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_result_contains_only_never_ordered_products(self):
        """Check that only products that have never been ordered are returned."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute("SELECT DISTINCT product_id FROM orders")
        ordered_product_ids = set(row[0] for row in self.cursor.fetchall())
        self.cursor.execute(query)
        rows = self.cursor.fetchall()
        columns = [desc[0] for desc in self.cursor.description]
        df = pd.DataFrame(rows, columns=columns)
        if not df.empty:
            not_ordered = df['product_id'].apply(lambda x: x not in ordered_product_ids).all()
        else:
            not_ordered = True
        _dynamic_test(
            self,
            not_ordered,
            "Returned only products never ordered.",
            "Returned products that have been ordered."
        )

    def test_all_columns_returned(self):
        """Check that all columns from products table are returned."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        result_columns = [desc[0] for desc in self.cursor.description]
        self.cursor.execute("SELECT * FROM products LIMIT 1")
        products_columns = [desc[0] for desc in self.cursor.description]
        condition = set(result_columns) == set(products_columns)
        _dynamic_test(
            self,
            condition,
            "Returned all columns from products table.",
            f"Did not return all columns from products table. Returned: {result_columns}"
        )

    def test_no_ordered_products_in_result(self):
        """Ensure no product that has been ordered appears in the result."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        rows = self.cursor.fetchall()
        columns = [desc[0] for desc in self.cursor.description]
        df = pd.DataFrame(rows, columns=columns)
        self.cursor.execute("SELECT DISTINCT product_id FROM orders")
        ordered_product_ids = set(row[0] for row in self.cursor.fetchall())
        if not df.empty:
            overlap = set(df['product_id']).intersection(ordered_product_ids)
        else:
            overlap = set()
        condition = len(overlap) == 0
        _dynamic_test(
            self,
            condition,
            "No ordered products returned.",
            f"Returned product_ids that have been ordered: {overlap}"
        )

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

Master the art of writing and applying subqueries in SQL through real-world scenarios. This course covers the theory and practice of subqueries, including their use in SELECT, WHERE, and FROM clauses, as well as correlated subqueries. Each section features a unique dataset and practical challenges to reinforce your learning.

Explore subqueries using an e-commerce dataset, focusing on orders, customers, and products. Learn to extract insights and solve business problems using subqueries.

Apply subqueries to HR data, including employees, departments, and salaries. Tackle real-world HR analytics tasks.

Use subqueries to solve problems in a library management system, including books, members, and borrowings.

Challenge: Products Never Ordered

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Challenge: Products Never Ordered

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