从NumPy，matplotlib包导入python子模块有什么区别 [英] what is the difference between importing python sub-modules from NumPy, matplotlib packages

问题描述

当我尝试使用matplotlib中的pyplot时:

import matplotlib
print matplotlib.pyplot  # just checking

它给了我AttributeError: 'module' object has no attribute 'pyplot'

可以通过以下方式解决:

It can be solved with:

import matplotlib.pyplot

但是我真正困惑的是，

import numpy
print numpy.random

给我<module 'numpy.random' from '/Applications/Canopy.app/appdata/canopy-1.0.3.1262.macosx-x86_64/Canopy.app/Contents/lib/python2.7/site-packages/numpy/random/__init__.pyc'>

两种情况有什么区别?在第一个示例中不能调用pyplot，但是在第二个示例中可以调用random.我认为这与某种包和模块有关.但是我对python并不是那么专业，因此要求一个答案.

What is the difference between two cases? pyplot cannot be called in the first example, but random was in the second. I think it's related with some kind of packages and modules. But I'm not such a professional to the python, thus asking for an answer.

推荐答案

对于权威教程，阅读.

但是对于您的特定情况，看来是这样:

But for your specific case, it looks like this is what's happening:

每个基于目录的python模块(例如matplotlib和numpy)都有一个__init__.py文件，该文件确定将什么内容带入模块的顶级范围.默认情况下(__init__.py为空)，范围不存在.

Every directory-based python module (like matplotlib and numpy) has an __init__.py file, which determines what is brought into the module's top-level scope. By default (when __init__.py is empty), nothing is in scope.

但是，某些模块(如numpy)决定通过向__init__.py添加import语句来将功能提升到顶层.即使您仅显式导入了numpy，这也将这些子模块纳入了范围.

However, some modules (like numpy) have decided to hoist functionality into the top-level by adding import statements to __init__.py. This brings those submodules into scope, even if you've only explicitly imported numpy.

要检查我们的假设，让我们看一下消息源！

To check our assumptions, let's look at the source!

• matplotlib的__init__.py 不包括语句import pyplot.
• numpy的__init__.py 确实包含，在第176行.

• matplotlib's __init__.py doesn't include the statement import pyplot.
• numpy's __init__.py does include import random, on line 176.

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