Summary  
This chapter explains how to use the COUNT() aggregate function to count rows in a table or count non-null values in a specific column based on given criteria.

General domain of usage  
Database querying and reporting

`COUNT()` is a function that allows you to count rows in a table or count how many rows match certain criteria. 

Let's see an example:

To count the total number of rows in the table, we can use the following syntax:

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_count_asian_countries_population_over_1m(self):
        """Check if the query returns the correct count for Asian countries with population > 1,000,000."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        rows = self.cursor.fetchall()
        # There are 3 countries in Asia with population > 1,000,000: Japan, Thailand, Philippines
        expected_count = 3
        # The result should be a single row with a single value
        condition = (
            len(rows) == 1 and
            len(rows[0]) == 1 and
            rows[0][0] == expected_count
        )
        _dynamic_test(
            self,
            condition,
            "Correct count returned for Asian countries with population over 1,000,000.",
            f"Expected count {expected_count}, but got {rows[0][0] if rows and rows[0] else 'no result'}."
        )

    def test_no_extra_rows(self):
        """Ensure only a single row is returned by the query."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        rows = self.cursor.fetchall()
        condition = len(rows) == 1
        _dynamic_test(
            self,
            condition,
            "Query returns exactly one row.",
            f"Query returned {len(rows)} rows instead of 1."
        )

    def test_no_extra_columns(self):
        """Ensure only a single column is returned by the query."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        rows = self.cursor.fetchall()
        condition = len(rows) > 0 and len(rows[0]) == 1
        _dynamic_test(
            self,
            condition,
            "Query returns exactly one column.",
            f"Query returned {len(rows[0]) if rows else 0} columns instead of 1."
        )

    def test_query_is_case_sensitive_for_asia(self):
        """Ensure the query does not match 'asia' in lowercase: only 'Asia' should be matched."""
        # Insert a country with continent as 'asia' (lowercase) and population > 1M
        self.cursor.execute("INSERT INTO country (id, name, continent, region, surfacearea, capital, population) VALUES (100, 'FakeAsia', 'asia', NULL, 1000, 'FakeCity', 2000000);")
        self.connection.commit()
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        rows = self.cursor.fetchall()
        expected_count = 3  # Should NOT count the lowercase 'asia' row
        condition = (
            len(rows) == 1 and
            len(rows[0]) == 1 and
            rows[0][0] == expected_count
        )
        _dynamic_test(
            self,
            condition,
            "Query is case sensitive for 'Asia'.",
            f"Query counted rows with 'asia' (lowercase). Expected {expected_count}, got {rows[0][0] if rows and rows[0] else 'no result'}."
        )
        # Clean up
        self.cursor.execute("DELETE FROM country WHERE id=100;")
        self.connection.commit()

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

Focuses on practical SQL skills for filtering data with WHERE, sorting results with ORDER BY, and summarizing information using GROUP BY and aggregate functions. Hands-on challenges reinforce each concept, preparing learners to analyze and summarize real-world datasets effectively.

The COUNT() Function

解答