4 ms·

Yeah exactly. However, what I'd say is that a short launch from rest is an even more obscure use case than the one numpy supports. numpy has made the correct

• eesmith 4y ago
  While my observation is that most other Python packages don't import all subpackages. "import urllib" does not also import urllib.parse, so you can't do: import urllib urllib.parse.quote("A&W") but instead must explicitly import urllib.parse. scikit-learn supports essentially the same use cases as NumPy and it doesn't import all its subpackages: >>> import sklearn >>> sklearn.linear_model Traceback (most recent call last): File "<stdin>", line 1, in <module> AttributeError: module 'sklearn' has no attribute 'linear_model' >>> import sklearn.linear_model >>> sklearn.linear_model <module 'sklearn.linear_model' from '[...]sklearn/linear_model/__init__.py'> Thus leading to my earlier comment: > The NumPy developers think "practicality beats purity" is more important, and their main use-case is long-running programs where startup costs are slow, which I interpret as meaning their special cases is special enough to break the rules.