f"{lang_pair[1]}-{lang_pair[0]}"
        
        files = {}

        # 根據新的檔案命名規則更新檔案路徑
        train_path = os.path.join("train", f"{lang_pair_str}_translations_train.csv")
        files["train"]= train_path
        test_path = os.path.join("test", f"{lang_pair_str}_translations_test.csv")
        files["test"] = test_path   

        try:
            data_dir = dl_manager.download_and_extract(files)
        except:
            files.pop("test")
            data_dir = dl_manager.download_and_extract(files)
            
        output = []
        if "train" in files:
            train = datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "filepath": data_dir["train"]
                }
            )
            output.append(train)

        if "test" in files:
            test = datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={
                    "filepath": data_dir["test"]
                }
            )
            output.append(test)

        return output

    # # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
    # def _generate_examples(self, filepath):
    #     """Yields examples."""
    #     with open(filepath, encoding="utf-8") as f:
    #         reader = csv.reader(f, delimiter=",", quotechar='"')
    #         for id_, row in enumerate(reader):
    #             if id_ == 0:
    #                 continue
    #             yield id_, {
    #                 "instruction": row[0],
    #                 "input": row[1],
    #                 "output": row[2]
    #             }
    def _generate_examples(self, filepath):
      """Yields examples from the CSV file where each row contains translations in JSON format."""
      with open(filepath, encoding="utf-8") as f:
          reader = csv.reader(f, delimiter=",", quotechar='"')
          for id_, row in enumerate(reader):
            if id_ == 0:  # 假設第一行是標題行，所以跳過它
                continue
            # 假設你的CSV文件結構是每行一個JSON字符串
            translation_data = json.loads(row[0])
            print(translation_data)
            yield id_, {
                'translation': translation_data,
            }