Loops in Python

Python is an interesting language in a sense that it is one of the few languages which does not implement C-style for loop. In this sense it is similar to Pascal.

Instead of for look Python language designed propose to use range function. Python provides built-in functions range (and, in v2, xrange) to generate integer sequences. The simplest way to loop n times in Python is:

for i in range(n):
    statement(s)

Generally Python stresses the importance of  implicit iteration over collections, which is noble goal, which is mired by disign blunder like exclusion of C-style for loop. 

All Python loops can include an else clause, and break and continue statements.  The break and continue statements are identical to C.  While weíre looking at oddballs, we will also study the loop else clause here because it is intertwined with break, and Pythonís empty placeholder statement, pass (which is not tied to loops per se, but falls into the general category of simple one-word statements). In Python:

break
Jumps out of the closest enclosing loop (past the entire loop statement)
continue
Jumps to the top of the closest enclosing loop (to the loopís header line)
pass
Does nothing at all: itís an empty statement placeholder
Loop else block
Runs if and only if the loop is exited normally (i.e., without hitting a break)

The while Statement

The while statement repeats execution of a statement or block of statements, controlled by a conditional expression. There are no suprises here:

while expression:
    statement(s)

A while statement can also include an else clause, and break and continue statements. Here's a very simple example:

count = 0
while x > 0:
    x //= 2            # truncating division
    count += 1
print('The approximate log2 is', count)

A loop within a function's body also ends if the loop body executes a return statement, since in this case the whole function ends.

The for Statement

The for statement repeats execution of a statement, or block of statements, controlled by an iterable expression. Here's the syntax of the for statement:

for target in iterable:
    statement(s)

The in keyword is part of the syntax of the for statement; its purpose here is distinct from the in operator, which tests membership.

You can iterate over stings:

for letter in 'abba':
    print('give me a', letter, '...')

You can also have a target with multiple identifiers, like in an unpacking assignment. In this case, the iterator's items must be iterables, each with exactly as many items as there are identifiers in the target (in v3 only, precisely one of the identifiers can be preceded by a star, in which case the starred item is bound to a list of all items, if any, that were not assigned to other targets). For example, when d is a dictionary, this is a typical way to loop on the items (key/value pairs) in d:

for key, value in d.items():
    if key and value:             # print only true keys and values
        print(key, value)

The items method returns a list (in v2; another kind of iterable, in v3) of key/value pairs, so we use a for loop with two identifiers in the target to unpack each item into key and value. Although components of a target are commonly identifiers, values can be bound to any acceptable LHS expression as covered in "Assignment Statements":

prototype = [1, 'placemarker', 3]
for prototype[1] in 'xyz': print(prototype)
# prints [1, 'x', 3], then [1, 'y', 3], then [1, 'z', 3]

When an iterable has a mutable underlying object, don't alter that object during a for loop on it. For example, the preceding key/value printing example cannot alter d in v3 (and couldn't in v2 if it used iteritems instead of items). iteritems in v2 (and items in v3) return iterables whose underlying object is d, so the loop body cannot mutate the set of keys in d (e.g., by executing del d[key]). d.items() in v2 (and list(d.items()) in v3) return new, independent lists, so that d is not the underlying object of the iterable; therefore, the loop body could mutate d. Specifically:

The control target variable(s) may be rebound in the loop body, but get rebound again to the next item in the iterator at the next iteration of the loop. The loop body does not execute at all if the iterator yields no items. In this case, the control variable is not bound or rebound in any way by the for statement. However, if the iterator yields at least one item, then, when the loop statement terminates, the control variable remains bound to the last value to which the loop statement has bound it. The following code is therefore correct only when someseq is not empty:

for x in someseq:
    process(x)
print('Last item processed was', x)

Iterators

An iterator is an object i such that you can call next(i). next(i) returns the next item of iterator i or, when iterator i has no more items, raises a StopIteration exception.

Alternatively, you can call next(i, default), in which case, when iterator i has no more items, the call returns default.

When you write a class (see "Classes and Instances"), you can allow instances of the class to be iterators by defining a special method __next__ (in v2 the method must be called next-this was eventually seen as a design error) that takes no argument except self, and returns the next item or raises StopIteration. Most iterators are built by implicit or explicit calls to built-in function iter, covered in Table 7-2. Calling a generator also returns an iterator, as we'll discuss in "Generators".

The for statement implicitly calls iter to get an iterator. The statement:

for x in c:
    statement(s)

is exactly equivalent to:

_temporary_iterator = iter(c)
while True:
    try: x = next(_temporary_iterator)
    except StopIteration: break
    statement(s)

where _temporary_iterator is an arbitrary name not used elsewhere in the current scope.

Thus, when iter(c) returns an iterator i such that next(i) never raises StopIteration (an unbounded iterator), the loop for x in c never terminates (unless the statements in the loop body include suitable break or return statements, or raise or propagate exceptions). iter(c), in turn, calls special method c.__iter__() to obtain and return an iterator on c. We'll talk more about the special method __iter__ in "Container methods".

Many of the best ways to build and manipulate iterators are found in the standard library module itertools, covered in "The itertools Module".

range and xrange

Looping over a sequence of integers is a common task, so Python provides built-in functions range (and, in v2, xrange) to generate integer sequences. The simplest way to loop n times in Python is:

for i in range(n):
    statement(s)

In v2, range(x) returns a list whose items are consecutive integers from 0 (included) up to x (excluded). range(x, y) returns a list whose items are consecutive integers from x (included) up to y (excluded). The result is the empty list when x is greater than or equal to y. range(x, y, stride) returns a list of integers from x (included) up to y (excluded), such that the difference between each two adjacent items is stride. If stride is less than 0, range counts down from x to y. range returns the empty list when x is greater than or equal to y and stride is greater than 0, or when x is less than or equal to y and stride is less than 0. When stride equals 0, range raises an exception.

While range, in v2, returns a normal list object, usable for any purpose, xrange (v2 only) returns a special-purpose object, intended just for use in iterations like the for statement shown previously (xrange itself does not return an iterator; however, you can easily obtain such an iterator, should you need one, by calling iter(xrange(...))). The special-purpose object returned by xrange consumes less memory (for wide ranges, much less memory) than the list object range returns; apart from such memory issues, you can use range wherever you could use xrange, but not vice versa. For example, in v2:

>>> print(range(1, 5))
[1, 2, 3, 4]
>>> print(xrange(1, 5))
xrange(1, 5)

Here, range returns a perfectly ordinary list, which displays quite normally, but xrange returns a special-purpose object, which displays in its own special way.

In v3, there is no xrange, and range works similarly to v2's xrange. In v3, if you need a list that's an arithmetic progression of ints, call list(range(...)).


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