import unittest
import psycopg2
import pandas as pd

class TestTask(unittest.TestCase):
    @classmethod
    def setUpClass(cls):
        cls.connection = psycopg2.connect(
            host="localhost",
            user="agent",
            password="qwerty",
            dbname="testdb",
            sslmode="disable"
        )
        cls.cursor = cls.connection.cursor()

    def test_selects_correct_columns(self):
        """Check that only 'name', 'region', 'capital' columns are selected and in correct order."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        columns = [desc[0] for desc in self.cursor.description]
        expected_columns = ["name", "region", "capital"]
        _dynamic_test(
            self,
            columns == expected_columns,
            "Selected columns are correct and in the right order.",
            f"Selected columns are not correct or not in the right order. Got: {columns}, expected: {expected_columns}."
        )

    def test_result_sorted_by_region_and_capital_desc(self):
        """Check that results are sorted by region DESC, then capital DESC."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        rows = self.cursor.fetchall()
        if not rows:
            _dynamic_test(
                self,
                False,
                "Result is not empty.",
                "Query result is empty, cannot check sorting."
            )
            return
        df = pd.DataFrame(rows, columns=[desc[0] for desc in self.cursor.description])
        # For sorting, None values are considered less than any string in DESC order
        def safe_str(x):
            # Place None after all strings in DESC order
            return (x is None, x)
        sorted_df = df.sort_values(by=["region", "capital"], ascending=[False, False], key=lambda col: col.map(safe_str))
        # Reset index for comparison
        df = df.reset_index(drop=True)
        sorted_df = sorted_df.reset_index(drop=True)
        is_sorted = df.equals(sorted_df)
        _dynamic_test(
            self,
            is_sorted,
            "Results are sorted by region and capital in descending order.",
            "Rows are not sorted by region and capital in descending order."
        )

    def test_query_returns_all_rows(self):
        """Check that the query returns all rows from the country table."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute("SELECT COUNT(*) FROM country")
        expected_count = self.cursor.fetchone()[0]
        self.cursor.execute(query)
        result_count = len(self.cursor.fetchall())
        _dynamic_test(
            self,
            result_count == expected_count,
            "Query returns all rows from the country table.",
            f"Query does not return all rows. Got {result_count}, expected {expected_count}."
        )

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()

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


test_solution.py

This course is perfect for beginners ready to explore the world of SQL. Whether you're just starting out in database management or aiming to use SQL for your application development projects, this course covers the essentials. You'll quickly learn how to leverage the full potential of SQL, from querying and managing data to seamlessly integrating it into real-world applications. By the end of the course, you'll have the confidence and skills to solve practical problems with SQL and enhance your development process.

In this section, we will learn how to use the SQL SELECT statement to get a single table column, multiple table columns, and all table columns. We will also find out how to return unique values.

In this section, we’ll explore how to organize and prioritize the data returned by a query using the ORDER BY clause. Placed at the end of a SELECT statement, this clause lets you sort your results by one or multiple columns, either in ascending or descending order, enabling more meaningful and easily interpretable data output.

In this section, we will learn how to filter returned data using the SELECT statement's WHERE clause. We will learn how to test for equality, inequality, more and less significant than value ranges, and NULL values.

In this section, we’ll explore how to refine your search conditions by combining WHERE clauses with the AND and OR operators. We’ll also cover how the NOT operator can be used to exclude certain results.

In this section, we will learn what the SQL aggregate functions are and how to use them to summarize table data.

Challenge: Sort the Countries by Region and Capital

Solution