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_performance_column_exists(self):
        """Check if 'performance' column is present in query output."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        columns = [desc[0] for desc in self.cursor.description]
        _dynamic_test(
            self,
            "performance" in [c.lower() for c in columns],
            "'performance' column exists in output.",
            "'performance' column is missing from output."
        )

    def test_all_rows_included(self):
        """Check if all rows from sales table are present in output."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute("SELECT COUNT(*) FROM sales;")
        expected_count = self.cursor.fetchone()[0]
        self.cursor.execute(query)
        rows = self.cursor.fetchall()
        _dynamic_test(
            self,
            len(rows) == expected_count,
            f"All {expected_count} rows from sales are included.",
            f"Expected {expected_count} rows but found {len(rows)}."
        )

    def test_top_label(self):
        """Rows with quantity >= 50 AND price >= 100 must be labeled 'Top'."""
        with open("query.sql", "r") as file:
            query = file.read()
        # Insert a matching row
        self.cursor.execute("INSERT INTO sales (id, product, quantity, price, region) VALUES (100, 'TestProd', 55, 150, 'TestReg') ON CONFLICT DO NOTHING;")
        self.cursor.connection.commit()
        self.cursor.execute(query)
        df = pd.DataFrame(self.cursor.fetchall(), columns=[desc[0] for desc in self.cursor.description])
        row = df[(df['id'] == 100)]
        label = row['performance'].iloc[0] if not row.empty else None
        _dynamic_test(
            self,
            label == 'Top',
            "Rows with quantity >= 50 and price >= 100 are labeled 'Top'.",
            "Row with quantity >= 50 and price >= 100 is not labeled 'Top'."
        )

    def test_average_label(self):
        """Rows with only one of quantity >= 50 or price >= 100 must be labeled 'Average'."""
        with open("query.sql", "r") as file:
            query = file.read()
        # Insert two rows: one with quantity >= 50, one with price >= 100
        self.cursor.execute("INSERT INTO sales (id, product, quantity, price, region) VALUES (101, 'TestProd', 51, 50, 'TestReg') ON CONFLICT DO NOTHING;")
        self.cursor.execute("INSERT INTO sales (id, product, quantity, price, region) VALUES (102, 'TestProd', 10, 120, 'TestReg') ON CONFLICT DO NOTHING;")
        self.cursor.connection.commit()
        self.cursor.execute(query)
        df = pd.DataFrame(self.cursor.fetchall(), columns=[desc[0] for desc in self.cursor.description])
        row1 = df[(df['id'] == 101)]
        row2 = df[(df['id'] == 102)]
        label1 = row1['performance'].iloc[0] if not row1.empty else None
        label2 = row2['performance'].iloc[0] if not row2.empty else None
        cond = (label1 == 'Average') and (label2 == 'Average')
        _dynamic_test(
            self,
            cond,
            "Rows with only one condition met are labeled 'Average'.",
            "Rows with only one condition met are not labeled 'Average'."
        )

    def test_low_label(self):
        """Rows with neither quantity >= 50 nor price >= 100 must be labeled 'Low'."""
        with open("query.sql", "r") as file:
            query = file.read()
        # Insert a row with neither condition met
        self.cursor.execute("INSERT INTO sales (id, product, quantity, price, region) VALUES (103, 'TestProd', 10, 50, 'TestReg') ON CONFLICT DO NOTHING;")
        self.cursor.connection.commit()
        self.cursor.execute(query)
        df = pd.DataFrame(self.cursor.fetchall(), columns=[desc[0] for desc in self.cursor.description])
        row = df[(df['id'] == 103)]
        label = row['performance'].iloc[0] if not row.empty else None
        _dynamic_test(
            self,
            label == 'Low',
            "Rows with neither condition met are labeled 'Low'.",
            "Row with neither condition met is not labeled 'Low'."
        )

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

SQLにおけるCASE WHEN文を基礎的な条件分岐からデータ分析・レポーティングでの高度な活用例まで習得できる包括的なモジュールです。理論と実践的な課題を通じて、複雑なビジネス要件に対応する表現力豊かなクエリの作成方法を学びます。

CASE WHEN文の基本、構文、およびSQLクエリでの単純な条件付きロジックへの活用方法を学習します。

チャレンジ：販売実績ラベル

解答