第247页 | Learning Python | 阅读 ‧ 电子书库

Assignment Creates References, Not Copies

Because this is such a central concept, I’ll mention it again: you need to understand what’s going on with shared references in your program. For instance, in the following example, the list object assigned to the name L is referenced from L and from inside the list assigned to the name M. Changing L in-place changes what M references, too:

>>> L = [1, 2, 3]
>>> M = ['X', L, 'Y']           # Embed a reference to L
>>> M
['X', [1, 2, 3], 'Y']

>>> L[1] = 0                    # Changes M too
>>> M
['X', [1, 0, 3], 'Y']

This effect usually becomes important only in larger programs, and shared references are often exactly what you want. If they’re not, you can avoid sharing objects by copying them explicitly. For lists, you can always make a top-level copy by using an empty-limits slice:

>>> L = [1, 2, 3]
>>> M = ['X', L[:], 'Y']        # Embed a copy of L
>>> L[1] = 0                    # Changes only L, not M
>>> L
[1, 0, 3]
>>> M
['X', [1, 2, 3], 'Y']

Remember, slice limits default to 0 and the length of the sequence being sliced; if both are omitted, the slice extracts every item in the sequence and so makes a top-level copy (a new, unshared object).