Avoiding Mutable Argument Changes

This behavior of in-place changes to mutable arguments isn’t a bug—it’s simply the way argument passing works in Python. Arguments are passed to functions by reference (a.k.a. pointer) by default because that is what we normally want. It means we can pass large objects around our programs without making multiple copies along the way, and we can easily update these objects as we go. In fact, as we’ll see in Part VI, Python’s class model depends upon changing a passed-in “self” argument in-place, to update object state.

If we don’t want in-place changes within functions to impact objects we pass to them, though, we can simply make explicit copies of mutable objects, as we learned in Chapter 6. For function arguments, we can always copy the list at the point of call:

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L = [1, 2]
changer(X, L[:])        # Pass a copy, so our 'L' does not change

We can also copy within the function itself, if we never want to change passed-in objects, regardless of how the function is called:

def changer(a, b):
   b = b[:]             # Copy input list so we don't impact caller
   a = 2
   b[0] = 'spam'        # Changes our list copy only

Both of these copying schemes don’t stop the function from changing the object—they just prevent those changes from impacting the caller. To really prevent changes, we can always convert to immutable objects to force the issue. Tuples, for example, throw an exception when changes are attempted:

L = [1, 2]
changer(X, tuple(L))    # Pass a tuple, so changes are errors

This scheme uses the built-in tuple function, which builds a new tuple out of all the items in a sequence (really, any iterable). It’s also something of an extreme—because it forces the function to be written to never change passed-in arguments, this solution might impose more limitations on the function than it should, and so should generally be avoided (you never know when changing arguments might come in handy for other calls in the future). Using this technique will also make the function lose the ability to call any list-specific methods on the argument, including methods that do not change the object in-place.

The main point to remember here is that functions might update mutable objects like lists and dictionaries passed into them. This isn’t necessarily a problem if it’s expected, and often serves useful purposes. Moreover, functions that change passed-in mutable objects in place are probably designed and intended to do so—the change is likely part of a well-defined API that you shouldn’t violate by making copies.

However, you do have to be aware of this property—if objects change out from under you unexpectedly, check whether a called function might be responsible, and make copies when objects are passed if needed.