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Source channel @githubtrending · Post #15250 · Oct 26
#python#agent#agentic_ai#llm#mlops#reinforcement_learning Agent Lightning is a tool that helps improve AI agents using reinforcement learning. It allows you to train your agents without making big changes to their code, which is very convenient. You can use it with many different frameworks like LangChain or OpenAI Agent SDK. It also supports various training methods, including reinforcement learning and automatic prompt optimization. This means you can make your agents better at their tasks without a lot of extra work. https://github.com/microsoft/agent-lightning
Search: #processes
@amazingeo · Post #647 · 02/25/2026, 08:31 PM
🌍 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 👉subscribe Amazing Geography 👉more Channels
@amazingeo · Post #39 · 08/13/2025, 12:12 AM
🌍 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 👉subscribe Amazing Geography🌍
@djangoproject · Post #430 · 09/02/2017, 03:23 AM
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
@djangoproject · Post #290 · 04/04/2017, 09:36 PM
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