Dear devs, Sorry for posting a numpy-issue on the scipy-list. I am not (yet) subscribed to the numpy list, but I believe that the two community have a big enough overlap so it shouldn't matter too much where I post it. I recently encountered the issue that I found that np.any(x) is sort of veeeery slow for big arrays, even if every element has a non-zero value and I only need a True/False response. So my thinking was that if np.any(x) encounters the first non-zero value it should simply return True, which should take basically no time at all if every element in the array is non-zero. Searching for it I found the following two old issues on numpy: 1. https://github.com/numpy/numpy/issues/2269 It is an issue from 2010, but got some traffic again in 2016 and 2017. 2. https://github.com/numpy/numpy/issues/3446 This is a related issue from 2013, reporting a potential performance regression between numpy 1.6.2 and 1.7.0, that got some traffic in 2016 again as well. I just wanted to ask about the opinions of devs more familiar with these two functions (np.all(), np.any()). Would there be better ways to check if any element in a big (1D or higher dimensions)-array is non-zero (or the reverse with np.all)? Thanks, Dieter