python

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create a a CAN simulation so when i run it i undertsand how CAN works crteate it in python

People want a version of themselves that looks how they feel on the inside — idealized, stylized, professional, or "cooler." Profile pictures are identity signals on every platform they use. Paying for a better signal is rational.

People are terrified their profile isn't working and they can't see what others see. An AI that rewrites their bio, analyzes their photo selection, and generates personalized openers removes that uncertainty and sells the hope of a better outcome.

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Expert-level Python code review prompt with 450+ checklist items covering type hints & runtime validation, None/mutable default traps, exception handling patterns, asyncio/threading/multiprocessing concurrency, GIL-aware performance, memory management, security vulnerabilities (eval/pickle/yaml injection, SQL injection via f-strings), dependency auditing, framework-specific issues (Django/Flask/FastAPI), Python version compatibility (3.9→3.12+ migration), and testing gaps.

People want to practice before risking real money. The simulation sells the hope of being competent enough to invest eventually — and the journal analysis layer sells the hope of becoming the kind of person whose judgment improves over time. If simulation doesn't reflect real market mechanics, it feels like a toy and loses credibility. Slippage, transaction costs, and realistic price impact must be simulated.

Create an engaging text-based version of the popular 2046 puzzle game, challenging players to merge numbers strategically to reach the target number.

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Note-taking is commoditized. Meaning-making is not. A tool that connects notes into a personal narrative — that shows you the throughline of your thinking across months and years — sells identity and continuity, not storage. If search and sync don't work flawlessly, users abandon immediately regardless of the narrative features. Reliability is table stakes; everything else is the differentiator.

This prompt guides a senior software engineer in implementing a new feature or project in a specified programming language, ensuring consistent styling, best practices, proper error handling, test coverage, and documentation updates. It also includes generating a recommended commit message summarizing the changes. Would really appreciate help making it better 😁

Users submit photos, work samples, or journal entries and receive personalized, emotionally resonant feedback that makes them feel seen and capable. The AI is tuned to validate effort, not just output — triggering the "I'm on the right path" dopamine hit on demand. Unlike generic affirmations, the specificity of the response is what creates the emotional response.