# coding=utf-8
# 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.
"""Dataloader for RotoWire English-German dataset."""

import json
import os

import datasets
import re

# Find for instance the citation on arxiv or on the dataset repo/website
_CITATION = """\
@article{hayashi2019findings,
  title={Findings of the Third Workshop on Neural Generation and Translation},
  author={Hayashi, Hiroaki and Oda, Yusuke and Birch, Alexandra and Konstas, Ioannis and Finch, Andrew and Luong, Minh-Thang and Neubig, Graham and Sudoh, Katsuhito},
  journal={EMNLP-IJCNLP 2019},
  pages={1},
  year={2019}
}
"""

# You can copy an official description
_DESCRIPTION = """\
Dataset for the WNGT 2019 DGT shared task on "Document-Level Generation and Translation”.
"""

_HOMEPAGE = "https://sites.google.com/view/wngt19/dgt-task"

_LICENSE = "CC-BY 4.0"

# The HuggingFace dataset library don't host the datasets but only point to the original files
# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
_URLs = {
    "train": "train.json",
    "validation": "validation.json",
    "test": "test.json"
}

NUM_PLAYERS = 13
player_line = "<PLAYER> %s <TEAM> %s <POS> %s <RANK> %s <MIN> %d <PTS> %d <FG> %d %d %d <FG3> %d %d %d " \
              "<FT> %d %d %d <REB> %d <AST> %d <STL> %s " \
              "<BLK> %d <DREB> %d <OREB> %d <TO> %d"

team_line = "%s <TEAM> %s <CITY> %s <TEAM-RESULT> %s <TEAM-PTS> %d <WINS-LOSSES> %d %d <QTRS> %d %d %d %d " \
            "<TEAM-AST> %d <3PT> %d <TEAM-FG> %d <TEAM-FT> %d <TEAM-REB> %d <TEAM-TO> %d"

def detokenize(text):
    """
    Untokenizing a text undoes the tokenizing operation, restoring
    punctuation and spaces to the places that people expect them to be.
    Ideally, `untokenize(tokenize(text))` should be identical to `text`,
    except for line breaks.
    """
    step1 = text.replace("`` ", '"').replace(" ''", '"').replace('. . .',  '...')
    step2 = step1.replace(" ( ", " (").replace(" ) ", ") ")
    step3 = re.sub(r' ([.,:;?!%]+)([ \'"`])', r"\1\2", step2)
    step4 = re.sub(r' ([.,:;?!%]+)$', r"\1", step3)
    step5 = step4.replace(" '", "'").replace(" n't", "n't").replace(
         "can not", "cannot").replace(" 've", "'ve")
    step6 = step5.replace(" ` ", " '")
    return step6.strip()

class RotowireEnglishGerman(datasets.GeneratorBasedBuilder):
    """Dataset for WNGT2019 shared task on Document-level Generation and Translation."""

    VERSION = datasets.Version("1.1.0")

    # This is an example of a dataset with multiple configurations.
    # If you don't want/need to define several sub-sets in your dataset,
    # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.

    # If you need to make complex sub-parts in the datasets with configurable options
    # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
    # BUILDER_CONFIG_CLASS = MyBuilderConfig

    # You will be able to load one or the other configurations in the following list with
    # data = datasets.load_dataset('my_dataset', 'first_domain')
    # data = datasets.load_dataset('my_dataset', 'second_domain')
    # BUILDER_CONFIGS = [
    #     datasets.BuilderConfig(name="nlg_en", version=VERSION, description="NLG: Data-to-English text."),
    #     datasets.BuilderConfig(name="nlg_de", version=VERSION, description="NLG: Data-to-German text."),
    #     datasets.BuilderConfig(name="mt_en-de", version=VERSION, description="MT: English-to-German text."),
    #     datasets.BuilderConfig(name="mt_de-en", version=VERSION, description="MT: German-to-English text."),
    #     datasets.BuilderConfig(name="nlg+mt_en-de", version=VERSION, description="NLG+MT: Data+English-to-German text."),
    #     datasets.BuilderConfig(name="nlg+mt_de-en", version=VERSION, description="NLG+MT: Data+German-to-English text."),
    # ]

    def _info(self):
        # max 26 entries in each box_score field.
        box_score_entry = {str(i): datasets.Value("string") for i in range(26)}
        box_score_features = {
            "FIRST_NAME": box_score_entry,
            "MIN": box_score_entry,
            "FGM": box_score_entry,
            "REB": box_score_entry,
            "FG3A": box_score_entry,
            "PLAYER_NAME": box_score_entry,
            "AST": box_score_entry,
            "FG3M": box_score_entry,
            "OREB": box_score_entry,
            "TO": box_score_entry,
            "START_POSITION": box_score_entry,
            "PF": box_score_entry,
            "PTS": box_score_entry,
            "FGA": box_score_entry,
            "STL": box_score_entry,
            "FTA": box_score_entry,
            "BLK": box_score_entry,
            "DREB": box_score_entry,
            "FTM": box_score_entry,
            "FT_PCT": box_score_entry,
            "FG_PCT": box_score_entry,
            "FG3_PCT": box_score_entry,
            "SECOND_NAME": box_score_entry,
            "TEAM_CITY": box_score_entry,
        }
        line_features = {
            "TEAM-PTS_QTR2": datasets.Value("string"),
            "TEAM-FT_PCT": datasets.Value("string"),
            "TEAM-PTS_QTR1": datasets.Value("string"),
            "TEAM-PTS_QTR4": datasets.Value("string"),
            "TEAM-PTS_QTR3": datasets.Value("string"),
            "TEAM-CITY": datasets.Value("string"),
            "TEAM-PTS": datasets.Value("string"),
            "TEAM-AST": datasets.Value("string"),
            "TEAM-LOSSES": datasets.Value("string"),
            "TEAM-NAME": datasets.Value("string"),
            "TEAM-WINS": datasets.Value("string"),
            "TEAM-REB": datasets.Value("string"),
            "TEAM-TOV": datasets.Value("string"),
            "TEAM-FG3_PCT": datasets.Value("string"),
            "TEAM-FG_PCT": datasets.Value("string")
        }
        features = datasets.Features(
            {
                "id":datasets.Value("string"),
                "gem_id":datasets.Value("string"),
                "home_name": datasets.Value("string"),
                "box_score": box_score_features,
                "vis_name": datasets.Value("string"),
                "summary": datasets.Sequence(datasets.Value("string")),
                "home_line": line_features,
                "home_city": datasets.Value("string"),
                "vis_line": line_features,
                "vis_city": datasets.Value("string"),
                "day": datasets.Value("string"),
                "detok_summary_org": datasets.Value("string"),
                "detok_summary":  datasets.Value("string"),
                "summary_en": datasets.Sequence(datasets.Value("string")),
                "sentence_end_index_en": datasets.Sequence(datasets.Value("int32")),
                "summary_de": datasets.Sequence(datasets.Value("string")),
                "target": datasets.Value("string"),
                "references": [datasets.Value("string")],
                "sentence_end_index_de": datasets.Sequence(datasets.Value("int32")),
                "linearized_input": datasets.Value("string")
            }
        )
        return datasets.DatasetInfo(
            # This is the description that will appear on the datasets page.
            description=_DESCRIPTION,
            # This defines the different columns of the dataset and their types
            features=features,  # Here we define them above because they are different between the two configurations
            # If there's a common (input, target) tuple from the features,
            # specify them here. They'll be used if as_supervised=True in
            # builder.as_dataset.
            supervised_keys=None,
            # Homepage of the dataset for documentation
            homepage=_HOMEPAGE,
            # License for the dataset if available
            license=_LICENSE,
            # Citation for the dataset
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
        # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name

        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLs
        # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
        # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
        data_dir = dl_manager.download_and_extract(_URLs)
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                # These kwargs will be passed to _generate_examples
                gen_kwargs={
                    "filepath": data_dir["train"],
                    "split": "train",
                },
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                # These kwargs will be passed to _generate_examples
                gen_kwargs={
                    "filepath": data_dir["test"],
                    "split": "test"
                },
            ),
            datasets.SplitGenerator(
                name=datasets.Split.VALIDATION,
                # These kwargs will be passed to _generate_examples
                gen_kwargs={
                    "filepath": data_dir["validation"],
                    "split": "validation",
                },
            ),
        ]

    def handle_na(self, value):
        return "0" if value == "N/A" else value

    def tokenize_initials(self, value):
        attrib_value = re.sub(r"(\w)\.(\w)\.", r"\g<1>. \g<2>.", value)
        return attrib_value

    def sort_points(self, entry):
        home_team_map = {}
        vis_team_map = {}
        bs = entry["box_score"]
        nplayers = 0
        for k, v in bs["PTS"].items():
            nplayers += 1

        num_home, num_vis = 0, 0
        home_pts = []
        vis_pts = []
        for i in range(nplayers):
            player_city = entry["box_score"]["TEAM_CITY"][str(i)]
            player_name = bs["PLAYER_NAME"][str(i)]
            if player_city == entry["home_city"]:
                if num_home < NUM_PLAYERS:
                    home_team_map[player_name] = bs["PTS"][str(i)]
                    if bs["PTS"][str(i)] != "N/A":
                        home_pts.append(int(bs["PTS"][str(i)]))
                    num_home += 1
            else:
                if num_vis < NUM_PLAYERS:
                    vis_team_map[player_name] = bs["PTS"][str(i)]
                    if bs["PTS"][str(i)] != "N/A":
                        vis_pts.append(int(bs["PTS"][str(i)]))
                    num_vis += 1
        if entry["home_city"] == entry["vis_city"] and entry["home_city"] == "Los Angeles":
            num_home, num_vis = 0, 0
            for i in range(nplayers):
                player_name = bs["PLAYER_NAME"][str(i)]
                if num_vis < NUM_PLAYERS:
                    vis_team_map[player_name] = bs["PTS"][str(i)]
                    if bs["PTS"][str(i)] != "N/A":
                        vis_pts.append(int(bs["PTS"][str(i)]))
                    num_vis += 1
                elif num_home < NUM_PLAYERS:
                    home_team_map[player_name] = bs["PTS"][str(i)]
                    if bs["PTS"][str(i)] != "N/A":
                        home_pts.append(int(bs["PTS"][str(i)]))
                    num_home += 1
        home_seq = sorted(home_pts, reverse=True)
        vis_seq = sorted(vis_pts, reverse=True)
        return home_team_map, vis_team_map, home_seq, vis_seq

    def sort_player_and_points(self, entry):
        bs = entry["box_score"]
        nplayers = 0
        for k, v in bs["PTS"].items():
            nplayers += 1

        num_home, num_vis = 0, 0
        home_pts = []
        vis_pts = []
        for i in range(nplayers):
            player_city = entry["box_score"]["TEAM_CITY"][str(i)]
            player_name = bs["PLAYER_NAME"][str(i)]
            if player_city == entry["home_city"]:
                if num_home < NUM_PLAYERS:
                    if bs["PTS"][str(i)] != "N/A":
                        home_pts.append((player_name, int(bs["PTS"][str(i)])))
                    else:
                        home_pts.append((player_name, -1))
                    num_home += 1
            else:
                if num_vis < NUM_PLAYERS:
                    if bs["PTS"][str(i)] != "N/A":
                        vis_pts.append((player_name, int(bs["PTS"][str(i)])))
                    else:
                        vis_pts.append((player_name, -1))
                    num_vis += 1
        if entry["home_city"] == entry["vis_city"] and entry["home_city"] == "Los Angeles":
            num_home, num_vis = 0, 0
            for i in range(nplayers):
                player_name = bs["PLAYER_NAME"][str(i)]
                if num_vis < NUM_PLAYERS:
                    if bs["PTS"][str(i)] != "N/A":
                        vis_pts.append((player_name, int(bs["PTS"][str(i)])))
                    else:
                        vis_pts.append((player_name, -1))
                    num_vis += 1
                elif num_home < NUM_PLAYERS:
                    if bs["PTS"][str(i)] != "N/A":
                        home_pts.append((player_name, int(bs["PTS"][str(i)])))
                    else:
                        home_pts.append((player_name, -1))
                    num_home += 1
        home_seq = sorted(home_pts, key=lambda x: -x[1])
        vis_seq = sorted(vis_pts, key=lambda x: -x[1])
        return home_seq, vis_seq

    def get_players(self, entry):
        player_team_map = {}
        bs = entry["box_score"]
        nplayers = 0
        home_players, vis_players = [], []
        for k, v in entry["box_score"]["PTS"].items():
            nplayers += 1

        num_home, num_vis = 0, 0
        for i in range(nplayers):
            player_city = entry["box_score"]["TEAM_CITY"][str(i)]
            player_name = bs["PLAYER_NAME"][str(i)]
            second_name = bs["SECOND_NAME"][str(i)]
            first_name = bs["FIRST_NAME"][str(i)]
            if player_city == entry["home_city"]:
                if len(home_players) < NUM_PLAYERS:
                    home_players.append((player_name, second_name,
                                         first_name))
                    player_team_map[player_name] = " ".join(
                        [player_city, entry["home_line"]["TEAM-NAME"]])
                    num_home += 1
            else:
                if len(vis_players) < NUM_PLAYERS:
                    vis_players.append((player_name, second_name,
                                        first_name))
                    player_team_map[player_name] = " ".join(
                        [player_city, entry["vis_line"]["TEAM-NAME"]])
                    num_vis += 1

        if entry["home_city"] == entry["vis_city"] and entry["home_city"] == "Los Angeles":
            home_players, vis_players = [], []
            num_home, num_vis = 0, 0
            for i in range(nplayers):
                player_name = bs["PLAYER_NAME"][str(i)]
                second_name = bs["SECOND_NAME"][str(i)]
                first_name = bs["FIRST_NAME"][str(i)]
                if len(vis_players) < NUM_PLAYERS:
                    vis_players.append((player_name, second_name,
                                        first_name))
                    player_team_map[player_name] = " ".join(
                        ["Los Angeles", entry["vis_line"]["TEAM-NAME"]])
                    num_vis += 1
                elif len(home_players) < NUM_PLAYERS:
                    home_players.append((player_name, second_name,
                                         first_name))
                    player_team_map[player_name] = " ".join(
                        ["Los Angeles", entry["home_line"]["TEAM-NAME"]])
                    num_home += 1

        players = []
        for ii, player_list in enumerate([home_players, vis_players]):
            for j in range(NUM_PLAYERS):
                players.append(player_list[j] if j < len(player_list) else ("N/A", "N/A", "N/A"))
        return players, player_team_map

    def get_result_player(self, player_name, home_name, vis_name, home_won, player_team_map):
        if player_team_map[player_name] == home_name:
            result = "won" if home_won else "lost"
        elif player_team_map[player_name] == vis_name:
            result = "lost" if home_won else "won"
        else:
            assert False
        return result

    def get_box_score(self, entry):
        box_score_ = entry["box_score"]
        if int(entry["home_line"]["TEAM-PTS"]) > int(entry["vis_line"]["TEAM-PTS"]):
            home_won = True
        else:
            home_won = False
        descs = []
        desc = []
        if home_won:
            home_line = self.get_team_line(entry["home_line"], "won", "home")
            vis_line = self.get_team_line(entry["vis_line"], "lost", "vis")
        else:
            home_line = self.get_team_line(entry["home_line"], "lost", "home")
            vis_line = self.get_team_line(entry["vis_line"], "won", "vis")
        descs.append(home_line)
        descs.append(vis_line)
        players_list, player_team_map = self.get_players(entry)
        home_team_map, vis_team_map, home_player_pts, vis_player_pts = self.sort_points(entry)
        home_player_seq, vis_player_seq = self.sort_player_and_points(entry)
        desc = []
        for player_name, _ in home_player_seq + vis_player_seq:
            if player_name == "N/A":
                continue
            result = self.get_result_player(player_name, entry["home_city"] + " " + entry["home_line"]["TEAM-NAME"],
                                       entry["vis_city"] + " " + entry["vis_line"]["TEAM-NAME"], home_won,
                                       player_team_map)
            player_line = self.get_player_line(box_score_, player_name, player_team_map, home_player_pts,
                                          vis_player_pts, home_team_map, vis_team_map, result)
            desc.append(player_line)
        descs.extend(desc)
        return descs

    def get_rank(self, player_name, home_seq, vis_seq, home_team_map, vis_team_map, result):
        if player_name in home_team_map:
            if home_team_map[player_name] == 'N/A':
                rank = 'HOME-DIDNTPLAY'
            else:
                rank = 'HOME-' + str(home_seq.index(int(home_team_map[player_name])))
        elif player_name in vis_team_map:
            if vis_team_map[player_name] == 'N/A':
                rank = 'VIS-DIDNTPLAY'
            else:
                rank = 'VIS-' + str(vis_seq.index(int(vis_team_map[player_name])))
        else:
            print("player_name", player_name)
            assert False
        return rank

    def get_player_line(self, bs, input_player_name, player_team_map, home_player_pts, vis_player_pts, home_team_map,
                        vis_team_map, result):
        rank = self.get_rank(input_player_name, home_player_pts, vis_player_pts, home_team_map, vis_team_map, result)
        player_names = list(bs["PLAYER_NAME"].items())
        player_found = False
        player_tup = None
        for (pid, name) in player_names:
            if name == input_player_name:
                player_tup = (self.tokenize_initials(name), player_team_map[input_player_name],
                              bs["START_POSITION"][pid],
                              rank,
                              int(self.handle_na(bs["MIN"][pid])),
                              int(self.handle_na(bs["PTS"][pid])),
                              int(self.handle_na(bs["FGM"][pid])),
                              int(self.handle_na(bs["FGA"][pid])), int(self.handle_na(bs["FG_PCT"][pid])),
                              int(self.handle_na(bs["FG3M"][pid])), int(self.handle_na(bs["FG3A"][pid])),
                              int(self.handle_na(bs["FG3_PCT"][pid])),
                              int(self.handle_na(bs["FTM"][pid])), int(self.handle_na(bs["FTA"][pid])),
                              int(self.handle_na(bs["FT_PCT"][pid])),
                              int(self.handle_na(bs["REB"][pid])), int(self.handle_na(bs["AST"][pid])),
                              int(self.handle_na(bs["STL"][pid])),
                              int(self.handle_na(bs["BLK"][pid])), int(self.handle_na(bs["DREB"][pid])),
                              int(self.handle_na(bs["OREB"][pid])), int(self.handle_na(bs["TO"][pid])))
                player_found = True
                break
        assert player_found
        return player_line % (player_tup)

    def get_team_line(self, line, result, type):
        city = line["TEAM-CITY"]
        name = line["TEAM-NAME"]
        wins = int(line["TEAM-WINS"])
        losses = int(line["TEAM-LOSSES"])
        pts = int(line["TEAM-PTS"])
        ast = int(line["TEAM-AST"])
        three_pointers_pct = int(line["TEAM-FG3_PCT"])
        field_goals_pct = int(line["TEAM-FG_PCT"])
        free_throws_pct = int(line["TEAM-FT_PCT"])
        pts_qtr1 = int(line["TEAM-PTS_QTR1"])
        pts_qtr2 = int(line["TEAM-PTS_QTR2"])
        pts_qtr3 = int(line["TEAM-PTS_QTR3"])
        pts_qtr4 = int(line["TEAM-PTS_QTR4"])
        reb = int(line["TEAM-REB"])
        tov = int(line["TEAM-TOV"])
        updated_type = "<" + type.upper() + ">"
        team_tup = (updated_type, name, city, result, pts, wins, losses, pts_qtr1, pts_qtr2, pts_qtr3, pts_qtr4, ast,
                    three_pointers_pct, field_goals_pct, free_throws_pct, reb, tov)
        return team_line % (team_tup)

    def linearize_input(self, entry):
        output = self.get_box_score(entry)
        linearized_input = " ".join(output)
        linearized_input = linearized_input.replace("  ", " ")
        return linearized_input

    def _generate_examples(
        self, filepath, split  # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
    ):
        """ Yields examples as (key, example) tuples. """
        # This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
        # The `key` is here for legacy reason (tfds) and is not important in itself.

        with open(filepath, encoding="utf-8") as f:
            all_data = json.load(f)
            for id_, data in enumerate(all_data):
                detok_target = detokenize(" ".join(data['summary_de']))
                data['linearized_input'] = self.linearize_input(data)
                data['target'] = detok_target
                data['references'] = [detok_target]
                yield id_, data