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

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Challenge: Transaction Type Breakdown

解答