Coding: Intro to computer science – Python

What is Python?

Python is a high-level, interpreted programming language known for its simplicity and readability. Created by Guido van Rossum and first released in 1991, Python’s design philosophy emphasizes code readability and simplicity, making it an excellent choice for beginners and experienced programmers alike. Python is versatile and can be used for a variety of applications, including web development, data analysis, artificial intelligence, scientific computing, and more.

Key features of Python include:

• Easy to Read and Write: Python’s syntax is clear and intuitive, which reduces the cost of program maintenance and development.
• Interpreted Language: Python is executed line by line, which makes debugging easier and quicker.
• Dynamic Typing: Python does not require explicit declaration of variable types, allowing for more flexible code.
• Extensive Standard Library: Python comes with a large standard library that supports many common programming tasks, such as connecting to web servers, reading and modifying files, and more.
• Cross-Platform: Python runs on many operating systems, including Windows, macOS, and various distributions of Linux.

Installing Python and Setting Up the Environment

Before you start coding in Python, you need to install it on your computer. Here’s a step-by-step guide to installing Python:

For Windows:

1. Download the Installer:
   • Go to the official Python website: python.org.
   • Click on the “Downloads” tab and select the Python version compatible with your system. The latest stable version is recommended.
2. Run the Installer:
   • Open the downloaded file to run the installer.
   • Ensure you check the box that says “Add Python to PATH” before clicking “Install Now”. This will make Python accessible from the command line.
3. Verify the Installation:
   • Open Command Prompt (you can search for it in the Start menu).
   • Type python --version and press Enter. You should see the installed Python version number.

For macOS:

1. Download the Installer:
   • Go to python.org and click on “Downloads”.
   • Choose the latest version of Python for macOS.
2. Run the Installer:
   • Open the downloaded .pkg file to run the installer.
   • Follow the prompts to complete the installation.
3. Verify the Installation:
   • Open Terminal (you can find it in Applications > Utilities).
   • Type python3 --version and press Enter. The installed Python version should be displayed.

For Linux:

Python is usually pre-installed on most Linux distributions. To check if Python is installed, open a terminal and type:

python3 --version

If Python is not installed, you can install it using the package manager. For example, on Debian-based systems like Ubuntu, you can use:

sudo apt update
sudo apt install python3

Running Your First Python Program

Once Python is installed, you can start writing and running Python programs. Let’s create a simple program that prints “Hello, World!” to the screen.

1. Open a Text Editor:
   • You can use any text editor, such as Notepad (Windows), TextEdit (macOS), or gedit (Linux). Alternatively, you can use an Integrated Development Environment (IDE) like PyCharm, VS Code, or Sublime Text.
2. Write the Code:
   • In your text editor, type the following code:

print("Hello, World!")

3. Save the File:

• Save the file with a .py extension. For example, you can save it as hello.py.

4. Run the Program:

• Open a terminal or command prompt.
• Navigate to the directory where you saved the file using the cd command. For example

cd path/to/your/file

Run the program by typing:

python hello.py

You should see the output:

Hello, World!

Congratulations! You’ve just written and executed your first Python program. As you continue learning, you’ll explore more features and capabilities of Python that will help you develop more complex and useful applications. You can also using some online python compiler for coding practice.

Computational Thinking with Variables

The Programming Platform

Before diving into coding, it’s important to understand the environment in which you’ll be writing and executing your programs. The programming platform refers to the tools and interfaces that support coding activities. Here are the essential components of a Python programming platform:

1. Text Editor or Integrated Development Environment (IDE):
   • A text editor or IDE is where you write your code. Popular text editors include VS Code, Sublime Text, and Atom. IDEs like PyCharm and Jupyter Notebook provide additional features such as debugging tools, code suggestions, and project management.
2. Interpreter:
   • The Python interpreter is a program that reads and executes your Python code. When you install Python, the interpreter is included, allowing you to run your programs from the command line or terminal.
3. Command Line or Terminal:
   • This is where you run your Python scripts. You can open a command line interface (CLI) or terminal window to execute your Python files by typing commands.

Program Execution

Program execution in Python involves running the code you’ve written to perform specific tasks. Here’s a basic outline of the process:

1. Write the Code:
   • Open your text editor or IDE and write your Python code. For example, you might write a program to calculate the sum of two numbers.
2. Save the File:
   • Save your code with a .py extension. For instance, sum.py.
3. Run the Program:
   • Open your command line or terminal.
   • Navigate to the directory where your file is saved using the cd command.
   • Execute the program by typing python sum.py and pressing Enter.

Variables and Data Types (int, float, string, bool)

Variables are used to store data that can be used and manipulated within a program. Python supports several data types:

1. Integer (int):
   • Whole numbers, positive or negative, without decimals. Example:

age = 25

2. Float (float):

• Numbers that contain a decimal point. Example:

price = 19.99

3. String (str):

A sequence of characters enclosed in quotes. Example:

name = "Alice"

4. Boolean (bool):

• Represents True or False values. Example:

is_student = True

Basic Operations and Arithmetic Expressions

Python supports various basic operations and arithmetic expressions to manipulate data. Here are some common ones:

Arithmetic Operations:

Addition (+): Adds two numbers

result = 10 + 5  # result is 15

Subtraction (-): Subtracts one number from another.

result = 10 - 5  # result is 5

Multiplication (*): Multiplies two numbers

result = 10 * 5  # result is 50

Division (/): Divides one number by another:

result = 10 / 5  # result is 2.0

Modulus (%): Returns the remainder of a division:

result = 10 % 3  # result is 1

2. Assignment Operations:

Assign values to variables using “=”

x = 10
y = 5
x += y  # x is now 15

3. Comparison Operations:

Compare values using ==, !=, >, <, >=, and <=

x = 10
y = 5
print(x > y)  # True

Comments and Code Readability

Comments are crucial for making your code understandable. They are ignored by the interpreter and are used to explain the code to anyone reading it, including your future self.

1. Single-line Comments:
   • Use the # symbol to add a comment on a single line.

# This is a single-line comment
x = 10  # Assign 10 to x

2. Multi-line Comments:

• Use triple quotes (''' or """) to add comments spanning multiple lines

"""
This is a multi-line comment
that explains the following code
in detail.
"""
x = 10
y = 5
result = x + y

3. Code Readability:

• Use meaningful variable names to make your code more understandable

total_price = 19.99
number_of_items = 3

Follow the PEP 8 style guide for Python code to ensure consistency and readability. For example, use 4 spaces per indentation level and limit lines to 79 characters.
By mastering these foundational concepts, you’ll be well-equipped to write clear, efficient, and effective Python code.

Control Structures

Designing Algorithms with Conditionals

In programming, control structures enable you to dictate the flow of execution based on certain conditions or repeat actions multiple times. Conditionals allow your program to make decisions and execute different branches of code depending on various conditions.

Boolean Conditions

A Boolean condition evaluates to either True or False. These conditions are fundamental in controlling the flow of a program. For example:

is_raining = True
if is_raining:
    print("Take an umbrella.")
else:
    print("Enjoy the sunshine!")

Compound Boolean Expressions

Compound Boolean expressions combine multiple Boolean conditions using logical operators like and, or, and not. These operators allow you to create more complex conditions.

• and: True if both conditions are True.
• or: True if at least one condition is True.
• not: Inverts the Boolean value.

Example:

age = 20
has_ticket = True

if age >= 18 and has_ticket:
    print("You can enter the concert.")
else:
    print("You cannot enter the concert.")

Conditional Statements (if, elif, else)

Conditional statements execute different blocks of code based on whether a condition is true or false.

if Statement

The if statement executes a block of code if its condition is True.

temperature = 30
if temperature > 25:
    print("It's hot outside.")

elif Statement

The elif (else if) statement checks another condition if the previous if condition is False.

temperature = 20
if temperature > 25:
    print("It's hot outside.")
elif temperature > 15:
    print("It's warm outside.")

else Statement

The else statement executes a block of code if none of the preceding conditions are True

temperature = 10
if temperature > 25:
    print("It's hot outside.")
elif temperature > 15:
    print("It's warm outside.")
else:
    print("It's cold outside.")

Loops (for, while)

Loops allow you to execute a block of code multiple times.

for Loop

The for loop iterates over a sequence (such as a list, tuple, or string) and executes a block of code for each item.

fruits = ["apple", "banana", "cherry"]
for fruit in fruits:
    print(fruit)

while Loop

The while loop executes a block of code as long as its condition is True.

count = 0
while count < 5:
    print(count)
    count += 1

Break and Continue Statements

The break and continue statements alter the flow of loops.

• break: Exits the loop prematurely.

for i in range(10):
    if i == 5:
        break
    print(i)

continue: Skips the current iteration and moves to the next one.

for i in range(10):
    if i % 2 == 0:
        continue
    print(i)

Chained Conditionals

Chained conditionals allow you to check multiple conditions in sequence. Using if, elif, and else statements, you can create a series of checks.

score = 85
if score >= 90:
    print("Grade: A")
elif score >= 80:
    print("Grade: B")
elif score >= 70:
    print("Grade: C")
else:
    print("Grade: D or lower")

Nested Conditionals

Nested conditionals involve placing one conditional statement inside another. This allows for more complex decision-making processes.

num = 10
if num > 5:
    if num % 2 == 0:
        print("The number is greater than 5 and even.")
    else:
        print("The number is greater than 5 and odd.")
else:
    print("The number is 5 or less.")

Example: Putting It All Together

Here’s an example that combines various control structures to create a simple grading system:

def get_grade(score):
    if score >= 90:
        return "A"
    elif score >= 80:
        return "B"
    elif score >= 70:
        return "C"
    elif score >= 60:
        return "D"
    else:
        return "F"

scores = [95, 82, 67, 58, 91]
for score in scores:
    grade = get_grade(score)
    print(f"Score: {score}, Grade: {grade}")

This example uses conditional statements to determine the grade based on the score and a for loop to iterate over a list of scores. By mastering these control structures, you’ll be able to write more flexible and powerful Python programs.

Functions in Python

Defining and Calling Functions

Functions are reusable blocks of code designed to perform a specific task. They help in breaking down complex problems into simpler, manageable pieces, promoting code reusability and readability.

Defining a Function

To define a function in Python, use the def keyword followed by the function name and parentheses. The code block within the function is indented.

def greet():
    print("Hello, world!")

Calling a Function

To call a function, use its name followed by parentheses.

greet()  # Output: Hello, world!

Function Arguments and Return Values

Functions can accept inputs (arguments) and return outputs.

Function Arguments

Arguments are specified within the parentheses in the function definition. You can pass values to these arguments when calling the function.

def greet(name):
    print(f"Hello, {name}!")

greet("Alice")  # Output: Hello, Alice!

Default Arguments

You can provide default values for arguments. If no value is passed, the default is used.

def greet(name="world"):
    print(f"Hello, {name}!")

greet()  # Output: Hello, world!
greet("Bob")  # Output: Hello, Bob!

Return Values

Functions can return values using the return statement.

def add(a, b):
    return a + b

result = add(3, 5)
print(result)  # Output: 8

Built-in Functions and Modules

Python provides many built-in functions and modules to perform common tasks.

Built-in Functions

Some common built-in functions include:

• print(): Outputs text to the console.
• len(): Returns the length of an object.
• type(): Returns the type of an object.

print(len("Hello"))  # Output: 5
print(type(42))  # Output: <class 'int'>

Modules

Modules are files containing Python code that can be imported into your program to extend its functionality. The standard library includes many useful modules.

import math

print(math.sqrt(16))  # Output: 4.0

Function Control Flow

The control flow within a function is similar to that in the main program. You can use conditional statements, loops, and other control structures inside functions.

def check_even_odd(number):
    if number % 2 == 0:
        return "Even"
    else:
        return "Odd"

print(check_even_odd(7))  # Output: Odd

Code Organization

Organizing your code into functions and modules makes it more manageable, readable, and reusable.

Using Functions for Code Organization

Functions help separate different parts of your code, making it easier to understand and maintain.

def get_user_input():
    return input("Enter your name: ")

def greet_user(name):
    print(f"Hello, {name}!")

def main():
    name = get_user_input()
    greet_user(name)

if __name__ == "__main__":
    main()

In this example, the main function coordinates the flow of the program, calling other functions as needed.

Modules for Code Organization

You can organize your code into modules by saving related functions in separate files. This promotes modularity and reusability.

greetings.py

def greet(name):
    print(f"Hello, {name}!")

main.py

import greetings

greetings.greet("Alice")  # Output: Hello, Alice!

By splitting your code into multiple files, you can maintain and update each part independently, improving overall code quality and manageability.

Example: Combining Everything

Here’s a comprehensive example that combines function definition, arguments, return values, control flow, and code organization:

math_operations.py

def add(a, b):
    return a + b

def subtract(a, b):
    return a - b

def multiply(a, b):
    return a * b

def divide(a, b):
    if b == 0:
        return "Cannot divide by zero"
    return a / b

main.py

import math_operations as mo

def main():
    x = 10
    y = 5
    print(f"{x} + {y} = {mo.add(x, y)}")
    print(f"{x} - {y} = {mo.subtract(x, y)}")
    print(f"{x} * {y} = {mo.multiply(x, y)}")
    print(f"{x} / {y} = {mo.divide(x, y)}")

if __name__ == "__main__":
    main()

In this example, the mathematical operations are defined in a separate module (math_operations.py), and the main program (main.py) imports and uses these functions. This separation of concerns makes the codebase easier to manage and extend.

Data Structures in Python

Python provides several built-in data structures that are essential for organizing and managing data efficiently. The primary data structures include lists, tuples, dictionaries, and sets.

Lists

Lists are ordered, mutable collections of items. They can store elements of different types, including other lists.

Creating a List

You can create a list using square brackets [].

fruits = ["apple", "banana", "cherry"]

Accessing List Elements

Elements in a list can be accessed by their index. Python uses zero-based indexing.

print(fruits[0])  # Output: apple
print(fruits[1])  # Output: banana

Modifying List Elements

Lists are mutable, so you can change their elements.

fruits[1] = "blueberry"
print(fruits)  # Output: ['apple', 'blueberry', 'cherry']

Adding and Removing Elements

You can add elements to a list using the append(), insert(), or extend() methods. Remove elements using remove(), pop(), or del.

# Adding elements
fruits.append("date")
print(fruits)  # Output: ['apple', 'blueberry', 'cherry', 'date']

# Removing elements
fruits.remove("blueberry")
print(fruits)  # Output: ['apple', 'cherry', 'date']

List Slicing

You can extract a portion of a list using slicing.

print(fruits[1:3])  # Output: ['cherry', 'date']

Tuples

Tuples are ordered, immutable collections of items. Once created, the elements of a tuple cannot be changed.

Creating a Tuple

You can create a tuple using parentheses ().

coordinates = (10.0, 20.0)

Accessing Tuple Elements

Like lists, tuple elements are accessed by their index.

print(coordinates[0])  # Output: 10.0

Tuple Packing and Unpacking

You can pack multiple values into a tuple and unpack them into variables.

# Packing
point = (1, 2)

# Unpacking
x, y = point
print(x)  # Output: 1
print(y)  # Output: 2

Dictionaries

Dictionaries are unordered collections of key-value pairs. They are indexed by keys, which can be of any immutable type.

Creating a Dictionary

You can create a dictionary using curly braces {}.

person = {
    "name": "Alice",
    "age": 25,
    "city": "New York"
}

Accessing Dictionary Elements

Elements in a dictionary are accessed using their keys.

print(person["name"])  # Output: Alice

Modifying Dictionary Elements

Dictionaries are mutable, so you can add, modify, or remove elements.

# Adding a new key-value pair
person["email"] = "[email protected]"
print(person)

# Modifying an existing value
person["age"] = 26
print(person)

# Removing a key-value pair
del person["city"]
print(person)

Dictionary Methods

Common dictionary methods include keys(), values(), and items().

print(person.keys())  # Output: dict_keys(['name', 'age', 'email'])
print(person.values())  # Output: dict_values(['Alice', 26, '[email protected]'])
print(person.items())  # Output: dict_items([('name', 'Alice'), ('age', 26), ('email', '[email protected]')])

Sets

Sets are unordered collections of unique elements. They are useful for storing and manipulating unique values.

Creating a Set

You can create a set using curly braces {} or the set() function.

fruits_set = {"apple", "banana", "cherry"}

Adding and Removing Elements

You can add elements to a set using the add() method and remove elements using the remove() or discard() methods.

# Adding an element
fruits_set.add("date")
print(fruits_set)  # Output: {'apple', 'banana', 'cherry', 'date'}

# Removing an element
fruits_set.remove("banana")
print(fruits_set)  # Output: {'apple', 'cherry', 'date'}

Set Operations

Sets support mathematical operations like union, intersection, difference, and symmetric difference.

set1 = {1, 2, 3}
set2 = {3, 4, 5}

# Union
print(set1 | set2)  # Output: {1, 2, 3, 4, 5}

# Intersection
print(set1 & set2)  # Output: {3}

# Difference
print(set1 - set2)  # Output: {1, 2}

# Symmetric Difference
print(set1 ^ set2)  # Output: {1, 2, 4, 5}

Example: Using Data Structures

Here is an example that uses various data structures to store and manipulate data.

# List
fruits = ["apple", "banana", "cherry"]
fruits.append("date")

# Tuple
coordinates = (10.0, 20.0)

# Dictionary
person = {
    "name": "Alice",
    "age": 25,
    "city": "New York"
}
person["email"] = "[email protected]"

# Set
unique_numbers = {1, 2, 3, 3, 4}
unique_numbers.add(5)

# Printing the structures
print(fruits)  # Output: ['apple', 'banana', 'cherry', 'date']
print(coordinates)  # Output: (10.0, 20.0)
print(person)  # Output: {'name': 'Alice', 'age': 25, 'city': 'New York', 'email': '[email protected]'}
print(unique_numbers)  # Output: {1, 2, 3, 4, 5}

By understanding and utilizing these data structures, you can efficiently organize, manage, and manipulate data in your Python programs.