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Source channel @githubtrending · Post #15242 · Oct 23

#python#ant_colony_algorithm#artificial_intelligence#fish_swarms#genetic_algorithm#heuristic_algorithms#immune#immune_algorithm#optimization#particle_swarm_optimization#pso#simulated_annealing#travelling_salesman_problem#tsp You can use scikit-opt, a Python library offering many heuristic optimization algorithms like Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony, Immune Algorithm, and Artificial Fish Swarm Algorithm. It supports user-defined functions to customize operators, allows continuing runs from previous iterations, and accelerates computations via vectorization, multithreading, multiprocessing, and caching. GPU support is in development. It helps solve complex optimization problems such as function minimization and the Traveling Salesman Problem efficiently, with easy installation and rich examples. This saves you time and effort in implementing and tuning optimization algorithms yourself. https://github.com/guofei9987/scikit-opt

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djangoproject

@djangoproject · Post #170 · 09/22/2016, 02:27 PM

https://pypi.python.org/pypi/uvloop #uvloop is a fast, drop-in replacement of the built-in #asyncio event loop. uvloop is released under the MIT license. uvloop and asyncio, combined with the power of async/await in Python 3.5, makes it easier than ever to write high-performance #networking code in Python. uvloop makes asyncio fast. In fact, it is at least 2x faster than #nodejs, #gevent, as well as any other Python #asynchronous framework. The performance of uvloop-based asyncio is close to that of Go programs.