__init__ method behavior in Python - Deep Dive

Overview - __init__ method behavior

What is it?

The __init__ method in Python is a special function inside a class that runs automatically when you create a new object from that class. It helps set up the object by giving it initial values or preparing it to be used. Think of it as the setup step that happens right after making a new thing from a blueprint. Without __init__, objects would start empty and need extra steps to be ready.

Why it matters

Without the __init__ method, every time you create a new object, you would have to manually set up its starting details, which is slow and error-prone. This method makes creating objects easy, consistent, and less buggy by automating the setup. It helps programmers write cleaner code and makes programs easier to understand and maintain.

Where it fits

Before learning __init__, you should understand what classes and objects are in Python. After mastering __init__, you can learn about other special methods like __str__ or __repr__, and how to customize object behavior further.

Mental Model

Core Idea

The __init__ method is the automatic setup routine that prepares a new object with its starting values right when it is created.

Think of it like...

It's like when you buy a new phone and the first thing you do is set it up with your name, language, and preferences before using it. The __init__ method does this setup for a new object automatically.

┌───────────────┐
│   Class       │
│  Blueprint    │
└──────┬────────┘
       │ create new object
       ▼
┌───────────────┐
│  __init__     │  ← runs automatically
│  (setup)      │
└──────┬────────┘
       │
       ▼
┌───────────────┐
│  Object       │  ← ready to use
│  with values  │
└───────────────┘

Build-Up - 7 Steps

1

Foundation

What is __init__ method

Concept: Introducing __init__ as a special method that runs when an object is created.

In Python, classes can have a method named __init__. This method runs automatically when you make a new object from the class. It usually sets up the object's starting values. Example: class Dog: def __init__(self): print('A new dog is born!') my_dog = Dog() # This prints: A new dog is born!

Result

When you create my_dog, the message 'A new dog is born!' appears automatically.

Understanding that __init__ runs right after creating an object helps you know where to put setup code.

2

Foundation

Using __init__ to set attributes

Concept: How __init__ assigns values to the new object's properties.

You can give __init__ parameters to set up the object's details. Example: class Dog: def __init__(self, name, age): self.name = name self.age = age my_dog = Dog('Buddy', 3) print(my_dog.name) # Buddy print(my_dog.age) # 3

Result

The object my_dog has name 'Buddy' and age 3 stored inside it.

Knowing that self refers to the new object lets you store information inside it during setup.

3

Intermediate

Why self is needed in __init__

🤔Before reading on: do you think self is a keyword or just a name? Commit to your answer.

Concept: Understanding self as the reference to the object being created.

Inside __init__, the first parameter is always self. This is not a keyword but a strong convention. It means 'this object' and lets you assign values to the object itself. Example: class Cat: def __init__(self, color): self.color = color kitty = Cat('black') print(kitty.color) # black

Result

The kitty object remembers its color because self.color stores it.

Understanding self is key to accessing and changing the object's own data during initialization.

4

Intermediate

Default values in __init__ parameters

🤔Before reading on: do you think __init__ can have default values for parameters? Commit to yes or no.

Concept: Using default values to make parameters optional in __init__.

You can give default values to __init__ parameters so the caller doesn't have to provide all arguments. Example: class Bird: def __init__(self, species='sparrow'): self.species = species bird1 = Bird() bird2 = Bird('eagle') print(bird1.species) # sparrow print(bird2.species) # eagle

Result

Objects can be created with or without specifying all details, making code flexible.

Knowing default parameters helps you write __init__ methods that are easier to use and less error-prone.

5

Intermediate

Multiple __init__ parameters and order

🤔Before reading on: do you think the order of parameters in __init__ matters? Commit to yes or no.

Concept: How parameter order affects object creation and argument passing.

The order of parameters in __init__ matters because arguments are matched by position unless named. Example: class Car: def __init__(self, make, year): self.make = make self.year = year car = Car('Toyota', 2020) print(car.make) # Toyota print(car.year) # 2020 # If you swap arguments: car_wrong = Car(2020, 'Toyota') print(car_wrong.make) # 2020 (wrong!) print(car_wrong.year) # Toyota (wrong!)

Result

Passing arguments in the wrong order leads to wrong data stored in the object.

Understanding parameter order prevents bugs when creating objects with multiple details.

6

Advanced

What happens if __init__ is missing

🤔Before reading on: do you think Python allows creating objects without __init__? Commit to yes or no.

Concept: How Python uses a default __init__ if none is defined in the class.

If you don't write an __init__ method, Python provides a default one that does nothing. Example: class Fish: pass fish = Fish() # This works fine # But you cannot pass arguments: # fish2 = Fish('goldfish') # Error: Fish() takes no arguments

Result

Objects can be created without __init__, but you cannot set initial values during creation.

Knowing the default __init__ behavior helps you understand when you need to write your own.

7

Expert

How __init__ differs from __new__ method

🤔Before reading on: do you think __init__ creates the object or just sets it up? Commit to your answer.

Concept: Distinguishing __init__ as initializer vs __new__ as creator of the object.

In Python, __new__ is the method that actually creates the object in memory. __init__ only sets up the object after it's created. Example: class Example: def __new__(cls): print('Creating object') return super().__new__(cls) def __init__(self): print('Initializing object') obj = Example() # Output: # Creating object # Initializing object

Result

Object creation and initialization are two separate steps handled by __new__ and __init__.

Understanding this separation clarifies advanced object creation and customization techniques.

Under the Hood

When you create an object by calling a class, Python first calls the __new__ method to allocate memory and create the empty object. Then, Python calls the __init__ method on that object to set up its initial state by assigning attributes or running setup code. The __init__ method receives the new object as self and any arguments passed during creation. This two-step process allows Python to separate object creation from initialization.

Why designed this way?

Python separates object creation (__new__) from initialization (__init__) to allow advanced customization. For example, __new__ can return instances of different classes or cached objects, while __init__ focuses on setting up the object's data. This design gives flexibility and control, unlike languages that combine these steps. It also supports immutable types that need special creation logic.

Class call
   │
   ▼
┌───────────┐
│  __new__  │  ← creates empty object
└─────┬─────┘
      │
      ▼
┌───────────┐
│  Object   │
│  created  │
└─────┬─────┘
      │
      ▼
┌───────────┐
│  __init__ │  ← sets up object attributes
└─────┬─────┘
      │
      ▼
┌───────────┐
│  Ready    │
│  Object   │
└───────────┘

Myth Busters - 4 Common Misconceptions

Quick: Does __init__ create the object or just set it up? Commit to your answer.

Common Belief: Many think __init__ creates the object in memory.

Reality: __init__ only initializes an already created object; __new__ creates it.

Why it matters: Confusing creation with initialization can lead to errors when customizing object creation or subclassing immutable types.

Quick: Can __init__ return a value other than None? Commit to yes or no.

Common Belief: Some believe __init__ can return values like normal functions.

Reality: __init__ must always return None; returning anything else causes an error.

Why it matters: Trying to return values from __init__ causes runtime errors and confusion about object creation.

Quick: If a class has no __init__, can you pass arguments when creating objects? Commit to yes or no.

Common Belief: People often think you can pass arguments even if __init__ is missing.

Reality: Without __init__, the default constructor takes no arguments; passing any causes an error.

Why it matters: This misconception leads to runtime errors and wasted debugging time.

Quick: Does self have to be named 'self'? Commit to yes or no.

Common Belief: Many think self is a Python keyword and must be named exactly 'self'.

Reality: self is just a strong naming convention; you can name it differently but it is discouraged.

Why it matters: Not understanding this can cause confusion reading others' code or writing unclear code.

Expert Zone

1

The __init__ method is not a constructor but an initializer; the real constructor is __new__, which is rarely overridden except in advanced cases.

2

Mutable default arguments in __init__ parameters can cause shared state bugs if not handled carefully.

3

Using keyword-only arguments in __init__ (Python 3+) improves clarity and prevents argument order mistakes.

When NOT to use

Avoid putting heavy computation or side effects in __init__; instead, use factory methods or separate setup functions. For immutable objects, override __new__ instead of __init__ to set values.

Production Patterns

In real-world code, __init__ often validates inputs, sets default values, and calls helper methods. Data classes (Python 3.7+) automate __init__ creation for simple classes. Dependency injection frameworks use __init__ to receive dependencies cleanly.

Connections

Constructors in other languages

Similar pattern of object setup but often combined creation and initialization.

Knowing __init__ differs from constructors in languages like Java helps understand Python's flexible object model.

Factory design pattern

Builds on __init__ by controlling object creation and setup externally.

Understanding __init__ clarifies how factories create and initialize objects in complex systems.

Human onboarding process

Both involve preparing a new member with necessary information and setup before full use.

Seeing __init__ as onboarding helps grasp why setup steps are automated and standardized.

Common Pitfalls

#1 Forgetting to include self as the first parameter in __init__.

Wrong approach:

class Person:
def __init__(name):
self.name = name

Correct approach:

class Person:
def __init__(self, name):
self.name = name

Root cause:

Misunderstanding that self is required to refer to the object instance inside methods.

#2 Using mutable default arguments in __init__ parameters.

Wrong approach:

class Bag:
def __init__(self, items=[]):
self.items = items

Correct approach:

class Bag:
def __init__(self, items=None):
if items is None:
items = []
self.items = items

Root cause:

Mutable defaults are shared across all instances, causing unexpected shared state.

#3 Trying to return a value from __init__.

Wrong approach:

class Example:
def __init__(self):
return 5

Correct approach:

class Example:
def __init__(self):
pass

Root cause:

Misunderstanding that __init__ must return None and is not a normal function.

Key Takeaways

The __init__ method runs automatically to set up new objects with initial values.

The self parameter in __init__ refers to the object being created and is essential for storing data.

Python separates object creation (__new__) from initialization (__init__), giving flexibility.

Default parameters and argument order in __init__ affect how objects are created and used.

Common mistakes include forgetting self, using mutable defaults, and returning values from __init__.