
import unittest
import user_code
import ast
import re   
import importlib
import csv
import io
import sys
import importlib
import asyncio
import time
from contextlib import redirect_stdout
import unittest

class TestTask(unittest.TestCase):
    def test_boil_water_output_and_timing(self):
        import user_code
        
        # Patch asyncio.sleep to actually wait and measure time
        # We'll reload the module to re-run the coroutine
        # We'll capture stdout to check the print output
        code = ""
        with open("user_code.py", "r") as f:
            code = f.read()
        ns = {}
        buffer = io.StringIO()
        start = time.time()
        with redirect_stdout(buffer):
            exec(code, ns)
        end = time.time()
        output = normalize_text(buffer.getvalue())
        expected_first = normalize_text("Kettle is on...")
        expected_second = normalize_text("Ding! Water is boiled.")
        _dynamic_test(
            self,
            expected_first in output,
            'Output includes "Kettle is on..."',
            f'Expected "Kettle is on..." in output, got: {output}'
        )
        _dynamic_test(
            self,
            expected_second in output,
            'Output includes "Ding! Water is boiled."',
            f'Expected "Ding! Water is boiled." in output, got: {output}'
        )
        # Check time between prints is at least 1.8 seconds (allowing for minor timing errors)
        _dynamic_test(
            self,
            (end - start) >= 2.8,
            'Coroutine waits at least 3 seconds before printing second message',
            f'Expected at least 3 seconds delay, got: {end - start} seconds'
        )

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

Sie werden praktische Fähigkeiten in Pythons Modulen und Importen für effizientes Code-Management erwerben. Beherrschen Sie fortgeschrittene Fehlerbehandlungstechniken für zuverlässigere Anwendungen, automatisieren Sie Dateioperationen mit Dateiverwaltung und lernen Sie robuste Teststrategien mit Pytest und Unittest, um die Integrität Ihres Codes sicherzustellen.

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Explore advanced techniques for file operations and resource management using context managers.

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Challenge: Der Digitale Wasserkocher

Lösung