import unittest
import psycopg2
import pandas as pd
import re

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_one_row_per_month(self):
        """Check that the query returns one row per month present in the table."""
        with open("query.sql", "r") as file:
            query = file.read()

        self.cursor.execute("SELECT DISTINCT TO_CHAR(transaction_date, 'YYYY-MM') FROM transactions")
        expected_months = set(row[0] for row in self.cursor.fetchall())

        self.cursor.execute(query)
        rows = self.cursor.fetchall()
        months = set(row[0] for row in rows)

        condition = months == expected_months and len(rows) == len(expected_months)
        _dynamic_test(
            self,
            condition,
            "Returned one row per month present in the table.",
            f"Returned months: {months}, but expected: {expected_months}."
        )

    def test_purchase_count_column(self):
        """Check that purchase_count column shows correct count of 'purchase' transactions per month."""
        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]
        result_df = pd.DataFrame(rows, columns=columns)

        self.cursor.execute("""
            SELECT TO_CHAR(transaction_date, 'YYYY-MM') AS month, COUNT(*) AS purchase_count
            FROM transactions
            WHERE transaction_type = 'purchase'
            GROUP BY TO_CHAR(transaction_date, 'YYYY-MM')
        """)
        expected = dict(self.cursor.fetchall())

        for idx, row in result_df.iterrows():
            m = row['month']
            actual = row['purchase_count']
            expected_count = expected.get(m, 0)
            condition = actual == expected_count
            _dynamic_test(
                self,
                condition,
                f"Correct purchase_count for month {m}.",
                f"Incorrect purchase_count for month {m}: got {actual}, expected {expected_count}."
            )

    def test_refund_count_column(self):
        """Check that refund_count column shows correct count of 'refund' transactions per month."""
        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]
        result_df = pd.DataFrame(rows, columns=columns)

        self.cursor.execute("""
            SELECT TO_CHAR(transaction_date, 'YYYY-MM') AS month, COUNT(*) AS refund_count
            FROM transactions
            WHERE transaction_type = 'refund'
            GROUP BY TO_CHAR(transaction_date, 'YYYY-MM')
        """)
        expected = dict(self.cursor.fetchall())

        for idx, row in result_df.iterrows():
            m = row['month']
            actual = row['refund_count']
            expected_count = expected.get(m, 0)
            condition = actual == expected_count
            _dynamic_test(
                self,
                condition,
                f"Correct refund_count for month {m}.",
                f"Incorrect refund_count for month {m}: got {actual}, expected {expected_count}."
            )

    def test_fee_count_column(self):
        """Check that fee_count column shows correct count of 'fee' transactions per month."""
        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]
        result_df = pd.DataFrame(rows, columns=columns)

        self.cursor.execute("""
            SELECT TO_CHAR(transaction_date, 'YYYY-MM') AS month, COUNT(*) AS fee_count
            FROM transactions
            WHERE transaction_type = 'fee'
            GROUP BY TO_CHAR(transaction_date, 'YYYY-MM')
        """)
        expected = dict(self.cursor.fetchall())

        for idx, row in result_df.iterrows():
            m = row['month']
            actual = row['fee_count']
            expected_count = expected.get(m, 0)
            condition = actual == expected_count
            _dynamic_test(
                self,
                condition,
                f"Correct fee_count for month {m}.",
                f"Incorrect fee_count for month {m}: got {actual}, expected {expected_count}."
            )

    def test_month_format(self):
        """Check that the month column is in 'YYYY-MM' format and represents a valid year and month."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        rows = self.cursor.fetchall()
        months = [str(row[0]) for row in rows]
        pattern = r"^\d{4}-\d{2}$"
        all_valid = all(re.match(pattern, m) for m in months)
        _dynamic_test(
            self,
            all_valid,
            "Month column is in 'YYYY-MM' format.",
            f"Month column not in correct format: {months}."
        )

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：トランザクションタイプの内訳

解答