Learn python programming full tutorial for beginners

Python is a powerful, general-purpose, high-level programming language created by Guido van Rossum and first released in 1991.Python is a popular programming language.

Python can be used on a server to create web applications.

Common Uses of Python:

• Web Development: Python frameworks like Django and Flask are popular for building web applications.
• Data Science and Machine Learning: Python libraries like NumPy, Pandas, TensorFlow, and sci-kit-learn make it a powerful tool for data analysis and machine learning tasks.
• Automation: Python scripts can be used to automate repetitive tasks on your computer.
• Scripting: Python is often used for scripting various tasks, such as system administration, network automation, and testing.
• Scientific Computing: Python is used in scientific computing due to its numerical computing libraries like NumPy and SciPy.

• Python is Simple and easy.
• Python is Free and Open Source.
• Python High-level language.
• Python is portable.
• Python was developed by Guido Van Rossum.

• web development (server-side),
• software development,
• mathematics,
• system scripting.

Python Syntax

Python syntax refers to the set of rules that define how you write Python programs. It's known for being clear and readable, resembling natural language in many ways. Here are some key aspects of Python syntax:

• Indentation: Unlike many other languages that use curly braces ({}) to define code blocks, Python uses indentation with spaces or tabs. Consistent indentation is crucial as it determines the program's structure. All lines within a block (like if statements or loops) must have the same level of indentation.

• Variables: Variables store data and are named using letters, numbers, and underscores. They follow naming conventions to improve readability (e.g., using lowercase with underscores for separation).

• Data Types: Python is dynamically typed, meaning you don't need to declare a variable's data type beforehand. Common data types include integers, floats, strings, booleans, and lists.

• Operators: Python has various operators for performing operations like arithmetic (+, -, *, /), comparison (==, !=, <, >), and logical (and, or, not).

• Keywords: These are reserved words with specific meanings in Python. Examples include if, else, for, while, def, and class.

• Comments: Comments are lines ignored by the interpreter, used to explain your code or add notes. They start with the # symbol.

Example:-

print("Hello, World!")

Adding two numbers:-

number1 = 10

number2 = 20

sum = number1 + number2

print("The sum of", number1, "and", number2, "is", sum)

User Input:-

name = input("My Name is Rahul Bharadwaj? ") 

 print(name)

Python Comments

Comments in Python are lines of code ignored by the Python interpreter when running the program. Their purpose is to enhance code readability and understanding for both yourself and other programmers. Here's a breakdown of comments in Python:

• Comments can be used to explain Python code.
• Comments can be used to make the code more readable.
• Comments can be used to prevent execution when testing code.

Types of Comments:

• Single-line comments: These start with the hash symbol (#) and extend to the end of the line. They're useful for brief explanations of variables, expressions, or code sections.

Example:-

# Python can be used on a server to create web applications.

Multiline comments: While Python doesn't have a dedicated syntax for multiline comments, there are two common workarounds:

1. Multiple single-line comments: You can write multiple lines, each starting with a hash symbol.

Example:-

# Python can be used on a server to create web applications.

# Python can be used on a server to create web applications.

# Python can be used on a server to create web applications.

# Python can be used on a server to create web applications.

2. Multiline strings: You can enclose your comment within triple quotes (either three single quotes or . three double quotes). This is treated as a string literal but ignored during execution.

Example:-

"""

 Python can be used

on a server to

create web applications.

"""

Python Variables

variables act as named containers that store data values. They're a fundamental concept in programming, allowing you to work with information throughout your code.

Creating Variables:

• Python is dynamically typed, meaning you don't explicitly declare a variable's data type beforehand. The type is inferred based on the value you assign.

• To create a variable, you simply give it a name and assign a value using the equal sign (=).

Example:-

x = 5 y = "John" print(x) print(y)

 

Variable Types:

Python supports various data types to store different kinds of information:

• Integers (int): Whole numbers (positive, negative, or zero).
• Floats (float): Numbers with decimal points.
• Strings (str): Sequences of characters enclosed in single or double quotes.
• Booleans (bool): Logical values representing True or False.
• Lists (list): Ordered collections of items enclosed in square brackets []. Elements can be of different data types.
• Tuples (tuple): Immutable (unchangeable) ordered collections of items enclosed in parentheses ().
• Dictionaries (dict): Unordered collections of key-value pairs enclosed in curly braces {}. Keys are unique and can be of any data type (often strings).
• Sets (set): Unordered collections of unique items enclosed in curly braces {}.
• None: A special data type representing the absence of a value.

Example:-

x = str(3)    # x will be '3'
y = int(3)    # y will be 3
z = float(3)  # z will be 3.0

Variable Naming Rules:

• Variable names must start with a letter (a-z or A-Z) or an underscore (_).
• They can contain letters, numbers, and underscores.
• Names are case-sensitive (e.g., name and Name are different variables).
• Avoid using reserved keywords (words with special meanings in Python) as variable names. You can find a list of reserved keywords in the Python documentation.

Example:-

x = "John"
# is the same as
x = 'John'

Using Variables:

Once you have variables, you can use them in various ways in your Python code:

• Perform calculations: total_price = price * quantity
• Create data structures like lists and dictionaries.
• Build control flow statements (if, else, for, while) based on variable values.
• Store input from the user.
• Pass information between functions.

Python Data Types

Data types are essential building blocks in Python.

Built-in Data Types

Data types are essential building blocks in Python, defining the kind of information a variable can hold and the operations you can perform on it. Python offers a variety of built-in data types to cater to different needs:

Text Type:	str
Numeric Types:	int, float, complex
Sequence Types:	list, tuple, range
Mapping Type:	dict
Set Types:	set, frozenset
Boolean Type:	bool
Binary Types:	bytes, bytearray, memoryview
None Type:	NoneType

Numeric Types:

• Integers (int): Represent whole numbers, positive, negative, or zero. Examples: 10, -25, 0
• Floats (float): Represent numbers with decimal points. Examples: 3.14, -12.56, 1.0e+3 (scientific notation for 1000)
• Complex Numbers (complex): Represent numbers with a real and imaginary part (a+bi). Examples: 3+2j, 1j

Text Type:

• Strings (str): Sequences of characters enclosed in single (') or double (") quotes. Can include letters, numbers, symbols, and whitespace. Examples: "Hello, world!", 'This is a string'

Logical Type:

• Booleans (bool): Represent logical values, either True or False. Used for conditions and comparisons.

Sequence Types:

• Lists (list): Ordered collections of items (elements) enclosed in square brackets []. Elements can be of different data types. Mutable (changeable). Examples: [1, "apple", 3.4], [] (empty list)
• Tuples (tuple): Ordered collections of items enclosed in parentheses (). Elements are immutable (unchanggeable) once created. Examples: (10, "banana", True), () (empty tuple)

Collection Types:

• Sets (set): Unordered collections of unique elements enclosed in curly braces {}. Elements can be of any data type (often used for strings or numbers). Duplicates are not allowed. Mutable. Examples: {1, 2, "orange"}, set() (empty set)
• Frozen Sets (frozenset): Immutable versions of sets. Once created, elements cannot be changed. Examples: frozenset({3, 4, "cherry"})

Mapping Type:

• Dictionaries (dict): Unordered collections of key-value pairs enclosed in curly braces {}. Keys must be unique and can be of any data type (often strings). Values can be of any data type. Mutable. Examples: {"name": "Alice", "age": 30}, {} (empty dictionary)

Special Type:

• None: Represents the absence of a value. Used to indicate that a variable doesn't point to any object.

Checking Data Types:

Use the built-in type() function to determine the data type of a variable:

 Getting the Data Type

You can get the data type of any object by using the type() function:

Example:-

#Print the data type of the variable y :

y = 50

print(type(y))        # type -  <class 'int'>

Setting the Specific Data Type

If you want to specify the data type, you can use the following constructor functions:

Example	Data Type
x = str("Hello World")	str
x = int(54)	int
x = float(45.5)	float
x = complex(3j)	complex
x = list(("Apple", "Mango", "Papaya"))	list
x = tuple(("Apple", "Mango", "Papaya"))	tuple
x = range(4)	range
x = dict(name="Rahul", age=45)	dict
x = set(("apple", "Mango", "Papaya"))	set
x = frozenset(("apple", "Mango", "Papaya"))	frozenset
x = bool(5)	bool
x = bytes(5)	bytes
x = bytearray(5)	bytearray
x = memoryview(bytes(5))	memoryview