Lab 05: Understanding Python Program Components

Pull and Update in VS Code

This lab will guide you through identifying and understanding the essential components that make up every Python program. Understanding these building blocks is crucial for writing clean, readable, and functional code.

Before starting any lab, you need to make sure that the repo in your GitHub is the latest one. Sync the repo if the upstream repo have been updated.

Once the online repo is in-sync, bring those changes down to your PC by clicking Source Control and then ... beside Changes and click Pull.

Introduction to Python Program Components

Understanding Python's basic components is like learning the vocabulary and grammar of the Python language. Just as you need to understand words, punctuation, and sentence structure to write effectively in English, you need to understand these programming components to write effective Python code.

In this lab, we'll explore each component through examples and exercises.

Identifiers and Variables

Identifiers are the names we give to elements in our Python programs. Think of them as labels that help us identify and reference different parts of our code. Variables are a type of identifier that stores data values that can change during program execution.

The usage of variables is that they allow us to store, retrieve, and manipulate data throughout our program's execution.

Launch VS Code and open the exercise.py file in /labs/lab05/. Let's start by exploring identifiers and variables.

# Examples of valid identifiers and variables
student_name = "Alice"
age = 20
total_score = 95.5
is_enrolled = True
course_code = "CP115"

# Examples of identifier naming conventions
firstName = "John"        # camelCase (less common in Python)
first_name = "Jane"       # snake_case (Python convention)
MAXIMUM_ATTEMPTS = 3      # UPPER_CASE for constants

Notice how each variable name follows specific rules. Python identifiers must start with a letter or underscore, can contain letters, numbers, and underscores, but cannot start with a number or contain spaces.

The naming convention in Python typically uses lowercase letters with underscores separating words, known as snake_case. Don't worry too much about the snake_case, we will learn more about this in our lecture.

Variables in Python are dynamically typed, meaning you don't need to declare their type explicitly. The Python interpreter determines the type based on the value you assign. This flexibility makes Python code more readable and easier to write.

TIP

Choose meaningful variable names that clearly describe what the variable represents. student_grade is much better than sg or x.

Reserved Words and Keywords

Python has a set of reserved words, also called keywords, that have special meaning in the language. These words cannot be used as identifiers because Python has already assigned specific functions to them. Understanding these keywords is essential because they form the foundation of Python's syntax and control structures.

Some of the most commonly used Python keywords include if, else, while, for, def, class, import, from, return, True, False, None, and, or, not, in, is, try, except, finally, with, as, break, continue, pass, global, nonlocal, lambda, yield, and del.

These keywords are highlighted differently in VS Code because the editor recognizes them as special Python syntax. Notice how VS Code uses color coding to help you identify different types of code elements. Keywords typically appear in a different color than variables or strings.

Listing Python Keyword Task

Copy this code into your exercise.py file:

# Let's see Python keywords
import keyword
print(keyword.kwlist)

To run this code, click the ▶ at the top right corner of VS Code. This shows you all the Python keywords. Don't worry about understanding the import or how this works - just run it and see what words Python considers special. Do you recognize any of these words?

Data Types

Python supports several built-in data types that allow you to work with different kinds of information. Understanding data types is crucial because different types of data require different operations and have different behaviors in your programs.

The fundamental data types in Python include integers for whole numbers, floats for decimal numbers, strings for text, booleans for true/false values, and more complex types like lists, tuples, dictionaries, and sets for storing collections of data.

Copy these data type examples into your exercise.py file:

# Numeric data types
age = 21                    # int (integer)
height = 5.9               # float (floating-point number)
temperature = -15.5        # float (can be negative)

# String data type
student_name = "Muhammad Ali"    # str (string)
course_title = 'Python Programming'  # str (single or double quotes)
description = """This is a multi-line
string that spans several lines."""   # str (triple quotes)

# Boolean data type
is_active = True           # bool (boolean)
has_submitted = False      # bool (boolean).

# Special data type
nothing = None             # NoneType (represents absence of value)

Each data type has specific characteristics and uses. Integers are perfect for counting and indexing, floats handle decimal calculations, strings manage text data, and booleans control logical operations. Collections like lists and dictionaries allow you to organize related data together.

Python provides built-in functions to check and convert between data types. The type() function tells you what type a variable is, while functions like int(), float(), str(), and bool() can convert between types when possible.

## Try this
print(type(age))
print(type(temperature))
print(type(student_name))
print(type(is_active))
print(type(nothing))

Import Statements

Import statements allow you to use code from other Python modules and libraries. Python's strength comes from its extensive standard library and the big ecosystem of third-party packages.

There are several ways to import modules in Python. You can import entire modules or import specific functions or classes from modules.

Copy these different types of import examples into your exercise.py file.

# Import entire modules
import math
import random
import datetime

# Using imported modules
circle_area = math.pi * (5 ** 2)
random_number = random.randint(1, 100)
current_date = datetime.date.today()

# Import specific functions from modules
from math import sqrt, pow, sin, cos
from random import choice, shuffle
from datetime import datetime, timedelta

# Using imported functions directly (no module prefix needed)
square_root = sqrt(25)
power_result = pow(2, 8)
random_choice = choice(['apple', 'banana', 'cherry'])

Different import styles serve different purposes. Importing entire modules keeps the namespace clean and makes it clear where functions come from. Importing specific functions can make your code more readable when you use certain functions frequently.

The placement of import statements matters. Python convention places all imports at the top of the file, after any module comments and docstrings but before anything else. To sum up, just put it at the top of the file, whether you are going to use it early on or later.

Input and Output Statements

Input and output statements are how your Python programs communicate with users. The input() function captures user input from the keyboard, while the print() function displays output to the screen.

The input() function always returns a string, regardless of what the user types. If you need numeric input, you must convert the string to the appropriate numeric type using functions like int() or float(). The print() function can display multiple values and offers various formatting options.

Copy this example into your exercise.py file

# Basic input and output
print("Welcome to the Grade Calculator!")
print("This program will calculate your course grade.")

# Getting user input (always returns a string)
student_name = input("Enter your name: ")
course_name = input("Enter the course name: ")

# Getting numeric input requires conversion
assignment_score = float(input("Enter your assignment score (0-100): "))
exam_score = float(input("Enter your exam score (0-100): "))
participation_score = float(input("Enter your participation score (0-100): "))

# Calculating final grade
final_grade = (assignment_score * 0.4) + (exam_score * 0.5) + (participation_score * 0.1)

# Formatted output using string concatenation
print()
print("Student: " + student_name)
print("Course: " + course_name)
print("Final Grade: " + str(final_grade) + "%")

Exercise 1: Student Information System Task

Create a new file called exercise1.py in the /labs/lab05/ directory. This exercise combines variables, data types, and input/output statements.

Write a program that:

1. Asks the user for their name, age, and course code
2. Stores this information in appropriately named variables
3. Displays the student information and shows the data types

Exercise 2: Circle Calculator Task

Create a new file called exercise2.py in the /labs/lab05/ directory. This exercise combines import statements, variables, and data types.

Write a program that:

1. Imports the math module
2. Takes a radius of circle from the user
3. Print the area and circumference of the circle

Exercise 3: Random Student Selector Task

Create a new file called exercise3.py in the /labs/lab05/ directory. This exercise combines import statements, variables, and input/output statements.

Write a program that:

1. Imports the random module
2. Takes the student's class name from the user
3. Generates a random number and displays class information

Exercise 4: Shopping Cost Calculator Task

Create a new file called exercise4.py in the /labs/lab05/ directory. This exercise combines variables, data types, and input/output statements.

Write a program that:

1. Takes item name and price from the user
2. Creates variables for quantity (3 items) and tax rate (6%)
3. Calculates and displays subtotal, tax amount, and total cost

Exercise 5: Average Score Calculator Task

Create a new file called exercise5.py in the /labs/lab05/ directory. This exercise combines variables, data types, and input/output statements.

Write a program that:

1. Takes three test scores from the user
2. Calculates the total score and average score
3. Displays all individual scores, total, and average

Exercise 6: Time Converter Task

Create a new file called exercise6.py in the /labs/lab05/ directory. This exercise combines variables, data types, and input/output statements.

Write a program that:

1. Takes time in minutes from the user
2. Converts minutes to hours and remaining minutes
3. Displays the original minutes and converted time format

Exercise 7: Advanced Math Operations Task

Create a new file called exercise7.py in the /labs/lab05/ directory. This exercise combines import statements, variables, and data types.

Write a program that:

1. Imports the math module
2. Takes one number from the user
3. Calculates and displays: square root, square (power of 2), cube (power of 3), and sine value

Commit and Push Your Work

After completing all the exercises, save all your files and commit them to your repository. Make sure your files are properly saved in the /labs/lab05/ directory, including exercise.py, exercise1.py, exercise2.py, exercise3.py, exercise4.py, exercise5.py, exercise6.py, and exercise7.py.

Use VS Code's source control panel to stage your changes, add a meaningful commit message like "Complete Lab 5: Python Program Components with Exercises", and push your changes to GitHub. Check your repository online to ensure all files have been uploaded successfully and that any automated tests pass.