🚀 Day 26/150 – Print Numbers from 1 to N in Python

 

🚀 Day 26/150 – Print Numbers from 1 to N in Python

Printing numbers from 1 to N is one of the most basic and important programming exercises. It helps you understand loops, iteration, and how Python executes repeated tasks.

Let’s explore different ways to achieve this 👇

🔹 Method 1 – Using for Loop

The most common and beginner-friendly approach.

n = 10

for i in range(1, n + 1):
    print(i)

✅ Explanation:

• range(1, n + 1) generates numbers from 1 to N
• The loop prints each number one by one

🔹 Method 2 – Taking User Input

Make the program dynamic by taking input from the user.

n = int(input("Enter a number: ")) for i in range(1, n + 1): print(i)

 


✅ Explanation

input() takes value from the user

int() converts it into an integer

Loop prints numbers accordingly

🔹 Method 3 – Using while Loop

A condition-based approach.

n = 10
i = 1

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

✅ Explanation:

• Starts from i = 1
• Runs until i <= n
• Increments i after each iteration

🔹 Method 4 – Using List Comprehension

A more compact and Pythonic way.

n = 10

numbers = [i for i in range(1, n + 1)]
print(numbers)

✅ Explanation:

• Creates a list of numbers from 1 to N
• Prints all values at once

🎯 Final Thoughts

• Use for loop for simple iteration ✅
• Use while loop when working with conditions 🔄
• Use list comprehension for compact code 🧠

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🚀 Day 25/150 – Check Alphabet, Digit, or Special Character in Python

 

🚀 Day 25/150 – Check Alphabet, Digit, or Special Character in Python

This is a very practical problem that helps you understand character classification in Python. It’s commonly used in input validation, password checking, and text processing.

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📌 Goal

Given a character, determine whether it is:

• 🔤 Alphabet (A–Z, a–z)
• 🔢 Digit (0–9)
• ⚡ Special Character (anything else like @, #, $, etc.)

🔹 Method 1 – Using if-elif-else

char = 'A'

if char.isalpha():
    print("Alphabet")
elif char.isdigit():
    print("Digit")
else:
    print("Special Character")

🧠 Explanation:

• isalpha() → checks if character is a letter
• isdigit() → checks if it’s a number
• Anything else → special character

👉 Best for: Clean and beginner-friendly logic

🔹 Method 2 – Taking User Input

char = input("Enter a character: ") if char.isalpha(): print("Alphabet") elif char.isdigit(): print("Digit") else: print("Special Character")

🧠 Explanation:

• Makes program interactive
• Works for real-time inputs

👉 Best for: Practical use

🔹 Method 3 – Using Function

def check_char(c):
    if c.isalpha():
        return "Alphabet"
    elif c.isdigit():
        return "Digit"
    else:
        return "Special Character"

print(check_char('@'))

🧠 Explanation:

• Function makes code reusable
• Returns result instead of printing

👉 Best for: Modular code

🔹 Method 4 – Using Lambda Function

check = lambda c: "Alphabet" if c.isalpha() else "Digit" if c.isdigit() else "Special Character"

print(check('5'))

🧠 Explanation:

• One-line compact logic
• Uses nested conditional expressions

👉 Best for: Short expressions

⚡ Key Takeaways

• isalpha() → Alphabet
• isdigit() → Digit
• Else → Special Character
• Always validate input length

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💡 Pro Tip

Try extending this:

• Count alphabets, digits, and symbols in a string
• Build a password strength checker
• Analyze text data

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April Python Bootcamp Day 13

 

What is a Module?

A module is a single Python file (.py) that contains functions, variables, or classes which can be reused in other programs.

Example:
If you create a file named utils.py, it becomes a module.

Why modules are important:

• Promote code reusability
• Help in organizing large codebases
• Reduce redundancy

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What is a Package?

A package is a folder that contains multiple modules.

Structure example:

my_package/
    ├── module1.py
    ├── module2.py
    └── __init__.py

Packages allow you to structure your project logically and scale your code efficiently.

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Importing Modules

There are multiple ways to import modules:

1. Import Entire Module

import math
print(math.sqrt(16))

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2. Import Specific Functions

from math import sqrt, ceil

print(sqrt(16))
print(ceil(4.2))

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3. Using Module Alias

import math as m
print(m.factorial(5))

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Built-in Modules in Python

Python provides many built-in modules that simplify development.

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Math Module

Used for mathematical operations.

import math

print(math.sqrt(16))
print(math.ceil(4.2))
print(math.floor(4.9))
print(math.pow(2, 3))
print(math.factorial(5))

Common functions:

• sqrt()
• ceil()
• floor()
• pow()
• factorial()

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Random Module

Used for generating random values.

import random

print(random.random())
print(random.randint(1, 10))
print(random.choice([1, 2, 3, 4]))

Shuffling example:

lst = [1, 2, 3, 4]
random.shuffle(lst)
print(lst)

Other function:

• uniform(a, b) → random float between a and b

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Datetime Module

Used for working with dates and time.

from datetime import datetime, date, timedelta

print(datetime.now())
print(date.today())

d = datetime.now()
print(d.strftime("%Y-%m-%d"))

new_date = d + timedelta(days=5)
print(new_date)

Key functionalities:

• Current date and time
• Formatting dates
• Date arithmetic

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OS Module

Used for interacting with the operating system.

import os

print(os.getcwd())
print(os.listdir())

Common operations:

• Get current directory
• List files
• Create/delete folders
• Rename files

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Key Takeaways

• Modules help reuse code
• Packages help organize large projects
• Built-in modules save development time
• Proper imports improve code readability

---

Assignment Questions

Basic Level

1. Import the math module and find square root of a number
2. Import specific functions from math and use ceil() and floor()
3. Generate a random number between 1 and 50
4. Print current date using datetime
5. Print current working directory using os

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Intermediate Level

1. Generate a list of 5 random numbers using random.randint()
2. Shuffle a list of numbers using random.shuffle()
3. Format current date as DD-MM-YYYY
4. Create a program to add 7 days to current date
5. List all files in your current directory

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Advanced Level

1. Create your own module with functions (e.g., add, subtract) and import it
2. Create a package with at least 2 modules and use them
3. Build a mini project using math and random (e.g., number guessing game)
4. Write a script to organize files in a folder using os
5. Combine datetime and os to log file creation time

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Summary

Modules and packages are fundamental for writing scalable Python applications.

• Modules allow code reuse
• Packages provide structure
• Built-in modules handle complex operations easily

Understanding this concept is essential before moving into:

• Large projects
• Frameworks
• Real-world software development

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April Python Bootcamp Day 12

 

Lambda Functions

A lambda function is a small, anonymous function written in a single line. It does not require a function name or the def keyword.

Syntax

lambda arguments: expression

Key characteristics:

• No function name
• No def keyword
• Only one expression allowed
• Used for short and simple operations

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Normal Function vs Lambda Function

Normal Function

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

print(add(4, 5))

Lambda Function

add1 = lambda a, b: a + b
print(add1(2, 3))

Another example:

square = lambda x: x ** 2
print(square(5))

Lambda functions are useful when you need a quick function for a short period of time.

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Higher Order Functions

A higher order function is a function that:

• Takes another function as input, or
• Returns a function as output

Common examples include:

• map()
• filter()
• sorted()

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map() Function

Applies a function to every element of an iterable.

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

result = list(map(lambda x: x * 2, nums))
print(result)

Output:

[2, 4, 6, 8, 10]

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filter() Function

Filters elements based on a condition.

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

even = list(filter(lambda x: x % 2 == 0, nums))
print(even)

Output:

[2, 4]

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sorted() with Lambda

Used for custom sorting logic.

students = [("Piyush", 20), ("Rahul", 18), ("Amar", 24)]

sorted_list = sorted(students, key=lambda x: len(x[0]))
print(sorted_list)

This sorts based on the length of names.

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Key Points About Lambda Functions

• Best for short and simple logic
• Can take multiple arguments
• Limited to a single expression
• Not suitable for complex logic

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Recursion

Recursion is a technique where a function calls itself to solve a problem.

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Rules of Recursion

Every recursive function must have:

1. Base Case
   Condition where recursion stops
2. Recursive Case
   Function calling itself

Without a base case, recursion will lead to infinite calls and crash the program.

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Example: Print Numbers

def print_nums(n):
    if n > 5:  # Base case
        return
    print(n, end=" ")
    print_nums(n + 1)

print_nums(1)

Output:

1 2 3 4 5

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Example: Factorial Using Recursion

def factorial(n):
    if n == 1:
        return 1
    return n * factorial(n - 1)

print(factorial(5))

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When to Use Recursion

• When a problem can be broken into smaller subproblems
• Tree structures
• Backtracking problems
• Divide and conquer algorithms

---

When Not to Use Recursion

• When it increases complexity unnecessarily
• Risk of stack overflow
• When a loop provides a simpler solution

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Assignment Questions

Basic Level

1. Create a lambda function to add two numbers
2. Write a lambda function to find square of a number
3. Use map() with lambda to multiply all elements of a list by 3
4. Use filter() to get all odd numbers from a list
5. Sort a list of integers using lambda

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Intermediate Level

1. Use map() to convert a list of strings to uppercase
2. Use filter() to remove negative numbers from a list
3. Sort a list of tuples based on the second value
4. Write a recursive function to print numbers from 1 to n
5. Modify recursion example to print numbers in reverse

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Advanced Level

1. Write a recursive function to calculate factorial
2. Write a recursive function to calculate Fibonacci series
3. Create a function using both lambda and map() to square a list
4. Implement a recursive function to find sum of digits of a number
5. Compare recursion vs loop for factorial and analyze performance

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Summary

• Lambda functions provide a concise way to write small functions
• Higher order functions like map(), filter(), and sorted() enhance functional programming
• Recursion is powerful but must be used carefully
• Choosing between recursion and iteration depends on problem complexity

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