| import os | |
| import re | |
| import json | |
| from tqdm import tqdm | |
| from loguru import logger | |
| from pathlib import Path | |
| from typing import Tuple, List | |
| project_root = Path(__file__).parent.parent.parent | |
| problem_tag = 'Problem' | |
| solution_tag = 'Solution' | |
| def clean(text: str) -> str: | |
| return re.sub(r'\$\\underline\{\\text \{ (Solution de l\'exercice) \} (\d*)\}\$', r'\n\1 \2\n', text) | |
| def analyze(text: str) -> Tuple[List, int]: | |
| """ | |
| Analyze the text and return the tags and problem number. | |
| Args: | |
| text (str): The markdown text to analyze. | |
| Returns: | |
| Tuple[List, int]: A tuple containing the tags and problem number. | |
| """ | |
| problem_pattern = re.compile(r"(?i)(?:\n|##* )Exercice (\d+)[\.\n]") | |
| solution_pattern = re.compile(r"(?i)(?:\n|##* )(?:Solution de l'exercice\s*\d*|Solution\s*(\d+\s*)?[:\.\n]|(?:Première|Deuxième|Troisième|Quatrième) démonstration|Démonstration[:\.\n]|Corrigé[:\.\n]|Solution alternative)") | |
| tags = [] | |
| tags.extend([(x, problem_tag) for x in problem_pattern.finditer(text)]) | |
| problem_num = len(tags) | |
| tags.extend([(x, solution_tag) for x in solution_pattern.finditer(text)]) | |
| tags.sort(key=lambda x: x[0].start()) | |
| return tags, problem_num | |
| def segment(text: str, tags): | |
| starts = [] | |
| ends = [] | |
| for i in range(len(tags)): | |
| starts.append(tags[i][0].end()) | |
| if i + 1 < len(tags): | |
| ends.append(tags[i + 1][0].start()) | |
| else: | |
| ends.append(len(text)) | |
| return [text[start:end].strip().strip('#').strip() for start, end in zip(starts, ends)] | |
| def join(tags, segments): | |
| problem, solution = '', '' | |
| problem_label, problem_match, solution_match = '', '', '' | |
| pairs = [] | |
| for tag, segment in zip(tags, segments): | |
| if tag[1] == problem_tag: | |
| problem = segment | |
| problem_match = tag[0].group(0) | |
| problem_label = tag[0].group(1) | |
| elif problem != '': | |
| solution = segment | |
| solution_match = tag[0].group(0) | |
| pairs.append((problem, solution, problem_label, problem_match, solution_match)) | |
| return pairs | |
| def write_pairs(output_file: Path, pairs): | |
| year = re.search(r'(\d{4})', output_file.stem).group(1) | |
| output_jsonl_text = "" | |
| for problem, solution, problem_label, problem_match, solution_match in pairs: | |
| output_jsonl_text += json.dumps( | |
| { | |
| 'year': year, | |
| 'tier': 'T1', | |
| 'problem_label': problem_label, | |
| 'problem_type': None, | |
| 'problem': problem, | |
| 'solution': solution, | |
| 'metadata': { | |
| 'resource_path': output_file.relative_to(project_root).as_posix(), | |
| 'problem_match': problem_match, | |
| 'solution_match': solution_match | |
| } | |
| }, | |
| ensure_ascii=False | |
| ) + '\n' | |
| output_file.write_text(output_jsonl_text, encoding="utf-8") | |
| def main(): | |
| compet_base_path = Path(__file__).resolve().parent.parent | |
| compet_md_path = compet_base_path / "md" | |
| seg_output_path = compet_base_path / "segmented" | |
| total_problem_count = 0 | |
| total_solution_count = 0 | |
| for fr_tsts_md in tqdm(list(compet_md_path.glob('**/*.md')), desc='Segmenting'): | |
| output_file = seg_output_path / fr_tsts_md.relative_to(compet_md_path).with_suffix('.jsonl') | |
| output_file.parent.mkdir(parents=True, exist_ok=True) | |
| text = '\n' + clean(fr_tsts_md.read_text(encoding="utf-8")) | |
| tags, problem_num = analyze(text) | |
| segments = segment(text, tags) | |
| pairs = join(tags, segments) | |
| if pairs and problem_num > 0: | |
| write_pairs(output_file, pairs) | |
| total_problem_count += problem_num | |
| total_solution_count += len(pairs) | |
| else: | |
| logger.warning(f"No problem found in {fr_tsts_md}") | |
| logger.info(f"Total problem count: {total_problem_count}") | |
| logger.info(f"Total solution count: {total_solution_count}") | |
| if __name__ == '__main__': | |
| main() | |