#other
This collection of leaked GPT prompts offers a wide range of tools and ideas for interacting with AI models. It includes prompts for tasks like writing, coding, humor, and education, which can help users understand how GPT models work and improve their interactions with AI. By using these prompts, users can create more effective and personalized AI experiences, benefiting from the diverse contributions and insights shared by the community. This resource is valuable for both developers and users looking to enhance their AI interactions.
https://github.com/linexjlin/GPTs
🌍 Submarine hydrothermal vents on the ocean floor release superheated water and minerals, fueling unique ecosystems powered by chemical energy instead of sunlight. ✨
#processes⚡#ocean⚡#ecosystems⚡#geography⚡#nature⚡#earth
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🌍 Earth's crust is in constant motion due to convection currents—slow, swirling movement of hot rock deep below the surface. This drives plate movement, causing earthquakes and forming new land. ✨
#processes⚡#plate⚡#tectonics⚡#geology⚡#geography⚡#nature⚡#earth
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https://docs.python.org/3/library/subprocess.html
The #subprocess module allows you to spawn new #processes, connect to their input/output/error pipes, and obtain their return codes. This module intends to replace several older #modules and #functions.
#python
https://pymotw.com/3/asyncio/executors.html
Combining Coroutines with Threads and Processes
A lot of existing libraries are not ready to be used with #asyncio natively. They may block, or depend on concurrency features not available through the module. It is still possible to use those libraries in an application based on asyncio by using an #executor from #concurrent.futures to run the code either in a separate thread or a separate process.
#Threads
The #run_in_executor() method of the event loop takes an executor instance, a regular callable to invoke, and any arguments to be passed to the callable. It returns a Future that can be used to wait for the function to finish its work and return something. If no executor is passed in, a #ThreadPoolExecutor is created. This example explicitly creates an executor to limit the number of worker threads it will have available.
#Processes
A ProcessPoolExecutor works in much the same way, creating a set of worker #processes instead of threads. Using separate processes requires more system resources, but for computationally-intensive operations it can make sense to run a separate task on each CPU core.
#learn