Python Coding challenge - Day 1153| What is the output of the following Python Code?

 

Code Explanation:

🔹 1. First List Creation

a = [1,2,3]

✅ Explanation:

A list a is created.

Elements are:

[1, 2, 3]

🔹 2. Second List Creation

b = [4,5,6]

✅ Explanation:

Another list b is created.

Elements are:

[4, 5, 6]

🔹 3. Using map()

result = map(lambda x,y: x+y, a, b)

✅ Explanation:

map() applies a function to elements of iterables.

🔹 4. Lambda Function

lambda x,y: x+y

✅ Explanation:

Anonymous function (lambda)

Takes:

x, y

Returns:

x + y

🔹 5. Pairwise Processing

map() takes values from both lists together.

🔍 Internally:

x y x+y

1 4 5

2 5 7

3 6 9

🔹 6. map() Returns Iterator

✅ Explanation:

map() does NOT directly return list.

It returns:

map object (iterator)

which generates values lazily.

🔹 7. Converting to List

print(list(result))

✅ Explanation:

list() consumes iterator

Collects all generated values into list

Final list:

[5, 7, 9]

🎯 Final Output

[5, 7, 9]

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Python Coding challenge - Day 1152| What is the output of the following Python Code?

 

Code Explanation:

🔹 1. Generator Function Definition

def gen():

✅ Explanation:

A generator function gen() is created.

Since it uses yield, it becomes a generator.

🔹 2. Receiving Value with yield

x = yield

✅ Explanation:

This is a special use of yield.

🔍 What it does:

Pauses generator execution

Waits to RECEIVE a value using:

send(value)

The received value gets stored in:

x

🔹 3. Second yield

yield x * 2

✅ Explanation:

Multiplies received value by 2

Returns result using yield

🔹 4. Creating Generator Object

g = gen()

✅ Explanation:

Calling gen() does NOT run function immediately.

It creates a generator object g.

🔹 5. Starting Generator

next(g)

✅ Explanation:

Before using:

send(value)

generator must first reach the first yield.

🔍 What happens internally:

Execution starts:

x = yield

Generator pauses here waiting for value.

⚠️ Important:

At this moment:

x → not assigned yet

Generator is now ready to receive data.

🔹 6. Sending Value into Generator

g.send(5)

✅ Explanation:

Sends value 5 into paused generator.

That value becomes:

x = 5

🔹 7. Execution Resumes

After receiving value:

yield x * 2

Calculation:

5 * 2 = 10

Generator yields:

10

🔹 8. Printing Result

print(g.send(5))

✅ Output:

10

🎯 Final Output

10

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Python Coding challenge - Day 1151| What is the output of the following Python Code?

 

Code Explanation:

🔹 1. Class Definition

class Test:

✅ Explanation:

A class named Test is created.

Inside this class, a method gen() is defined.

🔹 2. Generator Method Definition

def gen(self):

✅ Explanation:

gen is an instance method.

self refers to the current object.

⚠️ Important:

Because this method contains yield,

it becomes a generator method.

🔹 3. for Loop Inside Generator

for i in range(3):

✅ Explanation:

Loop runs 3 times:

0, 1, 2

🔹 4. yield Statement

yield i

✅ Explanation:

yield returns one value at a time.

After returning value, function pauses.

State is saved for next iteration.

🔹 5. Object Creation

obj = Test()

✅ Explanation:

Creates object obj of class Test.

🔹 6. Calling Generator Method

obj.gen()

✅ Explanation:

Method does NOT execute immediately.

It returns a generator object.

🔹 7. for Loop Iteration

for x in obj.gen():

✅ Explanation:

Python internally calls:

next(generator)

again and again.

🔹 8. First Iteration

🔍 Execution:

i = 0

yield 0

✔️ Printed:

0

Function pauses here.

🔹 9. Second Iteration

🔍 Execution resumes:

i = 1

yield 1

✔️ Printed:

1

Function pauses again.

🔹 10. Third Iteration

🔍 Execution resumes:

i = 2

yield 2

✔️ Printed:

2

🔹 11. Generator Ends

✅ Explanation:

Loop finishes after i = 2

Generator has no more values

Python raises internal:

StopIteration

The for loop automatically handles it and stops.

🎯 Final Output

0

1

2

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Python Coding challenge - Day 1150| What is the output of the following Python Code?

 

Code Explanation:

🔹 1. Class Definition

class Test:

✅ Explanation:

A class named Test is created.

Inside this class:

A decorator function deco is defined

A method show is defined

🔹 2. Decorator Function Definition

def deco(func):

✅ Explanation:

deco is a decorator function.

It takes another function (func) as argument.

🔍 In this code:

func will be:

show()

🔹 3. Wrapper Function Inside Decorator

def wrapper(self):

✅ Explanation:

wrapper is a new function created inside decorator.

This function will replace original show() method.

self refers to current object (obj).

🔹 4. Modified Return Statement

return "Hello " + func(self)

✅ Explanation:

Calls original function:

func(self)

🔍 Original show() returns:

"World"

So final result becomes:

"Hello World"

🔹 5. Returning Wrapper

return wrapper

✅ Explanation:

Decorator returns wrapper.

So original function is replaced by wrapper function.

🔹 6. Applying Decorator

@deco

✅ Explanation:

This line means:

show = deco(show)

🔍 What happens:

Original show() is passed into deco

deco returns wrapper

show now points to wrapper

🔹 7. Original Method

def show(self):

    return "World"

✅ Explanation:

Original method simply returns:

"World"

But because of decorator,

this method is wrapped inside wrapper.

🔹 8. Object Creation

obj = Test()

✅ Explanation:

Creates object obj of class Test.

🔹 9. Calling Method

print(obj.show())

🔍 What happens internally:

Because of decorator:

obj.show()

actually becomes:

wrapper(obj)

🔹 10. Execution Inside Wrapper

Step 1:

func(self)

calls original:

show(obj)

returns:

"World"

Step 2:

Wrapper adds:

"Hello " + "World"

Result:

"Hello World"

🎯 Final Output

Hello World

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Python Coding challenge - Day 1149| What is the output of the following Python Code?

 

Code Explanation:

1. Generator Function Definition

def gen():

✅ Explanation:

A function gen() is created.

Since it contains yield, it becomes a generator function.

⚠️ Important:

Generator functions do NOT run immediately.

They return a generator object.

🔹 2. First Print Statement

print("A")

✅ Explanation:

When execution starts, "A" will be printed first.

🔹 3. First yield

yield 1

✅ Explanation:

yield returns a value (1)

Then pauses the function

Function state is remembered

🔹 4. Second Print Statement

print("B")

✅ Explanation:

This line runs only when generator resumes after first pause.

🔹 5. Second yield

yield 2

✅ Explanation:

Returns 2

Again pauses the generator

🔹 6. Creating Generator Object

g = gen()

✅ Explanation:

gen() is called

But function body does NOT execute yet

A generator object g is created

🔹 7. First next() Call

print(next(g))

🔍 What happens internally:

Generator starts execution from beginning.

Step-by-step:

Executes:

print("A")

Output:

A

Reaches:

yield 1

Returns:

1

Generator pauses here

✔️ Output so far:

A

1

🔹 8. Second next() Call

print(next(g))

🔍 What happens internally:

Generator resumes from where it paused.

Step-by-step:

Executes:

print("B")

Output:

B

Reaches:

yield 2

Returns:

2

Generator pauses again

🎯 Final Output

A

1

B

2

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Python Coding challenge - Day 1148| What is the output of the following Python Code?

 

Code Explanation:

🔹 1. Function Definition

def func():

✅ Explanation:

A function named func is created.

It contains:

try block

except block

finally block

🔹 2. try Block

try:

    print(10 / 0)

✅ Explanation:

Python tries to execute:

10 / 0

⚠️ Problem:

Division by zero is not allowed.

So Python raises:

ZeroDivisionError

🔹 3. Exception Occurs

ZeroDivisionError

✅ Explanation:

Since an error occurs inside try,

Python immediately stops the remaining try code

It searches for a matching except

🔹 4. except Block

except ZeroDivisionError:

    print("ERROR")

✅ Explanation:

This block catches only:

ZeroDivisionError

✔️ So it runs:

print("ERROR")

Output:

ERROR

🔹 5. finally Block

finally:

    print("DONE")

✅ Explanation:

finally always executes:

Error occurred ✅

No error ✅

Return statement ✅

✔️ So it prints:

DONE

🔹 6. Function Call

func()

✅ Execution Flow:

try → error occurs

       ↓

except runs

       ↓

finally runs

🎯 Final Output

ERROR

DONE

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Python Coding challenge - Day 1147| What is the output of the following Python Code?

 

Code Explanation:

🔹 1. Function Definition

def func():

✅ Explanation:

A function func is defined.

It contains try, except, and finally blocks.

🔹 2. try Block

try:

    print("A")

    return 1

✅ Explanation:

First, "A" is printed.

Then return 1 is executed.

⚠️ Important:

Even though return is reached, Python does NOT immediately exit

It will still execute the finally block

🔹 3. except Block

except:

    print("B")

✅ Explanation:

Runs only if an exception occurs in try

In this case:

No error happens

So this block is skipped

🔹 4. finally Block

finally:

    print("C")

✅ Explanation:

This block always executes, no matter what:

Return

Exception

Normal execution

👉 So "C" is printed even after return

🔹 5. Calling the Function

print(func())

🔍 Step-by-step execution:

print("A") → prints:

A

return 1 is prepared (but paused)

finally runs → prints:

C

Function returns 1

Outer print() prints:

1

🎯 Final Output

A

C

1

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Python Coding challenge - Day 1146| What is the output of the following Python Code?

 

 Code Explanation:

🔹 1. Outer Function Definition

def outer(x):

✅ Explanation:

A function outer is defined.

It takes one argument: x.

This function will return another function.

🔹 2. Inner Function Definition

def inner(y):

✅ Explanation:

Inside outer, another function inner is defined.

It takes parameter y.

🔹 3. Using Outer Variable Inside Inner

return x + y

✅ Explanation:

inner uses:

y → its own parameter

x → from outer function

👉 This is called a closure:

Inner function remembers the value of x even after outer finishes

🔹 4. Returning Inner Function

return inner

✅ Explanation:

outer does NOT return a value directly

It returns the function inner itself

🔹 5. Calling Outer Function

f = outer(5)

🔍 What happens:

outer(5) is executed

x = 5

Returns inner function

👉 Now:

f → inner (with x = 5 stored)

🔹 6. Calling Returned Function

print(f(3))

🔍 What happens:

Calls:

inner(3)

Inside inner:

x = 5 (remembered from closure)

y = 3

Calculation:

5 + 3 = 8

🎯 Final Output

8

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Python Coding challenge - Day 1137| What is the output of the following Python Code?

 

Code Explanation:

🔹 1. Initializing the List

funcs = []

An empty list funcs is created

This list will store functions

🔹 2. Starting the Loop

for i in range(3):

Loop runs 3 times with values:

i = 0, 1, 2

🔹 3. Defining the Function Inside Loop

def f():

    return i

A function f is defined in each iteration

⚠️ Important: The function does not store the current value of i immediately

Instead, it refers to i (late binding)

👉 This means:

All functions will look up i when they are called, not when they are created

🔹 4. Appending Function to List

funcs.append(f)

The function f is added to the list

After loop ends, funcs contains 3 functions

🔹 5. After Loop Ends

Final value of i is:

i = 2

All functions refer to this same i

🔹 6. Calling the Functions

print([f() for f in funcs])

Each function is called one by one

Each function returns the current value of i, which is 2

🔹 ✅ Final Output

[2, 2, 2]

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Python Coding challenge - Day 1136| What is the output of the following Python Code?

 

Code Explanation:

🔹 1. Metaclass Definition

class Meta(type):

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

        dct['x'] = 100

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

Meta is a metaclass (inherits from type)

__new__ runs when a class is being created, not an object

It receives the class attributes in dct

It modifies the class dictionary by setting:

x = 100

🔹 2. Class Creation (A)

class A(metaclass=Meta):

    x = 10

Python sends this class definition to the metaclass

Internally:

Meta.__new__(Meta, 'A', (), {'x': 10})

The metaclass changes:

{'x': 10} → {'x': 100}

🔹 3. Final Class Structure

After metaclass processing, class A becomes:

class A:

    x = 100

The original x = 10 is overwritten

🔹 4. Object Creation

obj = A()

Creates an instance of class A

obj itself has no x attribute

🔹 5. Attribute Lookup

print(obj.x)

Python checks:

obj → not found

class A → finds x = 100

🔹 ✅ Final Output

100

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Python Coding challenge - Day 1141| What is the output of the following Python Code?

 

Code Explanation:

🔹 1. Importing Module

import copy

✅ Explanation:

Imports Python’s built-in copy module.

This module provides:

copy.copy() → shallow copy

copy.deepcopy() → deep copy

🔹 2. Creating Nested List

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

✅ Explanation:

a is a list of lists (nested structure).

Memory structure:

Outer list contains two inner lists

a → [ [1,2], [3,4] ]

🔹 3. Deep Copy

b = copy.deepcopy(a)

✅ Explanation:

Creates a completely independent copy of a.

Both:

Outer list

Inner lists

are copied separately.

🔍 Important:

b ≠ a

b[0] ≠ a[0]

✔️ No shared references

🔹 4. Modifying Copied List

b[0][0] = 100

✅ Explanation:

Changes first element of first inner list in b

So:

b → [ [100,2], [3,4] ]

🔹 5. Printing Original List

print(a)

✅ Explanation:

Since a and b are completely independent,

Changes in b do NOT affect a

🎯 Final Output

[[1, 2], [3, 4]]

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Python Coding challenge - Day 1140| What is the output of the following Python Code?

 

 Code Explanation:

🔹 1. Function Definition

def gen():

✅ Explanation:

A function gen is defined.

Because it uses yield, it becomes a generator function (not a normal function).

🔹 2. First yield

yield 1

✅ Explanation:

yield produces a value without ending the function.

It pauses execution and remembers its state.

🔹 3. Second yield

yield 2

✅ Explanation:

When resumed, the function continues from where it stopped.

Now it yields 2.

🔹 4. Third yield

yield 3

✅ Explanation:

On next resume, it yields 3.

After this, the generator is exhausted.

🔹 5. Creating Generator Object

g = gen()

✅ Explanation:

Calling gen() does NOT execute the function immediately.

It returns a generator object.

Execution starts only when next() is called.

🔹 6. First next() Call

print(next(g))

🔍 What happens:

Starts execution of gen()

Runs until first yield

✔️ Output:

1

🔹 7. Second next() Call

print(next(g))

🔍 What happens:

Resumes from previous pause

Continues to second yield

✔️ Output:

2

🎯 Final Output

1

2

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Python Coding challenge - Day 1139| What is the output of the following Python Code?

 

Code Explanataion:

🧩 1. Decorator Function Definition

def decorator(func):

Defines a function named decorator.

It takes another function (func) as an argument.

This is the core idea of decorators: functions that modify other functions.

🔁 2. Wrapper Function Inside Decorator

    def wrapper():

A nested function wrapper is defined.

This function will replace/extend the behavior of func.

✖️ 3. Modify Original Function Output

        return func() * 2

Calls the original function func().

Multiplies its result by 2.

Returns the modified value.

🔙 4. Return Wrapper Function

    return wrapper

The decorator returns the wrapper function.

This means the original function will be replaced by wrapper.

🎯 5. Applying the Decorator

@decorator

This is syntactic sugar for:

say = decorator(say)

It passes say into decorator and replaces it with wrapper.

📦 6. Original Function Definition

def say():

    return 5

A simple function that returns 5.

But due to the decorator, this function will not run directly.

🔄 7. What Actually Happens Internally

After decoration:

say = decorator(say)

Now say actually refers to wrapper.

When you call say(), it calls wrapper().

🖨️ 8. Function Call and Output

print(say())

Execution Flow:

say() → actually calls wrapper()

wrapper() → calls original func() → returns 5

5 * 2 = 10

✅ Final Output

10

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Python Coding challenge - Day 1138| What is the output of the following Python Code?

 

Code Explanation:

🧩 1. Function Definition: outer

def outer():

This defines a function named outer.

It acts as an enclosing (parent) function.

📦 2. Variable Initialization

    x = 10

A local variable x is created inside outer.

Initial value of x is 10.

🔁 3. Inner Function Definition

    def inner():

A nested function named inner is defined inside outer.

It has access to variables of outer (like x).

🔗 4. Using nonlocal

        nonlocal x

nonlocal means:

“Use the variable x from the nearest enclosing scope (outer function), not create a new one.”

Without nonlocal, modifying x would cause an error.

➕ 5. Modify the Variable

        x += 5

Adds 5 to the existing value of x.

Since x is nonlocal, it updates the outer function’s x.

🔙 6. Return Updated Value

        return x

Returns the updated value of x.

📤 7. Return Inner Function

    return inner

The outer function returns the inner function itself, not its result.

This creates a closure (function + its environment).

🎯 8. Create Function Instance

f = outer()

Calls outer(), which returns inner.

Now f becomes a reference to inner, with x = 10 preserved.

🖨️ 9. Function Calls and Output

print(f(), f())

First Call: f()

x = 10

x += 5 → 15

Returns 15

Second Call: f()

x = 15 (value persists due to closure)

x += 5 → 20

Returns 20

✅ Final Output

15 20

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Python Coding challenge - Day 1131| What is the output of the following Python Code?

 

Code Explanation:

🔹 1. Base Class Definition

class A: 

    pass

✅ Explanation:

A class A is created.

pass means the class has no attributes or methods (empty class).

🔹 2. Derived Class (Inheritance)

class B(A): 

    pass

✅ Explanation:

Class B is created and inherits from class A.

This means:

B gets all properties of A.

B IS-A A (important concept in OOP).

🔹 3. Object Creation

obj = B()

✅ Explanation:

An object obj of class B is created.

So:

obj belongs to class B

But also indirectly belongs to class A (because of inheritance)

🔹 4. isinstance() Check

isinstance(obj, A)

✅ Explanation:

Checks if obj is:

An instance of class A OR

Any subclass of A

🔍 In this case:

obj is instance of B

B inherits from A

So:

True

🔹 5. type() Comparison

type(obj) == A

✅ Explanation:

type(obj) returns the exact class of the object.

Here:

type(obj) → B

So comparison becomes:

B == A  → False

🔹 6. Final Print Statement

print(isinstance(obj, A), type(obj) == A)

✅ Output:

True False

🎯 Final Output

True False

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Python Coding challenge - Day 1130| What is the output of the following Python Code?

 

Code Explanation:

🔹 1. Class Definition

class Test:

✅ Explanation:

A class named Test is created.

It will contain a variable and two methods.

🔹 2. Class Variable

x = 10

✅ Explanation:

x is a class variable.

Shared across all instances of the class.

Accessible via:

Test.x

cls.x (inside class methods)

🔹 3. Class Method (@classmethod)

@classmethod

def show(cls):

    return cls.x

✅ Explanation:

@classmethod decorator defines a method that works with the class, not instance.

cls refers to the class (Test).

🔍 What happens:

cls.x → accesses class variable x

Returns:

10

🔹 4. Static Method (@staticmethod)

@staticmethod

def display():

    return Test.x

✅ Explanation:

@staticmethod creates a method that:

Does NOT take self or cls

Works like a normal function inside the class

🔍 What happens:

Directly accesses:

Test.x

Returns:

10

🔹 5. Calling Methods

print(Test.show(), Test.display())

✅ Step-by-step:

➤ Test.show()

Calls class method

cls = Test

Returns:

10

➤ Test.display()

Calls static method

Returns:

10

🎯 Final Output

10 10

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Python Coding challenge - Day 1129| What is the output of the following Python Code?

 

Code Explanation:

🔹 1. Class Definition

class Test:

✅ Explanation:

A class named Test is created.

This class will define how its objects are represented as strings.

🔹 2. __str__ Method

def __str__(self):

    return "STR"

✅ Explanation:

__str__ is a magic method used for user-friendly string representation.

It is called when:

print(obj)

str(obj)

Here, it returns:

"STR"

🔹 3. __repr__ Method

def __repr__(self):

    return "REPR"

✅ Explanation:

__repr__ is another magic method used for:

Debugging

Developer-friendly representation

It is called when:

You type obj in interpreter

Or when __str__ is not defined

🔹 4. Creating Object

obj = Test()

✅ Explanation:

An object obj of class Test is created.

No constructor (__init__) is defined, so default is used.

🔹 5. Printing Object

print(obj)

✅ What happens internally:

Python follows this priority:

Call __str__()

If not available → call __repr__()

🔍 In this case:

__str__ exists → used

So:

obj.__str__()

returns:

"STR"

🎯 Final Output

STR

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Python Coding challenge - Day 1127| What is the output of the following Python Code?

 

Code Explanation:

🔹 1. Class Definition

class Test:

    x = []

✅ Explanation:

A class named Test is created.

x = [] is a class variable (shared by all objects).

This means:

Only one list exists in memory.

All instances (a, b, etc.) will refer to the same list unless overridden.

🔹 2. Constructor (__init__ method)

def __init__(self, value):

    self.x.append(value)

✅ Explanation:

This method runs whenever an object is created.

self refers to the current object.

self.x.append(value):

Python first looks for x inside the instance.

Not found → it looks in the class.

Finds x (the shared list).

So, it appends the value to the same shared list.

🔹 3. Creating First Object

a = Test(1)

✅ What happens:

Object a is created.

__init__(1) runs.

self.x.append(1) → list becomes:

[1]

🔹 4. Creating Second Object

b = Test(2)

✅ What happens:

Object b is created.

__init__(2) runs.

Again, self.x refers to the same class list.

2 is appended → list becomes:

[1, 2]

🔹 5. Printing Values

print(a.x, b.x)

✅ Explanation:

Both a.x and b.x refer to the same list.

So output is:

[1, 2] [1, 2]

⚠️ Key Concept (Very Important)

🔸 Class Variable vs Instance Variable

Type Defined Where Shared?

Class Variable Inside class ✅ Yes

Instance Variable Inside __init__ using self ❌ No

🔥 Why This Happens

Because:

x = []

is defined at class level, not inside __init__.

✅ How to Fix (If You Want Separate Lists)

class Test:

    def __init__(self, value):

        self.x = []      # instance variable

        self.x.append(value)

✔️ Output now:

[1] [2]

🎯 Final Answer

[1, 2] [1, 2]

 Book:  500 Days Python Coding Challenges with Explanation

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Python Coding challenge - Day 1126| What is the output of the following Python Code?

 

Code Explanation:

1️⃣ Defining the Class

class A:

Explanation

A class A is created.

It will contain variables and methods.

2️⃣ Defining Class Variable

x = 10

Explanation

x is a class variable.

It belongs to the class, not individual objects.

3️⃣ Defining @classmethod

@classmethod

def f(cls):

Explanation

f is a class method.

It receives the class itself as cls.

4️⃣ Accessing Class Variable via cls

return cls.x

Explanation

Accesses class variable x using cls.

Works for inheritance too (dynamic reference).

5️⃣ Defining @staticmethod

@staticmethod

def g():

Explanation

g is a static method.

It does NOT receive self or cls.

6️⃣ Accessing Class Variable Directly

return A.x

Explanation

Directly accesses class A.

Not flexible for inheritance (hardcoded).

7️⃣ Calling Methods

print(A.f(), A.g())

Explanation

Calls both methods using class A.

🔄 Method Execution

🔹 A.f()

cls = A

Returns:

A.x → 10

🔹 A.g()

Directly returns:

A.x → 10

📤 Final Output

10 10

Book:  700 Days Python Coding Challenges with Explanation

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Python Coding challenge - Day 1125| What is the output of the following Python Code?

 

Code Explanation:

1️⃣ Importing dataclass

from dataclasses import dataclass

Explanation

Imports the dataclass decorator.

It auto-generates methods like __init__, __repr__, etc.

2️⃣ Applying @dataclass

@dataclass

Explanation

Converts class A into a dataclass.

Automatically creates constructor like:

def __init__(self, x=[]):

    self.x = x

⚠️ Important: x=[] is evaluated once, not per object.

3️⃣ Defining Class

class A:

Explanation

Defines class A.

4️⃣ Defining Attribute with Default Value

x: list = []

Explanation ⚠️ CRITICAL

x is given a default value of an empty list.

This list is shared across all instances.

👉 Only ONE list is created in memory.

5️⃣ Creating First Object

a1 = A()

Explanation

a1.x refers to the shared list.

6️⃣ Creating Second Object

a2 = A()

Explanation

a2.x refers to the same shared list.

👉 So:

a1.x is a2.x → True

7️⃣ Modifying List from a1

a1.x.append(1)

Explanation

Adds 1 to the shared list.

👉 Now shared list becomes:

[1]

8️⃣ Printing from a2

print(a2.x)

Explanation

Since a2.x points to the same list:

[1]

📤 Final Output

[1]

Book: 100 Python Projects — From Beginner to Expert

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