LEARN COMPLETE PYTHON IN 24 HOURS
🟦 Advanced Python – Table of Contents
🔹 1. Python Intermediate Recap & Advanced Setup
1.1 Quick Review: Lists, Dicts, Functions, Modules
1.2 Virtual Environments & pip (venv, requirements.txt)
1.3 Code Formatting & Linting (Black, Flake8, isort)
1.4 Type Hints & Static Typing (typing module, mypy)
1.5 Debugging Techniques (pdb, logging, VS Code debugger)
🔹 2. Object-Oriented Programming (OOP) in Depth
2.1 Classes & Objects – Advanced Features
2.2 init, self, str, repr
2.3 Inheritance & super()
2.4 Method Overriding & Polymorphism
2.5 Encapsulation: Private & Protected Members
2.6 Properties (@property, @setter, @deleter)
2.7 Class Methods, Static Methods, @classmethod, @staticmethod
2.8 Multiple Inheritance & Method Resolution Order (MRO)
2.9 Abstract Base Classes (abc module)
2.10 Composition vs Inheritance
🔹 3. Advanced Data Structures & Collections
3.1 collections module: namedtuple, deque, Counter, defaultdict, OrderedDict
3.2 dataclasses (Python 3.7+)
3.3 Heapq – Priority Queues
3.4 Bisect – Binary Search & Insertion
🔹 4. Functional Programming Tools
4.1 Lambda Functions
4.2 map(), filter(), reduce()
4.3 List, Dict & Set Comprehensions
4.4 Generator Expressions
4.5 Generators & yield
4.6 Generator Functions
4.7 yield from
4.8 itertools module
🔹 5. Decorators & Higher-Order Functions
5.1 What are Decorators?
5.2 Writing Simple Decorators
5.3 Decorators with Arguments
5.4 @property, @classmethod, @staticmethod
5.5 @lru_cache (functools)
5.6 Chaining Decorators
5.7 Class Decorators
🔹 6. Context Managers & with Statement
6.1 Understanding Context Managers
6.2 Custom Context Managers (enter, exit)
6.3 @contextmanager
6.4 Common Use Cases
🔹 7. Exception Handling – Advanced
7.1 try-except-else-finally
7.2 Raising Custom Exceptions
7.3 Custom Exception Classes
7.4 Exception Chaining
7.5 Logging vs print()
🔹 8. File Handling & Data Formats
8.1 Reading/Writing Files
8.2 with Statement Best Practices
8.3 CSV – csv module
8.4 JSON – json module
8.5 Pickle
8.6 Large Files Handling
🔹 9. Concurrency & Parallelism
9.1 Threading vs Multiprocessing vs Asyncio
9.2 threading module
9.3 multiprocessing
9.4 asyncio – Async/Await
9.5 aiohttp
9.6 GIL & Use Cases
🔹 10. Mtaclasses & Advanced OOP
10.1 What are Metaclasses?
10.2 type() as Metaclass
10.3 Custom Metaclasses
10.4 new vs init
10.5 Use Cases
🔹 11. Design Patterns in Python
11.1 Singleton, Factory, Abstract Factory
11.2 Observer, Strategy, Decorator Pattern
11.3 Pythonic Alternatives
🔹 12. Performance Optimization
12.1 Time & Space Complexity
12.2 Profiling (cProfile, timeit)
12.3 Efficient Data Structures
12.4 Caching & Memoization
12.5 NumPy & Pandas
🔹 13. Testing in Python
13.1 unittest vs pytest
13.2 Unit Testing
13.3 Mocking
13.4 TDD Basics
🔹 14. Popular Libraries & Tools
14.1 requests
14.2 BeautifulSoup & Scrapy
14.3 pandas & NumPy
14.4 Flask / FastAPI
14.5 SQLAlchemy / Django ORM
🔹 15. Mini Advanced Projects & Best Practices
15.1 CLI Tool (argparse / click)
15.2 Async Web Scraper
15.3 Decorator-based Logger
15.4 Thread-Safe Counter
15.5 Data Pipeline
15.6 PEP 8, PEP 257, Git Workflow
7. Exception Handling – Advanced
7.1 try-except-else-finally Deep Dive
The full structure of exception handling in Python:
Python
try: # Code that might raise an exception risky_operation() except ExceptionType1 as e1: # Handle specific exception type 1 print(f"Type1 error: {e1}") except (Type2, Type3) as e23: # Handle multiple types print(f"Type2/3 error: {e23}") except Exception as e: # Catch-all (broad, use carefully) print(f"Unexpected error: {e}") # Optionally re-raise: raise else: # Runs only if NO exception occurred print("Success! No exceptions raised.") finally: # Always runs (cleanup), even on return/break/raise print("Cleanup: closing files, connections, etc.")
Key points to remember:
else → only executes if no exception was raised in try (great for code that should run only on success)
finally → always executes (cleanup, close files/connections, release locks)
Order matters: except blocks are checked from top to bottom → specific → general
Avoid bare except: (catches everything, including KeyboardInterrupt, SystemExit)
Real example – File processing with proper cleanup
Python
def process_file(filename): try: f = open(filename, "r") data = f.read() number = int(data.strip()) # might raise ValueError except FileNotFoundError: print("File not found!") return None except ValueError as ve: print(f"Invalid number format: {ve}") return None else: print("File read successfully!") return number * 2 finally: if 'f' in locals(): f.close() print("File closed in finally.") print(process_file("numbers.txt"))
7.2 Raising Custom Exceptions
Use raise to signal errors explicitly.
Basic raise
Python
if age < 0: raise ValueError("Age cannot be negative!")
Raise with custom message
Python
def divide(a, b): if b == 0: raise ZeroDivisionError("Cannot divide by zero – check your input!") return a / b
Re-raise (preserve original traceback)
Python
try: risky_code() except Exception as e: print("Logging error...") raise # re-raises the original exception with full traceback
Chaining with raise ... from (see 7.4)
7.3 Creating Custom Exception Classes
Custom exceptions make error handling clearer and more semantic.
Basic custom exception
Python
class InvalidAgeError(ValueError): """Raised when age is invalid (negative or unrealistic).""" pass def set_age(age): if age < 0: raise InvalidAgeError("Age cannot be negative") if age > 150: raise InvalidAgeError("Age seems unrealistic") print(f"Age set to {age}")
Advanced custom exception with attributes
Python
class PaymentFailedError(Exception): def init(self, amount, reason, transaction_id=None): self.amount = amount self.reason = reason self.transaction_id = transaction_id super().__init__(f"Payment of ₹{amount} failed: {reason}") def str(self): msg = f"Payment failed: {self.reason} (₹{self.amount})" if self.transaction_id: msg += f" - Transaction ID: {self.transaction_id}" return msg try: # Simulate payment gateway failure raise PaymentFailedError(5000, "Card declined", "TXN987654") except PaymentFailedError as e: print(e) # Payment failed: Card declined (₹5000) - Transaction ID: TXN987654 print(f"Amount lost: ₹{e.amount}")
Best practice:
Inherit from built-in exceptions (ValueError, TypeError, RuntimeError, etc.)
Add custom attributes for debugging/info
Write docstrings for clarity
7.4 Exception Chaining (__cause__, context)
Python automatically tracks exception chains:
context → the exception that was being handled when this one was raised
cause → explicit cause (set with raise ... from)
Automatic chaining (implicit)
Python
try: 1 / 0 except ZeroDivisionError: raise ValueError("Division failed") # ValueError.__context__ = ZeroDivisionError
Explicit chaining with from
Python
def load_config(): try: with open("config.json") as f: return json.load(f) except FileNotFoundError as fnf: raise RuntimeError("Configuration loading failed") from fnf try: load_config() except RuntimeError as re: print(re) # Configuration loading failed print(re.__cause__) # shows FileNotFoundError
Use from None to suppress context
Python
raise ValueError("Bad value") from None # hides previous context
When to use:
from → when new exception is a direct consequence (cleaner traceback)
Automatic context → when handling one error leads to another
7.5 Logging vs print() for Production
print() → good for debugging, bad for production
logging → standard for real applications
Basic logging setup (recommended)
Python
import logging import sys # Configure once at app startup logging.basicConfig( level=logging.DEBUG, # DEBUG / INFO / WARNING / ERROR / CRITICAL format="%(asctime)s [%(levelname)s] %(name)s: %(message)s", datefmt="%Y-%m-%d %H:%M:%S", handlers=[ logging.FileHandler("app.log"), logging.StreamHandler(sys.stdout) ] ) logger = logging.getLogger(__name__) # name = current module name def process_payment(amount): try: if amount <= 0: raise ValueError("Amount must be positive") logger.info(f"Processing payment of ₹{amount}") # simulate success logger.debug("Payment gateway response: success") return True except ValueError as ve: logger.error("Payment validation failed", exc_info=True) # includes traceback return False except Exception as e: logger.critical("Unexpected error in payment", exc_info=True) raise
Levels quick reference:
debug → detailed info (disabled in production)
info → normal operation messages
warning → something unexpected but not fatal
error → handled error (operation failed)
critical → severe error (app may crash)
Advantages over print():
Levels (turn off debug in production)
File + console output
Timestamps, module names, tracebacks
Configurable via logging.config (dictConfig, fileConfig)
Thread-safe
Pro tip: Use logger.exception("Message") instead of logger.error(..., exc_info=True) — shorter and includes traceback automatically.
Mini Project – Robust File Processor with Logging & Custom Exception
Python
import logging from contextlib import contextmanager logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s") class FileProcessingError(Exception): pass @contextmanager def safe_file_read(filename): try: with open(filename, "r") as f: yield f.read() except FileNotFoundError: raise FileProcessingError(f"File {filename} not found") except PermissionError: raise FileProcessingError(f"No permission to read {filename}") except Exception as e: raise FileProcessingError(f"Unexpected error reading {filename}: {e}") try: with safe_file_read("config.txt") as content: logging.info("File read successfully") print(content) except FileProcessingError as fpe: logging.error(str(fpe))
This completes the full Exception Handling – Advanced section — now you can build robust, production-ready Python applications that handle errors gracefully!
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