🚀 Welcome to the Python Learning Guide!
This repository is your step-by-step roadmap to mastering Python — from the basics to advanced topics. Whether you're a beginner or looking to sharpen your skills, this guide has got you covered.
📘 Each section builds on the previous one, so you can follow along in order or jump straight into the topic you need.
🔹 Learn the basic structure and syntax of Python code.
- 🔤 Variables – Understand how variables work and how to name them meaningfully.
- 📜 Strings – Work with text data and perform common string operations.
- 🧮 Numbers – Explore integers and floating-point numbers.
- 🚦 Booleans – Use
TrueandFalse, and understand truthy and falsy values. - 🛑 Constants – Learn how to define constants (by convention).
- 💬 Comments – Add notes and explanations inside your code.
- 🔁 Type conversion – Convert between types like strings, integers, and floats.
🛠️ Learn to manipulate data using operators.
- ➕ Arithmetic operators – Perform math operations (
+,-,*,/, etc.) - ✍️ Assignment operators – Assign and update variable values efficiently.
- 🔍 Comparison operators – Compare two values (
==,!=,<,>, etc.) - 🧠 Logical operators – Combine conditions (
and,or,not)
🧠 Make decisions and control how your code runs.
- ❓ if…else statement – Run code based on conditions.
- 🎯 Ternary operator – Write compact conditionals.
- 🔁 for loop with range() – Loop for a set number of times.
- ⏳ while loop – Repeat while a condition is true.
- 🔚 break – Exit a loop early.
- ⏭️ continue – Skip current iteration and continue looping.
- 🪟 pass – Placeholder when no action is needed.
🧩 Write reusable blocks of code.
- 📌 Python functions – Define and call functions.
- 📥 Default parameters – Set default values for arguments.
- 📝 Keyword arguments – Make function calls more readable.
- 🔁 Recursive functions – Call functions within themselves.
- 🧊 Lambda Expressions – Create small anonymous functions.
- 📄 Docstrings – Document your functions clearly.
📂 Work with ordered collections of data.
- 📥 List – Store and manipulate multiple items.
- 🪐 Tuple – Immutable lists that stay constant.
- 🧹 Sort a list in place – Modify a list directly.
- 🧼 Sorted function – Get a new sorted list.
- 🧩 Slice a List – Extract parts of a list.
- 📦 Unpack a list – Assign elements to variables.
- 🔁 Iterate over a List – Loop through items.
- 🔍 Find index of an element – Locate where something is.
- 🔄 Map, Filter, Reduce – Transform and filter list elements.
- 💡 List comprehensions – Create lists quickly and cleanly.
🗄️ Use key-value pairs to organize data.
- 📁 Dictionary – Store data as keys and values.
- 🧰 Dictionary comprehension – Build dictionaries dynamically.
🧮 Work with unique collections of items.
- 🔒 Set – Store unique values.
- 🧱 Set comprehension – Create sets concisely.
- ∪ Union, Intersection, Difference – Combine and compare sets.
- ⊆ Subset, Superset, Disjoint sets – Check relationships between sets.
🛡️ Handle errors gracefully and keep your programs running.
- 🛑 try…except – Catch and handle exceptions.
- 🧹 try…except…finally – Always run cleanup code.
- ✅ try…except…else – Run code only if no error occurs.
🔁 Advanced looping techniques.
- 🔁 for…else – Run code after a loop finishes normally.
- ⏳ while…else – Run code after a while loop ends.
- 🔁 do…while emulation – Simulate do…while behavior in Python.
🔧 Master advanced function features.
- 📦 Unpacking tuples – Assign tuple values to variables.
- 📥 *args Parameters – Accept any number of positional arguments.
- 📝 *kwargs Parameters – Accept any number of keyword arguments.
- 🔧 Partial functions – Fix some arguments for reuse.
- 📏 Type hints – Improve readability and enable static type checking.
🧱 Organize and reuse your code effectively.
- 📄 Modules – Split code into separate files.
- 🔍 Module search path – Understand how Python finds modules.
- 🧠 name variable – Control script vs module behavior.
- 📁 Packages – Organize modules into folders.
- 🔒 Private functions – Hide internal implementation.
📂 Read from and write to files.
- 📖 Read from a text file
- ✍️ Write to a text file
- 📄 Create a new text file
- 🔍 Check if a file exists
- 📊 Read and write CSV files
- 🗑️ Rename and delete files
📁 Interact with your file system.
- 📁 Working with directories
- 🔍 List files in a directory
🔤 Advanced string manipulation.
- 🎞️ F-strings – Embed variables directly in strings.
- 🧊 Raw strings – Avoid escape character issues.
- 🧱 Backslash usage – Handle special characters.
📦 Install and manage external libraries.
- 📦 PyPI & pip – Install packages from the Python Package Index.
- 🧺 Virtual Environments – Isolate project dependencies.
- 💻 Install pipenv on Windows – Manage virtual environments easily.
This README provides a structured and beginner-friendly guide to Object-Oriented Programming (OOP) in Python. It's based on your uploaded content and includes:
- 🔹 Classes & Objects
- 🔹 Instance vs Class Variables
- 🔹
__init__()method - 🔹 Private attributes
- 🔹 Static methods
- 🔹 Inheritance
- 🔹 Special methods (
__str__,__repr__, etc.) - 🔹 Property management
- 🔹 Exceptions in OOP
Each concept is explained with code examples and best practices for writing clean, maintainable object-oriented code.
🧑💻 Build your first class and understand object-oriented programming.
- 🧱 Class definition and instance creation
- 📦 Instance vs class variables
- 🔐 Private attributes and name mangling
- 🛠️ Constructor
__init__() - 🧩 Instance methods and static methods
- 🧾 Method overloading via default and keyword arguments
- 💡 Best practices for readable OOP
🧠 Customize class behavior using special methods.
- 🖨️
__str__– user-friendly output - 🧾
__repr__– unambiguous representation - ✅
__eq__– define equality logic - 🔢
__hash__– make objects hashable - 🚫
__bool__– define truthiness - 🗑️
__del__– handle object destruction
🗝️ Control access to internal attributes.
- 🧩 Use
property()to create properties - 🎀 Use
@propertydecorator - 📥 Getter, setter, and deleter patterns
- 📝 Read-only properties
- 🧠 Best practices for encapsulation
👨👦 Learn inheritance and extend functionality.
- 🧬 Single inheritance –
class Child(Parent) - 🔁 Override methods
- 🚶 Use
super()to delegate to parent - 🧱 Use
__slots__for memory efficiency - 🧻 Abstract base classes with
abc.ABC
🧬 Understand method resolution order and mixin classes.
- 🧠 Implement multiple inheritance
- 🧭 MRO – Python’s method lookup strategy
- 🧩 Mixin classes for cross-cutting concerns
- 🚫 Avoid diamond problem with proper design
- 🧲 Combine behaviors without deep hierarchies
🔢 Represent fixed sets of constants.
- 🧱 Define enums with
enum.Enum - 🧷 Use
@uniqueto prevent duplicate values - 🧮 Auto-generate values with
auto() - 📦 Extend custom enum classes
- 🧠 Use enums instead of hardcoded strings
🛠️ Apply SOLID principles for maintainable designs.
- 📦 Single Responsibility Principle
- 🧩 Open/Closed Principle
- 🔄 Liskov Substitution Principle
- 📁 Interface Segregation Principle
- 🧠 Dependency Inversion Principle
🔗 Reuse attribute access logic with descriptors.
- 🧠 Descriptor protocol –
__get__,__set__,__delete__ - 📦 Data vs non-data descriptors
- 🧩 Reusable validation and computed properties
- 🧱 Descriptor examples: type checking, lazy loading
🔮 Modify or generate code at runtime.
- 🧬 Use
__new__to control object creation - 📦 Dynamically create classes using
type() - 🧩 Define custom metaclasses
- 🧱 Inject behavior via metaclass
- 🧠 Use
dataclassto auto-generate boilerplate
⚙️ Handle errors within object-oriented contexts.
- 🧠 Raise exceptions in methods
- 🧩 Create custom exception classes
- 🛡️ Catch and propagate exceptions
- 🧹 Graceful error recovery in OOP
- 📦 Exception best practices in real applications