import unittest
import psycopg2
import pandas as pd
import re

class TestTask(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_distinct_capital_values(self):
        """Check that only distinct capital values are returned."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        user_rows = self.cursor.fetchall()
        user_capitals = set([row[0] for row in user_rows])
        # Get expected distinct capitals from the table
        self.cursor.execute("SELECT DISTINCT capital FROM country;")
        expected_rows = self.cursor.fetchall()
        expected_capitals = set([row[0] for row in expected_rows])
        condition = user_capitals == expected_capitals
        _dynamic_test(
            self,
            condition,
            "Returned capitals are all unique and match expected distinct values.",
            f"Returned capitals do not match expected distinct values.\\nExpected: {expected_capitals}\\nGot: {user_capitals}"
        )

    def test_no_duplicate_capitals(self):
        """Check that there are no duplicate capital values in the result."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        user_rows = self.cursor.fetchall()
        capitals = [row[0] for row in user_rows]
        condition = len(capitals) == len(set(capitals))
        _dynamic_test(
            self,
            condition,
            "There are no duplicate capital values in the result.",
            "Duplicate capital values found in the result."
        )

    def test_column_name(self):
        """Check that the column name in the result is 'capital'."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        colnames = [desc[0] for desc in self.cursor.description]
        condition = len(colnames) == 1 and normalize_text(colnames[0]) == "capital"
        _dynamic_test(
            self,
            condition,
            "Result column name is 'capital'.",
            f"Result column name is not 'capital'. Got: {colnames}"
        )

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

This course is perfect for beginners ready to explore the world of SQL. Whether you're just starting out in database management or aiming to use SQL for your application development projects, this course covers the essentials. You'll quickly learn how to leverage the full potential of SQL, from querying and managing data to seamlessly integrating it into real-world applications. By the end of the course, you'll have the confidence and skills to solve practical problems with SQL and enhance your development process.

In this section, we will learn how to use the SQL SELECT statement to get a single table column, multiple table columns, and all table columns. We will also find out how to return unique values.

In this section, we’ll explore how to organize and prioritize the data returned by a query using the ORDER BY clause. Placed at the end of a SELECT statement, this clause lets you sort your results by one or multiple columns, either in ascending or descending order, enabling more meaningful and easily interpretable data output.

In this section, we will learn how to filter returned data using the SELECT statement's WHERE clause. We will learn how to test for equality, inequality, more and less significant than value ranges, and NULL values.

In this section, we’ll explore how to refine your search conditions by combining WHERE clauses with the AND and OR operators. We’ll also cover how the NOT operator can be used to exclude certain results.

In this section, we will learn what the SQL aggregate functions are and how to use them to summarize table data.

Challenge: Find Country Capitals

Solution

Challenge: Find Country Capitals

Solution