Introduction to Python

Introduction to Python

• Python is a versatile programming language known for being dynamically typed
• It is high-level, and uses a combination of compilation and interpretation.
• Python is garbage-collected and supports object-oriented, procedural, and functional programming paradigms
• Unique characteristics and advantages make it widely used as compared to Java and C++
• Guido van Rossum conceptualized Python in the late 1980s.
• The initial version, Python 0.9.0, was launched in 1991.

Key Features

• Readable syntax makes it suitable for both beginners and experts, leading to faster development and fewer errors.
• Data types are determined during runtime, improving code adaptability
• High-level nature makes code more human-readable
• Python code is compiled into bytecode before being interpreted line by line
• The standard Python implementation, CPython, is both compiled and interpreted.
• Memory management is automatic, freeing programmers from manual allocation/deallocation tasks.
• Everything in Python is treated as an object, including basic types like numbers and strings.
• Python is compatible with Windows, macOS, and Linux, enabling cross-platform software development.
• Python has a comprehensive collection of modules and functions for web development, data manipulation, machine learning and network communication
• Python can be used and distributed without cost

Basic Syntax

• Python does not use curly braces or semicolons
• Python uses indentation to define code blocks
• Indentation involves adding whitespace before statements to indicate the code block they belong to.

History of Python

• Guido van Rossum created Python as a successor to the ABC language, which he designed to be easy to read and efficient.
• Python's first public version, 0.9.0, was released in February 1991, marking its debut as an open-source project.
• The name "Python" is a reference to the British comedy series "Monty Python's Flying Circus".
• Python 1.0, a stable and usable version, was released in January 1994, including features still used today.
• From the 1990s to 2000s, Python popularity grew as a result of its simplicity, readability, and versatility
• Python 2.0 was released in October 2000, introducing list comprehensions, garbage collection, and Unicode support.
• Python 3.0 was released in December 2008, and included changes to improve readability and maintainability.
• Throughout the 2010s, Python became increasingly popular, particularly in computer science, machine learning, and web development because of libraries and frameworks.

Advantages of Learning Python

• Uses simple synatx to make it easier to read and learn as compared to C, C++, and Java for new coders:
• Allows developers to express complex concepts concisely, reducing development time.
• Python's interpreter allows for fast development and testing
• Object-oriented, Python makes code reusable and modular
• Community-driven and free to use, distribute, and modify.
• Python can be extended with modules written in C, C++, or other languages.
• GUI frameworks Tkinter and PyQt makes it easy to create desktop apps.
• Python integrates with languages like C/C++, Java, and .NET.
• Memory allocation is automated, simplifying development
• Libraries and frameworks NumPy, Pandas, Django, and Flask for solving a wide range of problems.
• Python is adaptable in machine learning, web development, data analysis, and academics.
• Leads to career opportunities in data science, AI, and web development.
• With rising automation and digital transformation, Python developers are in high demand across industries.
• Becomes the main language used for big data and machine learning with libraries like NumPy, Pandas, Scikit-learn, TensorFlow for data scientists and machine learning engineers

Key Applications

• Python is useful with NumPy, Pandas, and Matplotlib for data manipulation and visualization
• Can be used in GUI desktop apps with libraries like PyQt and Tkinter
• Commonly used to create command-line tools with input/output redirection and piping.
• Kivy or BeeWare, can be combined with frameworks for cross-platform mobile applications.
• Useful in the fields fo AI and machine learning because of libraries like TensorFlow, Keras, and PyTorch
• Web development frameworks: Django and Flask on the backend, and Javascript, HTML and CSS on the front end
• Develop large-scale enterprise applications with features such as distributed computing, networking, and parallel processing.
• CAD applications, supported by libraries such as Blender
• Used to develop ML algorithms and predictive models
• Can be used for OpenCV and Scikit-image to process and analyze images
• Used for speech recognition via SpeechRecognition and PyAudio libraries.
• Advanced numerical computing capabilities through libraries like NumPy, SciPy, and Pandas
• Used to teach beginners programming
• Used for automated UI testing with frameworks like unit tests and pytest
• Used with libraries like Pygame for developing games
• Python is used in IoT for developing scripts and applications for devices like Raspberry Pi, Arduino, and others.
• Used to develop scripts and apps for network automation, monitoring, and management.
• Has libraries like Pandas, Scikit-learn, and Statsmodels for financial modeling and analysis
• Has libraries like Pyaudio and Music21 for audio processing, synthesis, analysis, and music analysis

Frameworks and Libraries

• Widely used through machine learning, artificial intelligence, and web applications:
• Django, Flask, Pyramid, CherryPy for web development (Server-side)
• Tkinter, PyGTK, PyQt, PyJs for GUI based applications
• TensorFlow, PyTorch, Scikit-learn, Matplotlib, Scipy for Machine Learning
• NumPy and Pandas, etc for Mathematics

Python Interpreter

• Executes Python code by parsing it and running its instructions
• The interpreter reads Python code line by line.
• The interpreter ensures that the syntax and structure are correct.
• The interpreter carries out instructions such as carrying out calculations, printing results, and reading files
• Provides output based on the code instructions executed.
• Does not require a separate compilation step like C or Java
• Python code can be run directly in an interpreter without pre-compilation.

Using Python as a Calculator

• Python commands can be entered as commands in an interactive environment such as the Python shell
• Can perform basic arithmetic operations.
• Uses parentheses to control order of operations.
• Handles both integers and floating-point numbers (decimals).
• Can enter the Python interactive shell (REPL) and type and run expressions and see the results instantly.

Python Shell

• Python REPL (Read-Eval-Print Loop) is an interactive environment to write and execute Python code line by line
• Test commands, code snippets, and get feedback testing
• By typing python or python3 and pressing Enter
• The ">>>" symbol means ready, and in the shell
• Interactive mode: type commands; execute immidiately; see result
• Real-time feedback: Get assignments, calculations, etc, immidiately after typing
• Ability to test small functions without writing scripts
• Manipulate variables directly
• Can write multi-line code example defining a function
• Can import Python libraries and their functions directly
• To exit type exit() or press Ctrl + Z (Windows)

Indentation

• Crucial defining the structure and flow
• Defines code blocks
• Must start with 4 spaces per indentation level
• Makes code readable
• Used for loops, conditionals, function
• Helps visualizing the hierarchy for nested control structures

Atoms in Python

• Atoms refer to the simplest building blocks of the language
• The basic elements to form complex expressions and data structures

Types of Atoms or tokens

• Keywords (Reserved Words) e.g. "if", "else", "elif", "for", "while", "break", "continue"
• Identifiers
  • Variable and Function Names
  • Names assigned to variables, functions, classes, and objects
  • Can contain letters (a-z, A-Z), digits (0-9), and underscores (_)
  • Cannot start with a digit
  • Cannot be a Python keyword e.g. age , how
• Literals (Constant Values)
  • Fixed values assigned to variables:
  • Integer: 10, -5, 1000
  • Float: 3.14, -0.01, 1.5e3
  • String: "hello", 'Python', '''Multiline'''
  • Boolean: True, False
  • None: None
• Operators
  • Symbols that perform operations on variables and values
  • Arithmetic Operators: +, -, *, /, %, **, //
  • Comparison Operators: ==, !=, >, <, >=, <=
  • Logical Operators: and, or, not
  • Assignment Operators: =, +=, -=, *=, /=
  • Bitwise Operators: &, |, ^, ~, <<, >>
• Punctuators
  • Special symbols used in Python syntax
  • Parentheses: ()
  • Brackets: []
  • Braces: {}
  • Comma:,
  • Colon: :
  • Semicolon: ;
  • Dot: .

Identifiers (Variable & Function Names)

• Letters, digits, and underscores
• Must start with a letter or underscore
• Followed by letters, digits, or underscores
• Should not be a Python reserved keywords
• Case-sensitive
• No length restrictions
• No spaces, Use underscores) for readability, like first_name

Keywords

• Python unique words reserved with defined meanings/functions
• Used only for those functions
• No need to be imported, Permanently present, Python contains thirty-five keywords

Python Literals

• Python data given in a variable or constant, Values that are used directly in the code
  • String literals: Created enclosing text in the quotes, single and double
    • Single-line string: end in 1 line
    • Multi-line string: has 2 ways
      • Adding back slash at end line
      • Using triple quotation marks
  • Numeric Literals: Immutable, 4 different: -Int (signed integers): positive + negative, no fraction -Long (long integers): unlimited sized lowercase or uppercase -Float (floating point): real both integer + fractional -Complex (complex): a+bj real part, b imaginary part, 3.14j
  • Boolean literals: can have 2 values: True or False,
  • Special literals.: has one special, None
• Python has four types of literal collection:
  • List literals: -List contains items of different data types, modifiable -Separated by commas, bracketed
  • Dictionary: -Stores data in key-value pair -Enclosed by curly-braces and each pair separated by the commas.
  • Tuple:
    • Collection of different data-type. Immutable
    • Enclosed by the parentheses and each element is separated by the comma
  • Set:
    • Is the collection of the unordered dataset.
    • Enclosed by the {} and each element is separated by the comma.

Python Operators

• Used to perform a specific action on different values/variables.
• These values or variables are Operands
• Foundation for logioc constructed in a program
• Some operators perform several tasks
• Types:
  • 1.Arithmetic Operators
  • 2. Comparison Operators
  • 3.Assignment Operators
  • 4. Logical Operators
  • 5. Bitwise Operators
  • 6. Membership Operators
  • 7. Identity Operators
• Arithmetic
  • Two Opponents and perform basic math
  • Addition +
  • Subtraction -
  • Multiplication *
  • Division /
  • Modulus %
  • Exponent **
  • Floor Division //
• Comparison
  • Compare 2 values or variables
  • Returns Boolean
  • == Equals to
  • != Not Equals to
  • <= Less than or equals to #
  • >= Greater than or equals to#
  • > Greater than#
  • < Less than#
• Assignment operators
  • The right Expression's value assigned to operands
  • Assignment =
  • Addition with Assignment +=
  • Subtraction with Assignment -=
  • Multiplication Assignment *
  • Division with Assignment /=
  • Modulus with Assignment %=
  • Exponent with Assignment **=
  • Float Division with Assignment //=
• Bitwise Operators -Process two operands values bit by bit
  • Bitwise And & (A & b)
  • Bitwise OR | (Bitwise OR)
  • Bitwise XOR ^ (Bitwise XOR)
  • Bitwise Not ~ (Bitwise Not)
  • Bitwise Left Shift << (Bitwise Left Shift)
  • Bitwise Right Shft >> (Bitwise Right Shft)
• Logical Operators
  • Assessment of expressions and making decisions
  • The logical AND, the first one is 0, it does not depend upon the second one
  • The logical OR, the first one is 1, it does not depend on the second one
  • And Logical AND
  • Or Logical OR
  • Not Logical NOT
• Membership -Verify the membership of a value
  • Is result to true if the variable/code is in tuple, dictionary, list
  • "In" if Value in the sequence true
  • "Not in" if value is not present in second true
• Identity
  • Used to check of 2 values locate in parts of memory 2 variables are equal no imply identical.
  • "Is" both sides references point to = true
  • "Is not" The references do not point at the same object, determined to be true

Operator Precedence

• Order in Operators get examined crucial to understanding precedence
• Tables are ranked with highest priority listed first

Input and Output Statements

• Input Statements: takes user to input as a string
• Output Statements: Used to display the output to the console.
• Combining Input and Output

Control Statements

• Control flow/execution of Python programs.
• The if statement tests a certain condition and runs executes block of statements known the IF code block, only if the condition holds.
• With the if-else statement, it gets combined with an ELSE code block that is run if the condition is false
• The elif statement makes it possible to check a string of conditions and execute statements in an efficient way when the condition is true.

Looping Statements

• Used to execute a block of code multple timses until a condition is met.
  • For loop: used for iterations of a sequence
  • Wile loop: condition is True it runs
• loop control statements (break, continue, pass)

For Loop

• Number of iterations known or iterating (list,tuple,string,etc.)

While loop

• Loop executes as long as true

Loop control statements

• Break exit loop immdiately
• Continue Skip Current Iteration
• Pass Placeholder Statement

4 Else with loops

• Else block only run during the loop completion without Break

Defining functions

• A function Is reusable and performs task within code def. Is defined using def keywords, followed function nan parentheses

Syntax:

• def function (parameters)
  • Return values

Example: function show

• Def print hello welcome to python!
  • Calling funct: show!
  • Result Print hello welcome to python!

Funtions with parametrs, Dynamic use

• Def show(name):, Pring(hello,(name)!)
  • calling Funcions show Call show ( pramod!) show( amit.)

Result

• Printhello Welcome!
• Show name guest is name shows, default, call parmod. Function can return value def adds and returns value
• Call def adds
• Prints("some",result )

result print 8

function multiple

• def( multiply a,b.x a * b* b: C: multiply def number of functions

function with multiple parameters pass argument function return def multiply

• return

Arguments multiple key word pairs

Used dictionary Key key and pairs def

• argument ( Multiple positional arguments, used number arguments)

lamdba Anonymous Functions

A function is a one liner function without a name

• 9 nextest function within functions functions can defined inner - outer

10 recursive Function

Function CAlls itself