Teachers often need to summarize class performance. In this challenge, you'll calculate the average, highest, and lowest grades from a dictionary of student grades.


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_average_grade(self):
        import user_code
        importlib.reload(user_code)
        f = io.StringIO()
        grades = {"Alice": 88, "Bob": 92, "Charlie": 76, "Diana": 85}
        with redirect_stdout(f):
            user_code.print_grade_statistics(grades)
        output = normalize_text(f.getvalue())
        _dynamic_test(
            self,
            "average grade: 85.25" in output,
            "Correct average grade printed for sample dictionary.",
            f"Expected average grade 85.25 in output, got: {output}",
        )

    def test_highest_grade(self):
        import user_code
        importlib.reload(user_code)
        f = io.StringIO()
        grades = {"Alice": 88, "Bob": 92, "Charlie": 76, "Diana": 85}
        with redirect_stdout(f):
            user_code.print_grade_statistics(grades)
        output = normalize_text(f.getvalue())
        _dynamic_test(
            self,
            "highest grade: 92" in output,
            "Correct highest grade printed for sample dictionary.",
            f"Expected highest grade 92 in output, got: {output}",
        )

    def test_lowest_grade(self):
        import user_code
        importlib.reload(user_code)
        f = io.StringIO()
        grades = {"Alice": 88, "Bob": 92, "Charlie": 76, "Diana": 85}
        with redirect_stdout(f):
            user_code.print_grade_statistics(grades)
        output = normalize_text(f.getvalue())
        _dynamic_test(
            self,
            "lowest grade: 76" in output,
            "Correct lowest grade printed for sample dictionary.",
            f"Expected lowest grade 76 in output, got: {output}",
        )

    def test_single_student(self):
        import user_code
        importlib.reload(user_code)
        f = io.StringIO()
        grades = {"Eve": 100}
        with redirect_stdout(f):
            user_code.print_grade_statistics(grades)
        output = normalize_text(f.getvalue())
        _dynamic_test(
            self,
            "average grade: 100.0" in output and "highest grade: 100" in output and "lowest grade: 100" in output,
            "Correct statistics printed for single-student dictionary.",
            f"Expected all grades to be 100 for single student, got: {output}",
        )

    def test_all_same_grades(self):
        import user_code
        importlib.reload(user_code)
        f = io.StringIO()
        grades = {"A": 77, "B": 77, "C": 77}
        with redirect_stdout(f):
            user_code.print_grade_statistics(grades)
        output = normalize_text(f.getvalue())
        _dynamic_test(
            self,
            "average grade: 77.0" in output and "highest grade: 77" in output and "lowest grade: 77" in output,
            "Correct statistics printed when all grades are the same.",
            f"Expected all statistics to be 77, 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: Calculate Grade Statistics

Ratkaisu

Challenge: Calculate Grade Statistics

Ratkaisu