Summary  
The AVG() aggregate function computes the mean of a numeric column’s values and can be combined with a WHERE clause to average only rows that meet specified conditions.

General domain of usage  
Data analysis and reporting in database queries

`AVG()` returns the average value of a certain column. 
Let's see an example: 

`AVG()` can also be used to find the average of a selected set of columns or rows that meet certain conditions. Here’s an example:

SELECT AVG(population) 
FROM country
WHERE population < 4478500;

import unittest
import psycopg2
import pandas as pd
import decimal

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_avg_surfacearea_correctness(self):
        """Check that the query returns the correct average of the surfacearea column from country table."""
        with open("query.sql", "r") as file:
            query = file.read()
        # Calculate expected average
        self.cursor.execute("SELECT surfacearea FROM country")
        surfaceareas = [row[0] for row in self.cursor.fetchall() if row[0] is not None]
        expected_avg = sum(surfaceareas) / len(surfaceareas) if surfaceareas else None

        self.cursor.execute(query)
        result = self.cursor.fetchone()[0]
        # Accept float rounding error up to 6 decimals
        if isinstance(result, decimal.Decimal):
            result_float = float(result)
        else:
            result_float = result
        if isinstance(expected_avg, decimal.Decimal):
            expected_avg_float = float(expected_avg)
        else:
            expected_avg_float = expected_avg
        condition = expected_avg is not None and abs(result_float - expected_avg_float) < 1e-6
        _dynamic_test(
            self,
            condition,
            "Query returns the correct average value of surfacearea.",
            f"Expected average: {expected_avg}, but got: {result}."
        )

    def test_query_uses_avg_function(self):
        """Check that the query uses the AVG() function."""
        with open("query.sql", "r") as file:
            query = file.read()
        condition = "avg" in query.lower()
        _dynamic_test(
            self,
            condition,
            "Query uses the AVG() function.",
            "Query does not use the AVG() function."
        )

    def test_query_uses_select(self):
        """Check that the query uses the SELECT statement."""
        with open("query.sql", "r") as file:
            query = file.read()
        condition = query.strip().lower().startswith("select")
        _dynamic_test(
            self,
            condition,
            "Query uses the SELECT statement.",
            "Query does not use the SELECT statement."
        )

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):
    import re
    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

Learn the core fundamentals of SQL and relational databases. Understand how databases store and organize data, write basic SQL queries, work with tables and perform essential operations. Build a strong foundation for working with databases in backend development.

The AVG() Function

Solution