Category: Python

  • Python – Operators and Expressions

    In this lesson, we will learn about Operators and Expressions in Python.

    ✨ Types of Operators in Python

    1. Arithmetic Operators

    These are used for basic math:

    OperatorDescriptionExample (a = 10, b = 3)Result
    +Additiona + b13
    -Subtractiona - b7
    *Multiplicationa * b30
    /Divisiona / b3.33
    //Floor Divisiona // b3
    %Modulus (remainder)a % b1
    **Exponentiationa ** b1000

    πŸ“Œ Try this in Python:

    print(5 + 3)
    print(7 % 2)
    print(2 ** 3)
    

    2. Comparison (Relational) Operators

    Compare values and return True or False.

    OperatorDescriptionExample (a = 10, b = 3)Result
    ==Equal toa == bFalse
    !=Not equal toa != bTrue
    >Greater thana > bTrue
    <Less thana < bFalse
    >=Greater than or equala >= bTrue
    <=Less than or equala <= bFalse

    3. Logical Operators

    Used to combine conditional statements.

    OperatorDescriptionExampleResult
    andTrue if both are trueTrue and FalseFalse
    orTrue if at least one is trueTrue or FalseTrue
    notReverses resultnot TrueFalse

    4. Assignment Operators

    Assign values to variables.

    OperatorExampleSame As
    =x = 5Assign 5 to x
    +=x += 3x = x + 3
    -=x -= 2x = x - 2
    *=x *= 4x = x * 4
    /=x /= 2x = x / 2
    //=x //= 2x = x // 2
    %=x %= 2x = x % 2
    **=x **= 3x = x ** 3

    5.Bitwise Operators

    Bitwise operators work on bits (0s and 1s) of integers at the binary level.

    They are used to perform operations like AND, OR, XOR, NOT, etc., bit-by-bit.

    OperatorDescriptionExample
    &AND5 & 3 = 1
    ``OR
    ^XOR5 ^ 3 = 6
    ~NOT~5 = -6
    <<Left Shift5 << 1 = 10
    >>Right Shift5 >> 1 = 2

    πŸ§ͺ 6. Identity and Membership Operators

    Identity :

    x = [1, 2]
    y = x
    print(x is y)  # True
    

    Membership

    fruits = ["apple", "banana"]
    print("apple" in fruits)  # True
    

    Expressions in Python

    x = 10
    y = 5
    result = (x + y) * 2
    print(result) # Output: 30

    Operator Precedence

    Determines the order in which operations are performed.

    From highest to lowest:

    1. () – Parentheses
    2. ** – Exponentiation
    3. +, - (Unary)
    4. *, /, //, %
    5. +, - (Binary)
    6. <, <=, >, >=, ==, !=
    7. and
    8. or
    9. =, +=, -=, etc.

    Example :

    x = 10
    y = 4
    z = 3
    
    result = x + y * z - y / 2
    print(result)
    # Output: 10 + 12 - 2.0 = 20.0
    

    Examples


    πŸ”’ 1. Arithmetic Operators

    a = 10
    b = 3
    
    print(a + b)   # Output: 13
    print(a - b)   # Output: 7
    print(a * b)   # Output: 30
    print(a / b)   # Output: 3.333...
    print(a // b)  # Output: 3
    print(a % b)   # Output: 1
    print(a ** b)  # Output: 1000
    

    🀝 2. Comparison Operators

    x = 5
    y = 10
    
    print(x == y)  # Output: False
    print(x != y)  # Output: True
    print(x > y)   # Output: False
    print(x < y)   # Output: True
    print(x >= 5)  # Output: True
    print(y <= 10) # Output: True
    

    🧠 3. Logical Operators

    a = True
    b = False
    
    print(a and b)  # Output: False
    print(a or b)   # Output: True
    print(not a)    # Output: False
    
    

    🧱 4. Bitwise Operators

    a = 5      # 0101
    b = 3      # 0011
    
    print(a & b)  # Output: 1  (0001)
    print(a | b)  # Output: 7  (0111)
    print(a ^ b)  # Output: 6  (0110)
    print(~a)     # Output: -6 (inverts bits)
    print(a << 1) # Output: 10 (shifts left: 1010)
    print(a >> 1) # Output: 2  (shifts right: 0010)
    


    ✍️ 5. Assignment Operators

    x = 5
    x += 3     # Same as x = x + 3
    print(x)   # Output: 8
    
    x *= 2     # x = x * 2
    print(x)   # Output: 16
    
    

    πŸ” 6. Identity Operators

    a = [1, 2]
    b = a
    c = [1, 2]
    
    print(a is b)  # Output: True
    print(a is c)  # Output: False
    print(a == c)  # Output: True (values are same)
    

    🍎 7. Membership Operators

    fruits = ["apple", "banana", "cherry"]
    
    print("banana" in fruits)   # Output: True
    print("grape" not in fruits)  # Output: True
    

    🎯 8. Expressions Example

    result = (5 + 3) * 2 - 4 / 2
    print(result)  # Output: 14.0
    

    Welcome to the Python Programming Quiz!

    Test your knowledge by selecting the correct answers. You will immediately see if you’re right or wrong.

    Score: 0
  • Variables and Data Types (with Examples & Output)

    🎯 Learning Objectives

    By the end of this module, students will be able to:

    • Understand what variables are and how to use them.
    • Identify and apply different data types.
    • Perform type conversions (casting).
    • Avoid common variable naming mistakes.

    🧠 1. What is a Variable?

    • A variable is a name that refers to a value stored in memory.
    • Think of it as a label on a box that stores a piece of data.
    name = "Alice"
    age = 20
    

    name holds "Alice", age holds 20.

    πŸ—‚οΈ 2. Python Data Types

    Data TypeExampleDescription
    int25Whole numbers
    float3.14Decimal numbers
    str"Hi"Text values
    boolTrueLogical values (True/False)

    Example:

    x = 10        # int
    y = 3.5       # float
    name = "Sam"  # str
    flag = True   # bool
    

    πŸ“ 3. Variable Naming Rules

    βœ… Valid Names:

    • Must begin with a letter or _
    • Can contain letters, digits, and underscores
    • Case-sensitive (name β‰  Name)

    Example :

    # 2name = "Alex"    ❌ starts with number
    # user-name = "Bob" ❌ contains dash
    # my name = "Joe"   ❌ contains space
    

    πŸ”„ 4. Type Conversion (Casting)

    age = "20"          # str
    nextyearage=age+1   
    
    #TypeError: can only concatenate str (not "int") to str
    
    nextyearage=int(age)+1   
    print (nextyearage)      # 21
    

    Use int(), float(), str(), bool() for conversions.

    πŸ§ͺ 5. Checking Data Types

    use type() function

    print(type(10))        # <class 'int'>
    print(type("hello"))   # <class 'str'>
    

    ⚠️ 6. Common Mistakes

    MistakeWhy it’s wrongFix
    "age" + 5Can’t add string and integerConvert first: int("age") + 5
    user name = "Tom"Variable names can’t have spacesUse underscore: user_name

    🧩 7. Practice Time (Live Demo)

    1. Create a variable city and assign your city name.
    2. Create variables for your birth year and calculate your age.
    3. Convert a float to a string and print the result and type.
    4. Check if bool(0) and bool("Hi") return True or False.

    πŸ“š Quick Recap

    • Variables hold data values.
    • Data types define the kind of value.
    • Use type() to inspect types.
    • Convert types using casting functions like int(), str().
    • Follow naming rules for valid variables.

    Example 1:

    name = "John"
    age = 28
    height = 5.9
    
    print(name)
    print(age)
    print(height)
    
    Output

    John
    28
    5.9
    


    Example 2: Check Data Type

    print(type(name))   # str
    print(type(age))    # int
    print(type(height)) # float
    
    Output

    <class 'str'>
    <class 'int'>
    <class 'float'>
    


    Example 3: Type Casting

    age = 28
    height = 5.9
    
    age = float(age)
    height = str(height)
    
    print(age)
    print(type(age))
    print(height)
    print(type(height))
    
    Output

    28.0
    <class 'float'>
    5.9
    <class 'str'>
    

    Example 4: Assign multiple values in one line.

    a, b, c = 1, 2, 3
    print(a, b, c)
    
    Output

    1 2 3
    


    Example 5: Assign Same Value to Multiple Variables

    x = y = z = "Python"
    print(x, y, z)
    
    Output

    Python Python Python
    


    Example 6: String Concatenation using Variables

    first = "Hello"
    last = "World"
    message = first + " " + last
    print(message)
    
    Output

    Hello World
    


    Example 7: Numeric Calculation Using Variables

    price = 50
    quantity = 3
    total = price * quantity
    print("Total:", total)
    
    Output

    Total: 150
    


    Example 8: Boolean Example

    is_logged_in = True
    print("Login status:", is_logged_in)
    
    Output

    Login status: True
    


    Example 9: Dynamic Typing in Python

    var = 10
    print(type(var))  # int
    
    var = "Ten"
    print(type(var))  # str
    
    Output

    <class 'int'>
    <class 'str'>
    


    Example 10: Input and Type Conversion

    name = input("Enter your name: ")
    age = int(input("Enter your age: "))
    print(f"Hello {name}, you are {age} years old.")
    
    Output

    Enter your name: Alex
    Enter your age: 21
    
    Hello Alex, you are 21 years old.
    


    Example 11: Using type() in Debugging

    value = "123"
    print(value + " is a string")      # works
    # print(value + 5)                 # ❌ TypeError
    
    value = int(value)
    print(value + 5)                   # βœ… Now works
    
    Output

    123 is a string
    128
    


    Example 12: Calculate the Area of a Rectangle

    length = 10
    width = 5
    area = length * width
    print("Area of rectangle:", area)
    
    Output

    Area of rectangle: 50
    


    Example 13: Store and Display Product Info

    product_name = "Laptop"
    price = 799.99
    in_stock = True
    
    print("Product:", product_name)
    print("Price: $", price)
    print("Available:", in_stock)
    
    Output

    Product: Laptop
    Price: $ 799.99
    Available: True
    


    Example 14: Temperature Storage in Celsius and Fahrenheit

    celsius = 25
    fahrenheit = (celsius * 9/5) + 32
    
    print("Celsius:", celsius)
    print("Fahrenheit:", fahrenheit)
    
    Output

    Celsius: 25
    Fahrenheit: 77.0
    


    Example 15: Using Variables to Format Strings

    name = "Sara"
    score = 95
    
    print(f"{name} scored {score} points.")
    
    Output

    Sara scored 95 points.
    


    Example 16: Variable Reassignment

    x = 10
    print("Before:", x)
    
    x = 20
    print("After:", x)
    
    Output

    Before: 10
    After: 20
    


    Example 17: Using bool() Function

    print(bool(0))      # False
    print(bool(123))    # True
    print(bool(""))     # False
    print(bool("Hi"))   # True
    
    Output

    False
    True
    False
    True
    


    Example 18: Type Conversion with Errors (Demonstration)

    x = "ten"
    # y = int(x)  # This will cause an error
    
    print("Cannot convert non-numeric string to integer")
    
    Output

    Cannot convert non-numeric string to integer
    


    Example 19: Combining Strings and Numbers with Casting

    name = "Liam"
    score = 88
    
    print(name + " scored " + str(score) + " marks.")
    
    Output

    Liam scored 88 marks.
    


    Example 20: Constants (Using UPPERCASE by Convention)

    PI = 3.14159
    radius = 7
    area = PI * radius * radius
    
    print("Circle Area:", round(area, 2))
    
    Output

    Circle Area: 153.94
    

    Welcome to the Python Programming Quiz!

    Test your knowledge by selecting the correct answers. You will immediately see if you’re right or wrong.

    Score: 0
  • Learn Python Step by Step

  • Python Installation Step by Step

    1) Click to Download for Windows Operation System https://www.python.org/ftp/python/3.13.1/python-3.13.1-amd64.exe

    2)Run the installer (e.g., python-3.x.x.exe).

    3) On the first installation screen:

    3.1) Check the box for “Use admin privileges when installing py.exe” at the bottom.

    3.2) Check the box for “Add Python to PATH” at the bottom.

    3.3) Click “Install Now” for default settings.

    4) Wait for the installation to complete, and then click “Close”.

    5)Open a Command Prompt.
    5.1) In Search bar : Type CMD
    5.2)Click Command Prompt

    6) To Check If Python is Installed or Not
    type python –version in Command Prompt

    If a version number appears, Python is installed.

    7) How to Use IDLE Window for to run Python Program

    Interactive Mode

    7.1) Type idle in Search bard

    7.2) Click IDLE (python x.xx 64 bit)

    7.3) When IDLE opens, you’ll see the Python shell. You can type commands directly here, and they execute immediately.

    type print(“Hello World”)

    Press Enter to see the output.

    Script Mode

    To write and save Python programs:

    • Go to File β†’ New File.
    • A new editor window will open.
    • Write your Python script here.
    • Save the file (Ctrl + S) with a .py extension (e.g., my_program.py).

    To run the script:

    • Click Run β†’ Run Module (F5).

    You Can Customize Settings: In IDLE, go to Options β†’ Configure IDLE to adjust font size, colors, and other preferences.

  • Python Modules and Libraries: How to Use and Import Them


    1. Introduction

    “Hello everyone! Welcome back to our Python learning series. Today, we are going to talk about a very interesting topic: Modules and Libraries in Python. Whether you’re a student or working in an office, this concept will save you time and effort in coding. Let’s dive in!”


    2.What Are Modules and Libraries?

    • Definition of Modules:
      “Modules are like tools. Instead of writing everything from scratch, you can use these pre-built tools to do tasks quickly. For example, Python has a module called math for calculations.”
    • Definition of Libraries:
      “A library is a collection of many modules. Think of it like a toolbox full of different tools for different tasks. Libraries like pandas and openpyxl are used for tasks like managing Excel files.”

    3. How to Import Modules –

    • Basic Syntax:
    import module_name
    

    “For example, to use the math module, just type: import math.”

    • Example 1: Calculate Square Root with math Module
    import math 
    result = math.sqrt(16) 
    print("The square root of 16 is:", result)
    

    4. Import Specific Function:

    from math import sqrt 
    result = sqrt(25) 
    print("Square root of 25 is:", result)
    
    • “This way, we import only the part we need, making the code shorter.”

    5. Examples for Modules

    1. random Module for Selecting Random Items
    import random students = ["Amit", "Priya", "Rahul", "Sneha"] 
    chosen = random.choice(students) 
    print("The chosen student is:", chosen)
    

    2. datetime for Date and Time

    from datetime import datetime 
    now = datetime.now() 
    print("Current date and time:", now)
    

    6. Examples Useful Libraries

    1. openpyxl for Excel Files
      • “Imagine you have an Excel file and want to automate tasks like reading or writing data.”
    from openpyxl import Workbook
    workbook = Workbook() 
    sheet = workbook.active 
    sheet["A1"] = "Hello, Excel!"
    workbook.save("example.xlsx")
    print("Excel file created!")
    

    2. os for Managing Files

    • “This library helps you work with files and folders directly in Python.”

    import os os.makedirs("NewFolder") 
    print("Folder created!")
    

    7. How to Install External Libraries

    • Using pip Command:
      “To install a library not built into Python, use the pip command in command prompt. For example:
    pip install pandas 

    “This installs the pandas library, which is great for handling large datasets.


    Pre-installed modules and libraries:

    Python comes with a standard library that includes many pre-installed modules and libraries, making it easy to perform a wide range of tasks without installing additional packages. Below are some of the commonly used predefined modules and libraries included in Python:


    1. General Purpose Modules

    • sys: Provides access to system-specific parameters and functions.
      • Example: sys.argv for command-line arguments.
    • os: For interacting with the operating system.
      • Example: os.listdir() to list files in a directory.
    • time: Handles time-related tasks.
      • Example: time.sleep() to pause execution.
    • datetime: For working with dates and times.
      • Example: datetime.date.today() to get the current date.
    • platform: Provides information about the platform (OS, Python version, etc.).
      • Example: platform.system() to get the OS name.

    2. File and Directory Handling

    • shutil: High-level file and directory operations.
      • Example: shutil.copy() to copy files.
    • pathlib: Object-oriented approach to working with file paths.
      • Example: Path().exists() to check if a file exists.
    • glob: To find file paths using patterns.
      • Example: glob.glob('*.txt') to find all text files.

    3. Data Handling and Manipulation

    • json: For working with JSON data.
      • Example: json.dumps() to convert Python objects to JSON.
    • csv: For reading and writing CSV files.
      • Example: csv.reader() to read CSV files.
    • sqlite3: For working with SQLite databases.
      • Example: sqlite3.connect() to connect to a database.
    • pickle: For serializing and deserializing Python objects.
      • Example: pickle.dump() to save objects to a file.

    4. Math and Statistics

    • math: Provides mathematical functions.
      • Example: math.sqrt() to find the square root.
    • statistics: For statistical calculations.
      • Example: statistics.mean() to calculate the average.
    • random: For generating random numbers.
      • Example: random.randint() for random integers.

    5. Internet and Web

    • urllib: For working with URLs.
      • Example: urllib.request.urlopen() to fetch web pages.
    • http: For handling HTTP requests.
      • Example: http.client for HTTP communication.
    • email: For email processing.
      • Example: email.message to create email messages.

    6. Text Processing

    • re: For regular expressions.
      • Example: re.search() to search patterns in text.
    • string: Common string operations.
      • Example: string.ascii_letters to get all alphabets.
    • textwrap: For wrapping and formatting text.
      • Example: textwrap.wrap() to wrap text to a specified width.

    7. Debugging and Testing

    • logging: For logging messages.
      • Example: logging.info() to log informational messages.
    • unittest: For writing test cases.
      • Example: unittest.TestCase to define test cases.
    • pdb: Python debugger for debugging code.
      • Example: pdb.set_trace() to set a breakpoint.

    8. Networking

    • socket: For network communication.
      • Example: socket.socket() to create a socket.
    • ipaddress: For working with IP addresses.
      • Example: ipaddress.ip_network() to define a network.

    9. GUI Development

    • tkinter: For creating graphical user interfaces.
      • Example: tkinter.Tk() to create a window.

    10. Cryptography and Security

    • hashlib: For generating secure hashes.
      • Example: hashlib.md5() to generate MD5 hashes.
    • hmac: For keyed-hashing for message authentication.
      • Example: hmac.new() to create a hash object.

    11. Advanced Topics

    • itertools: For efficient looping.
      • Example: itertools.permutations() to generate permutations.
    • functools: For higher-order functions.
      • Example: functools.reduce() to reduce a list.
    • collections: High-performance data structures.
      • Example: collections.Counter() to count elements in a list.

    n Python, the terms module and library are often used interchangeably, but they do have slight distinctions:

    Key Differences

    • Module: A single Python file containing definitions (functions, classes, variables) and code.
    • Library: A collection of modules that provide related functionality. For example, Python’s standard library is a collection of modules and packages included with Python.

    Now, let’s clarify which items in the above list are modules and which are libraries:

    General Purpose

    • sys: Module
    • os: Module
    • time: Module
    • datetime: Module
    • platform: Module

    File and Directory Handling

    • shutil: Module
    • pathlib: Module
    • glob: Module

    Data Handling and Manipulation

    • json: Module
    • csv: Module
    • sqlite3: Module
    • pickle: Module

    Math and Statistics

    • math: Module
    • statistics: Module
    • random: Module

    Internet and Web

    • urllib: Library (contains submodules like urllib.request and urllib.parse)
    • http: Library (contains submodules like http.client and http.server)
    • email: Library (contains submodules like email.message and email.mime)

    Text Processing

    • re: Module
    • string: Module
    • textwrap: Module

    Debugging and Testing

    • logging: Module
    • unittest: Library (contains submodules like unittest.mock)
    • pdb: Module

    Networking

    • socket: Module
    • ipaddress: Module

    GUI Development

    • tkinter: Library (contains modules like tkinter.ttk and tkinter.messagebox)

    Cryptography and Security

    • hashlib: Module
    • hmac: Module

    Advanced Topics

    • itertools: Module
    • functools: Module
    • collections: Module

    Most famous external libraries in Python

    1. Data Science and Machine Learning

    • NumPy: For numerical computing and handling multi-dimensional arrays.
    • Pandas: For data manipulation and analysis.
    • Matplotlib: For creating static, animated, and interactive visualizations.
    • Seaborn: For statistical data visualization built on top of Matplotlib.
    • Scikit-learn: For machine learning, including classification, regression, and clustering.
    • TensorFlow: For deep learning and AI.
    • PyTorch: Another powerful deep learning library.
    • Keras: A high-level API for TensorFlow, focusing on ease of use.
    • Statsmodels: For statistical modeling and hypothesis testing.

    2. Data Visualization

    • Plotly: For interactive visualizations, including charts, graphs, and dashboards.
    • Bokeh: For creating interactive visualizations in a web browser.
    • Altair: Declarative statistical visualization library for Python.

    3. Web Development

    • Django: A high-level web framework for rapid development and clean, pragmatic design.
    • Flask: A lightweight and flexible web framework.
    • FastAPI: A modern web framework for building APIs with Python 3.6+.
    • Bottle: A micro web framework that is simple to use.

    4. Automation and Scripting

    • Selenium: For automating web browsers.
    • BeautifulSoup: For web scraping and parsing HTML/XML.
    • Requests: For making HTTP requests easily.
    • PyAutoGUI: For GUI automation tasks like controlling the mouse and keyboard.

    5. Game Development

    • Pygame: For developing 2D games.
    • Godot: Python bindings for the Godot game engine.
    • Arcade: Another library for developing 2D games.

    6. Networking

    • SocketIO: For WebSocket communication.
    • Paramiko: For SSH and SFTP.
    • Twisted: For event-driven networking.

    7. Database Handling

    • SQLAlchemy: For database access and object-relational mapping (ORM).
    • PyMongo: For MongoDB interaction.
    • Psycopg2: For working with PostgreSQL databases.

    8. Cryptography and Security

    • Cryptography: For secure encryption and decryption.
    • PyJWT: For JSON Web Tokens (JWT) authentication.
    • Passlib: For password hashing.

    9. GUI Development

    • PyQt: For building cross-platform graphical applications.
    • Kivy: For developing multi-touch applications.
    • Tkinter: The standard GUI toolkit for Python.

    10. Testing

    • pytest: A powerful framework for testing.
    • unittest: Built-in testing framework (but pytest is more flexible).
    • Mock: For mocking objects in tests.

    11. File Handling

    • PyPDF2: For working with PDF files.
    • OpenPyXL: For reading and writing Excel files.
    • Pillow: For image manipulation and processing.

    12. Other Popular Libraries

    • pytz: For timezone handling.
    • Arrow: For working with dates and times in an easy and human-friendly way.
    • Shapely: For geometric operations.
    • Geopy: For geocoding and working with geographic data.
    • MoviePy: For video editing.

    13. AI and Natural Language Processing (NLP)

    • NLTK: For natural language processing.
    • spaCy: Another NLP library for processing large text datasets.
    • OpenCV: For computer vision and image processing.
    • transformers (by Hugging Face): For working with state-of-the-art NLP models.