"""OAB Exams dataset"""

import datasets
import pandas as pd
import re

_CITATION = """@misc{delfino2017passing,
      title={Passing the Brazilian OAB Exam: data preparation and some experiments}, 
      author={Pedro Delfino and Bruno Cuconato and Edward Hermann Haeusler and Alexandre Rademaker},
      year={2017},
      eprint={1712.05128},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
"""

_DESCRIPTION = """
This repository contains the bar exams from the Ordem dos Advogados do Brasil (OAB) in Brazil from 2010 to 2018.
In Brazil, all legal professionals must demonstrate their knowledge of the law and its application by passing the OAB exams, the national bar exams. The OAB exams therefore provide an excellent benchmark for the performance of legal information systems since passing the exam would arguably signal that the system has acquired capacity of legal reasoning comparable to that of a human lawyer.
"""

_HOMEPAGE="https://github.com/legal-nlp/oab-exams"

BASE_URL = "https://raw.githubusercontent.com/legal-nlp/oab-exams/master/official/raw/"

FILES = [
 '2010-01.txt',
 '2010-02.txt',
 '2011-03.txt',
 '2011-04.txt',
 '2011-05.txt',
 '2012-06.txt',
 '2012-06a.txt',
 '2012-07.txt',
 '2012-08.txt',
 '2012-09.txt',
 '2013-10.txt',
 '2013-11.txt',
 '2013-12.txt',
 '2014-13.txt',
 '2014-14.txt',
 '2014-15.txt',
 '2015-16.txt',
 '2015-17.txt',
 '2015-18.txt',
 '2016-19.txt',
 '2016-20.txt',
 '2016-20a.txt',
 '2016-21.txt',
 '2017-22.txt',
 '2017-23.txt',
 '2017-24.txt',
 '2018-25.txt'
]

def join_lines(lines):
    texts = []
    for line in lines:
        if line.strip() == "":
            texts.append("\n")
        else:
            texts.append(line.strip() + " ")
    return "".join(texts).strip()

class OABExams(datasets.GeneratorBasedBuilder):

    VERSION = datasets.Version("1.1.0")
    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "question_id": datasets.Value("string"),
                    "question_number": datasets.Value("int32"),
                    "exam_id": datasets.Value("string"),
                    "exam_year": datasets.Value("int32"),
                    "question_type": datasets.Value("string"),
                    "question": datasets.Value("string"),
                    "choices": datasets.Sequence(feature={
                        "text": datasets.Value("string"),
                        "label": datasets.Value("string")
                    }),
                    "answerKey": datasets.Value("string"),
                    }),
            supervised_keys=None,
            homepage=_HOMEPAGE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        links = [BASE_URL + file for file in FILES] 
        downloaded_files = dl_manager.download(links)
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "filepaths": downloaded_files,
                    "filenames": FILES
                }
            )        
        ]

    def _generate_examples(self, filepaths, filenames):
        for filepath, filename in zip(filepaths, filenames):
            exam_id = filename.replace(".txt", "")
            exam_year = int(filename.split("-")[0])
            questions_temp = []
            with open(filepath, encoding="utf-8") as f:
                lines = f.readlines()
                for i, line in enumerate(lines):
                    # if line matches regex that validates "Questão 1" or "Questão 80 NULL"
                    if re.match(r"Questão \d{1,2}(\sNULL)?", line.strip()):
                        question_number = int(line.strip().split(" ")[1])
                        question_id = exam_id + "_" + str(question_number)
                        questions_temp.append(
                            {
                                "question_id": question_id,
                                "question_number": question_number,
                                "exam_id": exam_id,
                                "exam_year": exam_year,
                                "lines": [line]
                            }
                        )
                    else:
                        questions_temp[-1]["lines"].append(line)

            for question_temp in questions_temp:
                question_lines = question_temp["lines"]

                area_index = 2
                if question_lines[1].startswith("AREA"):
                    area_index = 1

                area_line = question_lines[area_index].strip()
                question_type = None if area_line == "AREA" else area_line.split(" ")[1]
                

                index_options = None
                for i, line in enumerate(question_lines):
                    if line.strip() == "OPTIONS":
                        index_options = i
                        break
                
                if index_options is None:
                    print(question_temp)      

                question = join_lines(question_lines[3:index_options])

                choices = {
                    "text": [],
                    "label": []
                }
                answerKey = None
                temp_question_text = None
                for i, line in enumerate(question_lines[index_options+2:]):
                    if "CORRECT)" in line:
                        answerKey = line[0]
                    if line[0] in ["A", "B", "C", "D", "E"] and (line[1:3] == ") " or line[1:11] == ":CORRECT) "):
                        if temp_question_text is not None:
                            choices["text"].append(join_lines(temp_question_text))
                        temp_question_text = [line[line.find(')')+2:]]
                        choices["label"].append(line[0])
                    else:
                        if temp_question_text is not None:
                            temp_question_text.append(line)
                if temp_question_text is not None:
                    choices["text"].append(join_lines(temp_question_text))
                    temp_question_text = None

                yield question_temp['question_id'], {
                    "question_id": question_temp['question_id'],
                    "question_number": question_temp['question_number'],
                    "exam_id": question_temp['exam_id'],
                    "exam_year": question_temp['exam_year'],
                    "question_type": question_type,
                    "question": question,
                    "choices": choices,
                    "answerKey": answerKey
                }