A collection of small utility functions for iterators (all functions can also be used with normal sequences). Among other things, the module provides generator ("lazy") versions of the built-in sequence-manipulation functions. The generators can be combined to produce a more specialised iterator.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 | from __future__ import generators, nested_scopes
def itercat(*iterators):
"""Concatenate several iterators into one."""
for i in iterators:
for x in i:
yield x
def iterwhile(func, iterator):
"""Iterate for as long as func(value) returns true."""
iterator = iter(iterator)
while 1:
next = iterator.next()
if not func(next):
raise StopIteration
yield next
def iterfirst(iterator, count=1):
"""Iterate through 'count' first values."""
iterator = iter(iterator)
for i in xrange(count):
yield iterator.next()
def iterstep(iterator, n):
"""Iterate every nth value."""
iterator = iter(iterator)
while 1:
yield iterator.next()
# skip n-1 values
for dummy in range(n-1):
iterator.next()
def itergroup(iterator, count):
"""Iterate in groups of 'count' values. If there
aren't enough values, the last result is padded with
None."""
iterator = iter(iterator)
values_left = [1]
def values():
values_left[0] = 0
for x in range(count):
try:
yield iterator.next()
values_left[0] = 1
except StopIteration:
yield None
while 1:
value = tuple(values())
if not values_left[0]:
raise StopIteration
yield value
def xzip(*iterators):
"""Iterative version of builtin 'zip'."""
iterators = map(iter, iterators)
while 1:
yield tuple([x.next() for x in iterators])
def xmap(func, *iterators):
"""Iterative version of builtin 'map'."""
iterators = map(iter, iterators)
values_left = [1]
def values():
# Emulate map behaviour, i.e. shorter
# sequences are padded with None when
# they run out of values.
values_left[0] = 0
for i in range(len(iterators)):
iterator = iterators[i]
if iterator is None:
yield None
else:
try:
yield iterator.next()
values_left[0] = 1
except StopIteration:
iterators[i] = None
yield None
while 1:
args = tuple(values())
if not values_left[0]:
raise StopIteration
yield func(*args)
def xfilter(func, iterator):
"""Iterative version of builtin 'filter'."""
iterator = iter(iterator)
while 1:
next = iterator.next()
if func(next):
yield next
def xreduce(func, iterator, default=None):
"""Iterative version of builtin 'reduce'."""
iterator = iter(iterator)
try:
prev = iterator.next()
except StopIteration:
return default
single = 1
for next in iterator:
single = 0
prev = func(prev, next)
if single:
return func(prev, default)
return prev
|
Tags: algorithms
Redundancy? Surely the builtins map(), filter() and reduce() will use iterators by default in Python 2.2? And what about the for loop? I was under the impression that "for x in seq" would in fact execute "for x in iter(seq)"?
I don't think so. The original builtins cannot be changed, since that would break a lot of existing code that expects lists from those functions.
These are indeed mostly redundant. I believe Martin is correct; python internals that iterated over sequences now use the iterator protocol.
"In 2.2, Python's for statement no longer expects a sequence; it expects something for which iter() will return an iterator. For backward compatibility and convenience, an iterator is automatically constructed for sequences that don't implement __iter__() or a tp_iter slot, so for i in [1,2,3] will still work. Wherever the Python interpreter loops over a sequence, it's been changed to use the iterator protocol."
--What's New in Python 2.2 (A. M. Kuchling)
I experimented and found that I could indeed use my own trivial iterator classes (as long as they provide __iter__ which returns self) with for loops, list comprehensions, map, filter, and reduce.