Difference between import numpy and import numpy as np-优快云博客

本文详细解释了在Python编程中如何正确地导入和使用numpy及其子模块f2py。通过对比不同导入方式的效果，文章帮助读者理解模块与子模块之间的关系，并避免因命名空间冲突而产生的错误。

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Difference between import numpy and import numpy as np

up vote 18 down vote favorite

I understand that when possible one should use

import numpy as np

This helps keep away any conflict due to namespaces. But I have noticed that while the command below works

import numpy.f2py as myf2py

the following does not

import numpy as np
np.f2py #throws no module named f2py

Can someone please explain this?

python numpy

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edited Mar 24 '14 at 23:20

mu 無

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asked Mar 24 '14 at 23:19

user1318806

3001311

@roippi have you tried exit your python and enter it and just do import numpy then numpy.f2py ? It throws an error in my case too – aha Mar 24 '14 at 23:24

Importing a module doesn't import sub-modules. You need to explicitly import the numpy.f2py module regardless of whether or not/how numpy itself has been imported. – alecb Mar 24 '14 at 23:39

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4 Answers

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up vote 13 down vote

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

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edited Mar 25 '14 at 0:31

answered Mar 24 '14 at 23:33

aha

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up vote 7 down vote

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

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answered Mar 25 '14 at 0:59

hbristow

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up vote 1 down vote

numpy.f2py is actually a submodule of numpy, and therefore has to be imported separately from numpy. As aha said before:

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

when you call the statement import numpy as np, you are shortening the phrase "numpy" to "np" to make your code easier to read. It also helps to avoid namespace issues. (tkinter and ttk are a good example of what can happen when you do have that issue. The UIs look extremely different.)

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answered Mar 24 '14 at 23:47

bspymaster

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up vote 1 down vote

This is a language feature. f2py is a subpackage of the module numpy and must be loaded separately.

This feature allows:

you to load from numpy only the packages you need, speeding up execution.
the developers of f2py to have namespace separation from the developers of another subpackage.

Notice however that import numpy.f2py or its variant import numpy.f2py as myf2py are still loading the parent module numpy.

Said that, when you run

import numpy as np
np.f2py

You receive an AttributeError because f2py is not an attribute of numpy, because the __init__() of the package numpy did not declare in its scope anything about the subpackage f2py.

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answered Mar 24 '14 at 23:57

gg349

7,67321739

when you do import numpy.f2py as myf2py, how do you access its parent numpy? it seems import numpy.f2py allows you to access its parent numpy, but import numpy.f2py as myf2py doesn't – aha Mar 25 '14 at 0:00

You don't access it because you decided you didn't want to use anything from numpy, and you only care of using the subpackage. It is similar to using from foo import bar: the name foo will not be accessible. See the comment after the first example of the docs, LINK – gg349 Mar 25 '14 at 0:05

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