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Source channel @githubtrending · Post #15571 · Mar 18

#python#newton_physics#nvidia_warp#physics_simulation#robotics Newton is a free, open-source GPU-accelerated physics engine for fast, accurate robot simulations, built by NVIDIA, Google DeepMind, and Disney Research. Install easily with `pip install "newton[examples]"` and run demos like pendulums, humanoids, cloth, cables, or hands via simple Python commands—it supports Linux/Windows/macOS with NVIDIA GPUs. You benefit by quickly testing robotics ideas with high-speed, differentiable physics for AI training, real-time adaptability, and complex tasks like manipulation, cutting weeks off development time. https://github.com/newton-physics/newton

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djangoproject

@djangoproject · Post #574 · 02/25/2018, 02:34 PM

http://www.paulbrownmagic.com/blog/python_partial_application Python Partial: Code Your Intention Of all the functional programming inspired features in Python, partial application must be the best kept secret that you really need to know. Partial application lets you create highly abstract functions and make them more specific for use, pass a function arguments without calling it yet, and so much more. #tuple#sort

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djangoproject

@djangoproject · Post #153 · 09/03/2016, 08:20 PM

http://wla.berkeley.edu/~cs61a/fa11/lectures/streams.html In this chapter, we continue our discussion of real-world applications by developing new tools to process #sequential#data. In Chapter 2, we introduced a sequence interface, implemented in Python by built-in data types such as #tuple and #list. #Sequences supported two operations: querying their length and accessing an element by index. In Chapter 3, we developed a user-defined implementations of the sequence interface, the Rlist class for representing recursive lists. These sequence types proved effective for representing and accessing a wide variety of sequential #datasets.