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_top_3_customers_by_total_quantity(self):
        """Check if the query returns the correct top 3 customers by total quantity purchased."""
        with open("query.sql", "r") as file:
            query = file.read()

        # Reference query for correct top 3 customers
        solution_query = '''
            SELECT c.customer_id, c.first_name, c.last_name, SUM(s.quantity) AS total_quantity, RANK() OVER (ORDER BY SUM(s.quantity) DESC) AS customer_rank
            FROM customers c
            JOIN sales s ON c.customer_id = s.customer_id
            GROUP BY c.customer_id, c.first_name, c.last_name
            ORDER BY customer_rank
            LIMIT 3;
        '''
        self.cursor.execute(solution_query)
        ref_rows = self.cursor.fetchall()
        ref_cols = [desc[0] for desc in self.cursor.description]
        ref_df = pd.DataFrame(ref_rows, columns=ref_cols)

        self.cursor.execute(query)
        rows = self.cursor.fetchall()
        cols = [desc[0] for desc in self.cursor.description]
        df = pd.DataFrame(rows, columns=cols)

        # Compare by customer_id and total_quantity
        missing_rows = []
        for _, ref_row in ref_df.iterrows():
            mask = (
                (df['customer_id'] == ref_row['customer_id']) &
                (df['first_name'] == ref_row['first_name']) &
                (df['last_name'] == ref_row['last_name']) &
                (df['total_quantity'] == ref_row['total_quantity']) &
                (df['customer_rank'] == ref_row['customer_rank'])
            )
            if not mask.any():
                missing_rows.append(ref_row.to_dict())
        condition = len(missing_rows) == 0 and len(df) == 3
        if not condition:
            failure_msg = f"Top 3 customers by total quantity are incorrect or missing. Missing/incorrect rows: {missing_rows}"
        else:
            failure_msg = ""
        _dynamic_test(self, condition, "Query returns correct top 3 customers by total quantity.", failure_msg)

    def test_includes_required_columns(self):
        """Check that the output includes customer_id, first_name, last_name, total_quantity, and customer_rank."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        columns = [desc[0] for desc in self.cursor.description]
        required = {'customer_id', 'first_name', 'last_name', 'total_quantity', 'customer_rank'}
        missing = required - set(columns)
        condition = len(missing) == 0
        if not condition:
            failure_msg = f"Missing required columns: {missing}"
        else:
            failure_msg = ""
        _dynamic_test(self, condition, "All required columns are present in the output.", failure_msg)

    def test_ranking_uses_window_function(self):
        """Check that a window function is used to rank customers by total quantity."""
        with open("query.sql", "r") as file:
            query = file.read().lower()
        # Look for RANK() or DENSE_RANK() or ROW_NUMBER() with OVER
        uses_window = (
            ("rank()" in query or "dense_rank()" in query or "row_number()" in query)
            and "over" in query
        )
        _dynamic_test(
            self,
            uses_window,
            "A window function is used to rank customers.",
            "No window function found for ranking customers."
        )

    def test_ranking_is_descending(self):
        """Check that ranking is applied in descending order of total quantity."""
        with open("query.sql", "r") as file:
            query = file.read().lower().replace("\\n", " ")
        # Look for ORDER BY SUM(s.quantity) DESC or similar inside OVER clause
        has_desc = "order by sum(s.quantity) desc" in query or "order by sum(quantity) desc" in query
        _dynamic_test(
            self,
            has_desc,
            "Ranking is applied in descending order of total quantity.",
            "Ranking is not applied in descending order of total quantity."
        )

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

実践的なデータ分析スキルに焦点を当て、SQLを基礎から学べる包括的で初心者向けのコースです。分かりやすい解説、実際の事例、実践的な課題を通じて、SQLを用いたデータのクエリ、変換、分析を習得します。

リレーショナルデータベースとSQLの基礎概念を学習します。テーブルからデータを取得、フィルタリング、並べ替える方法を探求し、より高度なデータ分析の基礎を築きます。

SQLの強力な集計機能を深く学びます。データを要約し、グループ化し、より深い洞察のために分析する方法を習得します。

複数のテーブルからデータを組み合わせる力を引き出します。さまざまな種類の結合を実行し、複雑なビジネス上の質問に答える方法を学びます。

サブクエリ、ウィンドウ関数、データ変換などを含む高度なSQL技術を習得し、強力なデータ分析を実現します。

チャレンジ：トップ3カスタマー

解答