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_all_rows_returned(self):
        """Check that the query returns all customers."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        rows = self.cursor.fetchall()
        _dynamic_test(
            self,
            len(rows) == 10,
            "Returned all rows from customers table.",
            f"Expected 10 rows, but got {len(rows)}."
        )

    def test_cleaned_city_no_spaces(self):
        """Check that cleaned_city has no leading or trailing spaces."""
        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]
        cleaned_city_idx = columns.index("cleaned_city")
        spaces_found = [row[cleaned_city_idx] for row in rows if row[cleaned_city_idx] != row[cleaned_city_idx].strip()]
        _dynamic_test(
            self,
            len(spaces_found) == 0,
            "No leading or trailing spaces in cleaned_city.",
            f"Found spaces in cleaned_city values: {spaces_found}"
        )

    def test_cleaned_city_first_letter_upper(self):
        """Check that first letter of cleaned_city is uppercase."""
        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]
        cleaned_city_idx = columns.index("cleaned_city")
        failures = [row[cleaned_city_idx] for row in rows if not row[cleaned_city_idx][0].isupper()]
        _dynamic_test(
            self,
            len(failures) == 0,
            "First letter of cleaned_city is uppercase for all rows.",
            f"First letter is not uppercase in: {failures}"
        )

    def test_cleaned_city_rest_lower(self):
        """Check that all other letters in cleaned_city are lowercase."""
        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]
        cleaned_city_idx = columns.index("cleaned_city")
        failures = []
        for row in rows:
            city = row[cleaned_city_idx]
            if len(city) > 1 and city[1:] != city[1:].lower():
                failures.append(city)
        _dynamic_test(
            self,
            len(failures) == 0,
            "All letters after the first in cleaned_city are lowercase.",
            f"Non-lowercase letters found in: {failures}"
        )

    def test_cleaned_city_matches_expected(self):
        """Check that cleaned_city contains the cleaned version of city for every customer."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        result_rows = self.cursor.fetchall()
        columns = [desc[0] for desc in self.cursor.description]
        result_df = pd.DataFrame(result_rows, columns=columns)
        # Build expected cleaned city column
        self.cursor.execute("SELECT id, city FROM customers")
        orig = self.cursor.fetchall()
        expected = {}
        for row in orig:
            city = row[1]
            city_trim = city.strip()
            if city_trim:
                cleaned = city_trim[0].upper() + city_trim[1:].lower()
            else:
                cleaned = ''
            expected[row[0]] = cleaned
        # Compare cleaned_city for each row
        mismatches = []
        for _, row in result_df.iterrows():
            if row['id'] in expected:
                if row['cleaned_city'] != expected[row['id']]:
                    mismatches.append((row['id'], row['cleaned_city'], expected[row['id']]))
        _dynamic_test(
            self,
            len(mismatches) == 0,
            "cleaned_city matches expected transformation for all rows.",
            f"Rows with mismatched cleaned_city: {mismatches}"
        )

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

組み込みSQL関数を活用して、文字列、日付、数値、論理値、NULL、JSONデータを操作する方法を習得します。本モジュールでは、実践的なアプローチでSQL関数の理解と応用を深め、現実のシナリオにおけるデータクエリおよび変換スキルを向上させます。

データベース内のテキストデータを操作および分析するための、SQLの強力な文字列関数を学習します。

チャレンジ：都市名のクリーンアップ

解答