KorigamiK · February 28, 2025 12:59
diff --git a/add_answers.py b/add_answers.py
 import re
 import csv
 from pathlib import Path

 def parse_questions(content):
    questions = []

    # Look for question patterns - Q.1, Q.2, etc. and capture the content until the next question
    question_pattern = re.compile(r'(Q\.\s*\d+(?:\s*–\s*Q\.\s*\d+)?\s+(?:Carry|carry)\s+(?:ONE|TWO|one|two)\s+marks?(?:\s+Each)?|Q\.\s*\d+(?:\s*–\s*Q\.\s*\d+)?)')

    # Split content by question headings
    parts = question_pattern.split(content)

    # Skip the first part before any questions
    parts = parts[1:]

    # Combine heading with content
    for i in range(0, len(parts), 2):
        if i+1 < len(parts):
            question_number = parts[i].strip()
            question_content = parts[i+1].strip()
            questions.append((question_number, question_content))

    return questions

 def extract_options(question_content):
    options = []

    # Look for (A), (B), (C), (D) patterns
    option_pattern = re.compile(r'\(([A-D])\)(.*?)(?=\([A-D]\)|$)', re.DOTALL)
    matches = option_pattern.findall(question_content)

    for option_letter, option_text in matches:
        options.append((option_letter, option_text.strip()))

    return options

 def load_answer_key(csv_path):
    answer_key = {}
    with open(csv_path, 'r') as f:
        reader = csv.DictReader(f)
        for row in reader:
            q_num = row['Q. No.']
            key = row['Key/Range']
            q_type = row['Q. Type']

            # Handle MSQ type answers (multiple select questions)
            if q_type == 'MSQ':
                # The format seems to be options separated by '+ADs-'
                options = key.split('+ADs-')
                answer_key[q_num] = options
            # Handle NAT type answers (numerical answer type)
            elif q_type == 'NAT':
                # The format seems to be a range like "0.25 to 0.25"
                range_parts = key.split(' to ')
                if len(range_parts) == 2:
                    answer_key[q_num] = range_parts
                else:
                    answer_key[q_num] = [key]
            # Handle MCQ type answers (multiple choice questions)
            else:
                answer_key[q_num] = [key]

    return answer_key

 def create_markdown(questions, answer_key):
    markdown = "# GATE 2025 Data Science & Artificial Intelligence (DA) Question Paper\n\n"

    current_section = None
    mark_type = None

    for question_number, question_content in questions:
        # Extract section and mark information
        if "General Aptitude" in question_content and "General Aptitude" != current_section:
            current_section = "General Aptitude"
            markdown += f"## {current_section}\n\n"
        elif "Data Science & Artificial Intelligence" in question_content and "Data Science & Artificial Intelligence" != current_section:
            current_section = "Data Science & Artificial Intelligence"
            markdown += f"## {current_section}\n\n"

        # Check if we have a new marks section
        if "ONE mark" in question_number or "one mark" in question_number:
            mark_type = "1 Mark Questions"
            markdown += f"### {mark_type}\n\n"
        elif "TWO marks" in question_number or "two marks" in question_number:
            mark_type = "2 Marks Questions"
            markdown += f"### {mark_type}\n\n"

        # Extract individual question number
        if "–" in question_number:
            # Range of questions
            range_match = re.search(r'Q\.\s*(\d+)\s*–\s*Q\.\s*(\d+)', question_number)
            if range_match:
                start, end = map(int, range_match.groups())
                markdown += f"#### Questions {start} to {end}\n\n"
                continue
        else:
            # Single question
            q_num_match = re.search(r'Q\.\s*(\d+)', question_number)
            if q_num_match:
                q_num = q_num_match.group(1)

                # Extract the actual question text
                question_text = re.split(r'\([A-D]\)', question_content)[0].strip()

                markdown += f"#### Question {q_num}\n\n{question_text}\n\n"

                # Extract options if available
                options = extract_options(question_content)
                if options:
                    markdown += "**Options:**\n\n"
                    for option_letter, option_text in options:
                        markdown += f"- ({option_letter}) {option_text}\n"
                    markdown += "\n"

                    # Add answer from answer key
                    if q_num in answer_key:
                        answers = answer_key[q_num]

                        # Handle different question types
                        if len(answers) == 1 and ' to ' not in answers[0]:  # MCQ
                            option_letter = answers[0]
                            # Find the matching option text
                            option_text = ""
                            for letter, text in options:
                                if letter == option_letter:
                                    option_text = text
                                    break
                            markdown += f"**Answer:** ({option_letter}) {option_text}\n\n"
                        elif len(answers) > 1:  # MSQ
                            markdown += "**Answer:** Multiple correct options: "
                            answer_texts = []
                            for letter in answers:
                                for opt_letter, opt_text in options:
                                    if opt_letter == letter:
                                        answer_texts.append(f"({letter}) {opt_text}")
                                        break
                            markdown += ", ".join(answer_texts) + "\n\n"
                        else:  # NAT with range
                            markdown += f"**Answer:** Numerical value in range {answers[0]}\n\n"
                    else:
                        markdown += "**Answer:** Not provided in answer key\n\n"
                else:
                    # For numerical answer type questions
                    if q_num in answer_key:
                        answers = answer_key[q_num]
                        if len(answers) == 2:  # NAT with range
                            markdown += f"**Answer:** Numerical value in range {answers[0]} to {answers[1]}\n\n"
                        else:
                            markdown += f"**Answer:** {answers[0]}\n\n"
                    else:
                        markdown += "**Answer:** Not provided in answer key\n\n"

    return markdown

 def main():
    input_path = Path("questions.md")
    answer_key_path = Path("answerkey.csv")
    output_path = Path("gate_questions_with_answers.md")

    content = input_path.read_text()

    # Remove the leading line that says "Here is the converted document in markdown format:"
    content = re.sub(r'^Here is the converted document in markdown format:', '', content, flags=re.MULTILINE).strip()

    questions = parse_questions(content)
    answer_key = load_answer_key(answer_key_path)
    markdown = create_markdown(questions, answer_key)

    output_path.write_text(markdown)
    print(f"Parsed questions with answers saved to {output_path}")

 if __name__ == "__main__":
    main()
diff --git a/calculate.py b/calculate.py
 import json

 with open("responses.json", "r") as f:
    responses = json.load(f)
 print(f'found {len(responses)} responses')

 with open("score.md", "r") as f:
    lines = f.readlines()
    score = 0
    index = 0
    correct_answers = 0
    incorrect_answers = 0
    total_questions = 0
    mcq_correct = 0
    mcq_incorrect = 0
    msq_correct = 0
    msq_incorrect = 0
    nat_correct = 0
    nat_incorrect = 0

    for line in lines:
        if line.strip() == "" or line.startswith("#"): continue
        total_questions += 1
        is_correct = int(line.split()[1].strip())
        question_type = responses[index]["type"]

        if is_correct > 0:
            correct_answers += 1
            if question_type == "MCQ":
                score += 1
                mcq_correct += 1
            elif question_type == "MSQ":
                score += 2
                msq_correct += 1
            elif question_type == "NAT":
                score += 2
                nat_correct += 1
        else:
            incorrect_answers += 1
            if question_type == "MCQ":
                score += -1/3
                mcq_incorrect += 1
            elif question_type == "MSQ":
                score += 0
                msq_incorrect += 1
            elif question_type == "NAT":
                score += 0
                nat_incorrect += 1

        index += 1

    accuracy = (correct_answers / total_questions) * 100 if total_questions > 0 else 0

    print(f"Total score: {score}")
    print(f"Total questions: {total_questions}")
    print(f"Correct answers: {correct_answers} ({accuracy:.2f}%)")
    print(f"Incorrect answers: {incorrect_answers}")
    print("\nBreakdown by question type:")
    print(f"MCQ: {mcq_correct} correct, {mcq_incorrect} incorrect")
    print(f"MSQ: {msq_correct} correct, {msq_incorrect} incorrect")
    print(f"NAT: {nat_correct} correct, {nat_incorrect} incorrect")
diff --git a/questions.md b/questions.md
diff --git a/questions_with_answers.md b/questions_with_answers.md
diff --git a/responses.js b/responses.js
 $$("table.menu-tbl").map((t) => {
  const x = {
    type: t.rows[0].cells[1].innerText,
    id: t.rows[1].cells[1].innerText,
    status: t.rows[2].cells[1].innerText,
    option: t.rows[3]?.cells[1].innerText,
  };

  if (x.option) {
    const selected = x.option.split(",").map((option) => option.trim());

    // Find the corresponding question table
    const questionTable = t.parentElement.firstChild;

    if (questionTable) {
      // Get all option rows (starting from the third row, index 2)
      const optionRows = Array.from(questionTable.rows).slice(2);

      // Process each option row
      optionRows.forEach((row, _) => {
        // Get the option letter (A, B, C, D, etc.)
        const optionCell = row.cells[1];
        if (optionCell) {
          const optionText = optionCell.textContent.trim();
          const optionLetter = optionText.charAt(0); // Extract first character (A, B, C, D)

          // Check if this option is selected
          if (selected.includes(optionLetter)) {
            // Highlight the selected option
            optionCell.style.backgroundColor = "#ffffcc"; // Light yellow highlight
            optionCell.style.fontWeight = "bold";
            optionCell.style.border = "2px solid green";

            // Also add a checkmark or indicator
            const marker = document.createElement("span");
            marker.innerHTML = " ✓ ";
            marker.style.color = "green";
            marker.style.fontWeight = "bold";
            optionCell.insertBefore(marker, optionCell.firstChild);
          }
        }
      });
    }
  }
 });
	import re
	import csv
	from pathlib import Path

	def parse_questions(content):
	questions = []

	# Look for question patterns - Q.1, Q.2, etc. and capture the content until the next question
	question_pattern = re.compile(r'(Q\.\s\d+(?:\s–\sQ\.\s\d+)?\s+(?:Carry\|carry)\s+(?:ONE\|TWO\|one\|two)\s+marks?(?:\s+Each)?\|Q\.\s\d+(?:\s–\sQ\.\s\d+)?)')

	# Split content by question headings
	parts = question_pattern.split(content)

	# Skip the first part before any questions
	parts = parts[1:]

	# Combine heading with content
	for i in range(0, len(parts), 2):
	if i+1 < len(parts):
	question_number = parts[i].strip()
	question_content = parts[i+1].strip()
	questions.append((question_number, question_content))

	return questions

	def extract_options(question_content):
	options = []

	# Look for (A), (B), (C), (D) patterns
	option_pattern = re.compile(r'\(([A-D])\)(.*?)(?=\([A-D]\)\|$)', re.DOTALL)
	matches = option_pattern.findall(question_content)

	for option_letter, option_text in matches:
	options.append((option_letter, option_text.strip()))

	return options

	def load_answer_key(csv_path):
	answer_key = {}
	with open(csv_path, 'r') as f:
	reader = csv.DictReader(f)
	for row in reader:
	q_num = row['Q. No.']
	key = row['Key/Range']
	q_type = row['Q. Type']

	# Handle MSQ type answers (multiple select questions)
	if q_type == 'MSQ':
	# The format seems to be options separated by '+ADs-'
	options = key.split('+ADs-')
	answer_key[q_num] = options
	# Handle NAT type answers (numerical answer type)
	elif q_type == 'NAT':
	# The format seems to be a range like "0.25 to 0.25"
	range_parts = key.split(' to ')
	if len(range_parts) == 2:
	answer_key[q_num] = range_parts
	else:
	answer_key[q_num] = [key]
	# Handle MCQ type answers (multiple choice questions)
	else:
	answer_key[q_num] = [key]

	return answer_key

	def create_markdown(questions, answer_key):
	markdown = "# GATE 2025 Data Science & Artificial Intelligence (DA) Question Paper\n\n"

	current_section = None
	mark_type = None

	for question_number, question_content in questions:
	# Extract section and mark information
	if "General Aptitude" in question_content and "General Aptitude" != current_section:
	current_section = "General Aptitude"
	markdown += f"## {current_section}\n\n"
	elif "Data Science & Artificial Intelligence" in question_content and "Data Science & Artificial Intelligence" != current_section:
	current_section = "Data Science & Artificial Intelligence"
	markdown += f"## {current_section}\n\n"

	# Check if we have a new marks section
	if "ONE mark" in question_number or "one mark" in question_number:
	mark_type = "1 Mark Questions"
	markdown += f"### {mark_type}\n\n"
	elif "TWO marks" in question_number or "two marks" in question_number:
	mark_type = "2 Marks Questions"
	markdown += f"### {mark_type}\n\n"

	# Extract individual question number
	if "–" in question_number:
	# Range of questions
	range_match = re.search(r'Q\.\s(\d+)\s–\sQ\.\s(\d+)', question_number)
	if range_match:
	start, end = map(int, range_match.groups())
	markdown += f"#### Questions {start} to {end}\n\n"
	continue
	else:
	# Single question
	q_num_match = re.search(r'Q\.\s*(\d+)', question_number)
	if q_num_match:
	q_num = q_num_match.group(1)

	# Extract the actual question text
	question_text = re.split(r'\([A-D]\)', question_content)[0].strip()

	markdown += f"#### Question {q_num}\n\n{question_text}\n\n"

	# Extract options if available
	options = extract_options(question_content)
	if options:
	markdown += "Options:\n\n"
	for option_letter, option_text in options:
	markdown += f"- ({option_letter}) {option_text}\n"
	markdown += "\n"

	# Add answer from answer key
	if q_num in answer_key:
	answers = answer_key[q_num]

	# Handle different question types
	if len(answers) == 1 and ' to ' not in answers[0]: # MCQ
	option_letter = answers[0]
	# Find the matching option text
	option_text = ""
	for letter, text in options:
	if letter == option_letter:
	option_text = text
	break
	markdown += f"Answer: ({option_letter}) {option_text}\n\n"
	elif len(answers) > 1: # MSQ
	markdown += "Answer: Multiple correct options: "
	answer_texts = []
	for letter in answers:
	for opt_letter, opt_text in options:
	if opt_letter == letter:
	answer_texts.append(f"({letter}) {opt_text}")
	break
	markdown += ", ".join(answer_texts) + "\n\n"
	else: # NAT with range
	markdown += f"Answer: Numerical value in range {answers[0]}\n\n"
	else:
	markdown += "Answer: Not provided in answer key\n\n"
	else:
	# For numerical answer type questions
	if q_num in answer_key:
	answers = answer_key[q_num]
	if len(answers) == 2: # NAT with range
	markdown += f"Answer: Numerical value in range {answers[0]} to {answers[1]}\n\n"
	else:
	markdown += f"Answer: {answers[0]}\n\n"
	else:
	markdown += "Answer: Not provided in answer key\n\n"

	return markdown

	def main():
	input_path = Path("questions.md")
	answer_key_path = Path("answerkey.csv")
	output_path = Path("gate_questions_with_answers.md")

	content = input_path.read_text()

	# Remove the leading line that says "Here is the converted document in markdown format:"
	content = re.sub(r'^Here is the converted document in markdown format:', '', content, flags=re.MULTILINE).strip()

	questions = parse_questions(content)
	answer_key = load_answer_key(answer_key_path)
	markdown = create_markdown(questions, answer_key)

	output_path.write_text(markdown)
	print(f"Parsed questions with answers saved to {output_path}")

	if __name__ == "__main__":
	main()
	import json

	with open("responses.json", "r") as f:
	responses = json.load(f)
	print(f'found {len(responses)} responses')

	with open("score.md", "r") as f:
	lines = f.readlines()
	score = 0
	index = 0
	correct_answers = 0
	incorrect_answers = 0
	total_questions = 0
	mcq_correct = 0
	mcq_incorrect = 0
	msq_correct = 0
	msq_incorrect = 0
	nat_correct = 0
	nat_incorrect = 0

	for line in lines:
	if line.strip() == "" or line.startswith("#"): continue
	total_questions += 1
	is_correct = int(line.split()[1].strip())
	question_type = responses[index]["type"]

	if is_correct > 0:
	correct_answers += 1
	if question_type == "MCQ":
	score += 1
	mcq_correct += 1
	elif question_type == "MSQ":
	score += 2
	msq_correct += 1
	elif question_type == "NAT":
	score += 2
	nat_correct += 1
	else:
	incorrect_answers += 1
	if question_type == "MCQ":
	score += -1/3
	mcq_incorrect += 1
	elif question_type == "MSQ":
	score += 0
	msq_incorrect += 1
	elif question_type == "NAT":
	score += 0
	nat_incorrect += 1

	index += 1

	accuracy = (correct_answers / total_questions) * 100 if total_questions > 0 else 0

	print(f"Total score: {score}")
	print(f"Total questions: {total_questions}")
	print(f"Correct answers: {correct_answers} ({accuracy:.2f}%)")
	print(f"Incorrect answers: {incorrect_answers}")
	print("\nBreakdown by question type:")
	print(f"MCQ: {mcq_correct} correct, {mcq_incorrect} incorrect")
	print(f"MSQ: {msq_correct} correct, {msq_incorrect} incorrect")
	print(f"NAT: {nat_correct} correct, {nat_incorrect} incorrect")
	$$("table.menu-tbl").map((t) => {
	const x = {
	type: t.rows[0].cells[1].innerText,
	id: t.rows[1].cells[1].innerText,
	status: t.rows[2].cells[1].innerText,
	option: t.rows[3]?.cells[1].innerText,
	};

	if (x.option) {
	const selected = x.option.split(",").map((option) => option.trim());

	// Find the corresponding question table
	const questionTable = t.parentElement.firstChild;

	if (questionTable) {
	// Get all option rows (starting from the third row, index 2)
	const optionRows = Array.from(questionTable.rows).slice(2);

	// Process each option row
	optionRows.forEach((row, _) => {
	// Get the option letter (A, B, C, D, etc.)
	const optionCell = row.cells[1];
	if (optionCell) {
	const optionText = optionCell.textContent.trim();
	const optionLetter = optionText.charAt(0); // Extract first character (A, B, C, D)

	// Check if this option is selected
	if (selected.includes(optionLetter)) {
	// Highlight the selected option
	optionCell.style.backgroundColor = "#ffffcc"; // Light yellow highlight
	optionCell.style.fontWeight = "bold";
	optionCell.style.border = "2px solid green";

	// Also add a checkmark or indicator
	const marker = document.createElement("span");
	marker.innerHTML = " ✓ ";
	marker.style.color = "green";
	marker.style.fontWeight = "bold";
	optionCell.insertBefore(marker, optionCell.firstChild);
	}
	}
	});
	}
	}
	});