Most Python developers stay stuck at average level… Not because they don’t work hard… But because they don’t know these small but powerful tricks. Today I’m sharing a FREE PDF that contains 👉 100 Python Tips & Tricks (Basic → Intermediate) This is the kind of stuff that: • Makes your code cleaner • Saves hours of time • Makes you stand out from 90% developers And the best part? These are practical shortcuts, not theory. 📌 Example things you’ll learn: Flatten nested lists in one line Merge dictionaries like a pro Use Python to automate real tasks Write cleaner & optimized code (Exactly the kind of knowledge most tutorials skip…) 💡 But here’s the truth: Knowing tricks ≠ Building real AI systems If you really want to move from Python → AI Engineer, you need to understand: 👉 RAG (Retrieval Augmented Generation) 👉 LangChain & LangGraph 👉 Real-world AI applications 🎯 That’s exactly why I created this: 🔥 LangGraph Mastery Course (Project-Based) 👉 Learn how to build real AI systems step-by-step 🔗 https://lnkd.in/dTz9H-8E ⚡ My suggestion: Go through this PDF Apply 5–10 tricks today Then move to building real-world AI projects If you found this helpful, comment “PYTHON” I’ll share more such resources 🚀 Pdf credit goes to respective owner. Follow Pratham Uday Chandratre for more!
Great share
Mudit Gupta
1mo
Python
122 pages of Python tips is a goldmine. The "most developers stay at average level" point is very real — Python has such a shallow learning curve that many devs get comfortable fast and stop growing. The jump from average to advanced is usually when you start properly using list comprehensions, generators (yield vs return memory implications), context managers, decorators for cross-cutting concerns, and dataclasses/Pydantic for structured data. A few tips that most beginners miss: using __slots__ in classes to significantly reduce memory overhead when creating many instances, understanding the GIL and why CPU-bound tasks need multiprocessing not multithreading, and the difference between deepcopy and copy. For backend development specifically, async/await patterns in Python with asyncio are now essential since FastAPI and modern frameworks expect them. One of the best intermediate challenges is implementing your own decorator that works both with and without arguments — it forces you to understand closures deeply. Which Python concept do you see developers struggle with the most when moving from intermediate to advanced?
Python