Summary
This chapter explains how to use the asterisk (`*`) wildcard in SQL to retrieve all columns from a table in a single query.

General domain of usage
Relational database querying

Instead of listing each column, you can use the asterisk `*` to retrieve all columns from the table at once. This is especially useful when you need to view all the data in a table without manually typing out each column name. Here’s an example:

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_query_selects_all_columns_with_asterisk(self):
        """Check that the query uses '*' to select all columns from country table."""
        with open("query.sql", "r") as file:
            query = file.read()
        # Normalize whitespace and lowercase
        norm_query = normalize_text(query)
        # Check for correct pattern
        condition = (
            'select * from country' in norm_query or
            'select*from country' in norm_query or
            'select *from country' in norm_query or
            'select* from country' in norm_query
        )
        _dynamic_test(
            self,
            condition,
            "Query uses '*' to select all columns from country table.",
            "Query does not use '*' to select all columns from country table."
        )

    def test_query_returns_all_columns(self):
        """Check that the query result returns all 7 columns from country table."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        result_columns = [desc[0] for desc in self.cursor.description]
        # Get actual columns from country table
        self.cursor.execute("SELECT * FROM country LIMIT 1")
        expected_columns = [desc[0] for desc in self.cursor.description]
        condition = result_columns == expected_columns
        _dynamic_test(
            self,
            condition,
            "Query returns all columns from country table.",
            f"Query does not return all columns. Expected: {expected_columns}, Got: {result_columns}"
        )

    def test_query_returns_all_rows(self):
        """Check that the query returns all rows from the country table."""
        with open("query.sql", "r") as file:
            query = file.read()
        self.cursor.execute(query)
        user_rows = self.cursor.fetchall()
        self.cursor.execute("SELECT * FROM country")
        expected_rows = self.cursor.fetchall()
        condition = len(user_rows) == len(expected_rows)
        _dynamic_test(
            self,
            condition,
            "Query returns all rows from country table.",
            f"Query does not return all rows. Expected {len(expected_rows)} rows, got {len(user_rows)} rows."
        )

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.

Retrieving All Columns

Solution

Retrieving All Columns

Solution