Learning Python - Mark Lutz [244]
Chapter 18. Arguments
Chapter 17 explored the details behind Python’s scopes—the places where variables are defined and looked up. As we learned, the place where a name is defined in our code determines much of its meaning. This chapter continues the function story by studying the concepts in Python argument passing—the way that objects are sent to functions as inputs. As we’ll see, arguments (a.k.a. parameters) are assigned to names in a function, but they have more to do with object references than with variable scopes. We’ll also find that Python provides extra tools, such as keywords, defaults, and arbitrary argument collectors, that allow for wide flexibility in the way arguments are sent to a function.
Argument-Passing Basics
Earlier in this part of the book, I noted that arguments are passed by assignment. This has a few ramifications that aren’t always obvious to beginners, which I’ll expand on in this section. Here is a rundown of the key points in passing arguments to functions:
Arguments are passed by automatically assigning objects to local variable names. Function arguments—references to (possibly) shared objects sent by the caller—are just another instance of Python assignment at work. Because references are implemented as pointers, all arguments are, in effect, passed by pointer. Objects passed as arguments are never automatically copied.
Assigning to argument names inside a function does not affect the caller. Argument names in the function header become new, local names when the function runs, in the scope of the function. There is no aliasing between function argument names and variable names in the scope of the caller.
Changing a mutable object argument in a function may impact the caller. On the other hand, as arguments are simply assigned to passed-in objects, functions can change passed-in mutable objects in place, and the results may affect the caller. Mutable arguments can be input and output for functions.
For more details on references, see Chapter 6; everything we learned there also applies to function arguments, though the assignment to argument names is automatic and implicit.
Python’s pass-by-assignment scheme isn’t quite the same as C++’s reference parameters option, but it turns out to be very similar to the C language’s argument-passing model in practice:
Immutable arguments are effectively passed “by value.” Objects such as integers and strings are passed by object reference instead of by copying, but because you can’t change immutable objects in-place anyhow, the effect is much like making a copy.
Mutable arguments are effectively passed “by pointer.” Objects such as lists and dictionaries are also passed by object reference, which is similar to the way C passes arrays as pointers—mutable objects can be changed in-place in the function, much like C arrays.
Of course, if you’ve never used C, Python’s argument-passing mode will seem simpler still—it involves just the assignment of objects to names, and it works the same whether the objects are mutable or not.
Arguments and Shared References
To illustrate argument-passing properties at work, consider the following code:
>>> def f(a): # a is assigned to (references) passed object
... a = 99 # Changes local variable a only
...
>>> b = 88
>>> f(b) # a and b both reference same 88 initially
>>> print(b) # b is not changed
88
In this example the variable a is assigned the object 88 at the moment the function is called with f(b), but a lives only within the called function. Changing a inside the function has no effect on the place where the function is called; it simply resets the local variable a to a completely different object.
That’s what is meant by a lack of name aliasing—assignment to an argument name inside a function (e.g., a=99) does not magically change a variable like b in the scope of the function call. Argument names may share passed objects initially (they are essentially pointers to those objects), but only temporarily,