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_selects_all_columns(self):
        """Check if query selects all columns from products table."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        columns = [desc[0] for desc in self.cursor.description]
        self.cursor.execute("SELECT * FROM products LIMIT 1;")
        expected_columns = [desc[0] for desc in self.cursor.description]
        condition = set(columns) == set(expected_columns)
        _dynamic_test(
            self,
            condition,
            "Query selects all columns from products table.",
            f"Query does not select all columns from products table. Found: {columns}"
        )

    def test_only_electronics_category(self):
        """Check if only products with category 'Electronics' are returned."""
        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)
        if len(df) == 0:
            condition = False
            failure_msg = "No rows returned. Should return products in 'Electronics' category."
        else:
            non_electronics = df[df['category'] != 'Electronics']
            condition = len(non_electronics) == 0
            if not condition:
                failure_msg = f"Found products not in 'Electronics' category: {non_electronics.to_dict('records')}"
            else:
                failure_msg = ""
        _dynamic_test(
            self,
            condition,
            "Only products in 'Electronics' category are returned.",
            failure_msg
        )

    def test_ordered_by_price_desc(self):
        """Check if results are ordered by price descending."""
        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)
        if len(df) == 0:
            condition = False
            failure_msg = "No rows returned. Cannot check order."
        else:
            prices = df['price'].tolist()
            sorted_prices = sorted(prices, reverse=True)
            condition = prices == sorted_prices
            failure_msg = f"Prices are not ordered descending: {prices}"
        _dynamic_test(
            self,
            condition,
            "Results are ordered by price descending.",
            failure_msg
        )


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：プロダクトテーブルの探索

解答