#Global Variables Python

Stop using Global Variables to track your state. 🛑🐍 Most developers treat functions like disposable tools: you call them, they execute, and they die. But when you’re building long-running AI agents or data pipelines, you need to maintain State. Beginners use Global variables (the #1 cause of spaghetti code). 🍝 Seniors use Generators. ⚙️ 🧠 The “Instruction Pointer” Secret: In a normal function, the execution marker is destroyed on return. In a Generator, the pointer is frozen at the yield statement. When you call next(), you don’t restart the function—you re-activate the frozen pointer exactly where you left off. ✅ The Payoff: Near-zero memory footprint. No Global variables polluting your namespace. Totally modular, scalable logic. 🚀 Build Better Architecture: We’re rewriting the rules of Python for the AI era. Follow Corpnce for advanced AI engineering. #datascience #ai #pythonprogramming #coding

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Here are some smart and quick optimisations that must be tried before burning bucks 🙌 ➡️ Use Pydantic to define strict schema and pass in response_format parameter. ➡️ Give few examples as part of the prompt in the expected format. ➡️ Add hard constraints in the prompt for not generating explanation or reasoning. ➡️ Multi-step workflow : First generate content then make an extra call to convert to required format. ➡️ Implement Auto Fix: Another LLM verifies the format, and sends the feedback to original LLM to improve or accept the output as is. 🌟 Follow @tech.with.prakhar for more! Related tags: [AI, Artifical Intelligence, Tech reels, Viral reels, LLM, GenerativeAI, ChatGPT, AI Models, MachineLearning, Data science, Tech interviews, Data science interview, Learn AI, Software Engineers] #aicontent #datasciencejobs #machinelearningtutorial #datascience #yfp