Weclome to Learning Python with me

1. Basics
2. Variables
3. Data Types
4. Input
5. 1st Exercise
6. Type Casting/Conversion
7. 2nd Exercise
8. String Operations
9. 3rd Exercise
10. Operators
11. Condition if/else statements
12. Mini Project Calculator
13. loops
14. 4th exercise
15. Python Data Structure
Lists
Tuple
Set
Dictionary
16. 5th exercise

1-basics

Python is case-sensitive.

print("Hello World")

print() is used to display output. like print("Tea") or print(10)

print("Hello", "World") // Multiple values can be printed together.

Comments

Use # for comments

and to selected multiple block of code just click Ctrl + /

in terminal to use the previous command just press upwards arrow (↑)

python is case senstive meaning print() will work but not Print()

2-variables

A variable stores a value.

For ex name = "Sarbesh" age = 26 cgpa = 8.5

Here: name → variable "Sarbesh" → value = → assignment operator

The assignment operator stores the value on the right-hand side in the variable on the left-hand side.

**Variables can be updated and the new variable will get printed **
age = 26
age = 25.5

print(age)

Output: 25.5

to print varibales just type print(variable name) and no need of " " even its a string

variable code-

name = "Sarbesh"

first_name = "Sarbesh"
last_name = "Mallick"
age = 26 
gender = "male"
eye = "brown"
age = 100


print(first_name)
print(age)

print(gender , eye)

print(30)

Output- Sarbesh 100 male brown 30

3-data-types

Python hv 4 primitive data types

Type	Meaning	Example
str	String / text	"Sarbesh"
int	Integer / whole number	25
float	Decimal number	8.5
bool	Boolean	True / False

Examples:

name = "Sarbesh" # str age = 25 # int cgpa = 8.5 # float isStudent = True # bool

Boolean values must use capital letters: True False

Not: true and false. Python is case-sensitive.

Checking the data type-

Use the built-in type() function:

print(type(variable name))

type check code-

name = "Sarbesh"
age = 26
balance = 0.5 
gender = "Male"


print (type(name))

print (type(age))

print (type(balance))

Output- <class 'str'> <class 'int'> <class 'float'>

type() tells us what type of value a variable currently contains.
in c++ we need to define our variable values like for numbers int num = 5; but in python we can just declare it as it is without typing int
to check what the type is we do print(type(variable name))

4-input

Use input() to take input from the user.

name = input("Enter your name: ") print(name)

Eg code-

name = input("What is ur name: ")
profession = input(" what is ur job: ")
age = input("what is ur age: ")

print(name)
print(profession)
print(age)

Input What is ur name: Sarbesh what is ur job: Dev what is ur age: 16

Output Sarbesh Dev 16

6. Input code-

name = input("Enter your name: ")

print("Namaste" , name)

Input Enter your name: Sarbesh

Output- Namaste Sarbesh

Tip-

suppose my python filename is 6. Input.py

if we run this program using python filename.py then remember as I have used spaces so use " " in terminal
like for example- python "6. Input.py"

Important-

input() always returns a string.

Even if the user enters: 23 Python initially stores it as: "23"
not: 23

input returns a string even it is a number(int)

Concatenation

concatenation means joining strings.

for eg:

name = "Sarbesh" print("Hello " + name)

Output- Hello Sarbesh

Remember Be careful about spaces:

"Hello" + name produces: HelloSarbesh

"Hello " + name produces: Hello Sarbesh

The + operator can concatenate strings.

7. concatenation code-

name = input("Enter your name: ")

print("Hello Namaste " + name)

Input Enter your name: Sarbesh

Output- Hello Namaste Sarbesh

5-First-Exercise

Problem stat- Add a person with first name as Tony and last name as Stark. Tony's age is 53. Tony's height is 1.85m. Tony is secretly a superhero. Take his superhero name as input & print it. -->

first_name = "Tony"
last_name = "Stark"

age = 53
height = 1.85 

name = input("What is his superhero name: ")
print(name)

Input What is his superhero name: Ironman

Output Ironman

6-Type-Casting-or-Type-Conversion

Because input() returns a string, we often need to convert it before performing calculations.

type casting -> when coders changes type conversion -> python interpreter automatically does it

Common conversion functions: int() float() str() bool()

type casting code-

age = input("Enter your age: ")

print (type(age))

print (age)

Input Enter your age: 23

Output <class 'str'> 23

Note-

print (age + 1) ❌ // we cannot do this as age varibale value i.e 23 is passed as string
see the age varibale is passed as string and not integer although 23 is an integer
if we have to do print (age + 1) we cannot do that
it will show TypeError: can only concatenate str (not "int") to str

Solution for this

age = input("Enter your age: ")

age = int(age)

print (type(age))

print (age)
print (age + 1)

Input Enter your age: 23

Output <class 'int'> 23 24

Now age is an integer

Temporary Conversion vs Reassignment

Let's understand this with code-

old_age = input("Enter ur age: ")

new_age = int(old_age) + 2

print(new_age)

print (float(new_age))                              # here we converted int to float. It is not conversion but Reassignment 

print (type(new_age))

Input- Enter ur age: 23

Output- 25 25.0 <class 'int'>

Note-

if u wondering after converting from int to float why class is int and not float because its a temporaray expression
new_age = float(new_age) // to convert it permanently

type casting -> when coders changes type conversion -> python interpreter automatically does it

Conversion examples- print (1 + 1.5) // python converts 1 into 1.0 and will give you answer in float (decimal)

Temporary Conversion-

age = 23

print(float(age)) print(type(age))

Output: 23.0 <class 'str'>

float(age) converted the value for that expression, but age itself remained a string.

Permanent conversion / reassignment-

age = 23

age = float(age)

print(age) print(type(age))

Output 23.0 <class 'float'>

The converted value was assigned back to age.

Easy rule

print(float(age)) → temporary conversion

converts the value for that expression; original variable remains unchanged.

age = float(age) print(age) → conversion + reassignment

converts the value and stores the converted value back in the variable.

You do not always need a new variable.

For example:

print(float(age) + 1.2)

is perfectly valid when you only need the converted value temporarily.

Another code eg-

age = input("enter age: ")

print(float(age) + 1.2)

print(type(age))

Input enter age: 23

Output 24.2 <class 'str>

Temp conversion- print(float(age)) // age is still a string

Permanent Conversion- age = float(age) // age is now float

age = input("enter age: ") age = print(float(age) + 1.2) print(type(age))

Input enter age: 23

output 24.2 <class 'NoneType'>

variable e like for example age = ... amra bina brackets chara use korte pari if we add smthng + Eg- age = age(...) + 1
but print e puro print statement ta bracket under e mane print(... + 1 )

Explicit vs Implicit Conversion

Implicit Conversion-

Python automatically performs a compatible conversion.

Example:

print(1 + 1.5)

Result: 2.5

the above code is implicit is automatically converted by python intepreter, 1 (int) is converted into 1.0(float)
Python promotes the integer to a float during the operation.

Explicit Conversion / Type Casting-

The programmer tells Python to convert the type.

example:

print(1 + int(2.9999))

// Python is explicitly told to convert 2.9999 to an integer.

Result: 3

another example: print (1 + int(1.5))

this is type casting
here in the above code we forced (type casting) 1.5 to become int and it got casted into 1 , so 1 + 1 = 2
Result: 2

Summary

print (1 + 2.9999) // Type Conversion (implicit) // Result: 3.9999 print (1 + int(2.9999)) // Type Casting (explicit) // Result: 3

7-Second-Exercise

Problem stat- Sum Program where a , b are integers nos & we hv to take input and calc the sum of a & b and print it

a = input("Enter first number: ")

b = input("Enter second number: ")

total = int(a) + int(b)                                                         

print("the sum is" , total)           

print(type(a))
print(type(total))

Input Enter first number: 10 Enter second number: 20

Output the sum is 30 <class 'str'> <class 'int'>

Alt a = int(input("Enter first number: "))
b = int(input("Enter second number: ")) total = (a + b) print(total)

a = int(input("Enter 1st number: "))
b = int(input("Enter 2nd number: "))

num_sum = a + b                                     

print("The sum of 2 integers is" , num_sum)

print(type(num_sum))
print(type(a))

Input Enter 1st number: 10 Enter 2nd number: 20

Output The sum of 2 integers is 30 <class 'int'> <class 'int'>

8-string-operations

Strings have useful methods
Strings are immutable.
String operations do not modify the original string rather a new string is produced.

let's understand from code-

name = "Sarbesh Mallick "

print (name)

print (name.upper())

print (name.lower())

print (name)                                              //  the original value is intact

Output- Sarbesh Mallick SARBESH MALLICK sarbesh mallick Sarbesh Mallick // the original value is intact cuz strings are immutable

find() method

find() searches for a substring/character and returns its index/position.
returns no of the index and not boolean (true/false)

example:

name = "Sarbesh" print(name.find("b"))

Output: 3

If the character exists, Python returns its index.
If it doesn't exist: name.find("z")
```
returns:
-1
```

Summary: find() → tells you where something occurs. It does not simply return True or False.

Code-

name = "Sarbesh Mallick"

print (name.find('M'))                                               // if that string exists then we will get the index of that thing

Output- 8

Remember- find function returns index which is position if we search something that is not present we will get -1 as value which is invalid

replace() method

replace() is a string method, not a standalone function.

for eg:

name = "Sarbesh Mallick" print(name.replace("Mallick", "Muthu"))

Result: Sarbesh Muthu

You call it using .
variable_name.replace(...)
.replace()

example code-

name = "Sarbesh Mallick"

print (name.replace("Sarbesh Mallick" , "Muthu"))
print (name.replace("Mallick" , "Muthu"))                           
print (name.replace("S" , "D"))                                         // when we need to replace smthng partial

Output- Muthu Sarbesh Muthu Darbesh Mallick

in operator

It is a check method.
it checks whether something exists or not and results comes in boolean (True/False)

for eg 1

name = "Sarbesh" print("S" in name)

Result: True

for eg 2 numbers = [10, 20, 30] print(20 in numbers)

Result: True

not in

for eg 3

numbers = [10, 20, 30] print(40 not in numbers)

Result: True

in is a keyword in python dictionary, we cannot use in as a varibale name, in operator job is to search

Note-

'S' in name → checks whether S exists anywhere

Whereas:

name.startswith('S') → checks whether the string starts with S.

Function vs Method

Functions are generally called independently:

print() input() int() float()

Methods are called on an object:

name.upper() name.lower() name.replace()

Functions → generally called independently: print(), input(), int()
Methods → called using . on an object: "hello".upper(), "hello".replace()

9-Third Exercise

Problem stat-

first_product = 101.55
second_product = 99.95
third_product = 15.15 


total = int(first_product) + int(second_product) + int(third_product)

print(total)

print ("the average price is: " , total/3)

name = input("What's your supehero name: ")

print (name.startswith('s') or name.startswith('S'))                            // Alt-    print(name.startswith(('s', 'S')))     OR       print(name.lower().startswith('s'))

Output- 215 the average price is: 71.66666666666667 What's your supehero name: Sarbesh True

if I want to check if S or s in the whole name is there or not then: print ('S' in name or 's' in name)

10-Operator

Arithmetic Operator

Arithmetic Operators-

Operator	Name	Example
+	Addition	5 + 2
-	Subtraction	5 - 2
*	Multiplication	5 * 2
/	Division	5 / 2
//	Floor Division	5 // 2
%	Modulus / Remainder	5 % 2
**	Exponentiation / Power	5 ** 2

print (5 + 3) // + is addition operator and 5,3 are operands print (5 - 3) print (5 * 3) print (5 / 3) // / is division operator

print (5 // 3) // is floor division and completely removes the decimal part, only int part is left

print (5 % 3) // % is modulus or remainder , very helpful to check even & odd

print (5 ** 3) // ** is exponent of or power of 5³ = 555 = 125

5/2 -> 2.5
5 // 2 -> 2

Very useful for checking even/odd: number % 2 == 0 → even number % 2 != 0 → odd
5 ** 2 -> 25 (5² = 25)

Operator Precedence

Python follows operator precedence rules when multiple operators appear in an expression.
just like in real life BODMAS is followed
operator precedence are rules that defines which operator has higher priority compared to other

For example:

2 + 5 * 3
= 17 Multiplication happens first

But parentheses have higher priority: (2 + 5) * 3 Result: 21

Basic rule to remember

()
**
- / // %

For operators with the same precedence, evaluation generally proceeds from left to right.
When in doubt, use parentheses to make the intended order clear.
if * and / both are present then our operations will start from Left -> Right
parantheses() have highest priority.

Operator comparison

Operator Comparison

Comparison operators compare values and produce a Boolean result: TRUE or FALSE

Operator	Meaning
>	Greater than
<	Less than
>=	Greater than or equal to
<=	Less than or equal to
==	Equal to
!=	Not equal to

Examples:

3 > 2 True

2 < 5 True

2 == 5 False

2 != 5 // != is NOT operator True

Remember-

= vs ==

= is the assignment operator: age = 25 It assigns a value.

== is the comparison operator: age == 25 It checks whether the values are equal.

= → assign == → compare

This distinction is extremely important in if statements.

Logical Operator

Logical Operator

Python has three main logical operators: and or not

and Both conditions must be true. (3 < 5) and (3 < 12) → True

Conceptually: True AND True → True True AND False → False False AND True → False False AND False → False

or At least one condition must be true. (3 > 5) or (3 > 2) → True

Conceptually: True OR True → True True OR False → True False OR True → True False OR False → False

not Reverses a Boolean value.

not True → False

not False → True

these operators work in statement or expression . for eg- () or ()

or -> (atleast one statement is true) and -> (both are true) not -> (reverses any value)

example

stt1 = 3 > 5 // False stt2 = 3 > 2 // True

print (stt1 or stt2) // Ans True (cuz one statement stt2 is True )

print ((3 > 5) or (3 > 2)) // we can write directly also

print ((3 < 5) and (3 < 12)) // Ans True (both the statements are true )

not operator always does the reverse

print (not(3 > 2)) // Ans False , although it is true but as it is not so False

print (not True) // Ans False

11-Conditional-statements

Conditional statements allow Python to make decisions.

if
elif
else

example code1-

age = 24 

if age >= 18:                                  # in cpp we use {} where if statement is true execute everything inside it. in py it is :
    print("you are adult")                      # 4 spaces . this is called identation which is proper spacing 
    print("you can vote")

elif age < 18:                                  # elif is else if . after if everything we can write in elif 
    print ("you can't vote / drive")

output you are an adult you can vote

example code 2-

Problm stat- Marks are given out of 100. Assign a grade based on the marks: 80–100 → A 60–80 → B 60 → C write a Python program using if, elif, and else to determine and print the grade.

marks = int(input("Enter marks: "))

if marks >= 80:
    print('A')

elif marks >= 60:
    print('B')

else:
    print('C')

If you want to explicitly add into a range then follow this-

if marks >= 60 and marks <= 80: print("B")

marks should be greater than or equal to 60 AND less than or equal to 80.

Cleaner way- if 60 <= marks <= 80: print("B")

few more examples combing if/esle with operators

age = 25

if age >= 18 and age <= 60: print("Eligible")

name = input("Enter name: ")

if "S" in name or "s" in name: print("S exists") else: print("S does not exist")

This combines: in → membership operator or → logical operator if/else → conditional statement

12-mini-project-calculator

Problem stat-

a = float(input("Enter first number: "))
b = float(input("Enter second number: "))

op = input("Enter operator (+, -, *, /, %, **): ")


if op == '+':
    print("Result:" , a+b)


elif op == '-':
    print("Result:" , a-b)


elif op == '*':
    print("Result:" , a*b)


elif op == '/':
    print("Result:" , a/b)


elif op == '%':
    print("Result:" , a%b)


elif op == '**':
    print("Result:" , a**b )


else:
    print("INVALID OPERATION")

13-loops

Range

range() function returns a range object that is a sequence of numbers. starts from 0

Structure for Range

range(start, stop, step)

range (start=0, stop, step=1) // default value if nothing specified. but we have to write a stop value everywhere

Example 1-

num = range(5)
print(num) // 0,1,2,3,4

Example 2- num = range(2, 6) print(num) // 2,3,4,5

Example 3-

num = range(10, 0, -2) print(num) // 10, 8, 6, 4 , 2

we use range in loops like for i in range(5): print(i)

while loop

Example 1

counter = 1 while counter <= 5: print("Sarbesh win") counter = counter + 1

Output: Sarbesh win Sarbesh win Sarbesh win Sarbesh win Sarbesh win

Example 2

counter = 1 // for counter we give variable name as i while counter <= 5: print(counter) counter = counter + 1

Output: 1 2 3 4 5

Example 3

i = 0

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

Output: 0 1 2 3 4

if we encounter infinite loop just press Ctrl + C to stop it

production

A while loop is useful when you don't necessarily know beforehand how many iterations you'll need.

password = ""

while password != "python123":
    password = input("Enter password: ")

Here we don't say: Run this 5 times.
Instead: Keep running while the condition is true.
for loop -> Iterate over a known sequence/range.
while loop -> Continue until some condition changes.

Danger of while loop

i = 0

while i < 5:
    print(i)

This never changes i.
So i = 0 0 < 5 → True print 0 < 5 → True print 0 < 5 → True print
That's an infinite loop.
we normally need state change

i = 0 while i < 5: print(i) i = i + 1

Example 1 of pattern printing using while

i = 1 while i <= 5: print(i * '*') i = i + 1

Output

Explaination-

whenever an integer number is multiplied by a string, that no of times the strings gets repeated. Multiplication * here is used as concatenation

like for eg i = 1 while i <= 5: print(i * 'hello') i = i + 1

Output: hello hellohello hellohellohello hellohellohellohello hellohellohellohellohello

Reverse pattern printing using while

i = 5 while i > 0: print(i * '*') i = i - 1

Output

** *

for loop

Example 1

for i in range(5): print(i)

Output: 0 1 2 3 4

Another example

nums = range(5)

for i in nums: print(i)

Output 0 1 2 3 4

Example 2

for i in range(2,6): print(i)

Output: 2 3 4 5

if its i in range(2,6,2): print(i) // 2 4
if its i in range(2,6,5) print(i) // 2

Example 3: Another way of finding even numbers

for i in range(2, 11, 2):
print(i)

Output: 2 4 6 8 10

Example 4: Cleaner approach for finding even numbers

for i in range(1, 11): // to check even no if i % 2 == 0: print(i)

Output: 2 4 6 8 10

Example 5: printing multiples of 3 from (1 to 30)

for i in range(1,31): if i % 3 == 0: print(i)

Output 3 6 9 12 15 18 21 24 27 30

Default structure of range

range (start, stop, step ) range (optional, must, optional) range (0,must,0)

Concept of for loop

in c++ we use for loops like this

for (int i = 0; i < 5; i++) { cout << i; }

Python doesn't require you to manually write:

initialization
condition
increment

Instead for i in range(5):

means "Take each value produced by range(5) and assign it to i, one at a time."

for loop dosen't require range() always

Python's for loop can directly iterate over collections.


names = ["Sarbesh", "Rahul", "Amit"]

for name in names:
    print(name)

Output Sarbesh Rahul Amit

Why this matters in production

Imagine you're processing data from an API:

users = get_users()

for user in users:
    process_user(user)

You don't care whether there are 10 users or 10,000 users.

break

It means Immediately terminate the current loop.

Example 1

for i in range(10): if i == 5: break

print(i)

Output 0 1 2 3 4

when i == 5 becomes true , Python executes break. The Loop ends immediately

Example 2: printing multiples of 3 from (1 to 30) but stop when number reaches 21

for i in range(1,31): if i == 21: break if i % 3 == 0: print(i)

print("out of loop")

Output 3 6 9 12 15 18 out of loop

Production : when break is uselful?

Imagine searching for something:

numbers = [4, 7, 2, 9, 15, 3]

for number in numbers: if number == 9: print("Found!") break

Once you've found what you're looking for, there's no reason to continue searching.

continue

It means Stop the current iteration right here and immediately move to the next iteration.
skiping some particular iteration

example 1

for i in range(1, 6):

if i == 3:
    continue

print(i)

Output 1 2 4 5

Trace:

Iteration 1 i = 1 i == 3? No print(1)

Iteration 2 i = 2 i == 3? No print(2)

Iteration 3 i = 3 i == 3? Yes continue // python dosent execute print(i) . It jumps back to the loop and starts the next iteration.

Iteration 4 i = 4 print(4)

Iteration 5 i = 5 print(5)

Remember

break ↓ EXIT LOOP COMPLETELY

continue ↓ SKIP THIS ITERATION ↓ NEXT ITERATION

Production : A realistic use of continue

Suppose you're processing numbers and only want to work with positive numbers:

numbers = [10, -5, 20, -3, 30]

for number in numbers:

    if number < 0:
        continue

    print(number)

Output 10 20 30

here continue means Negative numbers aren't relevant to this processing, so skip them. Filtering Logic

Example: printing multiples of 3 from (1 to 30) but skip the number 21

for i in range(1,31): if (i == 21): continue if (i % 3 == 0): print(i)

Output 3 6 9 12 15 18 24 27 30

Nested loop

A loop inside another loop

Example

for i in range(3): for j in range(3): print(i, j)

trace:

Outer loop starts: i = 0 Inner loop: j = 0 → print(0, 0) j = 1 → print(0, 1) j = 2 → print(0, 2)

Outer loop: i = 1 Inner loop starts again from begining j = 0 → print(1, 0) j = 1 → print(1, 1) j = 2 → print(1, 2)

Outer loop: i = 2 and again inner loop: j = 0 j = 1 j = 2

Output: 0 0 0 1 0 2 1 0 1 1 1 2 2 0 2 1 2 2

Mental model

The inner loop completes all its iterations for every single iteration of the outer loop.

Why nested loops matter for interviews?

Suppose:

for i in range(n): for j in range(n): print(i, j)

The outer loop runs n times.
For each outer iteration, the inner loop runs n times.
therefore, n × n = n²
time complexity -> O(n²)

You'll encounter them in: matrix problems 2D arrays brute-force solutions pair comparisons sorting algorithms graph algorithms pattern problems

nested loops + break

Consider:

for i in range(3):

for j in range(5):

    if j == 2:
        break

    print(i, j)

break breaks the inner loop only and not outer loop

for i = 0 inner loop: j = 0 → print j = 1 → print j = 2 → break

Output 0 0 0 1 1 0 1 1 2 0 2 1

14-multiple-exercises

Problem stat- Print all odd numbers from 1 to 20

for i in range(1,21):
  if (i % 2 != 0):
    print(i)

Output 1 3 5 7 9 11 13 15 17 19

ALternative way

for i in range(1,21,2): print(i)

Problem stat- Print the table of 57

for i in range(1,11):
  print(57 * i)

Output 57 114 171 228 285 342 399 456 513 570

refined way

for i in range(1, 11):
    print(57, "x", i, "=", 57 * i)

Result: 57 x 1 = 57 57 x 2 = 114 57 x 3 = 171 .. .. ....

same thing with while loop

i = 1

while i <= 10:
    print(57 * i)
    i = i + 1

Alt way of writing in while

i = 1

while i in range(1, 11):
    print(57 * i)
    i = i + 1

while expects condition in True or False unlike for loop but this thing can also work
but in real production code, you would usually use while with a condition that expresses the actual stopping rule rather than i in range(...).

Real usage of while

while password != correct_password: password = input("Enter password: ")

while not connected: connect_to_server()

while queue: item = queue.pop(0) process(item)

for → "Go through these things / repeat this known number of times." while → "Keep doing this until this condition changes."

Problem stat- Print all multiples of 3 from 1 to 50 but skip 15

for i in range(1,51):
  if (i == 15):
    continue 
  if (i % 3 == 0):
    print(i)

Output 3 6 9 12 18 21 24 27 30 33 36 39 42 45 48

Take two integers a and b as input. Find and print the first number between 1 and 1000 that is divisible by both numbers.

a = int(input("Enter first number: "))
b = int(input("Enter second number: "))


for i in range(1,1001):
  if (i % a == 0) and (i % b == 0):
    print("The first no to be divisible by both" , i)
    break

Output Enter first number: 4 Enter second number: 5 The first no to be divisible by both 20

Enter first number: 4 Enter second number: 6 The first no to be divisible by both 12

Remember

% -> "What is the remainder when the LEFT number is divided by the RIGHT number?"

X % Y == 0

20 is divisible by 5 20 % 5 == 0

36 is divisible by 9 36 % 9 == 0

i is divisible by a i % a == 0

15-Data-Structure

Lists- [] tuple= () set = {} dict = {}

Lists

A list stores multiple values in one variable.
It is written using square brackets []
A list can contain values of different data types.
Lists are Mutuable. You can change the contents of the list after creating it.

Let's say I want to type marks of different students and I need to type everytime seperately like: marks1 = 99 marks2 = 90 marks3 = 50

List solves it by grouping related values into one variable like: marks = [99, 90, 50]

marks = [99, 90, 50] ↑ ↑ ↑
0 1 2 // indexes

A list can contain different data types data = [10, "Python", 3.14, True]
Python allows this, although in production code you'll usually have logically related data in a list.

example 1

marks = [96, 98, 67, 'S']

print(marks) print(len(marks)) // calculating the length of the list

Output: [96, 98, 67, 'S'] 4

Accessing elements- indexes

Example 2

names = ["Sarbesh", "Rahul", "Amit"] print(name[0])

Output Sarbesh

Python, like C++, uses zero-based indexing.
Index: 0 1 2 ↓ ↓ ↓ Sarbesh Rahul Amit

names[0] // Sarbesh names[1] // Rahul names[2] // Amit

Example 3: Negative Indexing

names = ["Sarbesh", "Rahul", "Amit"] print(names[-1])

Output: Amit

Because -1 means last element.
Index: 0 1 2 -3 -2 -1 ↓ ↓ ↓ Sarbesh Rahul Amit

names[-1] # last // Amit names[-2] # second last // Rahul

Lists are mutuable

Lists are mutable, meaning their elements can be added, removed or changed.

example 4

marks = [98, 97, 95] marks[0] = 100

print(marks)

Output: [100, 97, 95]

example 5 marks = [85, 72, 91] marks[1] = 80

print(marks)

Output: [85, 80, 91]

The list itself was modified.

List → mutable Tuple → immutable

Adding elements — append()

append() adds an element at the end of the list

Example 6

names = ["Sarbesh", "Rahul"] names.append("Amit")

print(names)

Output: ["Sarbesh", "Rahul", "Amit"]

Adding at a particular position — insert()

insert() adds an element at a particular position.

Example 7: Suppose you want name Rahul between 2 names that is in 2nd postion

names = ["Sarbesh", "Amit"]

names.insert(1, "Rahul")

print(names)

Output: ["Sarbesh", "Rahul", "Amit"]

The first argument is the position, and the second is the value.

Syntax- list.insert(index, value)

Removing elements

remove()

remove() removes the value you specify.

Example 8 names = ["Sarbesh", "Rahul", "Amit"] names.remove("Rahul")

print(names)

Output ["Sarbesh", "Amit"]

pop()

Example 9 names = ["Sarbesh", "Rahul", "Amit"] names.pop() // pop() removes the last element unless specified

print(names)

Output: ["Sarbesh", "Rahul"]

Example 10 names = ["Sarbesh", "Rahul", "Amit"] names.pop(1) // pop(1) means remove the element at index 1

print(names)

Output ['Sarbesh', 'Amit']

pop() returns the removed element

removed = names.pop() print(removed)

clear()

Example 11

marks = [98, 97, 95, 93.5, "A"] marks.clear()

print(marks) print(len(marks))

Output [] 0

checking for an element

Example 12

marks = [98, 97, 95, 93.5, "A"] print(95 in marks) print(99 in marks)

Output True False

Remember-

num = range(5) print(num)

Output- range(0, 5)

❌ I will not get 0,1,2,3,4 . For that I need to convert them into list

Code:

num = range(5) print(list(num))

Output- [0, 1, 2, 3, 4]

looping directly over a list

Example 13: just see this , its not looping

numbers = [10, 20, 30, 40] print(numbers)

Output [10, 20, 30, 40]

Example 14: Looping directly over a list (pythonic)

numbers = [10, 20, 30, 40] for number in numbers: print(number)

Output 10 20 30 40

Example 15: by using range and len. I can use Eg 14 and I don't need this process

numbers = [10, 20, 30, 40] for i in range(len(numbers)): print(numbers[i])

Output 10 20 30 40

Both are valid. (Eg 14 & 15). The first is usually cleaner when the index isn't needed. First is more pythonic

Concept

Eg 14: First approach — iterate over the values

numbers = [10, 20, 30, 40]

for number in numbers:
    print(number)

Python directly takes each element/value from the list.
So number is actually holding the value.
You don't care where the value is located.
This is usually what you use in production

number → VALUE

For example, suppose you get users from a database/API:

users = ["Alice", "Bob", "Charlie"]

for user in users:
    send_email(user)

For every user, send an email. You don't care whether Alice is at index 0 or index 500.

Eg 15: Second approach — iterate over indexes

numbers = [10, 20, 30, 40]

for i in range(len(numbers)):
    print(numbers[i])

1st, len(numbers) gives 4
2nd, range(4) gives 0 1 2 3

So, the loop does: i = 0 → numbers[0] → 10 i = 1 → numbers[1] → 20 i = 2 → numbers[2] → 30 i = 3 → numbers[3] → 40

Here i is not the value. i is the index/location.

i → INDEX

Why we need index then?

Suppose you want to modify elements based on their position. numbers = [10, 20, 30, 40]

u want to double very element

numbers = [10, 20, 30, 40]
for i in range(len(numbers)):
    numbers[i] = numbers[i] * 2
    print(numbers[i])

Output 20 40 60 80

and there's another use case: Print the position of every number.

numbers = [10, 20, 30, 40]

for i in range(len(numbers)):
    print("Index:", i, "Value:", numbers[i])

Output Index: 0 Value: 10 Index: 1 Value: 20 Index: 2 Value: 30 Index: 3 Value: 40

Wrong version of Example 15: ❌

numbers = [10,20,30,40] for i in range(numbers): print(numbers[i])

Error-> TypeError: 'list' object cannot be interpreted as an integer

python can read what's there in numbers in list format
but range() needs integer values whereas in list integer, char, bool everything can get stored
python don't assume range([]) , it needs range(5) or range(2,6) or something integer bound
so len(numbers) solves this. if numbers = [10,20,30,30] then len(numbers) produces 4
len produces 4, so range(4)
range(4) means 0,1,2,3

Example 16: When we need index

numbers = [10, 20, 30]

for i in range(len(numbers)): print(i, numbers[i])

Output Output-> 0 10 1 20 2 30

python list vs C++ vector comparison

Python:

numbers = [10, 20, 30] numbers.append(40)

vector numbers = {10, 20, 30}; numbers.push_back(40);

Python	C++
list	vector
list[index]	vector[index]
append()	push_back()
len(list)	vector.size()
for x in list	for (auto x : vector)

So: list → collection of VALUES range → generates NUMBERS len → tells me HOW MANY values are in the list

slicing

Slicing extracts part of a list
it means Taking a portion of a list without changing the original list.

numbers = [10, 20, 30, 40, 50] Indexes:

Value: 10 20 30 40 50 Index: 0 1 2 3 4 -5 -4 -3 -2 -1

Basic syntax

list[start:stop]

start is included, stop is excluded.

Eg: numbers = [10, 20, 30, 40, 50] print(numbers[1:4])

means: start at index 1 ↓ 20 30 40 ↑ stop at 4 (not included)

Output: [20, 30, 40]

Leaving start or stop empty

Eg: from the beginning numbers = [10, 20, 30, 40, 50] print(numbers[:3]) // Start from the beginning and stop before index 3.

Output [10, 20, 30]

Eg: Until the end numbers = [10, 20, 30, 40, 50] print(numbers[2:])

Output [30, 40, 50]

So,

numbers[:3] # beginning → index 3 numbers[2:] # index 2 → end

Adding a step

list[start:stop:step]

Eg numbers = [10, 20, 30, 40, 50] numbers[0:5:2]

Start at 0, stop before 5, jump by 2:

Output [10, 30, 50]

Reverse a list

numbers = [10, 20, 30, 40, 50] numbers[::-1]

Output [50, 40, 30, 20, 10]

Remember

numbers[start:stop:step]
numbers[1:4] 1, 2, 3
numbers[:3] # beginning → 2 numbers[2:] # 2 → end
numbers[::2] # every 2nd element numbers[::-1] # reverse

Helpful in interview / prod

first_three = numbers[:3] last_three = numbers[-3:]

Tuple

A tuple stores multiple values and is written using parentheses ()
Tuples are immutable, so their elements cannot be changed
we use Tuple, when we want fixed values and not something changeable like GPS coordinates

Example 1

numbers = (10, 20, 30, 40) print(numbers)

Output (10, 20, 30, 40)

we can access the element just like the list.

numbers = (10, 20, 30, 40) print(numbers[0])

Output 10

Indexing and slicing works in tuple also numbers[-1] numbers[1:3]
I cannot modify

numbers = [10, 20, 30] // List can modify numbers[0] = 100 print(numbers) // [100, 20, 30]

numbers = (10, 20, 30) ❌❌❌ numbers[0] = 100

Because tuples are immutable.
Once the tuple is created, you cannot modify its elements.

Different data types supported just like List person = ("Sarbesh", 24, True)
I can loop through tuple

numbers = (10, 20, 30, 40) for number in numbers: print(number)

append() ❌ remove() ❌ pop() ❌ insert() ❌
count() ✔ index() ✔

Example 1

numbers = (10, 20, 20, 30) print(numbers.count(20))

Output 2

Example 2

numbers = (10, 20, 20, 30) print(numbers.index(30))

Output 3

Single element tuple needs a comma

x = (10, 20, 30) ✔ x = (10,) ✔ x = 10 ❌ // this is an integer

In Python code, you'll commonly encounter tuples when:

a function returns multiple values representing fixed groups of values working with dictionary keys working with database/query results unpacking values

person = ("Sarbesh", 24)

name, age = person

print(name)
print(age)

Output Sarbesh 24

Here the tuple contains two related values, and Python unpacks them into two variables.

Set

A set stores unique values and is written using curly brackets {}
Repeated values are automatically removed.
Sets are unordered, so their display order is not guaranteed.
They also do not support indexing.
looping is allowed

Example 1 numbers = {10, 20, 10, 30, 20, 40} print(numbers)

Output {10, 20, 30, 40} // removing the duplicates

3 characteristics of Set-

Unique elements
Unordered
Mutable
No duplicates + no indexing

Sets dont hv indexes

within a list: numbers = [10, 20, 30] print(numbers[0])

Output- 10

in set: numbers = {10, 20, 30} print(numbers[0])

Output- ❌error Because a set doesn't maintain elements in a meaningful positional order.

Real life-

checking permissions

permissions = {"read", "write", "delete"} if "write" in permissions: print("User can write")

You don't care whether "read" is conceptually first or "delete" is third.
You care about: Does this permission exist?

Membership checking

we can use- if value in my_set:

eg-

allowed_roles = {"admin", "manager", "developer"} if "developer" in allowed_roles: print("Access granted")

Adding elements .add()

Because sets are mutable, you can add elements.

Example 2

numbers = {10, 20, 30} numbers.add(40) print(numbers)

Output {10, 20, 30, 40}

but if u want to add numbers.add(20) nothing changes cuz no duplicates in sets

Removing elements .remove() , .discard()

example 3

numbers = {10, 20, 30} numbers.remove(20) print(numbers)

Output {10, 30}

we can also use discard instead of remove. remove checks if element exists or not before removing but discard dosen't checks

exmaple 4 numbers = {10, 20, 30} numbers.discard(50) // 50 dosent exists print(numbers)

Output {10, 20, 30}

looping over a set can be done but it is not ordered so be careful

Set Operations

Example 5: Union

A = {1, 2, 3, 4} B = {3, 4, 5, 6}

print(A | B) // Union (|) - Values present in either set // combine both sets and remove duplicates

Output {1, 2, 3, 4, 5, 6}

Example 6: Intersection

A = {1, 2, 3, 4} B = {3, 4, 5, 6}

print(A & B) // Intersection (&) - Values present in both // What do they have in common? // useful in data processing

Output {3, 4}

Example 7: Difference

A = {1, 2, 3, 4} B = {3, 4, 5, 6}

print(A - B) // Difference (-) - What does A have that B doesn't?

Output {1, 2}

Real world example of Set operations

Example 8

frontend = {"React", "JavaScript", "HTML", "CSS"}

backend = {"Python", "SQL", "JavaScript", "Docker"}

print(frontend & backend) -> {"Javascript"} // Technologies known by both

print(frontend | backend) -> {"React", "JavaScript", "HTML", "CSS", "Python", "SQL", "Docker"} // All technologies

print (frontend - backend) -> {"React", "HTML", "CSS"} // Frontend technologies not in backend

Converting a list into Set

Example 9

numbers = [10, 20, 10, 30, 20, 40] unique_set = set(numbers)

print(unique_set)

Output {40, 10, 20, 30} // as usual not ordered

Syntax Trap

An empty set is not {}
it is set()
{} -> Dictionary

Dictionary: x = {}

Set: x = set()

example code

numbers = {10, 20, 10, 30, 10}

print(numbers, len(numbers))

for value in numbers: print(value)

Output {10, 20, 30} 3 10 20 30

Dictionary

A dictionary is a set of key value & pairs
key & its pair is denoted by : like key : pair
key and its pair is sperated from another key and its pair by comma ,
key1 : pair1 , key2 : pair 2
we create dict by {}
syntax- {}
dictonaries are mutable just like lists and sets

Now imagine a situation

with a list we can access postion/index like for eg- numbers[0]
but we have to remember the the index right like 0 here which is not so readable

example

Name → Sarbesh Age → 24 Role → Developer

Using a list: person = ["Sarbesh", 24, "Developer"]

now u need to remember: 0 → name 1 → age 2 → role

A dictionary lets us associate a key with a value

Using dict:

person = { "name": "Sarbesh", "age": 24, "role": "Developer" }

print(person["name"]) // now we can directly say person("[name]") and get Sarbesh so print(variable["key"])

Output Sarbesh

print(person)

Output {'name': 'Sarbesh', 'age': 24, 'role': 'Developer'}

So List: index → value

Dictionary: key → value

example 2

marks = {"maths" : 99, "Physics" : 80, "Chemistry" : "Fail"} print(marks, "&&&" , type(marks), "&&&" , len(marks))

Output {'maths': 99, 'Physics': 80, 'Chemistry': 'Fail'} &&& <class 'dict'> &&& 3

we access value in dictionary using key

person = { "name": "Sarbesh", "age": 24, "role": "Developer" }

print(person["name"]) print(person["age"])

Output- Sarbesh 24

print(person[0]) -> ❌ // dictonaries expect a key

useful scenarios in API call

user = { "id": 101, "name": "Sarbesh", "email": "sarbesh@example.com", "active": True }

I can directly acess email by user["email"]

Dictonaries are mutable

example

person = { "name": "Sarbesh", "age": 24 }

person["age"] = 25 print(person)

Output {"name": "Sarbesh", "age": 25}

Adding a key value pair : we dont need add()

example

person = { "name": "Sarbesh", "age": 24 }

person["city"] = "Bengaluru"

print(person)

Output {'name': 'Sarbesh', 'age': 24, 'city': 'Bengaluru'}

if city dosen't exists create it , if it exists update its value

removing data : .pop() or del

example

person = { "name": "Sarbesh", "age": 24, "role": "Dev" }

person.pop("age") del person ["role"]

print(person)

Output {'name': 'Sarbesh'}

checking whether key exists or not

u can't search for pair, u hv to search key

eg

person = { "name": "Sarbesh", "age": 24, "email": "sarbeshmk@gmail.com" }

if "email" in person: print(person["email"])

if "name" in person: print(person["name"])

Output sarbeshmk@gmail.com Sarbesh

if "Sarbesh" in person -> ❌ // cuz "Sarbesh" is a key and not value if "name" in person -> ✔

person = { "name": "Sarbesh", "age": 24, "email": "sarbeshmk@gmail.com" }

print("name" in person) print("role" in person)

Output True False

.get() method

very frequently used with API/JSON data where some fields are missing

eg person = { "name": "Sarbesh", "age": 24 }

person["email"] -> KeyError // email dosen't exists

To mitigate this:

person.get("email") returns none

person.get("email", "Not provided") returns Not provided

example

person = { "name": "Sarbesh", "age": 24 }

print(person.get("email"))

Output None

print(person.get("email", "Not provided")) -> Not provided

example

person = { "name": "Sarbesh", "age": 24 }

print(person.get("email", "Not provided")) print(person.get("name", "Not provided"))

output Not provided Sarbesh

Looping through dictionary

Just Keys

Python's default dictionary iteration is over keys

example

person = { "name": "Sarbesh", "age": 24 }

for key in person: print(key)

Output name age

Keys and Value

we can use .items()

example

person = { "name": "Sarbesh", "age": 24 }

for key, value in person.items(): print(key, value) // print(key, ":", value) we can add colon to make it more natural

Ouput name Sarbesh age 24

person = { "name": "Sarbesh", "age": 24 }

for key in person: print(key, person[key])

Output name Sarbesh age 24

If you wan to print only values

eg

person = { "name": "Sarbesh", "age": 24 }

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

output Sarbesh 24

python dosent care about variable name here.
like for keys i cam literally do: person = { "name": "Sarbesh", "age": 24 } for value in person: print(value)

it will output- // here i want values but got keys so keys looping is default so here store the key in varibale named value name // if u need values then for x in person.values() age

even with keys and values

person = { "name": "Sarbesh", "age": "24 } for x,y in person.items(): print(x,y)

output- name Sarbesh age 24

Dictionary + Lists

example

users = [ {"name": "Alice", "age": 25}, {"name": "Bob", "age": 30}, {"name": "Charlie", "age": 28} ]

for user in users: print(user["name"])

output Alice Bob Charlie

model-

List ├── Dictionary ├── Dictionary └── Dictionary

interesting example 1

users = [ {"name": "Alice", "age": 25}, {"name": "Bob", "age": 30}, {"name": "Charlie", "age": 28} ]

for user in users: print(user)

output {'name': 'Alice', 'age': 25} {'name': 'Bob', 'age': 30} {'name': 'Charlie', 'age': 28}

interesting example 2

users = [ {"name": "Alice", "age": 25}, {"name": "Bob", "age": 30}, {"name": "Charlie", "age": 28} ]

for user in users: print(user) print(user["name"])

output {'name': 'Alice', 'age': 25} Alice {'name': 'Bob', 'age': 30} Bob {'name': 'Charlie', 'age': 28} Charlie

interesting example 3

users = [ {"name": "Alice", "age": 25}, {"name": "Bob", "age": 30}, {"name": "Charlie", "age": 28} ]

for user in users: print(users)

output [{'name': 'Alice', 'age': 25}, {'name': 'Bob', 'age': 30}, {'name': 'Charlie', 'age': 28}] [{'name': 'Alice', 'age': 25}, {'name': 'Bob', 'age': 30}, {'name': 'Charlie', 'age': 28}] [{'name': 'Alice', 'age': 25}, {'name': 'Bob', 'age': 30}, {'name': 'Charlie', 'age': 28}]

example 4

users = [ {"name": "Alice", "age": 25}, {"name": "Bob", "age": 30}, {"name": "Charlie", "age": 28} ]

print(users)

output [{'name': 'Alice', 'age': 25}, {'name': 'Bob', 'age': 30}, {'name': 'Charlie', 'age': 28}]

Dictionary + Dictionary

example

user = { "name": "Sarbesh", "address": { "city": "Delhi", "country": "India" } }

print(user["address"]["city"])

output Delhi

example

user = { "name": "Sarbesh", "address": { "city": "Delhi", "country": "India" } }

print(user["address"])

output {'city': 'Delhi', 'country': 'India'}

dictionary vs set

Set numbers = {10, 20, 30}
dict person = {"name": "Sarbesh", "age": 24}
Remember Set: {value, value, value}

Dictionary: {key: value, key: value}

empty dictionary

{}

empty set

set()

why dict matter in interviews

You want: 1 → 1 2 → 2 3 → 3

example

numbers = [1, 2, 2, 3, 3, 3] frequency = {}

for number in numbers: frequency[number] = frequency.get(number, 0) + 1

print(frequency)

output {1: 1, 2: 2, 3: 3}

🧠 Your final mental model

LIST → Ordered → Duplicates allowed → Mutable → Access by index

TUPLE → Ordered → Duplicates allowed → Immutable → Access by index

SET → Unique values → No meaningful indexing/order → Mutable → Fast membership checking

DICTIONARY → Key → Value → Keys are unique → Mutable → Access by key

Mutable data types are slower compared to immutable data types
Tuple is faster

16-Fifth-Exercise

Problem statement-

A. Given a list of roll numbers: [101, 105, 102, 101, 108, 105, 110]. Print all unique roll nums in the list.

B. Given Employee records in the form of a list of tuples where each tuple contains: (Employee ID, Employee Name, Salary) Example - [ (101, "Alice", 50000), (102, "Bob", 65000), (103, "Charlie", 45000) ] Ask user to enter Employee ID & search it inside records.

roll_number = [101, 105, 102, 101, 108, 105, 110]
unique_number = set(roll_number)
print("unique roll numbers" , unique_number)



records = [
  (101, "Alice", 50000),
  (102, "Bob", 65000),
  (103, "Charlie", 45000)
]


employee_id = int(input("Enter your employee id: "))


for record in records:
  if record[0] == employee_id:
      print(record)
      break

Input Enter your employee id: 102

Output unique roll numbers {101, 102, 105, 108, 110} (102, 'Bob', 65000)

Understand the code

There's a list and inside a list there are 3 tuples

records ↓ ┌─────────────────────────────┐ │ (101, "Alice", 50000) │ ← tuple 1 │ (102, "Bob", 65000) │ ← tuple 2 │ (103, "Charlie", 45000) │ ← tuple 3 └─────────────────────────────┘

Each tuple represents one employee.

And inside each tuple: (101, "Alice", 50000) ↑ ↑ ↑ ID Name Salary

Records is our entire list. The loop takes one element from the list at a time and puts it into the variable record.
- Record varibale always gets updated.
- First iteration -> (101, "Alice", 50000)
- Second iteration -> (102, "Bob", 65000) ...
- The variable record is not the entire list. It is one tuple at a time.
for record in record means

for number in numbers: number → one value from the list

for record in records: record → one tuple from the list

record = (101, "Alice", 50000) record = (102, "Bob", 65000) record = (103, "Charlie", 45000)

Then because record is a tuple, you can access its contents using: record[0] # ID record[1] # Name record[2] # Salary
Now lets talk about record[0]
- record is a tuple

During 1st iteration- record = (101, "Alice", 50000)

Tuples use indexes just like lists:

  index
    ↓

(101, "Alice", 50000) ↑ ↑ ↑ 0 1 2

record[0] -> Give me the value at index 0 of this tuple. -> 101 record[1] -> "Alice" record[2] -> 50000

if condition

if record[0] == employee_id:

Suppose the user entered: 102 So, employee_id = 102

First iteration

record = (101, "Alice", 50000)

Therefore, record[0] = 101

The condition becomes: 101 == 102 // that's false

That's false, So Python moves to the next iteration.

Second iteration

Now, record = (102, "Bob", 65000)

Therefore, record[0] = 102

The condition becomes: 102 == 102 // true

True. So, python enters if block

Mental model

Suppose the user enters: 102

The program effectively does:

employee_id = 102

record = (101, "Alice", 50000) ↓ record[0] = 101 ↓ 101 == 102 → False ↓ next iteration

record = (102, "Bob", 65000) ↓ record[0] = 102 ↓ 102 == 102 → True ↓ print(record) ↓ break ↓ STOP

Output: (102, "Bob", 65000)

Alternatives: if we want to show Invalid when user enters a wrong employee id

using found variable

records = [
    (101, "Alice", 50000),
    (102, "Bob", 65000),
    (103, "Charlie", 45000)
]

employee_id = int(input("Enter your employee id: "))

found = False

for record in records:
    if record[0] == employee_id:
        print(record)
        found = True
        break

if not found:
    print("Employee ID not found")

What is found?

found is simply a variable name found = False

I could write it as x x = False

True/False are booleaans here

Initially, found = False

Mental concept: if user enters 102

Now imagine the user enters 102 employee_id = 102

Initially, found = False

So our state is: employee_id = 102 found = False

First loop iteration

record = (101, "Alice", 50000) if record[0] == employee_id:

becomes, if 101 == 102:

False, So nothing inside the if runs. found is still: False

Second iteration

record = (102, "Bob", 65000)

The condition becomes: if 102 == 102:

True! ✅

So Python executes: print(record)

found = True // we found the employee break // stop the loop

What happens after the loop?

if not found: print("Employee ID not found")

Since: found = True

then: not found means not True which is False

Therefore the print("Employee ID not found") doesn't execute.

Now suppose the user enters 105

Initially: found = False

The loop checks: 101 == 105 → False 102 == 105 → False 103 == 105 → False

We never execute: found = True

So after the loop:

found = False

Then: if not found:

becomes: if not False:

which is: if True:

Employee ID not found gets printed

using else

records = [
  (101, "Alice", 50000),
  (102, "Bob", 65000),
  (103, "Charlie", 45000)
]


employee_id = int(input("Enter your employee id: "))


for record in records:
  if record[0] == employee_id:
      print(record)
      break
  
else:
  print("No employee ID found")

Note

write else seperately
do not write else just next line to break for eg is user enters 103 No employee ID found No employee ID found 103, "Charlie", 45000 // it will check every id and then execute the else statement but that's not we want

Notice where the else is:

for ├── if │ ├── print │ └── break │ └── else └── not found

Special Rule

A for loop's else executes only if the loop finishes normally without hitting break.

User enters 103:

101 → no match 102 → no match 103 → match ↓ print ↓ break ↓ loop's else is SKIPPED

User enters 105:

101 → no match 102 → no match 103 → no match ↓ loop finishes normally ↓ else executes ↓ "No employee ID found"

break is necessary

Did the loop hit break? ↓ YES → don't execute else NO → execute else

Even better: return from a function

In production code, if you're searching inside a function, you can often simply: This is often much cleaner because finding the employee is the function's job.

def find_employee(employee_id):
    for record in records:
        if record[0] == employee_id:
            return record

    return None

employee = find_employee(102)

if employee:
    print(employee)
else:
    print("Not found")

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Weclome to Learning Python with me

Table of Contents

1-basics

2-variables

variable code-

3-data-types

Checking the data type-

type check code-

4-input

Eg code-

6. Input code-

Tip-

Important-

Concatenation

7. concatenation code-

5-First-Exercise

6-Type-Casting-or-Type-Conversion

type casting code-

Solution for this

Temporary Conversion vs Reassignment

Temporary Conversion-

Permanent conversion / reassignment-

Easy rule

Another code eg-

Explicit vs Implicit Conversion

7-Second-Exercise

8-string-operations

let's understand from code-

find() method

Code-

replace() method

example code-

in operator

not in

Note-

Function vs Method

9-Third Exercise

10-Operator

Arithmetic Operator

Operator Precedence

Operator comparison

Remember-

Logical Operator

not operator always does the reverse

11-Conditional-statements

example code1-

example code 2-

few more examples combing if/esle with operators

12-mini-project-calculator

13-loops

Range

Structure for Range

while loop

Explaination-

for loop

Default structure of range

Concept of for loop

break

continue

Nested loop

Mental model

Why nested loops matter for interviews?

nested loops + break

14-multiple-exercises

ALternative way

refined way

same thing with while loop

Alt way of writing in while

Real usage of while

Remember

15-Data-Structure

Lists

Accessing elements- indexes

Lists are mutuable