import unittest
import psycopg2
import pandas as pd

class TestPostgresQuery(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):
        """Check that the query selects id, name, population in this exact 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 = ["id", "name", "population"]
        condition = columns == expected_columns
        _dynamic_test(
            self,
            condition,
            "Query selects columns id, name, population in the correct order.",
            f"Query does not select columns in the correct order. Found: {columns}"
        )

    def test_all_rows_present(self):
        """Check that the query returns all rows from the country table and correct values for the columns."""
        with open("query.sql", "r") as file:
            query = file.read()
        # Get expected result using the correct query
        solution_query = "SELECT id, name, population FROM country;"
        self.cursor.execute(solution_query)
        expected_rows = self.cursor.fetchall()
        self.cursor.execute(query)
        result_rows = self.cursor.fetchall()
        # Convert both to sets for order-insensitive comparison
        expected_set = set(expected_rows)
        result_set = set(result_rows)
        condition = expected_set == result_set and len(result_rows) == len(expected_rows)
        _dynamic_test(
            self,
            condition,
            "Query returns all expected rows and values for id, name, population.",
            f"Returned rows do not match expected rows.\\nExpected: {expected_rows}\\nGot: {result_rows}"
        )

    def test_only_three_columns(self):
        """Ensure that only three columns are returned."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        columns = [desc[0] for desc in self.cursor.description]
        condition = len(columns) == 3
        _dynamic_test(
            self,
            condition,
            "Query returns exactly three columns.",
            f"Query should return 3 columns, but returned {len(columns)} columns: {columns}"
        )

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

Focuses on practical SQL skills for filtering data with WHERE, sorting results with ORDER BY, and summarizing information using GROUP BY and aggregate functions. Hands-on challenges reinforce each concept, preparing learners to analyze and summarize real-world datasets effectively.

Challenge: Find Countries, Their IDs, and Their Populations

Ratkaisu