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| ''' Script to segment IMO shortlist md files using regex. It takes as input |
| the file en-compendium.md in en-shortlist and outputs the segmentation |
| (problem/solution pairs) in en-shortlist-seg |
| To run: |
| `python segment_compendium.py` |
| To debug (or see covered use cases by regex): |
| `pytest test_segment_compendium` |
| ''' |
|
|
| import os |
| import re |
| import pandas as pd |
|
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|
| base = 'en-shortlist' |
| seg_base = 'en-shortlist-seg' |
| basename = 'en-compendium' |
|
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|
| level1_re = re.compile(r"^##\s+(Problems|Solutions|Notation and Abbreviations)$") |
| year_re = re.compile(r"^[^=]*,\s+(\d{4})\s*$") |
| problem_section_re = re.compile(r"^###\s+(\d+\.\d+\.\d+)\s+(.+)$") |
| solution_section_re = re.compile(r"^###\s+(\d+\.\d+)\s+([\w\s]+)\s+(\d{4})$") |
| problem_or_solution_re = re.compile(r"^(?:\[.*?\])?\s*(\d+)\s*\.\s*(.+)$") |
|
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|
|
| def add_content(current_dict): |
| required_keys = ["year", "category", "section_label", "label", "lines"] |
| if not all(current_dict[key] for key in required_keys): |
| return |
| text_str = " ".join(current_dict["lines"]).strip() |
| entry = { |
| "year": current_dict["year"], |
| "category": current_dict["category"], |
| "section": current_dict["section_label"], |
| "label": current_dict["label"], |
| } |
| if current_dict["class"] == "problem": |
| entry["problem"] = text_str |
| current_dict["problems"].append(entry) |
| elif current_dict["class"] == "solution": |
| entry["solution"] = text_str |
| current_dict["solutions"].append(entry) |
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|
| def get_category(s:str): |
| cat = None |
| if 'contest' in s.lower(): |
| cat = 'contest' |
| elif 'shortlisted' in s.lower(): |
| cat = 'shortlisted' |
| elif 'longlisted' in s.lower(): |
| cat = 'longlisted' |
| return cat |
|
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|
|
| def get_matching_section_label(s:str): |
| """ |
| extracts the section number to be used a a join key to pair a problem and solution |
| for problems: 3.44.1 -> 44 |
| for solutions: 4.20 -> 20 |
| """ |
| return s.split('.')[1] |
|
|
|
|
| def parse(file): |
| with open(file, 'r') as file: |
| content = file.read() |
| |
| current = { |
| "year": None, |
| "category": None, |
| "section_label": None, |
| "label": None, |
| "class": None, |
| "lines": [], |
| "problems": [], |
| "solutions": [] |
| } |
| for line in content.splitlines(): |
| if match := level1_re.match(line): |
| add_content(current) |
| title, = match.groups() |
| current["class"] = { |
| "Problems": "problem", |
| "Solutions": "solution", |
| }.get(title, "other") |
| current["lines"] = [] |
| elif match := year_re.match(line): |
| add_content(current) |
| current["year"] = match.group(1) |
| current["lines"] = [] |
| elif match := problem_section_re.match(line): |
| add_content(current) |
| number, title = match.groups() |
| current["section_label"] = get_matching_section_label(number) |
| current["category"] = get_category(title) |
| current["lines"] = [] |
| elif match := solution_section_re.match(line): |
| add_content(current) |
| number, title, year = match.groups() |
| current["section_label"] = get_matching_section_label(number) |
| current["category"] = get_category(title) |
| current["year"] = year |
| current["lines"] = [] |
| elif match := problem_or_solution_re.match(line): |
| add_content(current) |
| current["label"] = match.group(1) |
| current["lines"] = [line] |
| else: |
| if current["lines"]: |
| current["lines"].append(line) |
| problems_df = pd.DataFrame(current["problems"]) |
| solutions_df = pd.DataFrame(current["solutions"]) |
| return problems_df, solutions_df |
|
|
| def join(problems_df, solutions_df): |
| pairs_df = problems_df.merge(solutions_df, on=["year", "category", "section", "label"], how="outer") |
| return pairs_df |
|
|
| def add_metadata(pairs_df): |
| problem_type_mapping = { |
| "A": "Algebra", |
| "C": "Combinatorics", |
| "G": "Geometry", |
| "N": "Number Theory" |
| } |
| pairs_df['problem_type'] = pairs_df['problem'].str.extract(r'^\d+\.\s*([ACGN])\d*')[0] |
| pairs_df['problem_type'] = pairs_df['problem_type'] .map(problem_type_mapping) |
| pairs_df['tier'] = 0 |
| pairs_df.rename(columns={"category": "problem_phase"}, inplace=True) |
| pairs_df = pairs_df.drop(columns=['section', 'label']) |
| return pairs_df |
|
|
| def write_pairs(filename, pairs_df): |
| pairs_df.to_json(filename, orient="records", lines=True) |
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|
| problems, solutions = parse(f"{base}/{basename}.md") |
| pairs_df = join(problems, solutions) |
| pairs_df = pairs_df[pairs_df.notnull().all(axis=1)] |
| pairs_df = add_metadata(pairs_df) |
| write_pairs(f"{seg_base}/{basename}.jsonl", pairs_df) |
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