"""PorSimplesSent dataset"""

import datasets
import pandas as pd

_CITATION = """
"""

_DESCRIPTION = """
"""
_URLS = {
    "nat_str": "https://raw.githubusercontent.com/sidleal/porsimplessent/c0b7bb6ccda6b40ebd7f5524b08a5699b2266ffe/pss/pss2_align_length_nat_str.tsv",
    "ori_nat": "https://raw.githubusercontent.com/sidleal/porsimplessent/c0b7bb6ccda6b40ebd7f5524b08a5699b2266ffe/pss/pss2_align_length_ori_nat.tsv",
    "ori_str": "https://raw.githubusercontent.com/sidleal/porsimplessent/c0b7bb6ccda6b40ebd7f5524b08a5699b2266ffe/pss/pss2_align_length_ori_str.tsv"
}

class PorSimplesSent(datasets.GeneratorBasedBuilder):

    VERSION = datasets.Version("1.0.0")
    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "sentence1": datasets.Value("string"),
                    "sentence2": datasets.Value("string"),
                    "label": datasets.Value("int32"),
                    "production_id": datasets.Value("int32"),
                    "level": datasets.Value("string"),
                    "changed": datasets.Value("string"),
                    "split": datasets.Value("string"),
                    "sentence_text_from": datasets.Value("string"),
                    "sentence_text_to": 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.TRAIN,
                gen_kwargs={
                    "nat_str": downloaded_files["nat_str"],
                    "ori_nat": downloaded_files["ori_nat"],
                    "ori_str": downloaded_files["ori_str"],
                    "split": "train"
                }
            ),
            datasets.SplitGenerator(
                name=datasets.Split.VALIDATION,
                gen_kwargs={
                    "nat_str": downloaded_files["nat_str"],
                    "ori_nat": downloaded_files["ori_nat"],
                    "ori_str": downloaded_files["ori_str"],
                    "split": "validation"
                }
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={
                    "nat_str": downloaded_files["nat_str"],
                    "ori_nat": downloaded_files["ori_nat"],
                    "ori_str": downloaded_files["ori_str"],
                    "split": "test"
                }
            )
        ]

    def _generate_examples(self, nat_str, ori_nat, ori_str, split):
        df1 = pd.read_csv(nat_str, sep="\t", on_bad_lines="skip")
        df2 = pd.read_csv(ori_nat, sep="\t", on_bad_lines="skip")
        df3 = pd.read_csv(ori_str, sep="\t", on_bad_lines="skip")
        df = pd.concat([df1, df2, df3], axis=0)
        df["mod"] = df["production_id"].apply(lambda x: x % 5)
        if split == "validation":
            df = df[df["mod"] == 1]
        elif split == "test":
            df = df[df["mod"] == 2]
        elif split == "train":
            df = df[df["mod"] != 1]
            df = df[df["mod"] != 2]
        
        df = df.sort_values(by=["production_id", "sentence_text_from", "sentence_text_to"])

        prod_id_set = sorted(list(set(df["production_id"].values.tolist())))

        records = df.to_dict("records")
        for idx, item in enumerate(records):
            row = {}
            for key in ["production_id", "level", "changed", "split", "sentence_text_from", "sentence_text_to"]:
                row[key] = item[key]
            if item["changed"] == "S":
                if prod_id_set.index(item["production_id"]) % 2 == 0:
                    row["sentence1"] = item["sentence_text_from"]
                    row["sentence2"] = item["sentence_text_to"]
                    row["label"] = 2
                else:
                    row["sentence1"] = item["sentence_text_to"]
                    row["sentence2"] = item["sentence_text_from"]
                    row["label"] = 0
            else:
                row["sentence1"] = item["sentence_text_from"]
                row["sentence2"] = item["sentence_text_to"]
                row["label"] = 1

            yield idx, row