
import unittest
import user_code
import ast
import re   
import importlib
import csv
import unittest
import importlib

class TestTask(unittest.TestCase):
    def test_merge_all_keys(self):
        import user_code
        importlib.reload(user_code)
        d1 = {'a': 1, 'b': 2}
        d2 = {'b': 3, 'c': 4}
        result = user_code.merge_dicts(d1, d2)
        expected = {'a': 1, 'b': 3, 'c': 4}
        _dynamic_test(
            self,
            isinstance(result, dict) and result == expected,
            "Merged dictionary contains all keys and correct values when keys overlap.",
            f"Expected {expected}, got {result}"
        )

    def test_merge_with_empty_first(self):
        import user_code
        importlib.reload(user_code)
        d1 = {}
        d2 = {'x': 10}
        result = user_code.merge_dicts(d1, d2)
        expected = {'x': 10}
        _dynamic_test(
            self,
            isinstance(result, dict) and result == expected,
            "Merging with an empty first dictionary works.",
            f"Expected {expected}, got {result}"
        )

    def test_merge_with_empty_second(self):
        import user_code
        importlib.reload(user_code)
        d1 = {'foo': 9}
        d2 = {}
        result = user_code.merge_dicts(d1, d2)
        expected = {'foo': 9}
        _dynamic_test(
            self,
            isinstance(result, dict) and result == expected,
            "Merging with an empty second dictionary works.",
            f"Expected {expected}, got {result}"
        )

    def test_no_modification_of_inputs(self):
        import user_code
        importlib.reload(user_code)
        d1 = {'a': 1, 'b': 2}
        d2 = {'b': 3, 'c': 4}
        d1_copy = d1.copy()
        d2_copy = d2.copy()
        result = user_code.merge_dicts(d1, d2)
        _dynamic_test(
            self,
            d1 == d1_copy and d2 == d2_copy,
            "Input dictionaries are not modified after merge.",
            f"Input dictionaries were modified. d1: {d1}, d2: {d2}"
        )

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

Bliv fortrolig med pakning/udpaking, fleksible funktionsargumenter, højere-ordens funktioner, lambdaer, variabelscope, closures, iteratorer og dekoratører. Udviklet til kursister, der har gennemført et introduktionskursus i Python og ønsker at skrive mere effektiv, udtryksfuld og kraftfuld kode.

Udforsk kunsten at pakke og udpakke lister, tupler og ordbøger for at skrive mere udtryksfuld og effektiv Python-kode.

Dyk ned i verdenen af højereordensfunktioner, overførsel af funktioner som argumenter og skrivning af korte anonyme funktioner med lambda.

Opdag hemmelighederne bag variabelscope, og lær hvordan indlejrede funktioner og closures muliggør effektiv indkapsling.

Dyk ned i Pythons iterationsprotokol, brugerdefinerede iteratorer og generatorfunktioner for effektiv databehandling.

Challenge: Sammensmeltning af Ordbøger med Udpakning

Løsning