Control Flow (if, elif, else) in Python
What is Control Flow?
Control flow allows your code to make decisions. You use if, elif, and else statements to run different blocks of code depending on conditions.
Basic Structure:
if condition:
# code runs if condition is True
elif another_condition:
# code runs if the second condition is True
else:
# code runs if none of the above are True
Example:
age = 20
if age < 18:
print("You are a minor.")
elif age == 18:
print("You just became an adult!")
else:
print("You are an adult.")
Comparison Operators:
== (equal to)
!= (not equal to)
< (less than)
> (greater than)
<= (less than or equal to)
>= (greater than or equal to)
Logical Operators:
and – Both conditions must be True
or – At least one condition must be True
not – Reverses the result (True becomes False)
Example with logical operators:
age = 25
is_student = False
if age > 18 and not is_student:
print("Eligible for the job.")
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What is Control Flow?
Control flow allows your code to make decisions. You use if, elif, and else statements to run different blocks of code depending on conditions.
Basic Structure:
if condition:
# code runs if condition is True
elif another_condition:
# code runs if the second condition is True
else:
# code runs if none of the above are True
Example:
age = 20
if age < 18:
print("You are a minor.")
elif age == 18:
print("You just became an adult!")
else:
print("You are an adult.")
Comparison Operators:
== (equal to)
!= (not equal to)
< (less than)
> (greater than)
<= (less than or equal to)
>= (greater than or equal to)
Logical Operators:
and – Both conditions must be True
or – At least one condition must be True
not – Reverses the result (True becomes False)
Example with logical operators:
age = 25
is_student = False
if age > 18 and not is_student:
print("Eligible for the job.")
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Python Projects & Resources
Control Flow (if, elif, else) in Python What is Control Flow? Control flow allows your code to make decisions. You use if, elif, and else statements to run different blocks of code depending on conditions. Basic Structure: if condition: # code runs…
Loops in Python (for & while)
What are Loops?
Loops let you repeat a block of code multiple times. They’re essential for tasks like iterating over data, automating repetitive steps, or checking conditions.
1. For Loop
Used to iterate over a sequence like a list, string, or range.
Example:
fruits = ["apple", "banana", "cherry"]
for fruit in fruits:
print(fruit)
You can also use range() to loop a specific number of times:
for i in range(5):
print(i)
2. While Loop
Repeats as long as a condition is True.
Example:
count = 0
while count < 3:
print("Count is:", count)
count += 1
Loop Control Statements:
break – exits the loop completely
continue – skips the current iteration and continues with the next
pass – does nothing (used as a placeholder)
Example:
for i in range(5):
if i == 3:
break
print(i)
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What are Loops?
Loops let you repeat a block of code multiple times. They’re essential for tasks like iterating over data, automating repetitive steps, or checking conditions.
1. For Loop
Used to iterate over a sequence like a list, string, or range.
Example:
fruits = ["apple", "banana", "cherry"]
for fruit in fruits:
print(fruit)
You can also use range() to loop a specific number of times:
for i in range(5):
print(i)
2. While Loop
Repeats as long as a condition is True.
Example:
count = 0
while count < 3:
print("Count is:", count)
count += 1
Loop Control Statements:
break – exits the loop completely
continue – skips the current iteration and continues with the next
pass – does nothing (used as a placeholder)
Example:
for i in range(5):
if i == 3:
break
print(i)
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Python Projects & Resources
Loops in Python (for & while) What are Loops? Loops let you repeat a block of code multiple times. They’re essential for tasks like iterating over data, automating repetitive steps, or checking conditions. 1. For Loop Used to iterate over a sequence like…
Functions in Python
Functions are reusable blocks of code that perform a specific task. They help keep your code organized, modular, and easier to debug.
Defining a Function:
You use the def keyword to define a function.
Syntax:
def function_name(parameters):
# code block
return result
Example:
def greet(name):
return f"Hello, {name}!"
message = greet("Alice")
print(message)
Key Concepts:
Parameters: Inputs you pass into the function (e.g., name)
Arguments: Actual values passed when calling the function (e.g., "Alice")
Return Statement: Sends back a result to wherever the function was called
Default Arguments:
You can set default values for parameters.
def greet(name="Guest"):
return f"Hello, {name}!"
Keyword Arguments:
Call functions using parameter names for clarity.
def add(a, b):
return a + b
result = add(b=3, a=2)
Why to use Functions:
- Reduce repetition
- Make code easier to understand and maintain
- Allow modular programming
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Functions are reusable blocks of code that perform a specific task. They help keep your code organized, modular, and easier to debug.
Defining a Function:
You use the def keyword to define a function.
Syntax:
def function_name(parameters):
# code block
return result
Example:
def greet(name):
return f"Hello, {name}!"
message = greet("Alice")
print(message)
Key Concepts:
Parameters: Inputs you pass into the function (e.g., name)
Arguments: Actual values passed when calling the function (e.g., "Alice")
Return Statement: Sends back a result to wherever the function was called
Default Arguments:
You can set default values for parameters.
def greet(name="Guest"):
return f"Hello, {name}!"
Keyword Arguments:
Call functions using parameter names for clarity.
def add(a, b):
return a + b
result = add(b=3, a=2)
Why to use Functions:
- Reduce repetition
- Make code easier to understand and maintain
- Allow modular programming
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Python Projects & Resources
Functions in Python Functions are reusable blocks of code that perform a specific task. They help keep your code organized, modular, and easier to debug. Defining a Function: You use the def keyword to define a function. Syntax: def function_name(parameters):…
List Comprehensions in Python
It’s a concise way to create new lists by applying an expression to each item in an iterable (like a list or range), optionally filtering with conditions.
Basic Syntax:
new_list = [expression for item in iterable]
Example:
squares = [x**2 for x in range(5)]
print(squares) # Output: [0, 1, 4, 9, 16]
With Condition:
even_numbers = [x for x in range(10) if x % 2 == 0]
print(even_numbers) # Output: [0, 2, 4, 6, 8]
Equivalent Without List Comprehension:
squares = []
for x in range(5):
squares.append(x**2)
Why to use list comprehensions?
- It’s more readable and compact
- Runs faster than traditional for loops (in most cases)
- Helps clean up your code
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It’s a concise way to create new lists by applying an expression to each item in an iterable (like a list or range), optionally filtering with conditions.
Basic Syntax:
new_list = [expression for item in iterable]
Example:
squares = [x**2 for x in range(5)]
print(squares) # Output: [0, 1, 4, 9, 16]
With Condition:
even_numbers = [x for x in range(10) if x % 2 == 0]
print(even_numbers) # Output: [0, 2, 4, 6, 8]
Equivalent Without List Comprehension:
squares = []
for x in range(5):
squares.append(x**2)
Why to use list comprehensions?
- It’s more readable and compact
- Runs faster than traditional for loops (in most cases)
- Helps clean up your code
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Dictionary in Python
A dictionary is a collection of key-value pairs. Each key is unique and maps to a value. Dictionaries are unordered (until Python 3.7) and mutable, meaning you can change them.
Creating a Dictionary:
person = {
"name": "Alice",
"age": 25,
"city": "New York"
}
Accessing Values:
print(person["name"]) # Output: Alice
print(person.get("age")) # Output: 25
Using .get() is safer because it won’t crash if the key doesn’t exist.
Adding or Updating Items:
person["email"] = "alice@example.com" # Add new key
person["age"] = 26 # Update value
Deleting Items:
del person["city"]
Looping through a Dictionary:
for key, value in person.items():
print(key, ":", value)
Why Use Dictionaries?
Fast access via keys
Ideal for storing structured data (like a JSON object)
Very flexible in combining with loops and functions
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A dictionary is a collection of key-value pairs. Each key is unique and maps to a value. Dictionaries are unordered (until Python 3.7) and mutable, meaning you can change them.
Creating a Dictionary:
person = {
"name": "Alice",
"age": 25,
"city": "New York"
}
Accessing Values:
print(person["name"]) # Output: Alice
print(person.get("age")) # Output: 25
Using .get() is safer because it won’t crash if the key doesn’t exist.
Adding or Updating Items:
person["email"] = "alice@example.com" # Add new key
person["age"] = 26 # Update value
Deleting Items:
del person["city"]
Looping through a Dictionary:
for key, value in person.items():
print(key, ":", value)
Why Use Dictionaries?
Fast access via keys
Ideal for storing structured data (like a JSON object)
Very flexible in combining with loops and functions
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Powerful One-Liners in Python You Should Know!
1. Swap Two Numbers
n1, n2 = n2, n1
2. Reverse a String
reversed_string = input_string[::-1]
3. Factorial of a Number
fact = lambda n: [1, 0][n > 1] or fact(n - 1) * n
4. Find Prime Numbers (2 to 10)
primes = list(filter(lambda x: all(x % y != 0 for y in range(2, x)), range(2, 10)))
5. Check if a String is Palindrome
palindrome = input_string == input_string[::-1]
Free Python Resources: https://news.1rj.ru/str/pythonproz
1. Swap Two Numbers
n1, n2 = n2, n1
2. Reverse a String
reversed_string = input_string[::-1]
3. Factorial of a Number
fact = lambda n: [1, 0][n > 1] or fact(n - 1) * n
4. Find Prime Numbers (2 to 10)
primes = list(filter(lambda x: all(x % y != 0 for y in range(2, x)), range(2, 10)))
5. Check if a String is Palindrome
palindrome = input_string == input_string[::-1]
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6-Week Python Learning Roadmap – Beginner Friendly
Guys, if you’ve been wanting to start learning Python but didn’t know where to begin, here’s a simple, structured 6-week plan to go from ZERO to writing your own Python projects!
No fluff. Just pure learning with practice!
Week 1: Python Basics – Lay the Foundation
Install Python & set up your IDE (VS Code or Jupyter Notebook)
Learn:
Variables & Data Types
Input / Output
Operators
Conditional Statements (if-elif-else)
Loops (for, while)
Mini Project: Build a simple number guessing game
Week 2: Data Structures – Your Python Toolbox
Master:
Lists & Tuples
Dictionaries & Sets
String Manipulation
Understand slicing, indexing & common methods
Practice:
Reverse a string
Sort a list
Remove duplicates from a list
Week 3: Functions & Modules – Code Like a Pro
Write your own functions
Understand:
Parameters & Return values
Lambda functions
Python Modules (math, random, etc.)
Challenge:
Create a BMI Calculator
Build a simple password generator
Week 4: Object-Oriented Programming (OOP) – Think in Objects
Learn:
Classes and Objects
Constructors (init)
Inheritance
Method Overriding
Practice:
Build a class for Bank Account or Student Record System
Week 5: Real-World Essentials
File Handling: Read/write files
Error Handling: try-except blocks
Explore Libraries:
NumPy for numerical operations
Pandas for data analysis
Matplotlib for data visualization
Mini Project: Analyze and visualize a CSV dataset
Week 6: Final Project Week
Choose a project idea:
To-do list CLI app
Weather app using API
Mini game with logic (Tic Tac Toe)
Spend time on:
Planning
Building
Debugging
Polishing your code
Practice consistently no matter how small: 1 hour > 0 hour
Keep solving mini problems and build your confidence step-by-step
Stay consistent and share your progress with others
For all resources and cheat sheets, check out my Telegram channel: https://news.1rj.ru/str/pythonproz
Like if it helps :)
Guys, if you’ve been wanting to start learning Python but didn’t know where to begin, here’s a simple, structured 6-week plan to go from ZERO to writing your own Python projects!
No fluff. Just pure learning with practice!
Week 1: Python Basics – Lay the Foundation
Install Python & set up your IDE (VS Code or Jupyter Notebook)
Learn:
Variables & Data Types
Input / Output
Operators
Conditional Statements (if-elif-else)
Loops (for, while)
Mini Project: Build a simple number guessing game
Week 2: Data Structures – Your Python Toolbox
Master:
Lists & Tuples
Dictionaries & Sets
String Manipulation
Understand slicing, indexing & common methods
Practice:
Reverse a string
Sort a list
Remove duplicates from a list
Week 3: Functions & Modules – Code Like a Pro
Write your own functions
Understand:
Parameters & Return values
Lambda functions
Python Modules (math, random, etc.)
Challenge:
Create a BMI Calculator
Build a simple password generator
Week 4: Object-Oriented Programming (OOP) – Think in Objects
Learn:
Classes and Objects
Constructors (init)
Inheritance
Method Overriding
Practice:
Build a class for Bank Account or Student Record System
Week 5: Real-World Essentials
File Handling: Read/write files
Error Handling: try-except blocks
Explore Libraries:
NumPy for numerical operations
Pandas for data analysis
Matplotlib for data visualization
Mini Project: Analyze and visualize a CSV dataset
Week 6: Final Project Week
Choose a project idea:
To-do list CLI app
Weather app using API
Mini game with logic (Tic Tac Toe)
Spend time on:
Planning
Building
Debugging
Polishing your code
Practice consistently no matter how small: 1 hour > 0 hour
Keep solving mini problems and build your confidence step-by-step
Stay consistent and share your progress with others
For all resources and cheat sheets, check out my Telegram channel: https://news.1rj.ru/str/pythonproz
Like if it helps :)
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Important Python concepts that every beginner should know
1. Variables & Data Types 🧠
Variables are like boxes where you store stuff.
Python automatically knows the type of data you're working with!
name = "Alice" # String
age = 25 # Integer
height = 5.6 # Float
is_student = True # Boolean
2. Conditional Statements 🔀
Want your program to make decisions?
Use if, elif, and else!
if age > 18:
print("You're an adult!")
else:
print("You're a kid!")
3. Loops 🔁
Repeat tasks without writing them 100 times!
For loop – Loop over a sequence
While loop – Loop until a condition is false
for i in range(5):
print(i) # 0 to 4
count = 0
while count < 3:
print("Hello")
count += 1
4. Functions ⚙️
Reusable blocks of code. Keeps your program clean and DRY (Don't Repeat Yourself)!
def greet(name):
print(f"Hello, {name}!")
greet("Bob")
5. Lists, Tuples, Dictionaries, Sets 📦
List: Ordered, changeable
Tuple: Ordered, unchangeable
Dict: Key-value pairs
Set: Unordered, unique items
my_list = [1, 2, 3]
my_tuple = (4, 5, 6)
my_dict = {"name": "Alice", "age": 25}
my_set = {1, 2, 3}
6. String Manipulation ✂️
Work with text like a pro!
text = "Python is awesome"
print(text.upper()) # PYTHON IS AWESOME
print(text.replace("awesome", "cool")) # Python is cool
7. Input from User ⌨️
Make your programs interactive!
name = input("Enter your name: ")
print("Hello " + name)
8. Error Handling ⚠️
Catch mistakes before they crash your program.
try:
x = 1 / 0
except ZeroDivisionError:
print("You can't divide by zero!")
9. File Handling 📁
Read or write files using Python.
with open("notes.txt", "r") as file:
content = file.read()
print(content)
10. Object-Oriented Programming (OOP) 🧱
Python lets you model real-world things using classes and objects.
class Dog:
def init(self, name):
self.name = name
def bark(self):
print(f"{self.name} says woof!")
my_dog = Dog("Buddy")
my_dog.bark()
React with ❤️ if you want me to cover each Python concept in detail.
For all resources and cheat sheets, check out my Telegram channel: https://news.1rj.ru/str/pythonproz
Python Projects: https://whatsapp.com/channel/0029Vau5fZECsU9HJFLacm2a
Latest Jobs & Internship Opportunities: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
Hope it helps :)
1. Variables & Data Types 🧠
Variables are like boxes where you store stuff.
Python automatically knows the type of data you're working with!
name = "Alice" # String
age = 25 # Integer
height = 5.6 # Float
is_student = True # Boolean
2. Conditional Statements 🔀
Want your program to make decisions?
Use if, elif, and else!
if age > 18:
print("You're an adult!")
else:
print("You're a kid!")
3. Loops 🔁
Repeat tasks without writing them 100 times!
For loop – Loop over a sequence
While loop – Loop until a condition is false
for i in range(5):
print(i) # 0 to 4
count = 0
while count < 3:
print("Hello")
count += 1
4. Functions ⚙️
Reusable blocks of code. Keeps your program clean and DRY (Don't Repeat Yourself)!
def greet(name):
print(f"Hello, {name}!")
greet("Bob")
5. Lists, Tuples, Dictionaries, Sets 📦
List: Ordered, changeable
Tuple: Ordered, unchangeable
Dict: Key-value pairs
Set: Unordered, unique items
my_list = [1, 2, 3]
my_tuple = (4, 5, 6)
my_dict = {"name": "Alice", "age": 25}
my_set = {1, 2, 3}
6. String Manipulation ✂️
Work with text like a pro!
text = "Python is awesome"
print(text.upper()) # PYTHON IS AWESOME
print(text.replace("awesome", "cool")) # Python is cool
7. Input from User ⌨️
Make your programs interactive!
name = input("Enter your name: ")
print("Hello " + name)
8. Error Handling ⚠️
Catch mistakes before they crash your program.
try:
x = 1 / 0
except ZeroDivisionError:
print("You can't divide by zero!")
9. File Handling 📁
Read or write files using Python.
with open("notes.txt", "r") as file:
content = file.read()
print(content)
10. Object-Oriented Programming (OOP) 🧱
Python lets you model real-world things using classes and objects.
class Dog:
def init(self, name):
self.name = name
def bark(self):
print(f"{self.name} says woof!")
my_dog = Dog("Buddy")
my_dog.bark()
React with ❤️ if you want me to cover each Python concept in detail.
For all resources and cheat sheets, check out my Telegram channel: https://news.1rj.ru/str/pythonproz
Python Projects: https://whatsapp.com/channel/0029Vau5fZECsU9HJFLacm2a
Latest Jobs & Internship Opportunities: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
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Some useful PYTHON libraries for data science
NumPy stands for Numerical Python. The most powerful feature of NumPy is n-dimensional array. This library also contains basic linear algebra functions, Fourier transforms, advanced random number capabilities and tools for integration with other low level languages like Fortran, C and C++
SciPy stands for Scientific Python. SciPy is built on NumPy. It is one of the most useful library for variety of high level science and engineering modules like discrete Fourier transform, Linear Algebra, Optimization and Sparse matrices.
Matplotlib for plotting vast variety of graphs, starting from histograms to line plots to heat plots.. You can use Pylab feature in ipython notebook (ipython notebook –pylab = inline) to use these plotting features inline. If you ignore the inline option, then pylab converts ipython environment to an environment, very similar to Matlab. You can also use Latex commands to add math to your plot.
Pandas for structured data operations and manipulations. It is extensively used for data munging and preparation. Pandas were added relatively recently to Python and have been instrumental in boosting Python’s usage in data scientist community.
Scikit Learn for machine learning. Built on NumPy, SciPy and matplotlib, this library contains a lot of efficient tools for machine learning and statistical modeling including classification, regression, clustering and dimensionality reduction.
Statsmodels for statistical modeling. Statsmodels is a Python module that allows users to explore data, estimate statistical models, and perform statistical tests. An extensive list of denoscriptive statistics, statistical tests, plotting functions, and result statistics are available for different types of data and each estimator.
Seaborn for statistical data visualization. Seaborn is a library for making attractive and informative statistical graphics in Python. It is based on matplotlib. Seaborn aims to make visualization a central part of exploring and understanding data.
Bokeh for creating interactive plots, dashboards and data applications on modern web-browsers. It empowers the user to generate elegant and concise graphics in the style of D3.js. Moreover, it has the capability of high-performance interactivity over very large or streaming datasets.
Blaze for extending the capability of Numpy and Pandas to distributed and streaming datasets. It can be used to access data from a multitude of sources including Bcolz, MongoDB, SQLAlchemy, Apache Spark, PyTables, etc. Together with Bokeh, Blaze can act as a very powerful tool for creating effective visualizations and dashboards on huge chunks of data.
Scrapy for web crawling. It is a very useful framework for getting specific patterns of data. It has the capability to start at a website home url and then dig through web-pages within the website to gather information.
SymPy for symbolic computation. It has wide-ranging capabilities from basic symbolic arithmetic to calculus, algebra, discrete mathematics and quantum physics. Another useful feature is the capability of formatting the result of the computations as LaTeX code.
Requests for accessing the web. It works similar to the the standard python library urllib2 but is much easier to code. You will find subtle differences with urllib2 but for beginners, Requests might be more convenient.
Additional libraries, you might need:
os for Operating system and file operations
networkx and igraph for graph based data manipulations
regular expressions for finding patterns in text data
BeautifulSoup for scrapping web. It is inferior to Scrapy as it will extract information from just a single webpage in a run.
NumPy stands for Numerical Python. The most powerful feature of NumPy is n-dimensional array. This library also contains basic linear algebra functions, Fourier transforms, advanced random number capabilities and tools for integration with other low level languages like Fortran, C and C++
SciPy stands for Scientific Python. SciPy is built on NumPy. It is one of the most useful library for variety of high level science and engineering modules like discrete Fourier transform, Linear Algebra, Optimization and Sparse matrices.
Matplotlib for plotting vast variety of graphs, starting from histograms to line plots to heat plots.. You can use Pylab feature in ipython notebook (ipython notebook –pylab = inline) to use these plotting features inline. If you ignore the inline option, then pylab converts ipython environment to an environment, very similar to Matlab. You can also use Latex commands to add math to your plot.
Pandas for structured data operations and manipulations. It is extensively used for data munging and preparation. Pandas were added relatively recently to Python and have been instrumental in boosting Python’s usage in data scientist community.
Scikit Learn for machine learning. Built on NumPy, SciPy and matplotlib, this library contains a lot of efficient tools for machine learning and statistical modeling including classification, regression, clustering and dimensionality reduction.
Statsmodels for statistical modeling. Statsmodels is a Python module that allows users to explore data, estimate statistical models, and perform statistical tests. An extensive list of denoscriptive statistics, statistical tests, plotting functions, and result statistics are available for different types of data and each estimator.
Seaborn for statistical data visualization. Seaborn is a library for making attractive and informative statistical graphics in Python. It is based on matplotlib. Seaborn aims to make visualization a central part of exploring and understanding data.
Bokeh for creating interactive plots, dashboards and data applications on modern web-browsers. It empowers the user to generate elegant and concise graphics in the style of D3.js. Moreover, it has the capability of high-performance interactivity over very large or streaming datasets.
Blaze for extending the capability of Numpy and Pandas to distributed and streaming datasets. It can be used to access data from a multitude of sources including Bcolz, MongoDB, SQLAlchemy, Apache Spark, PyTables, etc. Together with Bokeh, Blaze can act as a very powerful tool for creating effective visualizations and dashboards on huge chunks of data.
Scrapy for web crawling. It is a very useful framework for getting specific patterns of data. It has the capability to start at a website home url and then dig through web-pages within the website to gather information.
SymPy for symbolic computation. It has wide-ranging capabilities from basic symbolic arithmetic to calculus, algebra, discrete mathematics and quantum physics. Another useful feature is the capability of formatting the result of the computations as LaTeX code.
Requests for accessing the web. It works similar to the the standard python library urllib2 but is much easier to code. You will find subtle differences with urllib2 but for beginners, Requests might be more convenient.
Additional libraries, you might need:
os for Operating system and file operations
networkx and igraph for graph based data manipulations
regular expressions for finding patterns in text data
BeautifulSoup for scrapping web. It is inferior to Scrapy as it will extract information from just a single webpage in a run.
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Python Projects & Resources
Important Python concepts that every beginner should know 1. Variables & Data Types 🧠 Variables are like boxes where you store stuff. Python automatically knows the type of data you're working with! name = "Alice" # String age = 25 …
10 Python Mini Projects for Beginners
Guys, once you've got the basics of Python down, it’s time to build stuff!
Here are 10 mini project ideas that are fun, practical, and boost your confidence!
1. Number Guessing Game 🎯
The computer picks a number, and the user keeps guessing until they get it right.
Perfect to practice loops, conditionals, and user input.
2. Calculator App ➕➖✖️➗
Build a simple calculator that takes two numbers and performs addition, subtraction, multiplication, or division.
3. To-Do List (Console Version) ✅
Let users add, view, and delete tasks. Great to practice lists and file handling if you want to save tasks.
4. Password Generator 🔐
Create random passwords using letters, numbers, and symbols. Use the random and string modules.
5. Dice Rolling Simulator 🎲
Simulate rolling a die. Add cool features like rolling multiple dice or counting the frequency.
6. Rock Paper Scissors Game ✊✋✌️
Let the user play against the computer. Introduces randomness and conditional logic.
7. Quiz App ❓
Create a multiple-choice quiz that gives a score at the end. Store questions and answers using dictionaries.
8. Countdown Timer ⏱️
User inputs minutes or seconds, and the timer counts down to zero. Helps practice time.sleep().
9. Tip Calculator 🍽️
Calculate how much each person should pay including tip. Useful for string formatting and arithmetic.
10. Weather App (Using API) ☁️☀️🌧️
Use a public weather API to fetch real-time weather for a city. Great to explore APIs and the requests library.
For all resources and cheat sheets, check out my Telegram channel: https://news.1rj.ru/str/pythonproz
Hope it helps :)
Guys, once you've got the basics of Python down, it’s time to build stuff!
Here are 10 mini project ideas that are fun, practical, and boost your confidence!
1. Number Guessing Game 🎯
The computer picks a number, and the user keeps guessing until they get it right.
Perfect to practice loops, conditionals, and user input.
2. Calculator App ➕➖✖️➗
Build a simple calculator that takes two numbers and performs addition, subtraction, multiplication, or division.
3. To-Do List (Console Version) ✅
Let users add, view, and delete tasks. Great to practice lists and file handling if you want to save tasks.
4. Password Generator 🔐
Create random passwords using letters, numbers, and symbols. Use the random and string modules.
5. Dice Rolling Simulator 🎲
Simulate rolling a die. Add cool features like rolling multiple dice or counting the frequency.
6. Rock Paper Scissors Game ✊✋✌️
Let the user play against the computer. Introduces randomness and conditional logic.
7. Quiz App ❓
Create a multiple-choice quiz that gives a score at the end. Store questions and answers using dictionaries.
8. Countdown Timer ⏱️
User inputs minutes or seconds, and the timer counts down to zero. Helps practice time.sleep().
9. Tip Calculator 🍽️
Calculate how much each person should pay including tip. Useful for string formatting and arithmetic.
10. Weather App (Using API) ☁️☀️🌧️
Use a public weather API to fetch real-time weather for a city. Great to explore APIs and the requests library.
For all resources and cheat sheets, check out my Telegram channel: https://news.1rj.ru/str/pythonproz
Hope it helps :)
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7 Useful Python One-Liners
1. Reverse a string
print("Python"[::-1]) # Output: nohtyP
2. Check for Palindrome
is_palindrome = lambda s: s == s[::-1]
print(is_palindrome("madam")) # Output: True
3. Get all even numbers from a list
print([x for x in range(20) if x % 2 == 0])
4. Flatten a nested list
print([item for sublist in [[1,2],[3,4]] for item in sublist])
5. Find factorial of a number
import math; print(math.factorial(5)) # Output: 120
6. Count frequency of elements
from collections import Counter
print(Counter("banana")) # Output: {'a': 3, 'b': 1, 'n': 2}
7. Swap two variables
a, b = 5, 10
a, b = b, a
print(a, b) # Output: 10 5
For all resources and cheat sheets, check out my Telegram channel: https://news.1rj.ru/str/pythonproz
Python Projects: https://whatsapp.com/channel/0029Vau5fZECsU9HJFLacm2a
Latest Jobs & Internship Opportunities: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
Hope it helps :)
1. Reverse a string
print("Python"[::-1]) # Output: nohtyP
2. Check for Palindrome
is_palindrome = lambda s: s == s[::-1]
print(is_palindrome("madam")) # Output: True
3. Get all even numbers from a list
print([x for x in range(20) if x % 2 == 0])
4. Flatten a nested list
print([item for sublist in [[1,2],[3,4]] for item in sublist])
5. Find factorial of a number
import math; print(math.factorial(5)) # Output: 120
6. Count frequency of elements
from collections import Counter
print(Counter("banana")) # Output: {'a': 3, 'b': 1, 'n': 2}
7. Swap two variables
a, b = 5, 10
a, b = b, a
print(a, b) # Output: 10 5
For all resources and cheat sheets, check out my Telegram channel: https://news.1rj.ru/str/pythonproz
Python Projects: https://whatsapp.com/channel/0029Vau5fZECsU9HJFLacm2a
Latest Jobs & Internship Opportunities: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
Hope it helps :)
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