"""Test-Stanford dataset by Bansal et al.."""

import datasets
import pandas as pd

_CITATION = """
@misc{bansal2015deep,
      title={Towards Deep Semantic Analysis Of Hashtags}, 
      author={Piyush Bansal and Romil Bansal and Vasudeva Varma},
      year={2015},
      eprint={1501.03210},
      archivePrefix={arXiv},
      primaryClass={cs.IR}
}
"""

_DESCRIPTION = """
Manually Annotated Stanford Sentiment Analysis Dataset by Bansal et al..
"""
_URLS = {
    "test": "https://raw.githubusercontent.com/ruanchaves/hashformers/master/datasets/Test-Stanford.txt"
}

class TestStanford(datasets.GeneratorBasedBuilder):

    VERSION = datasets.Version("1.0.0")

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "index": datasets.Value("int32"),
                    "hashtag": datasets.Value("string"),
                    "segmentation": datasets.Value("string"),
                    "gold_position": datasets.Value("int32"),
                    "rank": datasets.Sequence(
                        {
                            "position": datasets.Value("int32"),
                            "candidate": datasets.Value("string")
                        }
                    )
                }
            ),
            supervised_keys=None,
            homepage="",
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        downloaded_files = dl_manager.download(_URLS)
        return [
            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"] }),
        ]

    def _generate_examples(self, filepath):

        names = ["id","hashtag","candidate", "label"]
        df = pd.read_csv(filepath, sep="\t", skiprows=1, header=None, 
            names=names)

        for col in names[0:-1]:
            df[col] = df[col].apply(lambda x: x.strip("'").strip())

        records = df.to_dict('records')

        output = []

        current_hashtag = None
        hashtag = None
        candidates = []
        ids = []
        label = []


        for row in records:
            hashtag = row["hashtag"]
            if current_hashtag != hashtag:
                new_row = {
                    "hashtag": current_hashtag,
                    "candidate": candidates,
                    "id": ids,
                    "label": label
                }
                
                if current_hashtag:
                    output.append(new_row)
                
                current_hashtag = row['hashtag']
                candidates = [row["candidate"]]
                ids = int(row["id"])
                label = [int(row["label"])]
            else:
                candidates.append(row["candidate"])
                label.append(int(row["label"]))            

        def get_gold_position(row):
            try:
                return row["label"].index(1)
            except ValueError:
                return None

        def get_rank(row):
            return [{
                "position": idx + 1,
                "candidate": item
            } for idx, item in enumerate(row["candidate"])]

        def get_segmentation(row):
            try:
                gold_idx = row["label"].index(1)
                return row["candidate"][gold_idx]
            except ValueError:
                return None

        for idx, row in enumerate(output):
            yield idx, {
                "index": int(row["id"]),
                "hashtag": row["hashtag"],
                "segmentation": get_segmentation(row),
                "gold_position": get_gold_position(row),
                "rank": get_rank(row)
            }