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The following file shows three ways to code this operation, at least one of which was suggested by a student in one of my courses:

 

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  • The first function fetches the first argument (args is a tuple) and traverses the rest by slicing off the first (there’s no point in comparing an object to itself, especially if it might be a large structure).
  • The second version lets Python pick off the first and rest of the arguments automatically, and so avoids an index and slice.
  • The third converts from a tuple to a list with the built-in list call and employs the list sort method.

The sort method is coded in C, so it can be quicker than the other approaches at times, but the linear scans of the first two techniques will make them faster most of the time.[41] The file mins.py contains the code for all three solutions:

def min1(*args):
    res = args[0]
    for arg in args[1:]:
        if arg < res:
            res = arg
    return res

def min2(first, *rest):
    for arg in rest:
        if arg < first:
            first = arg
    return first

def min3(*args):
    tmp = list(args)            # Or, in Python 2.4+: return sorted(args)[0]
    tmp.sort()
    return tmp[0]

print(min1(3,4,1,2))
print(min2("bb", "aa"))
print(min3([2,2], [1,1], [3,3]))

All three solutions produce the same result when the file is run. Try typing a few calls interactively to experiment with these on your own:

% python mins.py
1
aa
[1, 1]

Notice that none of these three variants tests for the case where no arguments are passed in. They could, but there’s no point in doing so here—in all three solutions, Python will automatically raise an exception if no arguments are passed in. The first variant raises an exception when we try to fetch item 0, the second when Python detects an argument list mismatch, and the third when we try to return item 0 at the end.

This is exactly what we want to happen—because these functions support any data type, there is no valid sentinel value that we could pass back to designate an error. There are exceptions to this rule (e.g., if you have to run expensive actions before you reach the error), but in general it’s better to assume that arguments will work in your functions’ code and let Python raise errors for you when they do not.