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🚀Welcome to the Python Learning Guide!
This repository is yourstep-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 – UseTrue andFalse, 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 toObject-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.

• 🧩 Useproperty() to create properties
• 🎀 Use@property decorator
• 📥 Getter, setter, and deleter patterns
• 📝 Read-only properties
• 🧠 Best practices for encapsulation

👨‍👦 Learn inheritance and extend functionality.

• 🧬 Single inheritance –class Child(Parent)
• 🔁 Override methods
• 🚶 Usesuper() to delegate to parent
• 🧱 Use__slots__ for memory efficiency
• 🧻 Abstract base classes withabc.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 withenum.Enum
• 🧷 Use@unique to prevent duplicate values
• 🧮 Auto-generate values withauto()
• 📦 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 usingtype()
• 🧩 Define custom metaclasses
• 🧱 Inject behavior via metaclass
• 🧠 Usedataclass to 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

⏱️Build high-performance & responsive Python applications using concurrency techniques.
🧠 Learn about multithreading, multiprocessing, and asynchronous programming to improve application performance and responsiveness.

• Build high-performance & responsive Python applications.
• Develop multithreaded programs usingthreading.
• Run parallel tasks usingmultiprocessing.
• Understand single-threaded concurrency viaasyncio.

🧵Use threads for I/O-bound tasks.

• 🧠Processes vs Threads – Understand differences and when to use each.
• 🧵Threading module – Usethreading for concurrent thread execution.
• 🧱Extending Thread class – Customize behavior by subclassingThread.
• 💬Returning values from threads – Capture results safely.
• 📈Multithreading Example – Scrape stock prices concurrently.
• 🌙Daemon threads – Background threads that don’t block program exit.
• 🧰Thread Pools – Efficiently manage threads usingThreadPoolExecutor.

🔐Avoid race conditions and ensure safe access.

• 🧱Lock – Prevent simultaneous access to shared data.
• 🚦Event – Communicate between threads (e.g., wait/signal patterns).
• ⏹️How to stop a thread – Safely terminate child threads.
• 🚧Semaphore – Control number of concurrent threads accessing a resource.

📦Exchange data safely across threads.

• 🧷Thread-safe Queue – Usequeue.Queue for safe inter-thread communication.

🔌Run CPU-bound tasks in parallel using separate processes.

• 🧲Multiprocessing module – Usemultiprocessing.Process to spawn new processes.
• 🧰Process Pools – Manage processes efficiently usingPool orProcessPoolExecutor.

⚡Write asynchronous, non-blocking code using coroutines.

• 🧠Understanding Event Loop – Core of async programming; manages coroutine execution.
• 🧶async/await – Define and await coroutines without blocking.
• 🧩Creating Tasks – Schedule coroutines for execution.
• 🚫Canceling Tasks – Cancel running tasks using.cancel().
• ⏳Timeout-based Cancellation – Useasyncio.wait_for() to cancel after timeout.
• 🕐asyncio.wait() – Run multiple awaitables concurrently.
• 🎯Future – UnderstandFuture objects for eventual results.
• 🧱Running multiple tasks concurrently with gather() – Run tasks concurrently usingasyncio.gather().