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_avg_function_used(self):
        with open("query.sql", "r") as file:
            query = file.read()
        condition = "avg" in query.lower()
        _dynamic_test(
            self,
            condition,
            "AVG function is used in the query.",
            "Your query does not use the AVG function."
        )

    def test_surfacearea_condition(self):
        with open("query.sql", "r") as file:
            query = file.read().lower().replace(" ","")
        condition = "where" in query
        _dynamic_test(
            self,
            condition,
            "Query filters records with surfacearea > 300000.",
            "Query does not filter records with surfacearea > 300000."
        )

    def test_correct_average_value(self):
        # Calculate expected average
        data = [
            (1,'Japan ',377829),
            (3,'Mexico',1958201),
            (6,'Sweden',449964),
            (7,'Ukraine',603700),
            (8,'United States',9363520),
            (9,'Thailand',513115),
            (10,'Paraguay',406752),
            (11,'Philippines',300000), # not included (must be strictly > 300000)
            (12,'New Zealand',270534), # not included
            (13,'Norway',323877),
        ]
        filtered = [r[2] for r in data if r[2] > 300000]
        expected_avg = sum(filtered) / len(filtered)
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        result = self.cursor.fetchone()
        if result is not None:
            user_avg = float(result[0])
        else:
            user_avg = None
        condition = user_avg is not None and abs(user_avg - expected_avg) < 0.01
        _dynamic_test(
            self,
            condition,
            f"Query returns the correct average value: {expected_avg}.",
            f"Query does not return the correct average value. Expected: {expected_avg}, Got: {user_avg}."
        )

    def test_query_runs(self):
        with open("query.sql", "r") as file:
            query = file.read()
        try:
            self.cursor.execute(query)
            _dynamic_test(
                self,
                True,
                "Query executes successfully.",
                ""
            )
        except Exception as e:
            _dynamic_test(
                self,
                False,
                "",
                f"Query failed to execute: {e}"
            )

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: Large Surface Area Average

Ratkaisu