Teachers need to follow up with students who miss assignments. In this challenge, you'll compare a list of all students with a list of submissions to find missing assignments.


import unittest
import user_code
import ast
import re   
import importlib
import csv
import unittest
import importlib
import io
from contextlib import redirect_stdout

class TestTask(unittest.TestCase):
    def test_prints_missing_students(self):
        import user_code
        importlib.reload(user_code)
        f = io.StringIO()
        all_students = ["Alice", "Bob", "Charlie", "Diana"]
        submitted_students = ["Alice", "Diana"]
        with redirect_stdout(f):
            user_code.print_missing_students(all_students, submitted_students)
        output = normalize_text(f.getvalue())
        expected = normalize_text(str(["Bob", "Charlie"]))
        _dynamic_test(
            self,
            expected in output,
            "Function prints correct missing students list",
            f"Expected: {expected}, got: {output}"
        )

    def test_prints_empty_when_all_submitted(self):
        import user_code
        importlib.reload(user_code)
        f = io.StringIO()
        all_students = ["Alice", "Bob"]
        submitted_students = ["Alice", "Bob"]
        with redirect_stdout(f):
            user_code.print_missing_students(all_students, submitted_students)
        output = normalize_text(f.getvalue())
        expected = normalize_text(str([]))
        _dynamic_test(
            self,
            expected in output,
            "Function prints empty list when all students have submitted",
            f"Expected: {expected}, got: {output}"
        )

    def test_prints_all_when_none_submitted(self):
        import user_code
        importlib.reload(user_code)
        f = io.StringIO()
        all_students = ["Alice", "Bob"]
        submitted_students = []
        with redirect_stdout(f):
            user_code.print_missing_students(all_students, submitted_students)
        output = normalize_text(f.getvalue())
        expected = normalize_text(str(["Alice", "Bob"]))
        _dynamic_test(
            self,
            expected in output,
            "Function prints all students when none have submitted",
            f"Expected: {expected}, got: {output}"
        )

def _dynamic_test(test_case, condition, success_message, failure_message):
    if condition:
        test_case._testMethodName = success_message
        test_case.assertTrue(True, success_message)
    else:
        test_case._testMethodName = failure_message
        test_case.fail(failure_message)

def normalize_text(text):
    text = text.lower()
    text = re.sub(r"\\s{2,}", " ", text)
    text = re.sub(r"\\s*([,:?])\\s*", r"\\1 ", text)
    return text.strip()

def change_var(code: str, var_name: str, value: str) -> str:
    tree = ast.parse(code)
    lines = code.splitlines()
    changed = False
    # Collect all assignment nodes to modify
    assign_nodes = [
        (i, node)
        for i, node in enumerate(tree.body)
        if isinstance(node, ast.Assign)
        and any(isinstance(target, ast.Name) and target.id == var_name for target in node.targets)
    ]

    # If nothing to change, return unmodified code
    if not assign_nodes:
        return code

    # Perform replacements for all matching assignments (from last to first to not break line offsets)
    for i, node in reversed(assign_nodes):
        start_line = node.lineno - 1
        line = lines[start_line]
        indent = ' ' * (len(line) - len(line.lstrip()))
        lines[start_line] = f"{indent}{var_name} = {value}"
        next_line = len(lines)
        for next_node in tree.body[i+1:]:
            if hasattr(next_node, 'lineno'):
                next_line = next_node.lineno - 1
                break
        if next_line > start_line + 1:
            lines[start_line+1:next_line] = []
        changed = True

    return '\\n'.join(lines) if changed else code

if __name__ == "__main__":
    unittest.main()


test_main.py

A beginner-friendly Python course designed specifically for teachers. Learn how to use Python to organize grades, analyze student performance, and automate classroom tasks with engaging, real-world examples.

Learn the basics of Python programming with a focus on classroom and grade organization. This section introduces Python syntax, variables, and simple data structures through relatable educational scenarios.

Dive deeper into Python by learning how to organize, analyze, and visualize student grades. This section covers dictionaries, conditional logic, and basic data analysis techniques tailored for teachers.

Explore how Python can automate common classroom tasks such as attendance tracking, assignment management, and generating reports. This section introduces file operations and more advanced automation techniques.

Challenge: Track Missing Assignments

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