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Source channel @githubtrending · Post #14867 · Jun 26
#python#mootdx#pytdx#tdx#tdxpy mootdx is a free, open-source Python tool that helps you easily read and use stock market data from Tongdaxin on Windows, MacOS, and Linux. It supports Python 3.8+ and can read offline daily, minute, and timeline stock data, as well as online real-time market quotes and financial files. You can install it simply with pip and use it to get detailed stock info for analysis or trading. This saves you time and effort by providing a ready-made, flexible way to access and work with Chinese stock market data in Python. It’s great for learning, research, and personal projects but not for commercial use[1][4]. https://github.com/mootdx/mootdx
Search: #asynchronously
@djangoproject · Post #585 · 03/23/2018, 02:43 AM
https://www.fullstackpython.com/celery.html #Celery is a task #queue implementation for Python web applications used to #asynchronously execute work outside the HTTP request-response cycle.
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@djangoproject · Post #262 · 02/16/2017, 07:24 AM
http://masnun.com/2015/11/20/python-asyncio-future-task-and-the-event-loop.html On any platform, when we want to do something #asynchronously, it usually involves an #event loop. An event loop is a loop that can register #tasks to be executed, execute them, delay or even cancel them and handle different events related to these operations. Generally, we #schedule multiple async functions to the event loop. The loop runs one function, while that function waits for #IO, it pauses it and runs another. When the first function completes IO, it is resumed. Thus two or more functions can #co_operatively run together. This the main goal of an event loop.