Python Notes

Introduction to Python

Python Overview

Python is a high-level, interpreted, general-purpose programming language that emphasizes code readability and simplicity. It was created by Guido van Rossum and first released in 1991. The name "Python" comes from the British comedy series "Monty Python's Flying Circus."

Key Features

• High-Level Language: Abstracts away low-level details
• Interpreted: Code executed line by line
• Dynamically Typed: No explicit type declarations
• Garbage Collected: Automatic memory management
• Multi-Paradigm: Supports procedural, OOP, and functional programming
• Extensive Standard Library: Rich collection of modules
• Cross-Platform: Runs on Windows, macOS, Linux
• Indentation-Based Syntax: Uses whitespace for code blocks

Why Learn Python?

• Beginner-friendly with gentle learning curve
• Versatile for web development, data science, AI, automation
• High demand in job market
• Large supportive community
• Rapid development capabilities
• Extensive libraries and frameworks

Installation and Setup

• Download from python.org
• Run installer, check "Add Python to PATH"
• Verify with python --version
• Use IDEs like VS Code, PyCharm, or IDLE
• Install packages with pip

Python Philosophy

• Beautiful is better than ugly
• Simple is better than complex
• Readability counts
• Explicit is better than implicit
• There should be one obvious way to do it

Python Basics

Variables and Data Types

Variables are created by assignment (=). Python has dynamic typing.

• int: Whole numbers (42, -10)
• float: Decimal numbers (3.14, -2.5)
• str: Text strings ("hello", 'world')
• bool: Boolean values (True, False)

Type conversion: int(), float(), str(), bool()

Operators

Arithmetic: +, -, *, /, //, %, **

Comparison: ==, !=, <, >, <=, >=

Logical: and, or, not

Assignment: =, +=, -=, *=, /=, //=, %=, **=

Control Structures

Conditional: if, elif, else with indentation

Loops: for (iterates over sequences), while (condition-based)

Loop Control: break (exit), continue (skip iteration)

range(): Generates number sequences

Functions

• Defined with def keyword
• Can take parameters and return values
• Parameters vs Arguments distinction
• Default parameters and keyword arguments
• Variable scope: local vs global
• return statement sends values back

Variable Naming Rules

• Start with letter or underscore
• Contain letters, digits, underscores
• Case-sensitive
• No reserved keywords
• Use descriptive names

Python Intermediate

Lists

Mutable ordered sequences. Created with [].

• Access: list[index], negative indexing
• Slicing: list[start:end:step]
• Methods: append(), insert(), remove(), pop(), sort(), reverse()
• Operations: +, *, in, len()
• List comprehensions: [expr for item in iterable if condition]

Tuples

Immutable ordered sequences. Created with ().

• Cannot modify after creation
• Faster than lists for read-only
• Can be used as dictionary keys
• Methods: count(), index()
• Unpacking: x, y = tuple

Dictionaries

Mutable key-value pairs. Created with {}.

• Keys must be immutable (strings, numbers, tuples)
• Access: dict[key] or dict.get(key, default)
• Methods: keys(), values(), items(), pop(), update()
• Dict comprehensions: {key_expr: value_expr for item in iterable}
• Fast lookups: O(1) average time complexity

File Handling

Use open() function with modes: 'r', 'w', 'a', 'x', 'b', 't', '+'

• Methods: read(), readline(), readlines(), write(), writelines()
• File pointer: seek(), tell()
• Best practice: with statement for automatic closing
• Error handling: try-except for FileNotFoundError, IOError
• Encoding: specify encoding='utf-8' for text files

Modules and Packages

• Import: import module, from module import function, import as alias
• Standard library: math, random, datetime, os, sys, json, re
• Custom modules: save as .py files
• Packages: directories with __init__.py
• if __name__ == "__main__": for executable modules

Python Advanced

Object-Oriented Programming

• Class: Blueprint for objects
• Object: Instance of a class
• Constructor: __init__ method
• self: Reference to current instance
• Inheritance: Child classes inherit from parent
• Polymorphism: Same method, different behavior
• Encapsulation: Hide internal details
• Special Methods: __str__, __repr__, __len__, __add__, etc.

Exception Handling

• try-except-else-finally blocks
• Built-in exceptions: ValueError, TypeError, KeyError, IndexError, ZeroDivisionError, FileNotFoundError
• Custom exceptions: inherit from Exception
• Raising exceptions: raise Exception(message)
• Exception hierarchy: BaseException → Exception → specific exceptions

Algorithms and Complexity

• Sorting: Bubble (O(n²)), Selection (O(n²)), Insertion (O(n²)), Merge (O(n log n)), Quick (O(n log n))
• Searching: Linear (O(n)), Binary (O(log n))
• Big O Notation: Measures algorithm efficiency
• Data Structures: Stack, Queue, Linked List, Tree, Graph, Hash Table

Data Analysis Libraries

NumPy:

• N-dimensional arrays (ndarray)
• Vectorized operations
• Broadcasting
• Mathematical functions
• Linear algebra operations
• Random number generation

Pandas:

• Series (1D) and DataFrame (2D)
• Data manipulation and cleaning
• Grouping and aggregation
• Merging and joining
• Time series handling
• Import/export: CSV, Excel, SQL

Matplotlib:

• Line plots, bar charts, histograms
• Scatter plots, pie charts
• Subplots and multiple figures
• Styling and customization
• 3D plotting capabilities