🐍 Python Coach - Python Cheat Sheet

Why Print Statements?

Print statements let you display messages on the screen - like sending a message to the user. Every program needs to communicate with its users!

What is print()?

The print() function displays text on the screen. Think of it like a loudspeaker for your code.

How to use print():

• Write print()
• Put your message inside the parentheses
• Wrap text in quotes: "like this" or 'like this'

Example 1: Hello World

The simplest program! Print displays text on screen.

Example 2: Multiple Messages

Each print() creates a new line of output.

Example 3: Numbers Don't Need Quotes

Text needs quotes, but numbers work without them!

Example 4: Real Use

Real programs use print() to give users feedback.

Common Mistakes

Why Comments?

Comments let you add notes in your code that Python ignores - like sticky notes for programmers! Professional programmers use comments to explain what their code does.

What are Comments?

Comments are notes in your code that Python completely ignores. They help you (and others) understand what the code does.

How to write comments:

• Start with the # symbol
• Write your note after the #
• Python ignores everything after # on that line

Example 1: Your First Comment

Comments are written with # and Python ignores them completely.

Example 2: Explaining Code

Use comments to explain what your code does - helpful when you come back later!

Example 3: Comments with Variables

Comments help document what variables store - very useful in longer programs.

Common Mistakes

Why Variables?

Variables are like labeled boxes that store information - you can put things in them, take things out, and use them later! They're the most fundamental building block of programming.

What are Variables?

A variable is a named storage location. Think of it like a labeled box where you store information.

How to create a variable:

• Choose a name (like name or age)
• Use an equals sign =
• Put the value: name = "Alex"
• The = means "store this value" - it's called assignment

Example 1: Storing Your Name

Store your name in a variable and print it.

Example 2: Numbers Work Too!

Variables can store numbers (no quotes needed for numbers).

Example 3: Changing Values

You can change what's stored in a variable anytime!

Common Mistakes

Why Data Types?

Python treats numbers, text, and true/false values differently - understanding types prevents errors! Knowing data types is essential for working with user input and calculations.

What are Data Types?

Every value in Python has a type that determines what you can do with it. There are 4 main types you need to know:

The 4 Main Types:

• int - Whole numbers like 42, -17, 0
• float - Decimal numbers like 3.14, -2.5, 0.0
• str - Text in quotes like "Hello", '123'
• bool - True or False (no quotes!)

Check types: Use type(value) to see what type something is!

Example 1: Checking Types

Use type() to check what type a value is - this is super useful for debugging!

Example 2: Converting with int()

input() always gives you a string - use int() to convert to a number for math!

Example 3: Converting to float()

Use float() when you need decimal numbers for precise calculations.

Example 4: Converting to str()

Use str() to convert numbers to text so you can combine them with + for display.

Common Mistakes

Why Arithmetic Operators?

Python can do all the math you need - from simple addition to powerful calculations! Understanding operators is essential for games, calculators, and data analysis.

What are Arithmetic Operators?

Operators are symbols that perform calculations on numbers. Python has 7 main arithmetic operators:

The 7 Operators:

• + Addition (10 + 5 = 15)
• - Subtraction (10 - 5 = 5)
• * Multiplication (10 * 5 = 50)
• / Division (10 / 5 = 2.0) - Always returns a float
• // Floor Division (10 // 3 = 3) - Returns whole number
• % Modulus (10 % 3 = 1) - Returns remainder
• ** Exponent (2 ** 3 = 8) - Power of

Operator Precedence (BIDMAS/PEMDAS)

Order matters! Python follows BIDMAS/PEMDAS rules:

• Brackets / Parentheses ()
• Indices / Exponents **
• Division /, Multiplication *, Modulus %, Floor Division // (left to right)
• Addition +, Subtraction - (left to right)

Example 1: Basic Math

Example 2: Division Types

Notice the difference between / and // (Floor Division).

Example 3: Order of Operations

Multiplication happens before addition (PEMDAS/BIDMAS). Use parentheses () to force a different order.

Common Mistakes

Why User Input?

User input makes programs interactive - it's like having a conversation with your code! Every game, app, and website needs to get information from users.

What is input()?

The input() function asks the user a question and waits for their answer. You must store the answer in a variable to use it later.

How to use input():

• Write input() with your question in quotes
• Store the answer in a variable
• Example: name = input("What's your name? ")
• IMPORTANT: input() always gives you text (a string), even if the user types a number!

Example 1: Basic Input

Ask a question and store the answer in a variable.

Example 2: Personalized Greeting

Use + to combine the user's input with your message.

Example 3: Multiple Inputs

You can ask multiple questions and use all the answers!

Example 4: Input with Numbers

Remember: input() gives you text! Convert to numbers with int() or float().

Common Mistakes

Why String Concatenation?

String concatenation lets you join pieces of text together - like building sentences from smaller parts! It's how programs create personalized messages.

What is String Concatenation?

Concatenation means joining strings together. Think of it like linking train carriages - you connect them end-to-end!

How to use the + operator:

• Put the + symbol between strings
• Python joins them automatically
• Example: "Hello" + "World" gives you "HelloWorld"
• Add spaces: "Hello " + "World" gives you "Hello World"

Example 1: Basic Joining

The + operator joins two strings into one.

Output: HelloWorld

Example 2: Adding Spaces

Don't forget spaces! "Hello " + "World" is different from "Hello" + "World"

Output:
Hello World
Python is awesome!

Example 3: Variables with Concatenation

You can join variables and strings together.

Output: Alex Smith

Example 4: Building Messages

Real programs use concatenation to create personalized output.

Output:
Player: Sam
Now playing: Python Quest

Common Mistakes

Why String Methods?

String methods are like tools that let you transform and manipulate text - make it LOUD, quiet, or measure it! They're essential for processing user input and formatting text.

What are String Methods?

Methods are special functions that belong to strings. You call them by putting a dot after a string.

Useful String Methods:

• .upper() - Converts all letters to UPPERCASE
• .lower() - Converts all letters to lowercase
• len() - Counts characters (length) - NOTE: This one doesn't use a dot!
• .strip() - Removes spaces from start and end

Example 1: Making Text LOUD

The .upper() method converts all letters to uppercase.

Output: HELLO

Example 2: Making Text Quiet

The .lower() method converts all letters to lowercase.

Output: python

Example 3: Counting Characters

len() tells you how many characters are in a string (including spaces!).

Output: 11

Example 4: Real-World Use

Methods are perfect for cleaning up user input and making comparisons case-insensitive.

Common Mistakes

Why String Slicing?

Strings are like lists of characters you can slice, dice, and manipulate! This is essential for processing data, extracting information, and text manipulation.

What is String Slicing?

Every character in a string has a position (index). Python counts from 0!

Key Techniques:

• text[0] - Get single character (index 0 = first character)
• text[0:5] - Slice (characters from index 0 up to, but NOT including, index 5)
• text[-1] - Last character (negative indexing counts from end)
• .split() - Split string into a list at spaces
• .replace() - Replace text with new text

Example 1: Accessing Characters by Index

Use square brackets [] with an index number to get a specific character.

Output:
P
n

Example 2: Slicing Strings

Use [start:stop] to get a section. The stop position is NOT included!

Output:
Hello
World

Example 3: Splitting Strings into Lists

Use .split() to break text into separate words (creates a list).

Output:
['Hello', 'my', 'name', 'is', 'Alex']
Hello

Example 4: Replacing Text

Use .replace(old, new) to swap text.

Output: Hello Python

Example 5: Combining Techniques

Real programs combine multiple string operations.

Output:
Username: user
Domain: example.com

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Why If Statements?

If statements let your program make decisions - like choosing different paths based on conditions! This is how programs become intelligent and responsive.

What are If Statements?

If statements check whether something is true or false, then execute code accordingly.

Basic Structure:

• if condition: - Check if condition is true
• Don't forget the colon (:)
• Indent the code inside (4 spaces or Tab)
• Use comparison operators: >, <, == (equals), != (not equals), >=, <=

Example 1: Simple If Statement

Check a condition and run code only if it's true.

Output: You can create a social media account

Example 2: Comparison Operators

Different ways to compare values.

Output:
Great job!
You scored some points

Example 3: If-Else (Two Paths)

Use else to handle when the condition is false.

Output: Keep trying!

Example 4: If-Elif-Else (Multiple Paths)

Use elif to check multiple conditions in order. Python stops at the first true condition!

Output: Nice weather

Example 5: Compound Conditions with 'and'

Use and when BOTH conditions must be true. Use or when at least ONE must be true.

Output:
You can watch the movie
Enjoy the show!

Common Mistakes

Why Elif and Else?

Programs often need to choose between MORE than two options - like grades A, B, C, D, or F! Elif and else let you handle multiple paths elegantly.

What are Elif and Else?

Elif (short for "else if") lets you check multiple conditions in sequence. Python checks them in order and stops at the first true one.

The Three-Part Structure:

• if - First condition to check
• elif - Additional conditions (can have multiple!)
• else - Fallback when nothing else is true

Example 1: Grade Calculator

Check conditions in order - Python stops at the first match!

Output: Grade: C

Example 2: Age Categories

Handle multiple age ranges with elif.

Output: Teenager

Example 3: Menu Selection

Real programs use elif for menu choices.

Common Mistakes

Why Boolean Logic?

Real programs need to check multiple conditions at once - like "if age > 18 AND has_license"! Boolean logic powers every decision in games, apps, and websites.

What is Boolean Logic?

Boolean logic lets you combine multiple True/False conditions using three special operators:

The Three Operators:

• and - True only if BOTH sides are True
• or - True if AT LEAST ONE side is True
• not - Reverses the value (True becomes False, False becomes True)

Example 1: Using 'and' - Both Must Be True

Both conditions must be True for the code to run.

Output: You can drive!

Example 2: Using 'or' - At Least One Must Be True

Only ONE condition needs to be True for the code to run.

Output: Sleep in!

Example 3: Using 'not' - Reversing a Condition

The not operator flips True to False and False to True.

Output: Go outside!

Example 4: Combining Operators

You can combine and, or, and not in complex conditions.

Output: Access granted

Common Mistakes

Why For Loops?

For loops let you repeat code a specific number of times - perfect for counting, processing lists, or repeating tasks! When you know HOW MANY times to repeat, use a for loop!

What are For Loops?

For loops repeat code for each item in a sequence.

Key Concepts:

• for i in range(5): - Repeat 5 times (counts 0, 1, 2, 3, 4)
• for item in list: - Repeat once for every item in a list
• Don't forget the colon (:) and indentation
• range(n) starts at 0 and goes up to n-1

Example 1: Using range()

The simplest for loop - i will be 0, 1, 2, 3, 4 automatically!

Output:
0
1
2
3
4

Example 2: Repeating Actions

Use for loops to repeat the same action multiple times.

Output:
Hello!
Hello!
Hello!

Example 3: Custom Starting Number

Use range(start, stop) to count from a specific number.

Output:
Count: 1
Count: 2
Count: 3
Count: 4
Count: 5

Example 4: Looping Through a List

For loops can iterate through every item in a list.

Output:
Hello, Alex
Hello, Sam
Hello, Jo

Example 5: Calculating a Total

Use for loops to process data and accumulate results.

Output:
Total: 350
Average: 87.5

Common Mistakes

Why While Loops?

While loops let your code repeat actions automatically - like counting, checking, or waiting until something happens! Use while loops when you DON'T know exactly how many times to repeat.

What are While Loops?

While loops repeat code over and over as long as a condition is true. Think of them like saying "keep doing this WHILE something is true."

Key Points:

• You must change the condition inside the loop, or you'll get an infinite loop!
• Structure: while condition:
• Use comparison operators: <, >, ==, !=, <=, >=

Example 1: Counting Up

A simple while loop that counts from 1 to 5.

Output:
1
2
3
4
5

Example 2: Simple Countdown

Count down from 5 to 1, then blast off!

Output:
5
4
3
2
1
Blast off!

Example 3: Loop Until User Says Stop

Keep asking the user until they type "stop".

Output (if user enters 'go' then 'stop'):
Type 'stop' to exit: go
Type 'stop' to exit: stop
Loop finished!

Example 4: Number Guessing Game

Loop until the user guesses correctly.

Common Mistakes

Why Lists?

Lists let you store multiple values in one variable - like a shopping list, a to-do list, or a collection of scores! Instead of making 10 variables, make 1 list!

What are Lists?

Lists are containers that hold multiple values in order. Each item has a position (index).

Key Concepts:

• Use square brackets [ ] to create them
• Values inside are separated by commas
• Python starts counting at 0, not 1!
• Use len() to count items
• Use .append() to add items to the end

Example 1: Creating Lists

Create a list with square brackets and commas between items.

Output:
['Alex', 'Sam', 'Jo']
[85, 92, 78, 95]

Example 2: Accessing Items by Index

IMPORTANT: Python starts counting at 0, not 1!

Output:
Alex
Sam
Jo

Example 3: Counting Items with len()

Use len() to find out how many items are in a list.

Output: Total names: 4

Example 4: Adding Items with .append()

Use .append() to add items to the end of a list.

Output:
Total tasks: 3
First task: homework
['homework', 'practice', 'read']

Example 5: Looping Through Lists

Combine lists with for loops to process every item.

Output:
Score: 85
Score: 92
Score: 78
Score: 95

Common Mistakes

Why 2D Lists?

Games, spreadsheets, and maps all use grids - 2D lists let you store data in rows and columns! Essential for tic-tac-toe, battleship, seating charts, and image processing.

What are 2D Lists?

A 2D list is a list of lists - like a table with rows and columns.

Key Concepts:

• The outer list holds the rows
• Each inner list is a row containing the columns (items)
• Use list[row][column] to access items
• Row index comes first, then column index

Example 1: Creating a 2D List

Create a grid by making a list of lists.

Output: [[1, 2, 3], [4, 5, 6], [7, 8, 9]]

Example 2: Accessing Specific Items

Use [row][column] with TWO separate brackets!

Output:
1
3
5
7

Example 3: Changing an Item

Update a specific position in the grid.

Output: ['.', 'O', '.']

Example 4: Looping Through 2D Lists

Use nested for loops to access every item in a 2D list.

Output:
1 2 3
4 5 6

Example 5: Tic-Tac-Toe Board

2D lists are perfect for game boards!

Output:
['X', 'O', 'X']
['O', 'X', 'O']
['.', '.', 'X']

Common Mistakes

Why Functions?

Don't Repeat Yourself! Functions let you write code once and use it many times! Real programmers use functions for EVERYTHING - they make code organized, readable, and maintainable.

What Are Functions?

A function is a named, reusable block of code that performs a specific task. They make code organized, easier to read, and simpler to debug.

Key Concepts:

• Define with the def keyword
• Must end with a colon (:)
• Code inside must be indented (4 spaces)
• Call it by name followed by parentheses: do_something()

Example 1: Defining and Calling

Create a simple function and call it multiple times.

Output:
Hello!
Hello!

Example 2: Functions Make Code Reusable

Write the code once, use it many times!

Output:
Welcome to Python Coach!
Let's learn together!

Example 3: Functions Without Parameters

Simple functions that do the same thing every time.

Output:
1. Start Game
2. Load Game
3. Quit

Common Mistakes

Why Parameters and Return?

Parameters let functions receive information, and return lets functions give back results! This makes functions incredibly powerful and flexible.

What are Parameters?

Parameters are variables listed inside the parentheses in the function definition. They let the function receive information when it's called.

Key Concepts:

• Parameters - Variables in the function definition
• Arguments - Actual values passed when calling
• return - Sends a value back to the caller

Example 1: Parameters (Giving Data to a Function)

Parameters make functions flexible - they can work with different data!

Output:
Hello, Alex!
Hello, Sam!

Example 2: Multiple Parameters

Functions can accept multiple pieces of information.

Output:
Area: 50
Area: 21

Example 3: The Return Statement

The return keyword sends a value back to the code that called the function.

Output:
12
52

Example 4: Return vs Print

Return gives data back, print just displays it. Return is more powerful!

Output:
Total: 8
Double: 16

Example 5: Real-World Function

Combine parameters and return for powerful, reusable code.

Output:
Grade 1: A
Grade 2: C

Common Mistakes

Why File Writing?

File writing is crucial for saving settings, recording high scores, logging program activity, or creating output reports. It lets your program persistently store information!

What is File Writing?

To write data, you must open the file in the correct mode:

Two Writing Modes:

• "w" (Write Mode) - Creates a new file or overwrites an existing file (erases old content!)
• "a" (Append Mode) - Creates a new file or adds content to the end of an existing file
• Use .write(content) to put data into the file
• You must manually add \n for new lines

Example 1: Overwriting with "w"

Write mode creates a new file or completely replaces existing content.

Warning: If run again, the previous content is erased!

Example 2: Appending with "a"

Append mode adds content to the end without erasing existing data.

Note: Each time this runs, a new entry is ADDED to the end.

Example 3: Writing Multiple Lines

Remember to add \n for each new line!

Example 4: Saving User Data

Real programs save user input to files.

Common Mistakes

Why Dictionaries?

Store information with labels! Like a real dictionary: look up a word (key) to get its meaning (value). Perfect for storing user profiles, game stats, and settings.

What are Dictionaries?

A dictionary is a collection of key-value pairs. Keys must be unique (like words in a dictionary), and they point to a value (the definition).

Key Concepts:

• Use curly braces { } to create them
• Key and value separated by a colon (:)
• Pairs separated by commas
• Keys must be unique
• Access values using dict['key']

Example 1: Creating a Dictionary

Create a dictionary with curly braces and key:value pairs.

Output: {'name': 'Sam', 'age': 16, 'score': 95}

Example 2: Accessing Values

Access values using the key in square brackets.

Output:
Name: Sam
Age: 16

Example 3: Adding New Key-Value Pairs

Add new data by assigning to a new key.

Output: {'name': 'Sam', 'age': 16, 'city': 'New York', 'score': 95}

Example 4: Changing Values

Update existing values by reassigning to the key.

Output: New score: 100

Example 5: Looping Through Items

Loop through all key-value pairs using .items() method.

Output:
name is Sam
age is 16
score is 95

Common Mistakes

Why Linear Search?

How do you find something in a list? Check each item, one by one, until you find it! This is called Linear Search - the most fundamental searching algorithm.

What is Linear Search?

Linear search is an algorithm that finds a target value by checking every single item in a list sequentially, from the first item to the last.

Key Characteristics:

• Simple and works on any type of list
• Slow for very large lists (might check every item)
• Best for small lists or unsorted data
• Returns the index where found, or -1 if not found

Example 1: Basic Search Logic

Use a for loop with range(len(list)) to get the indices.

Output: Found at index: 2

Example 2: Linear Search Function

Wrap the search logic in a function that returns the index, or -1 if not found.

Example 3: Using the Search Function

Call the function and check if the item was found.

Output: Mango is at index 3

Example 4: Searching for Numbers

Linear search works with any data type!

Output: Score 95 found at position 3

Example 5: Counting Comparisons

Understand how linear search works by counting comparisons.

Output: Found after 5 comparisons

Common Mistakes

Why Error Handling?

Stop your programs from crashing! Handle errors gracefully and keep your code running smoothly. Professional programs don't crash - they handle errors intelligently.

What is Error Handling?

Python provides the try...except structure to manage errors (exceptions) that could cause the program to stop.

Key Concepts:

• try: - Put the code that might cause an error here
• except: - Put the code that handles the error here
• If no error occurs in try, the except block is skipped
• ValueError - Common error when converting invalid data

Example 1: Handling Invalid Input

The int(input()) conversion causes a ValueError if the user types letters.

Output (if user enters 'hello'):
Error: Please enter only numbers!

Example 2: Specific Error Types

Catch specific errors to provide better error messages.

Example 3: Validating Input in a Loop

Combine try/except with a while loop to force valid input.

Example 4: File Handling with Error Protection

Handle errors when working with files that might not exist.

Example 5: Division Calculator with Error Handling

Complete example combining multiple error types.

Common Mistakes

Why File Reading?

Real programs need to load data from files - user settings, game saves, and datasets! File reading lets your programs persist data and work with external information.

What is File Reading?

You need to open a file, read its content, and then close it.

Key Concepts:

• open("data.txt", "r") - Opens the file "data.txt" in read ("r") mode
• Best Practice: Use with open(...) as file: statement
• It automatically closes the file, even if errors occur
• .read() - Reads entire file into a single string
• .readlines() - Reads all lines into a list of strings

Example 1: Reading the Whole File

Use .read() to get all content as one string.

Output: Hello from the file!

Example 2: The 'with' Statement

The with statement automatically closes the file - best practice!

Example 3: Reading Line by Line

Use .readlines() to get a list of all lines. Use .strip() to remove newline characters.

Output (for a file with two lines):
First line.
Second line.

Example 4: Processing File Data

Read a file and process each line.

Example 5: Error Handling with Files

Combine file reading with try/except for robust code.

Common Mistakes

Why Bubble Sort?

Imagine bubbles rising in water - the biggest ones float to the top first! That's exactly how bubble sort works with numbers. Bubble sort is the simplest sorting algorithm - perfect for learning how sorting works!

What is Bubble Sort?

Bubble sort repeatedly compares adjacent pairs of items and swaps them if they are in the wrong order. Each pass moves the next largest item to its final position at the end of the list (like a bubble rising).

Key Concepts:

• Requires nested loops
• The outer loop runs for the number of passes (i)
• The inner loop runs for the comparisons (j)
• Compare adjacent items: items[j] and items[j + 1]
• Swap if in wrong order using Python's swap syntax

Example 1: The Swap Operation

Python makes swapping easy with simultaneous assignment.

Output: [2, 5, 8, 1]

Example 2: Basic Bubble Sort

The complete bubble sort algorithm with nested loops.

Output: [12, 22, 25, 34, 64]

Example 3: Bubble Sort with Visualization

See how bubble sort works by printing after each pass.

Output:
Pass 1
[2, 5, 1, 8, 9]
Pass 2
[2, 1, 5, 8, 9]
Pass 3
[1, 2, 5, 8, 9]
Pass 4
[1, 2, 5, 8, 9]
Final sorted: [1, 2, 5, 8, 9]

Example 4: Bubble Sort Function

Wrap bubble sort in a reusable function.

Output: [78, 85, 88, 92, 95]

Example 5: Descending Order

Change the comparison operator to sort in descending order.

Output: [9, 8, 5, 2, 1]

Common Mistakes

Why Merge Sort?

Merge sort is used because simple sorts like bubble sort are SLOW. For 1000 items, bubble sort is ~50 times slower than merge sort. Merge sort uses divide and conquer - it's how Python's built-in sort() works!

What is Merge Sort?

The core idea is Divide, Conquer, and Combine.

The Three Steps:

• 1. Divide: The list is split into two halves
• 2. Conquer: Each half is recursively sorted until the list size is 1 (base case)
• 3. Combine (Merge): The two sorted halves are merged back together
• A single item list is the base case and is considered sorted
• The merging step compares the first items of the two lists

Example 1: Understanding the Divide Step

Split the list into two halves using the middle index.

Output:
Original: [38, 27, 43, 3, 9, 82, 10]
Left half: [38, 27, 43]
Right half: [3, 9, 82, 10]

Example 2: The Merge Function

Merge two sorted lists into one sorted list.

Output: [3, 9, 10, 27, 38, 82]

Example 3: Complete Merge Sort

The full recursive merge sort algorithm.

Output: [3, 9, 10, 27, 38, 43, 82]

Example 4: Visualizing Merge Sort

See the divide and conquer process in action.

Common Mistakes

Why Stacks and Queues?

Stacks and queues are fundamental data structures used everywhere in computing - from browser history (stack) to printer queues (queue)! Understanding these structures is essential for GCSE Computer Science.

What are Stacks?

A stack is a Last In, First Out (LIFO) data structure - like a stack of plates! The last plate you put on top is the first one you take off.

Stack Operations:

• Push - Add an item to the top (use .append())
• Pop - Remove and return the top item (use .pop())
• Peek - Look at the top item without removing it (use [-1])
• isEmpty - Check if stack is empty (use len() == 0)

Example 1: Stack Operations

Implement a stack using Python lists.

Output:
Stack: ['Page 1', 'Page 2', 'Page 3']
Top: Page 3
Removed: Page 3
Stack: ['Page 1', 'Page 2']

What are Queues?

A queue is a First In, First Out (FIFO) data structure - like a queue of people! The first person in line is the first person served.

Queue Operations:

• Enqueue - Add an item to the back (use .append())
• Dequeue - Remove and return the front item (use .pop(0))
• Front - Look at the front item (use [0])
• isEmpty - Check if queue is empty (use len() == 0)

Example 2: Queue Operations

Implement a queue using Python lists.

Output:
Queue: ['Customer 1', 'Customer 2', 'Customer 3']
Front: Customer 1
Served: Customer 1
Queue: ['Customer 2', 'Customer 3']

Example 3: Stack - Browser History

Real-world example: implementing browser back button.

Output:
Visiting: google.com
Visiting: youtube.com
Visiting: github.com
Back to: youtube.com
Back to: google.com

Example 4: Queue - Print Jobs

Real-world example: managing a printer queue.

Output:
Added: Document 1
Added: Document 2
Added: Document 3
Printing: Document 1
Printing: Document 2
Remaining: ['Document 3']

Common Mistakes

Why Authentication?

Every app and website needs to verify who's using it. Authentication means proving you are who you say you are (your identity). It's fundamental to modern computing security!

What is Authentication?

The core process is to Verify Identity using a Username + Password. Authorization is a different step that determines what you can do after logging in (your permissions).

Implementation Steps:

• 1. Storage: Store users (e.g., in a dictionary: {username: password})
• 2. Input: Ask the user for their username and password
• 3. Check: Check if the username exists in your storage
• 4. Validate: Compare the provided password with the stored password

Example 1: Basic User Storage

Store users in a dictionary with username as key and password as value.

Output: Registered users: ['alice', 'bob', 'charlie']

Example 2: Simple Login

Check if username exists and password matches.

Example 3: Registration Function

Let users create new accounts with validation.

Example 4: Complete Authentication System

Combine registration and login with validation.

Security Best Practices

Example 5: Password Strength Validation

Check that passwords meet security requirements.

Common Mistakes