Let's put together everything you've learned in this section and apply it.

In this task, your objective is to calculate the **total revenue for each product** in a grocery store based on their prices and quantities sold. 

After calculating the revenues, you will **sort the products alphabetically** and **display the results** in a formatted output.

import unittest
import importlib
import io
import re
import inspect
from contextlib import redirect_stdout
import user_code


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 strip_comments_from_source(module):
    try:
        source = inspect.getsource(module)
        lines = source.split('\\n')
        cleaned = []
        for line in lines:
            stripped = line.rstrip()
            if stripped.startswith('#'):
                continue
            if '#' in line:
                line = line.split('#')[0]
            if line.strip():
                cleaned.append(line)
        return '\\n'.join(cleaned)
    except Exception:
        return ""


class TestRevenueFunctions(unittest.TestCase):

    def normalize_text(self, text):
        text = text.lower()
        text = re.sub(r'\s+', ' ', text)
        text = re.sub(r'\s*([,:?\[\]$])\s*', r'\1', text)
        return text.strip()

    def test_calculate_revenue_works(self):
        importlib.reload(user_code)
        prices = [1.0, 2.0, 3.0]
        quantities = [10, 20, 30]
        expected = [10.0, 40.0, 90.0]
        result = user_code.calculate_revenue(prices, quantities)
        _dynamic_test(
            self,
            result == expected,
            "calculate_revenue returns correct result for sample input",
            f"Expected {expected}, got {result}"
        )

    def test_function_names_exist(self):
        importlib.reload(user_code)
        _dynamic_test(self, hasattr(user_code, "calculate_revenue"), "Function 'calculate_revenue' exists", "Function 'calculate_revenue' not found")
        _dynamic_test(self, hasattr(user_code, "formatted_output"), "Function 'formatted_output' exists", "Function 'formatted_output' not found")

    def test_revenue_combined_and_sorted(self):
        importlib.reload(user_code)
        expected_sorted = [
            ("Apples", 240.0),
            ("Bananas", 100.0),
            ("Bread", 75.0),
            ("Oranges", 250.0)
        ]
        sorted_output = sorted(user_code.revenue_per_product)
        _dynamic_test(
            self,
            sorted_output == expected_sorted,
            "Revenue per product is correctly zipped and sorted",
            f"Expected sorted result: {expected_sorted}, got {sorted_output}"
        )

    def test_output_format_correct(self):
        f = io.StringIO()
        with redirect_stdout(f):
            importlib.reload(user_code)
        output = self.normalize_text(f.getvalue())

        expected_lines = [
            "apples has total revenue of $240.0",
            "bananas has total revenue of $100.0",
            "bread has total revenue of $75.0",
            "oranges has total revenue of $250.0"
        ]

        for line in expected_lines:
            expected = self.normalize_text(line)
            _dynamic_test(
                self,
                expected in output,
                f"Output includes: {line}",
                f"Expected output: '{line}' not found."
            )

    def test_zip_and_sorted_used(self):
        source = strip_comments_from_source(user_code)
        uses_zip = re.search(r'zip\s*\(', source)
        uses_sorted = re.search(r'sorted\s*\(', source)
        _dynamic_test(
            self,
            uses_zip and uses_sorted,
            "Code uses zip() and sorted() to combine and sort data",
            "Expected zip() and sorted() not found in the code"
        )


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

test_main.py

Gain a solid foundation in Python for data analysis. Learn to work with variables, data types, strings, conditional statements, loops, core data structures, and functions using examples relevant to analytical tasks.

Challenge: Product Revenues Capstone

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