Mailman 3 July 2022 - NumPy-Discussion

Software Freedom Conservancy calls for move from Github
by Matthew Brett July 4, 2022

July 4, 2022

Hi, I just came across this: https://sfconservancy.org/GiveUpGitHub/ I guess this is something we should review and consider - although it would obviously have serious costs. Cheers, Matthew

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Fuzzing integration of Numpy into OSS-Fuzz
by david korczynski July 2, 2022

July 2, 2022

Hi Numpy maintainers, Would you be interested in integrating continuous fuzzing by way of OSS-Fuzz? Fuzzing is a way to automate test-case generation and has been heavily used for memory unsafe languages. Recently efforts have been put into fuzzing memory safe languages and Python is one of the languages where it would be great to use fuzzing. In this PR: https://github.com/google/oss-fuzz/pull/7681 I did an initial integration into OSS-Fuzz. Essentially, OSS-Fuzz is a free service run by Google that performs continuous fuzzing of important open source projects. If you would like to integrate, the only thing I need is a list of email(s) that will get access to the data produced by OSS-Fuzz, such as bug reports, coverage reports and more stats. Notice the emails affiliated with the project will be public in the OSS-Fuzz repo, as they will be part of a configuration file. There are already some important Python projects on OSS-Fuzz such as tensorflow-python (https://github.com/google/oss-fuzz/tree/master/projects/tensorflow-py) and it would be great to add Numpy to the list. Let me know your thoughts on this and if you have any questions as I’m happy to clarify or go more into details with fuzzing. Kind regards, David ADA Logics Ltd is registered in England. No: 11624074. Registered office: 266 Banbury Road, Post Box 292, OX2 7DL, Oxford, Oxfordshire , United Kingdom

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Feature request: function to get minimum and maximum values simultaneously (as a tuple)
by Ewout ter Hoeven July 1, 2022

July 1, 2022

A function to get the minimum and maximum values of an array simultaneously could be very useful, from both a convenience and performance point of view. Especially when arrays get larger the performance benefit could be significant, and even more if the array doesn't fit in L2/L3 cache or even memory. There are many cases where not either the minimum or the maximum of an array is required, but both. Think of clipping an array, getting it's range, checking for outliers, normalizing, making a plot like a histogram, etc. This function could be called aminmax() for example, and also be called like ndarray.minmax(). It should return a tuple (min, max) with the minimum and maximum values of the array, identical to calling (ndarray.min(), ndarray.max()). With such a function, numpy.ptp() and the special cases of numpy.quantile(a, q=[0,1]) and numpy.percentile(a, q=[0,100]) could also potentially be speeded up, among others. Potentially argmin and argmax could get the same treatment, being called argminmax(). There is also a very extensive post on Stack Overflow (a bit old already) with discussion and benchmarks: https://stackoverflow.com/questions/12200580/numpy-function-for-simultaneou…

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