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Other built-in functions support the iteration protocol as well (but frankly, are harder to cast in interesting examples related to files). For example, the sum call computes the sum of all the numbers in any iterable; the any and all built-ins return True if any or all items in an iterable are True, respectively; and max and min return the largest and smallest item in an iterable, respectively. Like reduce, all of the tools in the following examples accept any iterable as an argument and use the iteration protocol to scan it, but return a single result:

>>> sum([3, 2, 4, 1, 5, 0]) # sum expects numbers only

15

>>> any(['spam', '', 'ni'])

True

>>> all(['spam', '', 'ni'])

False

>>> max([3, 2, 5, 1, 4])

5

>>> min([3, 2, 5, 1, 4])

1

Strictly speaking, the max and min functions can be applied to files as well—they automatically use the iteration protocol to scan the file and pick out the lines with the highest and lowest string values, respectively (though I’ll leave valid use cases to your imagination):

>>> max(open('script1.py')) # Line with max/min string value

'x = 2\n'

>>> min(open('script1.py'))

'import sys\n'

Interestingly, the iteration protocol is even more pervasive in Python today than the examples so far have demonstrated—everything in Python’s built-in toolset that scans an object from left to right is defined to use the iteration protocol on the subject object. This even includes more esoteric tools such as the list and tuple built-in functions (which build new objects from iterables), the string join method (which puts a substring between strings contained in an iterable), and even sequence assignments. Consequently, all of these will also work on an open file and automatically read one line at a time:

>>> list(open('script1.py'))

['import sys\n', 'print(sys.path)\n', 'x = 2\n', 'print(2 ** 33)\n']

>>> tuple(open('script1.py'))

('import sys\n', 'print(sys.path)\n', 'x = 2\n', 'print(2 ** 33)\n')

>>> '&&'.join(open('script1.py'))

'import sys\n&&print(sys.path)\n&&x = 2\n&&print(2 ** 33)\n'

>>> a, b, c, d = open('script1.py')

>>> a, d

('import sys\n', 'print(2 ** 33)\n')

>>> a, *b = open('script1.py') # 3.0 extended form

>>> a, b

('import sys\n', ['print(sys.path)\n', 'x = 2\n', 'print(2 ** 33)\n'])

Earlier, we saw that the built-in dict call accepts an iterable zip result, too. For that matter, so does the set call, as well as the new set and dictionary comprehension expressions in Python 3.0, which we met in Chapters 4, 5, and 8:

>>> set(open('script1.py'))

{'print(sys.path)\n', 'x = 2\n', 'print(2 ** 33)\n', 'import sys\n'}

>>> {line for line in open('script1.py')}

{'print(sys.path)\n', 'x = 2\n', 'print(2 ** 33)\n', 'import sys\n'}

>>> {ix: line for ix, line in enumerate(open('script1.py'))}

{0: 'import sys\n', 1: 'print(sys.path)\n', 2: 'x = 2\n', 3: 'print(2 ** 33)\n'}

In fact, both set and dictionary comprehensions support the extended syntax of list comprehensions we met earlier in this chapter, including if tests:

>>> {line for line in open('script1.py') if line[0] == 'p'}

{'print(sys.path)\n', 'print(2 ** 33)\n'}

>>> {ix: line for (ix, line) in enumerate(open('script1.py')) if line[0] == 'p'}

{1: 'print(sys.path)\n', 3: 'print(2 ** 33)\n'}

Like the list comprehension, both of these scan the file line by line and pick out lines that begin with the letter “p.” They also happen to build sets and dictionaries in the end, but we get a lot of work “for free” by combining file iteration and comprehension syntax.

There’s one last iteration context that’s worth mentioning, although it’s a bit of a preview: in Chapter 18, we’ll learn that a special *arg form can be used in function calls to unpack a collection of values into individual arguments. As you can probably predict by now, this accepts any iterable, too, including files (see Chapter 18 for more details on the call syntax):

>>> def f(a, b, c, d): print(a, b, c, d, sep='&')

...

>>> f(1, 2, 3, 4)

1&2&3&4

>>> f(*[1, 2, 3, 4])