numpy is the top package name, and doing import numpy doesn’t import submodule numpy.f2py.

When you do import numpy it creats a link that points to numpy, but numpy is not further linked to f2py. The link is established when you do import numpy.f2py

In your above code:

import numpy as np # np is an alias pointing to numpy, but at this point numpy is not linked to numpy.f2py

import numpy.f2py as myf2py # this command makes numpy link to numpy.f2py. myf2py is another alias pointing to numpy.f2py as well

Here is the difference between import numpy.f2py and import numpy.f2py as myf2py:

import numpy.f2py

put numpy into local symbol table(pointing to numpy), and numpy is linked to numpy.f2py

both numpy and numpy.f2py are accessible

import numpy.f2py as myf2py

put my2py into local symbol table(pointing to numpy.f2py)

Its parent numpy is not added into local symbol table. Therefore you can not access numpy directly

The import as syntax was introduced in PEP 221 and is well documented there.

When you import a module via

import numpy

the numpy package is bound to the local variable numpy. The import as syntax simply allows you to bind the import to the local variable name of your choice (usually to avoid name collisions, shorten verbose module names, or standardize access to modules with compatible APIs).

Thus,

import numpy as np

is equivalent to,

import numpy

np = numpy

del numpy

When trying to understand this mechanism, it’s worth remembering that import numpy actually means import numpy as numpy.

When importing a submodule, you must refer to the full parent module name, since the importing mechanics happen at a higher level than the local variable scope. i.e.

import numpy as np

import numpy.f2py # OK

import np.f2py # ImportError

I also take issue with your assertion that “where possible one should [import numpy as np]”. This is done for historical reasons, mostly because people get tired very quickly of prefixing every operation with numpy. It has never prevented a name collision for me (laziness of programmers actually suggests there’s a higher probability of causing a collision with np)

Finally, to round out my exposé, here are 2 interesting uses of the import as mechanism that you should be aware of:

1. long subimports

import scipy.ndimage.interpolation as warp

warp.affine_transform(I, …)

2. compatible APIs

try:

import pyfftw.interfaces.numpy_fft as fft

except:

import numpy.fft as fft

# call fft.ifft(If) with fftw or the numpy fallback under a common name