Del删除变量及其所指向的对象的绑定。

>>> a = ['a', 'b', 'c']
>>> b = a
>>> del a
>>> b
['a', 'b', 'c']
>>> a
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
NameError: name 'a' is not defined

我能想到的一个简单的用例是，如果你已经使用内置函数名作为变量，并且你想在它已经被你的变量名“覆盖”之后使用该函数。

t = ('a', "letter")
value, type = t
print(value, type)
del type
print(type(value))

输出:

a letter
<class 'str'>

在以上回答的基础上补充几点: 德尔x

x的定义表示r -> o(一个引用r指向一个对象o)，但del x改变的是r而不是o。这是一个对对象的引用(指针)的操作，而不是与x相关的对象。区分r和o是这里的关键。

It removes it from locals(). Removes it from globals() if x belongs there. Removes it from the stack frame (removes the reference physically from it, but the object itself resides in object pool and not in the stack frame). Removes it from the current scope. It is very useful to limit the span of definition of a local variable, which otherwise can cause problems. It is more about declaration of the name rather than definition of content. It affects where x belongs to, not where x points to. The only physical change in memory is this. For example if x is in a dictionary or list, it (as a reference) is removed from there(and not necessarily from the object pool). In this example, the dictionary it belongs is the stack frame (locals()), which overlaps with globals().

我发现在使用Numpy处理大数据时，del对于伪手动内存管理非常有用。例如:

for image_name in large_image_set:
    large_image = io.imread(image_name)
    height, width, depth = large_image.shape
    large_mask = np.all(large_image == <some_condition>)
    # Clear memory, make space
    del large_image; gc.collect()

    large_processed_image = np.zeros((height, width, depth))
    large_processed_image[large_mask] = (new_value)
    io.imsave("processed_image.png", large_processed_image)

    # Clear memory, make space
    del large_mask, large_processed_image; gc.collect()

当Python GC无法跟上时，系统会疯狂地切换，这可能会导致脚本停止，而它在宽松的内存阈值下运行得非常流畅，从而在机器工作时留下了足够的空间来使用机器浏览和编码。

由于我还没有看到交互式控制台的答案，我将展示一个。

当foo=None时，该引用和对象存在，它不指向它。

而del foo也会销毁对象和引用。

如果你这样做如果foo是None并且它被删除了它就会升起NameError作为引用，它的对象所有介于两者之间的东西都会被del删除

删除目标列表会递归地从左到右删除每个目标。

与此同时，foo=None只是一个指向None的引用，因此引用仍然是有效的，对象也是如此。

[…在Python中，变量是对象的引用，任何变量都可以引用任何对象[…]

链接到引用1

链接到引用2

还有一个小众用途: 在带有ROOT5或ROOT6的pyroot中，"del"可以用于删除引用不再存在的c++对象的python对象。这允许pyroot的动态查找找到同名的c++对象，并将其绑定到python名称。所以你可以有这样一个场景:

import ROOT as R
input_file = R.TFile('inputs/___my_file_name___.root')
tree = input_file.Get('r')
tree.Draw('hy>>hh(10,0,5)')
R.gPad.Close()
R.hy # shows that hy is still available. It can even be redrawn at this stage.
tree.Draw('hy>>hh(3,0,3)') # overwrites the C++ object in ROOT's namespace
R.hy # shows that R.hy is None, since the C++ object it pointed to is gone
del R.hy
R.hy # now finds the new C++ object

希望ROOT7的更健全的对象管理能够填补这个空缺。

del is the equivalent of "unset" in many languages and as a cross reference point moving from another language to python.. people tend to look for commands that do the same thing that they used to do in their first language... also setting a var to "" or none doesn't really remove the var from scope..it just empties its value the name of the var itself would still be stored in memory...why?!? in a memory intensive script..keeping trash behind its just a no no and anyways...every language out there has some form of an "unset/delete" var function..why not python?