Python Coding challenge - Day 1118| What is the output of the following Python Code?

 

Code Explanation:

1️⃣ Importing dataclass

from dataclasses import dataclass

Explanation

Imports the dataclass decorator.

It helps automatically generate methods like:

__init__

__repr__

__eq__

2️⃣ Applying @dataclass Decorator

@dataclass

Explanation

This decorator modifies class A.

Automatically adds useful methods.

Saves you from writing boilerplate code.

3️⃣ Defining the Class

class A:

Explanation

A class A is created.

It will hold data (like a structure).

4️⃣ Defining Attributes with Type Hints

x: int

y: int

Explanation

Defines two attributes:

x of type int

y of type int

These are used by @dataclass to generate constructor.

5️⃣ Auto-Generated Constructor

👉 Internally, Python creates:

def __init__(self, x, y):

    self.x = x

    self.y = y

Explanation

You don’t write this manually.

@dataclass creates it automatically.

6️⃣ Creating Object

a = A(1,2)

Explanation

Calls auto-generated __init__.

Assigns:

a.x = 1

a.y = 2

7️⃣ Printing Object

print(a)

Explanation

Calls auto-generated __repr__() method.

👉 Internally behaves like:

"A(x=1, y=2)"

📤 Final Output

A(x=1, y=2)

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Python Coding challenge - Day 1117| What is the output of the following Python Code?

 

Code Explanation:

1️⃣ Importing chain

from itertools import chain

Explanation

Imports chain from Python’s itertools module.

chain is used to combine multiple iterables.

2️⃣ Creating First List

a = [1,2]

Explanation

A list a is created with values:

[1, 2]

3️⃣ Creating Second List

b = [3,4]

Explanation

Another list b is created:

[3, 4]

4️⃣ Using chain()

chain(a, b)

Explanation

chain(a, b) links both lists sequentially.

It does NOT create a new list immediately.

It returns an iterator.

👉 Internally behaves like:

1 → 2 → 3 → 4

5️⃣ Converting to List

list(chain(a, b))

Explanation

Converts the iterator into a list.

Collects all elements in order.

6️⃣ Printing Result

print(list(chain(a, b)))

Explanation

Displays the combined list.

📤 Final Output

[1, 2, 3, 4]

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Python Coding Challenge - Question with Answer (ID -010426)

Explanation:

1️⃣ Creating the list

clcoding = [[1, 2], [3, 4]]

A nested list (list of lists) is created.

Memory:

clcoding → [ [1,2], [3,4] ]

2️⃣ Copying the list

new = clcoding.copy()

This creates a shallow copy.

Important:

Outer list is copied

Inner lists are NOT copied (same reference)

👉 So:

clcoding[0]  → same object as new[0]

clcoding[1]  → same object as new[1]

3️⃣ Modifying the copied list

new[0][0] = 99

You are modifying inner list

Since inner lists are shared → original also changes

👉 Now both become:

[ [99, 2], [3, 4] ]

4️⃣ Printing original list

print(clcoding)

Because of shared reference, original is affected

👉 Output:

[[99, 2], [3, 4]] 

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Python Coding challenge - Day 1116| What is the output of the following Python Code?

 

Code Explanation:

1️⃣ Defining Generator Function

def gen():

Explanation

A function gen is defined.

Because it uses yield, it becomes a generator.

It does NOT execute immediately.

2️⃣ First Yield Statement

x = yield 1

Explanation

This line does two things:

Yields value 1

Pauses execution and waits for a value to assign to x

3️⃣ Second Yield Statement

yield x * 2

Explanation

After receiving value in x, it:

returns x * 2

4️⃣ Creating Generator Object

g = gen()

Explanation

Creates a generator object g.

Function has NOT started yet.

5️⃣ First Call → next(g)

print(next(g))

Explanation

Starts execution of generator.

Runs until first yield.

👉 Executes:

yield 1

Returns:

1

Pauses at:

x = yield 1

(waiting for value)

6️⃣ Second Call → g.send(5)

print(g.send(5))

Explanation

Resumes generator.

Sends value 5 into generator.

👉 So:

x = 5

Now executes:

yield x * 2 → 5 * 2 = 10

Returns:

10

📤 Final Output

1

10

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Python Coding challenge - Day 1115| What is the output of the following Python Code?

 

Code Explanation:

🔹 1. Defining the Decorator Function

def deco(func):

👉 This defines a decorator function named deco

👉 It takes another function func as input

🔹 2. Creating the Wrapper Function

    def wrapper():

👉 Inside deco, we define a nested function called wrapper

👉 This function will modify or extend the behavior of func

🔹 3. Calling Original Function + Modifying Output

        return func() + 1

👉 func() → calls the original function

👉 + 1 → adds 1 to its result

💡 So this decorator increases the return value by 1

🔹 4. Returning the Wrapper

    return wrapper

👉 Instead of returning the original function,

👉 we return the modified version (wrapper)

🔹 5. Applying the Decorator

@deco

👉 This is syntactic sugar for:

f = deco(f)

👉 It means:

pass function f into deco

replace f with wrapper

🔹 6. Defining the Original Function

def f():

    return 5

👉 This function simply returns 5

🔹 7. Calling the Function

print(f())

👉 Actually calls wrapper() (not original f)

👉 Inside wrapper:

func() → returns 5

+1 → becomes 6

✅ Final Output

6

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Python Coding challenge - Day 1114| What is the output of the following Python Code?

 

Code Explanation:

1️⃣ Defining the Decorator Function

def deco(func):

Explanation

deco is a decorator function.

It takes another function (func) as input.

2️⃣ Defining Inner Wrapper Function

def wrapper():

Explanation

A function wrapper is defined inside deco.

This function will modify the behavior of the original function.

3️⃣ Modifying the Original Function Output

return func() + 1

Explanation

Calls the original function func().

Adds 1 to its result.

👉 If original returns 5 → wrapper returns:

5 + 1 = 6

4️⃣ Returning Wrapper Function

return wrapper

Explanation

deco returns the wrapper function.

So original function gets replaced by wrapper.

5️⃣ Using Decorator

@deco

def f():

Explanation

This is equivalent to:

f = deco(f)

👉 So now:

f → wrapper function

6️⃣ Original Function Definition

def f():

    return 5

Explanation

Original function returns 5.

But it is now wrapped by decorator.

7️⃣ Calling the Function

print(f())

Explanation

Actually calls:

wrapper()

Which does:

func() + 1 → 5 + 1 = 6

📤 Final Output

6

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Python Coding challenge - Day 1113| What is the output of the following Python Code?

 

Code Explanation:

🔹 1. Importing the module

import threading

This line imports the threading module.

It allows you to create and manage threads (multiple flows of execution running in parallel).

🔹 2. Initializing a variable

x = 0

A global variable x is created.

It is initialized with value 0.

This variable will be accessed and modified by the thread.

🔹 3. Defining the task function

def task():

A function named task is defined.

This function will be executed inside a separate thread.

🔹 4. Declaring global variable inside function

global x

This tells Python that x refers to the global variable, not a local one.

Without this, Python would create a local x inside the function.

🔹 5. Modifying the variable

x = x + 1

The value of x is increased by 1.

Since x is global, the change affects the original variable.

🔹 6. Creating a thread

t = threading.Thread(target=task)

A new thread t is created.

The target=task means this thread will run the task() function.

🔹 7. Starting the thread

t.start()

This starts the thread execution.

The task() function begins running concurrently.

🔹 8. Waiting for thread to finish

t.join()

This makes the main program wait until the thread finishes execution.

Ensures that task() completes before moving forward.

🔹 9. Printing the result

print(x)

After the thread finishes, the updated value of x is printed.

Output will be:

1

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Python Coding Challenge - Question with Answer (ID -300326)

 

Explanation:

🔹 1. Importing pandas (implicit step)

Before this code runs, you usually need:

import pandas as pd

✅ Explanation:

pandas is a powerful Python library used for data manipulation.

pd is just an alias (short name) for pandas to make typing easier.

🔹 2. Creating the DataFrame

df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})

✅ Explanation:

pd.DataFrame() creates a table-like structure (rows and columns).

The input is a dictionary:

'A': [1, 2] → Column A with values 1 and 2

'B': [3, 4] → Column B with values 3 and 4

📊 Resulting DataFrame:

index A B

0 1 3

1 2 4

🧠 Key Points:

Columns are A and B

Default index starts from 0

🔹 3. Accessing Data using .loc

print(df.loc[0, 'A'])

✅ Explanation:

.loc[] is used to access data by label (row index + column name)

📌 Breakdown:

0 → Row index

'A' → Column name

So:

👉 df.loc[0, 'A'] means

➡️ “Get value from row 0 and column A”

🔹 4. Output

1

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Python Coding challenge - Day 1109| What is the output of the following Python Code?

 

Code Explanation:

1️⃣ Defining the Class

class A:

Explanation

A class named A is created.

It will have special string representation methods.

2️⃣ Defining __str__

def __str__(self):

    return "STR"

Explanation

__str__ defines human-readable representation.

Used when:

print(a)

str(a)

3️⃣ Defining __repr__

def __repr__(self):

    return "REPR"

Explanation

__repr__ defines official / developer representation.

Used in:

lists

debugging

interactive shell

4️⃣ Creating Object

a = A()

Explanation

Creates an instance a of class A.

5️⃣ Printing Inside List

print([a])

Explanation ⚠️ IMPORTANT

When printing a list:

Python uses __repr__, NOT __str__

👉 So internally:

repr(a)

Which returns:

"REPR"

📤 Final Output

['REPR']

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Python Coding challenge - Day 1111| What is the output of the following Python Code?

 

Code Explanation:

1️⃣ Importing Threading Module

import threading

Explanation

Imports Python’s built-in threading module.

Used to create and manage threads.

2️⃣ Defining Task Function

def task():

    print("X")

Explanation

A function task is defined.

This will run inside a thread.

It simply prints:

X

3️⃣ Creating a Thread Object

t = threading.Thread(target=task)

Explanation

A thread t is created.

target=task means:

When thread runs → it executes task().

4️⃣ Starting the Thread (First Time)

t.start()

Explanation

Starts execution of the thread.

Internally calls:

task()

👉 Output:

X

5️⃣ Waiting for Thread to Finish

t.join()

Explanation

Main thread waits until thread t completes.

Ensures thread has fully finished execution.

6️⃣ Starting the Same Thread Again ❌

t.start()

Explanation ⚠️ IMPORTANT

You are trying to restart the same thread object.

This is NOT allowed in Python.

👉 A thread can be started only once.

❌ What Happens?

Python raises an error:

RuntimeError: threads can only be started once

📤 Final Output

X

RuntimeError

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Python Coding challenge - Day 1112| What is the output of the following Python Code?

 

Code Explanation:

1️⃣ Importing Threading Module

import threading

Explanation

Imports Python’s threading module.

Used to create and run threads.

2️⃣ Global Variable Declaration

x = 0

Explanation

A global variable x is created.

Initial value:

x = 0

3️⃣ Defining Task Function

def task():

Explanation

Function task will run inside the thread.

4️⃣ Local Variable Inside Function

x = 10

Explanation ⚠️ IMPORTANT

This creates a local variable x inside the function.

It does NOT affect the global variable.

👉 So:

global x = 0   (unchanged)

local x = 10   (inside function only)

5️⃣ Creating Thread

t = threading.Thread(target=task)

Explanation

A thread t is created.

It will execute the task() function.

6️⃣ Starting Thread

t.start()

Explanation

Thread starts executing task().

Inside thread:

x = 10   (local variable)

Global x remains unchanged.

7️⃣ Waiting for Thread to Finish

t.join()

Explanation

Main thread waits until task() completes.

8️⃣ Printing Value

print(x)

Explanation

Prints the global variable x.

Since global x was never modified:

📤 Final Output

0

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Python Coding challenge - Day 1108| What is the output of the following Python Code?

 

Code Explanation:

1️⃣ Defining Class A

class A:

Explanation

A base class A is created.

It contains a method show().

2️⃣ Method in Class A

def show(self, x=1):

Explanation

Method show takes a parameter x.

Default value of x is 1.

3️⃣ Printing Value

print(x)

Explanation

Prints the value of x.

4️⃣ Defining Class B (Inheritance)

class B(A):

Explanation

Class B inherits from class A.

It can use and override methods of A.

5️⃣ Overriding Method in Class B

def show(self, x=2):

Explanation

show() is overridden in class B.

Default value of x is now 2.

6️⃣ Calling Parent Method Using super()

super().show(x)

Explanation

Calls the show() method of class A.

Passes value of x from class B.

7️⃣ Creating Object

b = B()

Explanation

Creates an instance b of class B.

8️⃣ Calling Method

b.show()

Explanation

Calls show() from class B.

Since no argument is passed:

x = 2   (default of class B)

Then:

super().show(2)

9️⃣ Execution in Class A

Parent method receives:

x = 2

Prints:

2

📤 Final Output

2

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Python Coding challenge - Day 1107| What is the output of the following Python Code?

 

Code Explanation:

1️⃣ Defining the Class

class A:

Explanation

A class named A is created.

It will be used to create objects.

2️⃣ Creating a Class Variable

x = 5

Explanation

x is a class variable.

It belongs to the class, not to individual objects.

All objects initially share this value.

3️⃣ Creating First Object

a = A()

Explanation

Creates an instance a of class A.

a can access class variable x.

4️⃣ Creating Second Object

b = A()

Explanation

Creates another instance b.

Both a and b currently share:

x = 5

5️⃣ Modifying Variable via Object

a.x = 10

Explanation ⚠️

This does NOT change the class variable.

Instead, it creates a new instance variable x inside object a.

👉 Now:

A.x = 5      # class variable

a.x = 10     # instance variable (new)

b.x = 5      # still uses class variable

6️⃣ Printing Values

print(A.x, a.x, b.x)

Explanation

A.x → class variable → 5

a.x → instance variable → 10

b.x → no instance variable → uses class variable → 5

📤 Final Output

5 10 5

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Python Coding Challenge - Question with Answer (ID -290326)

 

Explanation:

🔹 1. Creating an Empty Dictionary

d = {}

A dictionary d is created.

Dictionaries store data in key → value pairs.

Keys must be hashable (immutable types).

🔹 2. Creating a List as Key

key = [1, 2]

A list [1, 2] is created.

⚠️ Lists are mutable (can be changed later).

🔹 3. Assigning List as Dictionary Key

d[key] = "value"

Here Python tries to use the list as a dictionary key.

🚨 Problem:

Dictionary keys must be:

Immutable

Hashable

Lists are:

Mutable ❌

Not hashable ❌

👉 So Python raises an error:

TypeError: unhashable type: 'list'

🔹 4. Print Statement

print(d)

This line never executes because the program crashes earlier.

❗ Final Output

Error

TypeError: unhashable type: 'list'

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Python Coding challenge - Day 1106| What is the output of the following Python Code?

 

Code Explanation:

1️⃣ Defining Descriptor Class

class Descriptor:

Explanation

A class named Descriptor is created.

This class implements the descriptor protocol.

Descriptors control attribute access in Python.

2️⃣ Defining __get__ Method

def __get__(self, obj, objtype):

Explanation

Called when the attribute is accessed (e.g., a.x).

Parameters:

self → descriptor instance

obj → object (a)

objtype → class (A)

3️⃣ Returning Value in __get__

return obj._x

Explanation

Returns the value stored in _x inside the object.

_x is a hidden/internal attribute.

4️⃣ Defining __set__ Method

def __set__(self, obj, value):

Explanation

Called when assigning value to attribute (a.x = value).

Controls how value is stored.

5️⃣ Modifying Value Before Storing

obj._x = value * 2

Explanation

Multiplies value by 2 before storing.

Stores result in obj._x.

👉 So:

a.x = 5

becomes:

obj._x = 10

6️⃣ Defining Class Using Descriptor

class A:

Explanation

A class A is created.

7️⃣ Assigning Descriptor to Attribute

x = Descriptor()

Explanation

x is not a normal variable.

It is a descriptor object.

So x is controlled by __get__ and __set__.

8️⃣ Creating Object

a = A()

Explanation

Creates an instance a of class A.

9️⃣ Setting Value

a.x = 5

Explanation

Calls:

Descriptor.__set__(a, 5)

Stores:

a._x = 10

🔟 Getting Value

print(a.x)

Explanation

Calls:

Descriptor.__get__(a, A)

Returns:

a._x → 10

📤 Final Output

10

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Python Coding challenge - Day 1105| What is the output of the following Python Code?

 

Code Explanation:

1️⃣ Defining a Metaclass

class Meta(type):

Explanation

Meta is a metaclass.

A metaclass is used to control how classes are created.

By default, Python uses type to create classes.

Here, we customize that process.

2️⃣ Overriding __new__

def __new__(cls, name, bases, d):

Explanation

__new__ is called when a class is being created.

Parameters:

cls → the metaclass (Meta)

name → name of class (A)

bases → parent classes

d → dictionary of class attributes

3️⃣ Modifying Class Attributes

d['x'] = 100

Explanation

Adds a new attribute x to the class.

This happens before the class is actually created.

So every class using this metaclass will have:

x = 100

4️⃣ Creating the Class

return super().__new__(cls, name, bases, d)

Explanation

Calls the original type.__new__() method.

Actually creates the class A with updated attributes.

Returns the newly created class.

5️⃣ Defining Class with Metaclass

class A(metaclass=Meta):

Explanation

Class A is created using Meta.

So Meta.__new__() runs automatically.

It injects x = 100 into class A.

6️⃣ Empty Class Body

pass

Explanation

No attributes are defined manually.

But x is already added by the metaclass.

7️⃣ Creating an Object

a = A()

Explanation

Creates an instance a of class A.

Object can access class attributes.

8️⃣ Accessing Attribute

print(a.x)

Explanation

Python looks for x:

In object → not found

In class → found (x = 100)

📤 Final Output

100

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Python Coding challenge - Day 1104| What is the output of the following Python Code?

 

Code Explanation:

1️⃣ Creating an Empty List

funcs = []

Explanation

An empty list funcs is created.

It will store function objects.

2️⃣ Starting the Loop

for i in range(3):

Explanation

Loop runs 3 times.

Values of i:

0, 1, 2

3️⃣ Defining Function Inside Loop

def f():

    return i * i

Explanation ⚠️

A function f is defined in each iteration.

It returns i * i.

❗ BUT:

It does not store the value of i at that time.

It stores a reference to variable i (not value).

4️⃣ Appending Function to List

funcs.append(f)

Explanation

The function f is added to the list.

This happens 3 times → list contains 3 functions.

👉 All functions refer to the same variable i.

5️⃣ Loop Ends

After loop completes:

i = 2

6️⃣ Creating Result List

result = []

Explanation

Empty list to store outputs.

7️⃣ Calling Each Function

for fn in funcs:

    result.append(fn())

Explanation

Each stored function is called.

When called, each function evaluates:

i * i

👉 But current i = 2

So:

2 * 2 = 4

This happens for all 3 functions.

8️⃣ Printing Result

print(result)

📤 Final Output

[4, 4, 4]

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Python Coding challenge - Day 1103| What is the output of the following Python Code?

 

Code Explanation:

1️⃣ Outer try Block Starts

try:

Explanation

The outer try block begins.

Python will execute everything inside it.

If an exception occurs and is not handled inside → outer except runs.

2️⃣ First Statement

print("A")

Explanation

Prints:

A

No error yet, execution continues.

3️⃣ Inner try Block Starts

try:

Explanation

A nested try block begins inside the outer try.

It handles its own exceptions separately.

4️⃣ Raising an Exception

raise Exception

Explanation

An exception is raised manually.

Control immediately jumps to the inner except block.

5️⃣ Inner except Block

except:

Explanation

Catches the exception raised above.

Since it's a general except, it catches all exceptions.

6️⃣ Executing Inner except

print("B")

Explanation

Prints:

B

7️⃣ Inner finally Block

finally:

Explanation

finally always runs, whether exception occurred or not.

8️⃣ Executing Inner finally

print("C")

Explanation

Prints:

C

9️⃣ Outer except Block

except:

Explanation

This block runs only if an exception is not handled inside.

But here:

Inner except already handled the exception.

So outer except is NOT executed.

📤 Final Output

A

B

C

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Python Coding challenge - Day 1077| What is the output of the following Python Code?

 

Code Explanation:

1. Defining Class Counter

class Counter:

Explanation:

This line defines a class named Counter.

A class is a blueprint used to create objects (instances).

2. Creating Class Variable count

count = 0

Explanation:

count is a class variable.

It belongs to the class Counter, not to individual objects.

All objects created from this class share the same variable.

Initial value:

Counter.count = 0

3. Defining __call__ Method

def __call__(self):

Explanation:

__call__ is a special (magic) method in Python.

It allows an object to behave like a function.

Example:

a()

Python internally executes:

a.__call__()

4. Increasing the Counter

Counter.count += 2

Explanation:

Each time the object is called, the class variable count increases by 2.

Since count belongs to the class, all objects share the same counter.

Equivalent operation:

Counter.count = Counter.count + 2

5. Returning the Updated Value

return Counter.count

Explanation:

After increasing the counter, the updated value of Counter.count is returned.

6. Creating Object a

a = Counter()

Explanation:

This creates an instance a of class Counter.

Because of __call__, object a can be called like a function.

7. Creating Object b

b = Counter()

Explanation:

This creates another instance b of class Counter.

Both a and b share the same class variable count.

8. Executing the Print Statement

print(a(), b(), a())

Python evaluates the function calls from left to right.

8.1 First Call → a()

Python executes:

a.__call__()

Steps:

Counter.count = 0 + 2

Counter.count = 2

Return value:

2

8.2 Second Call → b()

Python executes:

b.__call__()

Steps:

Counter.count = 2 + 2

Counter.count = 4

Return value:

4

8.3 Third Call → a()

Python executes again:

a.__call__()

Steps:

Counter.count = 4 + 2

Counter.count = 6

Return value:

6

9. Final Output

The print statement outputs:

2 4 6

500 Days Python Coding Challenges with Explanation

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Python Coding challenge - Day 1078| What is the output of the following Python Code?

 

Code Explanation:

1. Defining Class A

class A:

    data = []

Explanation:

class A: creates a class named A.

data = [] defines a class variable called data.

This variable is an empty list.

Class variables are shared by all objects of the class unless an object creates its own attribute with the same name.

Initial state:

A.data → []

2. Creating Object a

a = A()

Explanation:

This creates an instance a of class A.

The object a does not have its own data yet.

So it refers to the class variable.

a.data → refers to A.data

3. Creating Object b

b = A()

Explanation:

This creates another instance b of class A.

Like a, it also refers to the class variable data.

b.data → refers to A.data

Current situation:

A.data → []

a.data → []

b.data → []

(All three point to the same list.)

4. Modifying the List Through a

a.data.append(1)

Explanation:

a.data refers to A.data.

.append(1) adds 1 to the list.

Since the list is shared, the change affects A.data and b.data as well.

Now:

A.data → [1]

a.data → [1]

b.data → [1]

5. Assigning a New List to b.data

b.data = [2]

Explanation:

This does not modify the shared list.

Instead, it creates a new instance attribute data for object b.

This new attribute overrides the class variable for b only.

Now:

A.data → [1]

a.data → [1]   (still using class variable)

b.data → [2]   (new instance variable)

6. Printing the Values

print(A.data, a.data, b.data)

Explanation:

A.data → [1]

a.data → [1] (still referring to class variable)

b.data → [2] (instance variable created in step 5)

7. Final Output

[1] [1] [2]

400 Days Python Coding Challenges with Explanation

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