Initial commit: PastPaper Master full stack
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
Zhao
233
backend/split_comp2211_2022_spring_midterm.py
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233
backend/split_comp2211_2022_spring_midterm.py
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"""Split COMP2211 Spring 2022 midterm top-level problems into subquestions."""
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from __future__ import annotations
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import json
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import re
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from dataclasses import dataclass
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from pathlib import Path
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from app.services.supabase_client import get_supabase
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EXAM_KEY = "COMP2211-2022-spring-midterm"
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TRUE_FALSE_OPTIONS = [{"label": "True", "text": "True"}, {"label": "False", "text": "False"}]
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@dataclass(frozen=True)
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class ChildSpec:
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question_number: str
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parent_question: str
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top_level_number: str
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path: tuple[str, ...]
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score: float
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question_type: str
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question_format: str | None = None
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page_number: int = 1
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def short_answer(
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question_number: str,
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parent_question: str,
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top_level_number: str,
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path: tuple[str, ...],
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score: float,
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*,
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page_number: int,
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) -> ChildSpec:
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return ChildSpec(
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question_number=question_number,
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parent_question=parent_question,
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top_level_number=top_level_number,
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path=path,
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score=score,
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question_type="long_question",
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question_format="short_answer",
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page_number=page_number,
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)
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CHILDREN: list[ChildSpec] = [
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*[
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ChildSpec(f"1{letter}", "1", "1", (letter,), 1.5, "true_false", page_number=2)
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for letter in "abcdefghij"
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],
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ChildSpec("2a_i", "2a", "2", ("a", "i"), 1, "fill_blank", page_number=4),
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ChildSpec("2a_ii", "2a", "2", ("a", "ii"), 1, "fill_blank", page_number=4),
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ChildSpec("2a_iii", "2a", "2", ("a", "iii"), 1, "fill_blank", page_number=4),
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ChildSpec("2a_iv", "2a", "2", ("a", "iv"), 1, "fill_blank", page_number=4),
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ChildSpec("2a_v", "2a", "2", ("a", "v"), 1, "fill_blank", page_number=4),
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ChildSpec("2b", "2", "2", ("b",), 2, "fill_blank", page_number=4),
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ChildSpec("2c", "2", "2", ("c",), 9, "long_question", "coding", page_number=5),
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ChildSpec("3a", "3", "3", ("a",), 2, "fill_blank", page_number=7),
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ChildSpec("3b_i", "3b", "3", ("b", "i"), 1.75, "fill_blank", page_number=7),
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ChildSpec("3b_ii", "3b", "3", ("b", "ii"), 1.75, "fill_blank", page_number=7),
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ChildSpec("3b_iii", "3b", "3", ("b", "iii"), 1.75, "fill_blank", page_number=7),
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ChildSpec("3b_iv", "3b", "3", ("b", "iv"), 1.75, "fill_blank", page_number=7),
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short_answer("3c", "3", "3", ("c",), 2, page_number=8),
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ChildSpec("4a", "4", "4", ("a",), 3, "long_question", "long_answer", page_number=9),
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short_answer("4b_i", "4b", "4", ("b", "i"), 3, page_number=9),
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short_answer("4b_ii", "4b", "4", ("b", "ii"), 3, page_number=9),
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ChildSpec("4c_i", "4c", "4", ("c", "i"), 2, "long_question", "long_answer", page_number=10),
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ChildSpec("4c_ii", "4c", "4", ("c", "ii"), 3, "long_question", "long_answer", page_number=10),
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ChildSpec("5a", "5", "5", ("a",), 4.5, "long_question", "long_answer", page_number=11),
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ChildSpec("5b", "5", "5", ("b",), 1.5, "fill_blank", page_number=11),
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ChildSpec("5c", "5", "5", ("c",), 4.5, "long_question", "long_answer", page_number=11),
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short_answer("5d", "5", "5", ("d",), 1.5, page_number=11),
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ChildSpec("6a", "6", "6", ("a",), 8, "long_question", "long_answer", page_number=12),
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short_answer("6b", "6", "6", ("b",), 2, page_number=13),
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ChildSpec("6c", "6", "6", ("c",), 10, "long_question", "coding", page_number=13),
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short_answer("7a", "7", "7", ("a",), 4, page_number=14),
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short_answer("7b", "7", "7", ("b",), 6, page_number=14),
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ChildSpec("7c", "7", "7", ("c",), 2, "fill_blank", page_number=15),
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]
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MARKER_RE = re.compile(r"(?m)^\(([a-z]+)\)\s*")
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PROBLEM_SEED_PATH = (
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Path(__file__).resolve().parent.parent
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/ "pastpaper-scraper"
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/ "reviews"
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/ "COMP2211"
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/ "problem_seed.json"
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)
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def split_sections(text: str) -> tuple[str, dict[str, str]]:
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matches = list(MARKER_RE.finditer(text))
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if not matches:
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return text.strip(), {}
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intro = text[: matches[0].start()].strip()
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sections: dict[str, str] = {}
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for idx, match in enumerate(matches):
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marker = match.group(1)
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end = matches[idx + 1].start() if idx + 1 < len(matches) else len(text)
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sections[marker] = text[match.start() : end].strip()
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return intro, sections
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def extract_segment(text: str, path: tuple[str, ...]) -> str:
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intro, sections = split_sections(text)
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if not path:
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return text.strip()
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first = sections.get(path[0], "")
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if not first:
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return text.strip()
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if len(path) == 1:
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return "\n".join(part for part in [intro, first] if part).strip()
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child_intro, child_sections = split_sections(first)
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second = child_sections.get(path[1], "")
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return "\n".join(part for part in [intro, child_intro, second] if part).strip()
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def extract_true_false_answers(answer_text: str) -> dict[str, str]:
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answers: dict[str, str] = {}
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matches = list(re.finditer(r"(?m)^\(([a-j])\)\s*\n?([TF])\b", answer_text))
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for match in matches:
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answers[match.group(1)] = match.group(2)
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return answers
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def derive_correct_answer(answer_text: str) -> str | None:
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if not answer_text:
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return None
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if "Answer:" in answer_text:
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tail = answer_text.split("Answer:", 1)[1]
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else:
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tail = answer_text
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lines = [line.strip() for line in tail.splitlines() if line.strip()]
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if not lines:
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return None
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first = lines[0]
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if first.lower().startswith("marking scheme"):
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return None
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if len(first) <= 240:
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return first
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return None
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def load_seed_rows() -> dict[str, dict]:
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data = json.loads(PROBLEM_SEED_PATH.read_text())
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return {
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row["question_number"]: row
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for row in data
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if row["source_exam_key"] == EXAM_KEY
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}
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def main() -> None:
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sb = get_supabase()
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paper = (
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sb.table("papers")
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.select("id")
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.eq("source_exam_key", EXAM_KEY)
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.execute()
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.data[0]
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)
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paper_id = paper["id"]
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current_rows = (
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sb.table("paper_questions")
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.select("*")
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.eq("paper_id", paper_id)
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.order("display_order")
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.execute()
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.data
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)
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existing_by_number = {row["question_number"]: row for row in current_rows}
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parent_rows = load_seed_rows()
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tf_answers = extract_true_false_answers(parent_rows["1"]["raw_answer_text"] or "")
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inserts = []
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for display_order, child in enumerate(CHILDREN, start=1):
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parent = parent_rows[child.top_level_number]
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existing = existing_by_number.get(child.question_number, {})
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question_text = extract_segment(parent["question_text"] or "", child.path)
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raw_answer_text = extract_segment(parent["raw_answer_text"] or "", child.path)
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correct_option = None
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correct_answer = None
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options = None
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if child.question_type == "true_false":
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marker = child.path[0]
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correct_option = tf_answers.get(marker)
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options = TRUE_FALSE_OPTIONS
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elif child.question_type == "fill_blank":
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correct_answer = derive_correct_answer(raw_answer_text)
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inserts.append(
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{
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"paper_id": paper_id,
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"question_number": child.question_number,
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"parent_question": child.parent_question,
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"display_order": display_order,
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"question_type": child.question_type,
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"question_format": child.question_format,
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"question_text": question_text,
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"score": child.score,
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"page_number": child.page_number,
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"page_y_ratio": existing.get("page_y_ratio"),
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"options": options,
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"correct_option": correct_option,
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"correct_answer": correct_answer,
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"raw_answer_text": raw_answer_text,
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"topics": existing.get("topics") or parent.get("topics"),
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"topic_primary": existing.get("topic_primary") or parent.get("topic_primary"),
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"analytics_topic": existing.get("analytics_topic") or parent.get("analytics_topic"),
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"topic_tags": existing.get("topic_tags") or parent.get("topic_tags"),
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"skill_tags": existing.get("skill_tags") or parent.get("skill_tags"),
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"difficulty": existing.get("difficulty") or parent.get("difficulty"),
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"knowledge_reminder": existing.get("knowledge_reminder", ""),
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"ai_hint": existing.get("ai_hint", ""),
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"solution": existing.get("solution", ""),
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}
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)
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sb.table("paper_questions").delete().eq("paper_id", paper_id).execute()
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sb.table("paper_questions").insert(inserts).execute()
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sb.table("papers").update({"question_count": len(inserts), "status": "processing"}).eq("id", paper_id).execute()
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print(f"Inserted {len(inserts)} rows for {EXAM_KEY}.")
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if __name__ == "__main__":
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main()
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