Clear and concise reporting is a cornerstone of effective QA work. Well-structured test execution reports allow QA teams to quickly identify issues, understand the quality of a release, and communicate results to stakeholders. As a QA engineer, you often need to process lists of test results and turn them into readable summaries that highlight both individual outcomes and overall trends. This challenge is designed to reinforce your ability to automate the creation of such reports using **Python**.


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 setUp(self):
        self.user_code = importlib.import_module("user_code")

    def test_output_contains_all_test_details(self):
        importlib.reload(self.user_code)
        test_cases = [
            {'id': 'TC100', 'status': 'Pass', 'description': 'Test login'},
            {'id': 'TC101', 'status': 'Fail', 'description': 'Test logout'}
        ]
        f = io.StringIO()
        with redirect_stdout(f):
            self.user_code.generate_test_report(test_cases)
        output = normalize_text(f.getvalue())
        _dynamic_test(
            self,
            'test id: tc100' in output and 'description: test login' in output and 'status: pass' in output,
            "Output contains all details for TC100",
            f"Output missing details for TC100: {output}"
        )
        _dynamic_test(
            self,
            'test id: tc101' in output and 'description: test logout' in output and 'status: fail' in output,
            "Output contains all details for TC101",
            f"Output missing details for TC101: {output}"
        )

    def test_summary_counts_passed_and_failed(self):
        importlib.reload(self.user_code)
        test_cases = [
            {'id': 'TC200', 'status': 'Pass', 'description': 'First'},
            {'id': 'TC201', 'status': 'Fail', 'description': 'Second'},
            {'id': 'TC202', 'status': 'PASS', 'description': 'Third'},
            {'id': 'TC203', 'status': 'fail', 'description': 'Fourth'}
        ]
        f = io.StringIO()
        with redirect_stdout(f):
            self.user_code.generate_test_report(test_cases)
        output = normalize_text(f.getvalue())
        _dynamic_test(
            self,
            'total passed: 2' in output and 'total failed: 2' in output,
            "Summary counts passes and fails correctly (2 each)",
            f"Summary incorrect: {output}"
        )

    def test_status_case_insensitive(self):
        importlib.reload(self.user_code)
        test_cases = [
            {'id': 'TC300', 'status': 'PASS', 'description': 'Upper'},
            {'id': 'TC301', 'status': 'fail', 'description': 'Lower'}
        ]
        f = io.StringIO()
        with redirect_stdout(f):
            self.user_code.generate_test_report(test_cases)
        output = normalize_text(f.getvalue())
        _dynamic_test(
            self,
            'status: pass' in output and 'status: fail' in output,
            "Function handles status case-insensitively",
            f"Status case sensitivity error in output: {output}"
        )

    def test_zero_test_cases(self):
        importlib.reload(self.user_code)
        test_cases = []
        f = io.StringIO()
        with redirect_stdout(f):
            self.user_code.generate_test_report(test_cases)
        output = normalize_text(f.getvalue())
        _dynamic_test(
            self,
            'total passed: 0' in output and 'total failed: 0' in output,
            "Handles zero test cases correctly (summary 0, 0)",
            f"Output for zero test cases incorrect: {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 practical course designed for QA Engineers to leverage Python for automating, validating, and analyzing software quality. Learn how to use Python to write robust test scripts, analyze test data, and automate repetitive QA tasks, all with real-world scenarios and hands-on challenges.

Learn how Python can automate common QA tasks, from basic scripting to automating test case execution and validation.

Explore how Python can help QA engineers analyze and visualize test data to identify trends, issues, and opportunities for improvement.

Delve into advanced Python techniques for QA, including test parameterization, random data generation, and integrating with external APIs for test data.

Challenge: Generate a Test Execution Report

Ratkaisu