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 setUp(self):
        with open("query.sql", "r") as file:
            self.query = file.read()

    def test_all_columns_returned(self):
        """Check that all columns from movies are returned."""
        self.cursor.execute(self.query)
        columns = [desc[0] for desc in self.cursor.description]
        expected_columns = set(["id", "title", "genre", "rating", "release_year", "box_office"])
        _dynamic_test(
            self,
            set(columns) == expected_columns,
            "All columns from movies table are returned.",
            f"Returned columns are incorrect: {columns}"
        )

    def test_sci_fi_after_2010_first(self):
        """Check that only Sci-Fi movies released after 2010 are at the top."""
        self.cursor.execute(self.query)
        rows = self.cursor.fetchall()
        columns = [desc[0] for desc in self.cursor.description]
        df = pd.DataFrame(rows, columns=columns)
        # Find all Sci-Fi movies released after 2010
        sci_fi_after_2010 = df[(df['genre'] == 'Sci-Fi') & (df['release_year'] > 2010)]
        # These should all be at the top
        if not sci_fi_after_2010.empty:
            top_n = len(sci_fi_after_2010)
            top_rows = df.head(top_n)
            top_rows_check = (top_rows['genre'] == 'Sci-Fi') & (top_rows['release_year'] > 2010)
            condition = top_rows_check.all()
        else:
            # There are no Sci-Fi movies after 2010 in test data, so pass
            condition = True
        _dynamic_test(
            self,
            condition,
            "All prioritized Sci-Fi movies (after 2010) are at the top.",
            "Not all prioritized Sci-Fi movies are at the top."
        )

    def test_no_non_sci_fi_in_priority_group(self):
        """Check that no non-Sci-Fi/<=2010 movies are mixed in with the prioritized group."""
        self.cursor.execute(self.query)
        rows = self.cursor.fetchall()
        columns = [desc[0] for desc in self.cursor.description]
        df = pd.DataFrame(rows, columns=columns)
        # Find all Sci-Fi movies released after 2010
        sci_fi_after_2010 = df[(df['genre'] == 'Sci-Fi') & (df['release_year'] > 2010)]
        top_n = len(sci_fi_after_2010)
        if top_n > 0:
            top_rows = df.head(top_n)
            # Ensure all top rows are ONLY Sci-Fi and release_year > 2010
            valid = ((top_rows['genre'] == 'Sci-Fi') & (top_rows['release_year'] > 2010)).all()
        else:
            valid = True
        _dynamic_test(
            self,
            valid,
            "No non-Sci-Fi or <=2010 movies are in the prioritized group.",
            "There are movies in the prioritized group that do not match the condition."
        )

    def test_rest_ordered_by_release_year_desc(self):
        """Check that all other movies are ordered by release_year descending."""
        self.cursor.execute(self.query)
        rows = self.cursor.fetchall()
        columns = [desc[0] for desc in self.cursor.description]
        df = pd.DataFrame(rows, columns=columns)
        sci_fi_after_2010 = df[(df['genre'] == 'Sci-Fi') & (df['release_year'] > 2010)]
        top_n = len(sci_fi_after_2010)
        rest = df.iloc[top_n:]
        # The rest should be ordered by release_year descending
        release_years = rest['release_year'].tolist()
        is_desc = all(release_years[i] >= release_years[i+1] for i in range(len(release_years)-1))
        _dynamic_test(
            self,
            is_desc,
            "Remaining movies are ordered by release_year descending.",
            "Remaining movies are not ordered by release_year descending."
        )

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：リリース年の優先順位

解答