Allan thank you for your draft! I agree with you that (not in mine ) in general case it would be hard to resolve all corner cases. Also I think if someone read numpy reference linearly, he/she will have some insight that list of tuples are necessary (but it was not my case).
For me one problem is that in some cases numpy allows a lot freedom, but in other it is unnecessarily strict. Another one is exception messages (but this is certainly subjective). 2017-03-24 19:48 GMT+03:00 Allan Haldane <allanhald...@gmail.com>: > On 03/23/2017 02:16 PM, Kirill Balunov wrote: > > It was the first time I tried to create a structured array in numpy. > > Usually I use pandas for heterogeneous arrays, but it is one more > > dependency to my project. > > > > It took me some time (really, much more than some), to understand the > > problem with structured array creation. As example: > > > > I had list of list of this kind: > > b=[[ 1, 10.3, 12.1, 2.12 ],...] > > > > And tried: > > np.array(b, dtype='i4,f4,f4,f4') > > > > Which raises some weird exception: > > TypeError: a bytes-like object is required, not 'int' > > > > Two hours later I found that I need list of tuples. I didn't find any > help > > in documentation and could not realize that the problem with the inner > > lists... > > > > Why there is such restriction - 'list of tuples' to create structured > > array? What is the idea behind that, why not list of lists, or tuple of > > lists or ...? > > > > Also the exception does not help at all... > > p.s.: It looks like that dtype also accepts only list of tuples. But I > can > > not catch the idea for this restrictions. > > > > The problem is that numpy needs to distinguish between multidimensional > arrays and structured elements. A "list of lists" will often trigger > numpy's broadcasting rules, which is not what you want here. > > For instance, should numpy interpret your input list as a 2d array of > dimension Lx4 containing integer elements, or a 1d array of length L of > structs with 4 fields? > > In this particular case maybe numpy could, in principle, figure it out > from what you gave it by calculating that the innermost dimension is > the same length as the number of fields. But there are other cases (such > as assignment) where similar ambiguities arise that are harder to > resolve. So to preserve our sanity we want to require that structures be > formatted as tuples all the time. > > I have a draft of potential updated structured array docs you can read > here: > https://gist.github.com/ahaldane/7d1873d33d4d0f80ba7a54ccf1052eee > > See the section "Assignment from Python Native Types (Tuples)", which > hopefully better warns that tuples are needed. Let me know if you think > something is missing from the draft. > > (WARNING: the section about multi-field assignment in the doc draft is > incorrect for current numpy - that's what I'm proposing for the next > release. The rest of the docs are accurate for current numpy) > > Agreed that the error message could be changed. > > Allan > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion >
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