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_columns_and_order(self):
        """Test that the query returns the correct columns in the 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', 'population', 'region', 'capital']
        condition = columns == expected_columns
        _dynamic_test(
            self,
            condition,
            "Query returns columns in correct order: name, population, region, capital.",
            f"Query columns/order incorrect. Got: {columns}, expected: {expected_columns}."
        )

    def test_population_filter(self):
        """Test that only countries with population >= 300000 are returned."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        rows = self.cursor.fetchall()
        population_idx = [desc[0] for desc in self.cursor.description].index('population')
        invalid_rows = [row for row in rows if row[population_idx] is not None and row[population_idx] < 300000]
        condition = len(invalid_rows) == 0
        _dynamic_test(
            self,
            condition,
            "All returned rows have population >= 300000.",
            f"Some rows have population < 300000: {invalid_rows}."
        )

    def test_expected_rows_present(self):
        """Test that all expected countries with population >= 300000 are included in the result."""
        solution_query = """
            SELECT name, population, region, capital 
            FROM country
            WHERE population >= 300000;
        """
        self.cursor.execute(solution_query)
        expected_rows = self.cursor.fetchall()
        with open("query.sql", "r") as file:
            user_query = file.read()
        self.cursor.execute(user_query)
        user_rows = self.cursor.fetchall()
        missing = [row for row in expected_rows if row not in user_rows]
        condition = len(missing) == 0
        _dynamic_test(
            self,
            condition,
            "All expected rows are present in the result.",
            f"Missing expected rows: {missing}."
        )

    def test_no_extra_rows(self):
        """Test that no extra countries (with population < 300000 or NULL) are included in the result."""
        with open("query.sql", "r") as file:
            user_query = file.read()
        self.cursor.execute(user_query)
        user_rows = self.cursor.fetchall()
        solution_query = """
            SELECT name, population, region, capital 
            FROM country
            WHERE population >= 300000;
        """
        self.cursor.execute(solution_query)
        expected_rows = self.cursor.fetchall()
        extra = [row for row in user_rows if row not in expected_rows]
        condition = len(extra) == 0
        _dynamic_test(
            self,
            condition,
            "No extra rows are present in the result.",
            f"Extra rows found: {extra}."
        )

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 module 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.

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.

Challenge: Population Threshold Query

Solution