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Pipeline multiprocessing for python with generators
Pipeline multiprocessing in Python with generators
Similar to mpipe, this short module lets you string together tasks so that they are executed in parallel.
The difference is that it lets you use generators, functions which yield results instead of returning them. Each yielded item gets passed to the next stage.
You can specify that one or more copies of the workers operate on the input queue.
Vizualize a 3D volume as a mosaic of slice-by-slice 2D images
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Priority dict: a priority queue with updatable priorities You may have needed a priority queue with the ability to change the priorities of elements that were in the queue. This recipe solves this problem in an efficient way. The priority queue is implemented as a dictionary, where keys are the items of the queue, and values are their priorities…
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I was at Amazon for about six and a half years, and now I've been at Google for that long. One thing that struck me immediately about the two companies -- an impression that has been reinforced almost daily -- is that Amazon does everything wrong, and Google does everything right. Sure, it's a sweeping generalization, but a surprisingly accurate one. It's pretty crazy. There are probably a hundred or even two hundred different ways you can compare the two companies, and Google is superior in all but three of them, if I recall correctly. I actually did a spreadsheet at one point but Legal wouldn't let me show it to anyone, even though recruiting loved it.
I mean, just to give you a very brief taste: Amazon's recruiting process is fundamentally flawed by having teams hire for themselves, so their hiring bar is incredibly inconsistent across teams, despite various efforts they've made to level it out. And their operations are a mess; they don't real