Welcome to CodingGear’s Python Cheatsheet, your ultimate quick reference guide to mastering the Python programming language! Whether you’re a student, a professional developer, or just someone curious about Python, this Python cheat sheet is your go-to resource for all things Python.

In this cheat sheet, we’ve distilled the essential Python concepts, syntax, and best practices; from variables and data types to control flow, functions, and libraries, we’ve got you covered. Whether you need to quickly review a specific topic or learn something new, this Python cheat sheet is your trusty companion on your Python journey. You can bookmark this page or download the PDF version of 22 pages.

Here’s more to know about the cheat sheet:

• It is inspired by the bestselling Python Crash Course book by Eric Matthes and is based on a part of its curriculum. However, the explanations are based on my own understanding of Python and so are the code snippets. I might earn a small commission if you purchase this book through the link I just provided.

• I do not include the output or results of the code snippets when run to make this page just a little shorter, so I recommend you to copy and paste the code snippets and run them in a code editor.

And another thing, don’t hesitate to let us know what you think about the Python Cheatsheet. If there are any mistakes you came across or even content you wish to be added, just put them down there in the comments section. We’re here for you.

PART 1: SUMMARY OF THE VERY BASICS

1. Variables and Strings

Hello world:

The basic “Hello, World!” program to introduce Python.

print("Hello, World!")

Hello world with a variable: Printing a greeting using a variable.

greeting = "Hello, World!"
print(greeting)

Concatenation (combining strings): Combining strings using the + operator and f-strings.

first_name = "John"
last_name = "Doe"

#using + operator
full_name = first_name + " " + last_name

#using f-strings
greeting = f'Hello world, my name is {first_name} and my surname is {last_name}'

print(full_name)
print(greeting)

2. Lists

Make a list:

Creating a list of items.

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

Get the first item in a list: Accessing the first item of a list.

first_fruit = fruits[0]

Get the last item in a list: Accessing the last item of a list.

last_fruit = fruits[-1]

Looping through a list: Iterating through a list using a for loop.

for fruit in fruits:
    print(fruit)

Adding items to a list: Appending items to an existing list.

fruits.append("grape")

Making numerical lists: Creating numerical lists using range.

numbers = list(range(1, 6))  # Creates [1, 2, 3, 4, 5]

List comprehensions: A concise way to create lists.

squares = [x ** 2 for x in range(1, 6)]  # Creates [1, 4, 9, 16, 25]

Slicing a list: Extracting specific portions of a list.

selected_fruits = fruits[1:3]  # Retrieves ['banana', 'cherry']

**Copying a list: Creating a copy of a list.

copied_fruits = fruits.copy()

3. Tuples

Making a tuple: Creating an immutable sequence of values.

dimensions = (200, 50)

4. If Statements

Conditional tests: Evaluating conditions using if statements.

age = 18

if age >= 18:
    print("You can vote!")

Conditional test with lists: Checking if an item is in a list.

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

if "apple" in fruits:
    print("We have apples!")

Assigning boolean values: Storing boolean results in variables.

is_adult = age >= 18

A simple if test: Using the if statement.

if condition:
    # Do something

if-elif-else statements: Handling multiple conditions.

age = 18

if age < 18:
    print("You're too young")
elif age == 18:
    print("You're just old enough")
else:
    print("You're an adult")

5. Dictionaries

A simple dictionary: Creating a key-value pair data structure.

person = {"first_name": "John", "last_name": "Doe"}

Accessing a value: Retrieving a value from a dictionary using its key.

first_name = person["first_name"]

Adding a new key-value pair: Expanding a dictionary with a new entry.

person["age"] = 30

Looping through all key-value pairs: Iterating through the items in a dictionary.

for key, value in person.items():
    print(key + ": " + str(value))

Looping through all keys: Iterating through the keys in a dictionary.

for key in person.keys():
    print(key)

Looping through all the values: Iterating through the values in a dictionary.

for value in person.values():
    print(value)

6. User Input

Prompting for a value: Asking the user for input.

name = input("What's your name? ")

Prompting for numerical input: Getting numerical input and converting it.

age = int(input("How old are you? "))

7. While Loops

A simple while loop: Creating a basic loop that repeats until a condition is met.

current_number = 1

while current_number <= 5:
    print(current_number)
    current_number += 1

Letting the user choose when to quit: Using a loop to keep a program running until the user decides to exit.

while True:

response = input("Enter 'quit' to exit: ")

    if response == 'quit':

        break

8. Functions

A simple function: Defining and calling a basic function.

def greet(name):
    print("Hello, " + name + "!")

Passing an argument: Passing data to a function.

greet("Alice")

Default values for parameters: Providing default values for function parameters.

def greet(name="Guest"):
    print("Hello, " + name + "!")

Returning a value: Getting a result from a function.

def add(a, b):
    return a + b

9. Classes

Creating a class: Defining a class to create objects.

class Dog:

    def __init__(self, name, breed):
        self.name = name
        self.breed = breed

Inheritance: Creating a subclass to inherit properties and methods.

class Beagle(Dog):
    pass

Method Overriding: Redefining methods in a subclass.

class Beagle(Dog):
    def speak(self):
        return "Woof!"

Encapsulation: Restricting access to certain attributes.

class Dog:
    def __init__(self, name):
        self.__name = name

Polymorphism: Using objects of different classes interchangeably.

def make_sound(animal):
    print(animal.speak())

10. Working with Files

Reading a file and storing its lines: Opening a file, reading its contents, and storing them.

with open('filename.txt') as file_object:
    lines = file_object.readlines()

Writing to a file: Creating a new file or overwriting an existing one.

with open('filename.txt', 'w') as file_object:
    file_object.write("Hello, World!")

Appending to a file: Adding content to an existing file.

with open('filename.txt', 'a') as file_object:
    file_object.write("Appending new content.")

11. Exceptions

Catching an exception: Handling errors gracefully.

try:
    result = 10 / 0
except ZeroDivisionError:
    print("You can't divide by zero.")

PART 2: GETTING INTO THE DETAILS OF THE VERY BASICS

1. LISTS

Defining Lists

Making a List

A list is an ordered collection of items, enclosed in square brackets []. Lists can contain elements of different data types.

my_list = [1, 2, 3, 4, 5]

Accessing Elements

Getting the First Element

You can access individual elements in a list by their index. In Python, indexing starts at 0, so the first element is at index 0.

first_element = my_list[0]  # Gets the first element (1)

Getting the Second Element

Similarly, you can access the second element at index 1:

second_element = my_list[1]  # Gets the second element (2)

Getting the Last Element

To access the last element, you can use negative indexing, where -1 represents the last item, -2 represents the second-to-last, and so on.

last_element = my_list[-1]  # Gets the last element (5)

Modifying Individual Items

Changing an Element

You can modify the value of an element in a list by assigning a new value to it using its index.

my_list[2] = 10  # Changes the third element to 10

Adding Elements

Adding an Element to the End of the List

You can append elements to the end of a list using the append() method.

my_list.append(6)  # Adds 6 to the end of the list

Starting with an Empty List

To create a list dynamically, start with an empty list and add elements as needed.

empty_list = []

empty_list.append(1)

empty_list.append(2)

Inserting Elements at a Particular Position

Use the insert() method to add an element at a specific index, shifting existing elements to accommodate the new one.

my_list.insert(2, 7)  # Inserts 7 at index 2, shifting elements

Removing Elements

Deleting an Element by Its Position

You can remove an element from a list by specifying its index using the del statement.

del my_list[3]  # Deletes the element at index 3 (4)

Removing an Item by Its Value

If you know the value you want to remove and don’t know its position, you can use the remove() method.

my_list.remove(5)  # Removes the first occurrence of value 5

Popping Elements

Pop the Last Item from a List

The pop() method removes and returns the last item in a list.

last_item = my_list.pop()  # Removes and returns the last item (6)

Pop the First Item in a List

To remove and return the first item, specify its index (0).

first_item = my_list.pop(0)  # Removes and returns the first item (1)

List Length

Find the Length of a List

The len() function returns the number of items in a list.

length = len(my_list)  # Gets the length of the list (4)

Sorting a List

Sorting a List Permanently

You can sort a list in ascending order using the sort() method.

my_list.sort()  # Sorts the list in ascending order

Sorting a List Permanently in Reverse Alphabetical Order

To sort a list in descending order, use the sort() method with the reverse parameter set to True.

my_list.sort(reverse=True)  # Sorts the list in descending order

Sorting a List Temporarily

The sorted() function creates a sorted copy of a list without modifying the original.

sorted_list = sorted(my_list)  # Creates a sorted copy of the list

Reversing the Order of a List

The reverse() method reverses the order of elements in a list.

my_list.reverse()  # Reverses the order of the list

Looping Through a List

Printing All Items in a List

You can use a for loop to iterate through all items in a list and perform operations on each element.

for item in my_list:
    print(item)

Printing a Message for Each Item, and a Separate Message Afterwards

You can also perform specific actions for each item in a list and additional actions after the loop.

for item in my_list:
    print(f"Item: {item}")

print("All items have been printed.")

The range() Function

Printing the Numbers 0 to 1000

The range() function generates a sequence of numbers, and you can use a for loop to print them.

for num in range(1001):
    print(num)

Printing the Numbers 1 to 1000

To print numbers from 1 to 1000, specify the starting value (1) in the range() function.

for num in range(1, 1001):
    print(num)

Making a List of Numbers from 1 to a Million

You can create a list of numbers from 1 to a million using the list() function with range().

million_nums = list(range(1, 1000001))

Simple Statistics

Finding the Minimum Value in a List

You can find the minimum value in a list using the min() function.

min_value = min(my_list)

Finding the Maximum Value

The max() function helps you find the maximum value in a list.

max_value = max(my_list)

Finding the Sum of All Values

To calculate the sum of all values in a list, use the sum() function.

total_sum = sum(my_list)

Slicing a List

Getting the First Three Items

Slicing allows you to extract a portion of a list. To get the first three items, use slicing with [:3].

first_three = my_list[:3]  # Gets the first three items [1, 2, 7]

Getting the Middle Three Items

You can extract a middle portion of a list using slicing with a specified range.

middle_three = my_list[1:4]  # Gets the middle three items [2, 7, 10]

Getting the Last Three Items

To obtain the last three items, use negative indexing and slicing.

last_three = my_list[-3:]  # Gets the last three items [7, 10, 6]

Copying a List

Making a Copy of a List

Creating a copy of a list ensures that changes made to the copy won’t affect the original list. You can use slicing to achieve this.

new_list = my_list[:]  # Creates a copy of my_list

List Comprehensions

Using a Loop to Generate a List of Square Numbers

A loop can be used to generate a list of square numbers.

squares = []

for num in range(1, 6):
    squares.append(num ** 2)

Using a Comprehension to Generate a List of Square Numbers

List comprehensions offer a concise way to create lists, especially for simple transformations.

squares = [num ** 2 for num in range(1, 6)]

Using a Loop to Convert a List of Names to Upper Case

You can loop through a list of names and convert them to uppercase.

names = ["alice", "bob", "carol"]

upper_names = []

for name in names:
    upper_names.append(name.upper())

Using a Comprehension to Convert a List of Names to Upper Case

List comprehensions can also be used to perform operations on each element of a list.

names = ["alice", "bob", "carol"]

upper_names = [name.upper() for name in names]

Tuples

Defining a Tuple

A tuple is similar to a list but is enclosed in parentheses () and is immutable, meaning its elements cannot be changed once defined.

my_tuple = (1, 2, 3)

Looping Through a Tuple

You can iterate through the elements of a tuple in the same way as a list.

for item in my_tuple:
    print(item)

2. DICTIONARIES

Defining a Dictionary

A dictionary is a collection of key-value pairs. In real-life scenarios, dictionaries are often used to represent data where each item has attributes.

Making a Dictionary

# Creating a dictionary representing a person

person = {
    'name': 'Alice',
    'age': 30,
    'city': 'New York'
}

Accessing Values

Getting the Value Associated with a Key

To access a value in a dictionary, use the key as an index. This is similar to looking up information in a real-life dictionary.

# Accessing the person's name

name = person['name']  # 'Alice'

Getting the Value with get()

Using get() is safer because it handles missing keys gracefully by returning a default value if the key doesn’t exist.

# Accessing age with get()

age = person.get('age', 0)  # If 'age' key doesn't exist, returns 0

Adding New Key-Value Pairs

Adding a Key-Value Pair

You can add new information to a dictionary by specifying a new key and its associated value.

# Adding the person's gender

person['gender'] = 'Female'

Adding to an Empty Dictionary

In real-life scenarios, you might start with an empty dictionary and populate it as you gather more information.

# Creating an empty dictionary and adding data

empty_dict = {}
empty_dict['name'] = 'Bob'
empty_dict['age'] = 25

Modifying Values

Modifying Values in a Dictionary

Dictionaries are mutable, so you can easily update values associated with existing keys.

# Modifying the person's age

person['age'] = 31

Removing Key-Value Pairs

Deleting a Key-Value Pair

In real-life applications, you may need to remove data from a dictionary when it’s no longer relevant.

# Removing the 'city' key-value pair

del person['city']

Looping Through a Dictionary

Looping Through All Key-Value Pairs

Iterating through a dictionary is useful for processing data or displaying information.

# Looping through and printing all key-value pairs

for key, value in person.items():
    print(f"{key}: {value}")

Looping Through All the Keys

Sometimes you might need to work with just the keys in a dictionary.

# Looping through and printing all keys

for key in person.keys():
    print(key)

Looping Through All the Values

Looping through values can be useful when you need to perform actions on data.

# Looping through and printing all values

for value in person.values():
    print(value)

Looping Through All the Keys in Order

In some situations, you might want to work with keys in a specific order, such as sorting them alphabetically.

# Looping through keys in sorted order

for key in sorted(person.keys()):
    print(key)

Dictionary Length

Finding a Dictionary’s Length

You can determine the size of a dictionary using the len() function, which is useful for managing and analyzing data.

# Finding the length of the dictionary

length = len(person)  # 2 (after removing 'city' key)

Nesting – A List of Dictionaries

Storing Dictionaries in a List

In real-life applications, you might have a list of items, each represented as a dictionary.

# Creating a list of dictionaries for items

items = [
    {'name': 'item1', 'price': 10},
    {'name': 'item2', 'price': 20}
]

Defining a List of Dictionaries Directly

You can directly define a list of dictionaries, especially when the data structure is known in advance.

# Creating a list of dictionaries directly

items = [
    {'name': 'item1', 'price': 10},
    {'name': 'item2', 'price': 20}
]

Nesting – Lists in a Dictionary

Storing Lists in a Dictionary

In real-life scenarios, you might use a dictionary to represent a person’s profile, including a list of hobbies or interests.

# Creating a dictionary with a list of hobbies

person = {
    'name': 'Alice',
    'hobbies': ['reading', 'painting', 'swimming']
}

Nesting – A Dictionary of Dictionaries

Storing Dictionaries in a Dictionary

Complex data structures can be represented by dictionaries of dictionaries, such as storing information about students in a class.

# Creating a dictionary of dictionaries for students

students = {
    'student1': {'name': 'Alice', 'age': 20},
    'student2': {'name': 'Bob', 'age': 22}
}

Using an OrderedDict

Preserving the Order of Keys and Values

In some applications where the order of data is important, you can use OrderedDict to maintain the order of key-value pairs.

from collections import OrderedDict

# Creating an ordered dictionary

ordered_dict = OrderedDict()
ordered_dict['b'] = 2
ordered_dict['a'] = 1

Generating a Million Dictionaries

Creating a large number of dictionaries can be useful for simulating data or handling a massive dataset.

# Generating a list of a million empty dictionaries (aliens)

aliens = [{} for _ in range(1000000)]

Disclaimer

While nesting can be a powerful tool for organizing data, it’s essential to strike a balance. Excessive nesting can make code complex and harder to maintain. Always consider the readability and maintainability of your code when deciding on data structures. In some cases, using classes or alternative data structures may provide a simpler solution.

3. IF STATEMENTS

What are If Statements

If statements allow you to make decisions in your code based on conditions. They control the flow of your program.

Conditional Control Flow

age = 18

if age >= 18:
    print("You are an adult.")

Conditional Tests

Checking for Equality

You can use == to check if two values are equal.

color = 'blue'

if color == 'blue':
    print("The color is blue.")

Ignoring Case When Making a Comparison

You can use .lower() or .upper() to make case-insensitive comparisons.

user_input = 'Yes'

if user_input.lower() == 'yes':
    print("User answered 'yes'.")

Checking for Inequality

Use != to check if two values are not equal.

status = 'active'

if status != 'inactive':
    print("The status is not inactive.")

Numerical Comparisons

Testing Equality and Inequality

Numerical values can be compared using == and !=.

age = 18

if age == 18:
    print("You are 18 years old.")

Comparison Operators

You can use comparison operators such as <, >, <=, and >= for numerical comparisons.

value = 42

if value > 50:
    print("Value is greater than 50.")

Checking Multiple Conditions

Using and to Check Multiple Conditions

To check if multiple conditions are true, use and.

age = 25

income = 50000

if age >= 18 and income > 30000:
    print("You are an adult with a good income.")

Using or to Check Multiple Conditions

To check if at least one condition is true, use or.

age = 16

score = 75

if age < 18 or score >= 70:
    print("You are either under 18 or have a good score.")

Boolean Values

Simple Boolean Values

Boolean values, True and False, are used in conditional statements.

is_sunny = True

if is_sunny:
    print("It's a sunny day.")

If Statements

Simple if Statement

A simple if statement tests a single condition.

temperature = 25

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

if-else Statements

An if-else statement allows you to specify what happens when the condition is not met.

age = 15

if age >= 18:
    print("You can vote.")
else:
    print("You cannot vote yet.")

The if-elif-else Chain

You can use multiple conditions with if-elif-else to handle different scenarios.

grade = 85

if grade >= 90:
    print("A")
elif grade >= 80:
    print("B")
else:
    print("C")

Conditional Tests with Lists

Testing if a Value is in a List

You can check if an item is in a list using in.

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

if 'banana' in fruits:
    print("Banana is in the list.")

Testing if a Value is Not in a List

To check if an item is not in a list, use not in.

if 'orange' not in fruits:
    print("Orange is not in the list.")

Checking if a List is Empty

You can use the if statement to check if a list is empty.

empty_list = []

if not empty_list:
    print("The list is empty.")

Accepting Input

Simple Input

You can use input() to accept user input.

name = input("Enter your name: ")

print(f"Hello, {name}!")

Accepting Numerical Input

To accept numerical input, you can convert the input to the desired data type.

age = int(input("Enter your age: "))

if age >= 18:
    print("You are an adult.")

If statements are fundamental for controlling the logic of your Python programs, allowing you to make decisions based on conditions and respond accordingly. They are crucial for creating dynamic and interactive applications.

4. WHILE LOOPS

What are While Loops

While loops are used to repeat a code block as long as a condition is true, making them useful for tasks that require repetitive execution.

Creating a While Loop

Counting to 5

A simple while loop can be used to count from 1 to 5.

# Counting to 5 with a while loop

count = 1

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

Letting the User Choose When to Quit

While loops are often used to create interactive programs that continue until the user decides to exit.

# Letting the user choose when to quit

while True:
    user_input = input("Enter 'quit' to exit: ")
    if user_input == 'quit':
        break

Using a Flag

A flag variable can control when a while loop should continue or stop.

# Using a flag to control a while loop

flag = True

while flag:
    user_input = input("Continue? (yes/no): ")
    if user_input.lower() == 'no':
        flag = False

Using break to Exit a Loop

The break statement allows you to exit a loop prematurely when a certain condition is met.

# Using break to exit a loop

while True:
    user_input = input("Enter 'quit' to exit: ")
    if user_input == 'quit':
        break

Using continue in a Loop

The continue statement allows you to skip the rest of the loop iteration and move to the next one.

# Using continue in a loop to skip even numbers

number = 0

while number < 10:
    number += 1
    if number % 2 == 0:
        continue
    print(number)

Avoiding Infinite Loops

An Infinite Loop

An infinite loop runs indefinitely because the condition never becomes False.

Removing All Instances of a Value from a List

# An infinite loop

while True:
    print("This loop runs forever!")

Removing All Instances

While loops can be used to remove all occurrences of a specific value from a list.

# Removing all instances of a value from a list

numbers = [1, 2, 3, 4, 2, 5, 2]

value_to_remove = 2

while value_to_remove in numbers:
    numbers.remove(value_to_remove)

While loops provide a powerful mechanism for creating iterative processes in Python. They are essential for tasks that require repetitive actions or interactive user input. However, it’s crucial to be cautious with while loops to avoid infinite loops that can freeze your program.

5. FUNCTIONS

What are Functions

Functions are reusable blocks of code that perform specific tasks. They help organize code and make it more manageable.

Reusable Code Blocks

# A simple function that greets the user

def greet_user():
    print("Hello!")

# Calling the function
greet_user()

Defining a Function

Making a Function

To create a function, use the def keyword followed by the function name and parentheses.

# Defining a function that adds two numbers

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

Passing Information to a Function

Passing a Single Argument

Functions can accept one or more arguments, allowing you to provide data to the function.

# Function that displays a message with a name

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

Positional and Keyword Arguments

Using Positional Arguments

Positional arguments are passed in the order defined by the function.

# Function with positional arguments

def describe_pet(animal_type, pet_name):
    print(f"I have a {animal_type} named {pet_name}.")

Using Keyword Arguments

Keyword arguments are passed with the parameter name, allowing for more clarity.

# Function with keyword arguments

def describe_person(name, age):
    print(f"Name: {name}, Age: {age}")

Default Values

Using a Default Value

Default values are assigned to parameters, making them optional when calling the function.

# Function with a default value

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

Using None to Make an Argument Optional

You can use None as a default value to make an argument truly optional.

# Function with None to make an argument optional

def describe_pet(pet_name, animal_type=None):
    if animal_type:
        print(f"I have a {animal_type} named {pet_name}.")
    else:
        print(f"I have a pet named {pet_name}.")

Return Values

Returning a Single Value

Functions can return values using the return statement.

# Function that returns the square of a number

def square(x):
    return x ** 2

Returning a Dictionary

Functions can return dictionaries to provide structured data.

# Function that returns a dictionary

def create_person(name, age):
    person = {'name': name, 'age': age}
    return person

Returning a Dictionary with Optional Values

You can include optional values in the dictionary returned by a function.

# Function that returns a dictionary with optional values

def create_car(make, model, year=None):
    car = {'make': make, 'model': model}
    if year:
        car['year'] = year
    return car

Passing a List to a Function

Passing a List as an Argument

Functions can accept lists as arguments for processing.

# Function that prints items from a list

def print_items(my_list):
    for item in my_list:
        print(item)

Allowing a Function to Modify a List

A function can modify a list passed as an argument.

# Function that modifies a list

def add_element(my_list, element):
    my_list.append(element)

Preventing a Function from Modifying a List

To avoid modifying the original list, you can pass a copy.

# Function that receives a copy of a list

def modify_list(my_list_copy):
    my_list_copy.append(42)

Passing an Arbitrary Number of Arguments

Collecting an Arbitrary Number of Arguments

You can use *args to collect an arbitrary number of positional arguments.

# Function with arbitrary positional arguments

def print_args(*args):
    for arg in args:
        print(arg)

Collecting an Arbitrary Number of Keyword Arguments

You can use **kwargs to collect an arbitrary number of keyword arguments.

# Function with arbitrary keyword arguments

def print_kwargs(**kwargs):
    for key, value in kwargs.items():
        print(f"{key}: {value}")

The Best Way to Structure a Function

Well-Structured Functions

Functions should have clear purposes, descriptive names, and appropriate documentation.

# A well-structured function

def calculate_average(numbers):
    """Calculate the average of a list of numbers."""

    total = sum(numbers)
    count = len(numbers)
    return total / count

Modules

Storing a Function in a Module

Functions can be stored in separate Python modules for organization.

# Function stored in a module named 'my_module.py'

# my_module.py:

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

Importing an Entire Module

You can import an entire module to use its functions.

# Importing an entire module

import my_module

my_module.greet("Alice")

Importing a Specific Function

You can import a specific function from a module.

# Importing a specific function from a module

from my_module import greet

greet("Bob")

Giving a Module an Alias

Modules can be given aliases to simplify their usage.

# Giving a module an alias

import my_module as mm

mm.greet("Carol")

Giving a Function an Alias

Functions can also be given aliases to make code more readable.

# Giving a function an alias

from my_module import greet as say_hello

say_hello("David")

Importing All Functions from a Module

You can import all functions from a module using *.

# Importing all functions from a module

from my_module import *

greet("Eve")

Functions are a fundamental concept in Python, allowing you to encapsulate logic, make code reusable, and create organized and maintainable programs. Understanding how to define, call, and structure functions is crucial for effective programming.

6. CLASSES

What are Classes

Classes are blueprints that define the structure and behavior of objects in Python. They encapsulate data and functions that operate on that data.

Creating and Using a Class

The Dog Class

A class is defined using the class keyword, followed by the class name.

# Defining a Dog class

class Dog:
    def __init__(self, name, age):
        self.name = name
        self.age = age

Creating an Object from a Class

Objects are instances of a class and are created using the class constructor.

# Creating a Dog object

my_dog = Dog("Buddy", 3)

Accessing Attribute Values

Attributes are accessed using dot notation.

# Accessing attribute values

print(my_dog.name)  # Output: Buddy

Calling Methods

Methods are functions defined within a class and can be called on objects.

# Defining a method in the Dog class

def sit(self):
    print(f"{self.name} is sitting.")

# Calling a method
my_dog.sit()  # Output: Buddy is sitting.

Creating Multiple Objects

Multiple objects can be created from the same class, each with its own set of attributes and behavior.

# Creating multiple Dog objects

dog1 = Dog("Rex", 5)
dog2 = Dog("Molly", 2)

Modifying Attributes

Modifying an Attribute Directly

Attributes can be modified directly.

# Modifying an attribute directly

my_dog.age = 4

Writing a Method to Update an Attribute’s Value

Methods can be used to update attribute values with more control.

# Writing a method to update an attribute's value

def update_age(self, new_age):
    self.age = new_age

my_dog.update_age(5)

Writing a Method to Increment an Attribute’s Value

Methods can be used to perform specific actions on attributes, like incrementing.

# Writing a method to increment an attribute's value

def increment_age(self, years):
    self.age += years

my_dog.increment_age(2)

Naming Conventions

Class Naming Convention

Class names should use CamelCase convention (each word capitalized).

class CarModel:
    # ...

Class Inheritance

The __init__() Method for a Child Class

Child classes can inherit from parent classes and extend them.

# Defining a child class

class Bulldog(Dog):
    def __init__(self, name, age, breed):
        super().__init__(name, age)
        self.breed = breed

Adding New Methods to the Child Class

Child classes can have their own methods in addition to inherited ones.

# Adding a new method to the child class

def guard(self):
    print(f"{self.name} is guarding the house.")

Using Child Methods and Parent Methods

Objects of child classes can use methods from both child and parent classes.

# Using child methods and parent methods

my_bulldog = Bulldog("Spike", 4, "Bulldog")
my_bulldog.sit()  # Inherited from Dog class
my_bulldog.guard()  # From the Bulldog class

Overriding Parent Methods

Child classes can override parent class methods to customize behavior.

# Overriding a parent method

def sit(self):
    print(f"{self.name} sits differently.")

my_bulldog.sit()  # Output: Spike sits differently.

Instances as Attributes

A Battery Class

Instances of one class can be used as attributes in another class.

# A Battery class

class Battery:
    def __init__(self, capacity):
        self.capacity = capacity
    def describe_battery(self):
        print(f"Battery capacity: {self.capacity} kWh")

Using an Instance as an Attribute

Instances of the Battery class can be used as attributes in an ElectricCar class.

# Using an instance as an attribute

class ElectricCar:

    def __init__(self, make, model, year):
        self.make = make
        self.model = model
        self.year = year
        self.battery = Battery(75)  # Using Battery instance

Using the Instance

You can call methods on the instance used as an attribute.

# Using the instance

my_electric_car = ElectricCar("Tesla", "Model 3", 2023)

my_electric_car.battery.describe_battery()

Importing Classes

Storing Classes in a File

Classes can be stored in separate Python files.

# Car.py (class stored in a file)

class Car:
    # ...

Importing Individual Classes from a Module

You can import specific classes from a module.

# Importing an individual class from a module

from Car import Car

Importing an Entire Module

You can import an entire module containing classes.

# Importing an entire module

import Car

my_car = Car.Car()

Importing All Classes from a Module

You can import all classes from a module.

# Importing all classes from a module

from Car import *

my_car = Car()

Storing Objects in a List

A Fleet of Rental Cars

Objects of the same class can be stored in a list for easy management.

# Storing objects in a list

fleet = []

fleet.append(Car())
fleet.append(ElectricCar("Tesla", "Model S", 2023))

Classes and objects are fundamental to object-oriented programming in Python. They allow you to model real-world entities and create reusable and organized code. Understanding how to create, inherit from, and use classes is essential for building complex and modular applications.

7. FILES

What are Files

Files are used for storing data on a computer’s file system. They are essential for reading and writing information in Python.

Reading from a File

Reading an Entire File at Once

You can read the entire contents of a file into a string.

# Reading an entire file at once

with open('filename.txt') as file:
    contents = file.read()

Reading Line by Line

Reading a file line by line is useful for large files or when processing data incrementally.

# Reading a file line by line

with open('filename.txt') as file:
    for line in file:
        print(line.rstrip())

Storing the Lines in a List

You can read the lines of a file into a list for easy access.

# Storing the lines in a list

with open('filename.txt') as file:
    lines = file.readlines()

Writing to a File

Writing to an Empty File

You can create a new file or overwrite an existing one to write data to it.

# Writing to an empty file

with open('new_file.txt', 'w') as file:
    file.write("Hello, world!")

Writing Multiple Lines to an Empty File

Multiple lines can be written to a file using a loop or list.

# Writing multiple lines to an empty file

lines = ['Line 1', 'Line 2', 'Line 3']

with open('new_file.txt', 'w') as file:
    for line in lines:
        file.write(line + '\n')

Appending to a File

Appending data to an existing file keeps the original content and adds new data.

# Appending to a file

with open('existing_file.txt', 'a') as file:
    file.write("This line is appended.")

File Paths

Opening a File from a Subfolder

You can specify a file’s path relative to the current working directory.

# Opening a file from a subfolder

with open('subfolder/filename.txt') as file:
    contents = file.read()

Opening a File Using an Absolute Path

An absolute path specifies the file’s location from the root directory.

# Opening a file using an absolute path

file_path = '/home/user/documents/myfile.txt'

with open(file_path) as file:
    contents = file.read()

Opening a File on Windows

Windows uses backslashes in file paths, which need to be escaped.

# Opening a file on Windows

file_path = 'C:\\Users\\User\\Documents\\myfile.txt'

with open(file_path) as file:
    contents = file.read()

Storing Data with JSON

Using json.dump() to Store Data

The json.dump() function allows you to store data in JSON format.

import json

data = {'name': 'Alice', 'age': 30}

with open('data.json', 'w') as file:
    json.dump(data, file)

Using json.load() to Read Data

The json.load() function reads JSON data from a file.

import json

with open('data.json') as file:
    loaded_data = json.load(file)

Making Sure the Stored Data Exists

You can check if the JSON file exists before attempting to read it.

import json

import os

if os.path.exists('data.json'):
    with open('data.json') as file:
        loaded_data = json.load(file)
else:
    print("File 'data.json' does not exist.")

Working with files is essential for managing data in Python. You can read and write files, specify file paths, and store data in various formats like JSON to interact with external resources and persist information between program runs.

8. EXCEPTIONS

The try-except Block

Exception handling in Python allows you to gracefully handle errors, preventing your program from crashing when unexpected situations arise. Use try, except, and else blocks to manage exceptions effectively and make your code more robust.

Handling the ZeroDivisionError Exception

Use a try-except block to handle exceptions, like ZeroDivisionError.

try:

    result = 10 / 0

except ZeroDivisionError:
    print("Division by zero is not allowed.")

Handling the FileNotFoundError Exception

Catch exceptions like FileNotFoundError when working with files.

try:
    with open('nonexistent.txt') as file:
        content = file.read()

except FileNotFoundError:
    print("File not found.")

Knowing Which Exception to Handle

Specific Exception Handling

Handle specific exceptions for precise error handling.

try:
    # Code that may raise an exception
except SpecificException:
    # Handle SpecificException
except AnotherException:
    # Handle AnotherException

The else Block

Using an else Block

The else block executes when no exceptions occur in the try block.

try:
    result = 10 / 2
except ZeroDivisionError:
    print("Division by zero is not allowed.")
else:
    print("Result:", result)

Preventing Crashes from User Input

Use else to handle exceptions and prevent crashes from user input.

try:
    number = int(input("Enter a number: "))
except ValueError:
    print("Invalid input.")
else:
    print(f"Square of {number}: {number**2}")

Failing Silently

Using the pass Statement in an else Block

You can use the pass statement in an else block to do nothing when an exception occurs.

try:
    result = 10 / 0
except ZeroDivisionError:
    print("Division by zero is not allowed.")
else:
    pass

Avoid Bare except Blocks

Don’t Use Bare except Blocks

Avoid using bare except blocks as they catch all exceptions, making debugging difficult.

try:
    # Code that may raise exceptions
except:
    # Avoid bare except blocks

Use Exception Instead

Use except Exception to catch all exceptions explicitly.

try:
    # Code that may raise exceptions
except Exception:
    # Handle all exceptions

Printing the Exception

You can print the exception message for debugging.

try:
    result = 10 / 0
except Exception as e:
    print(f"An exception occurred: {e}")