Ben Finney, 10.08.2013 07:05: > Skip Montanaro writes: >> Given that installing numpy or scipy is generally no more difficult >> that executing "pip install (scipy|numpy)" I'm not really feeling the >> need for a battery here... > > See the Rationale of PEP 450 for more reasons why “install NumPy” is not > a feasible solution for many use cases, and why having ‘statistics’ as a > pure-Python, standard-library package is desirable.
The rationale suggests that the module is meant as a simple toolset for non-NumPy users. Are the APIs (class model, function names, etc.) similar enough to make it easy to switch, preferably in both directions? It would be good if a stdlib statistics module could be used as a SciPy fallback for the "simple" things, and if users of the stdlib module could easily switch their code to SciPy if they need more speed/features/whatever at some point, without having to relearn the name of each single function. I'm not asking for compatibility (doesn't sound reasonable without NumPy arrays), but I think that a similarity in terms of API naming (as far as it makes sense) should be clearly stated, e.g. in the Design Decisions section. Stefan -- http://mail.python.org/mailman/listinfo/python-list
