Summary
This chapter explains how to apply the DISTINCT keyword in a SELECT statement to retrieve only unique values from a column, eliminating duplicates in query results.

General domain of usage
Database querying

Note that the `SELECT` statement returns all rows in a given column. However, what if we don't need all the values from a column, especially when they are duplicated, and you only need **unique values**? 

For such cases, it is convenient to use the keyword `DISTINCT`, placed immediately before the column names. See the example below:

import unittest
import psycopg2
import pandas as pd

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_correct_distinct_continents(self):
        """Check that the query returns the correct set of distinct continents from country table."""
        with open("query.sql", "r") as file:
            query = file.read()

        # Get expected distinct continents from the table
        self.cursor.execute("SELECT DISTINCT continent FROM country;")
        expected_rows = self.cursor.fetchall()
        expected_set = set([row[0] for row in expected_rows])

        # Run user's query
        self.cursor.execute(query)
        user_rows = self.cursor.fetchall()
        user_set = set([row[0] for row in user_rows])

        condition = user_set == expected_set
        _dynamic_test(
            self,
            condition,
            "Query returns the correct set of distinct continent values.",
            f"Query did not return the correct set of distinct continent values.\\nExpected: {expected_set}\\nGot: {user_set}"
        )

    def test_query_uses_distinct_keyword(self):
        """Check that the query uses the DISTINCT keyword."""
        with open("query.sql", "r") as file:
            query = file.read()
        condition = "distinct" in query.lower()
        _dynamic_test(
            self,
            condition,
            "Query uses the DISTINCT keyword.",
            "Query does not use the DISTINCT keyword."
        )

    def test_query_selects_continent_column(self):
        """Check that the query selects the continent column."""
        with open("query.sql", "r") as file:
            query = file.read()
        # Accepts "continent" or "(continent)"
        condition = "continent" in query.lower()
        _dynamic_test(
            self,
            condition,
            "Query selects the 'continent' column.",
            "Query does not select the 'continent' column."
        )

    def test_query_from_country_table(self):
        """Check that the query selects from the country table."""
        with open("query.sql", "r") as file:
            query = file.read()
        condition = "from country" in query.lower().replace("\\n", " ").replace("\t", " ")
        _dynamic_test(
            self,
            condition,
            "Query selects from the 'country' table.",
            "Query does not select from the 'country' table."
        )

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

Explore the essentials of SQL — from querying data to integrating it into real-world applications. 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.

Retrieving Distinct Rows

Solution