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Source channel @githubtrending · Post #15121 · Sep 5

#jupyter_notebook#chatgpt#finance#fingpt#fintech#large_language_models#machine_learning#nlp#prompt_engineering#pytorch#reinforcement_learning#robo_advisor#sentiment_analysis#technical_analysis FinGPT is an open-source AI tool designed specifically for finance, helping you analyze financial news, predict stock prices, and get personalized investment advice quickly and affordably. Unlike costly models like BloombergGPT, FinGPT can be updated frequently with new data at a low cost, making it more accessible and timely. It uses advanced techniques like reinforcement learning from human feedback to tailor advice to your preferences, such as risk tolerance. You can use FinGPT for tasks like sentiment analysis, robo-advising, fraud detection, and portfolio optimization, helping you make smarter financial decisions with up-to-date insights. https://github.com/AI4Finance-Foundation/FinGPT

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djangoproject

@djangoproject · Post #95 · 07/11/2016, 12:14 PM

https://docs.python.org/3/library/asyncio-dev.html#asyncio-multithreading 18.5.9.3. #Concurrency and #multithreading An event loop runs in a thread and executes all callbacks and tasks in the same thread. While a task is running in the event loop, no other task is running in the same thread. But when the task uses yield from, the task is suspended and the event loop executes the next task. To schedule a callback from a different thread, the BaseEventLoop.call_soon_threadsafe() method should be used. Example: loop.call_soon_threadsafe(callback, *args) Most asyncio objects are not thread safe. You should only worry if you access objects outside the event loop. For example, to cancel a future, don’t call directly its Future.cancel() method, but: loop.call_soon_threadsafe(fut.cancel) To handle signals and to execute subprocesses, the event loop must be run in the main thread. To schedule a coroutine object from a different thread, the run_coroutine_threadsafe() function should be used. It returns a concurrent.futures.Future to access the result: future = asyncio.run_coroutine_threadsafe(coro_func(), loop) result = future.result(timeout) # Wait for the result with a timeout The BaseEventLoop.run_in_executor() method can be used with a thread pool executor to execute a callback in different thread to not block the thread of the event loop. See also The Synchronization primitives section describes ways to synchronize tasks. The Subprocess and threads section lists asyncio limitations to run subprocesses from different threads.

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@githubtrending · Post #14740 · 05/23/2025, 12:30 PM

#python#async#asyncio#cross_platform#downloader#gui#multithreading#pyqt#pyside6#python#qt#software#streaming Ghost Downloader 3 is a fast, AI-powered download manager that works on Windows, Linux, and macOS. It speeds up downloads by splitting files into many parts and using multiple threads, dynamically adjusting to use your full bandwidth. It supports resuming downloads, proxy settings, SSL security, and clipboard monitoring for easy link capture. The interface is modern and user-friendly. This tool helps you download files more quickly and efficiently, with options to control speed and use proxies, making it ideal if you want faster, smarter, and more reliable downloads on your computer[1]. https://github.com/XiaoYouChR/Ghost-Downloader-3