itertools.grouper

[lieryan]

BPO	6021
Nosy	@rhettinger, @ericsnowcurrently

^{Note: these values reflect the state of the issue at the time it was migrated and might not reflect the current state.}

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GitHub fields:

assignee = 'https://github.com/rhettinger'
closed_at = <Date 2009-05-14.17:13:30.205>
created_at = <Date 2009-05-14.17:05:29.836>
labels = ['type-feature', 'library']
title = 'itertools.grouper'
updated_at = <Date 2012-06-29.22:20:33.591>
user = 'https://bugs.python.org/lieryan'

bugs.python.org fields:

activity = <Date 2012-06-29.22:20:33.591>
actor = 'eric.snow'
assignee = 'rhettinger'
closed = True
closed_date = <Date 2009-05-14.17:13:30.205>
closer = 'rhettinger'
components = ['Library (Lib)']
creation = <Date 2009-05-14.17:05:29.836>
creator = 'lieryan'
dependencies = []
files = []
hgrepos = []
issue_num = 6021
keywords = []
message_count = 4.0
messages = ['87743', '87745', '87750', '87756']
nosy_count = 4.0
nosy_names = ['rhettinger', 'lieryan', 'cvrebert', 'eric.snow']
pr_nums = []
priority = 'normal'
resolution = 'rejected'
stage = None
status = 'closed'
superseder = None
type = 'enhancement'
url = 'https://bugs.python.org/issue6021'
versions = ['Python 3.1', 'Python 2.7']

[lieryan]

An itertool to Group-by-n

>>> lst = range(15)
>>> itertools.grouper(lst, 5)
[[0, 1, 2, 3, 4], [5, 6, 7, 8, 9], [10, 11, 12, 13, 14]]

This function is often asked in several c.l.py discussions, such as these:
http://comments.gmane.org/gmane.comp.python.general/623377
http://comments.gmane.org/gmane.comp.python.general/622763

There are several issues. What should be done if the number of items in
the original list is not exactly divisible?

• raise an error as default
• pad with a value from 3rd argument
• make the last one shorter, maybe using keyword arguments or sentinel
  to 3rd argument

or should there be separate functions for each of them?

What about infinite list? Most recipes for the function uses zip which
breaks with infinite list.

[rhettinger]

This has been rejected before.

• It is not a fundamental itertool primitive. The recipes section in
  the docs shows a clean, fast implementation derived from zip_longest().

• There is some debate on a correct API for odd lengths. Some people
  want an exception, some want fill-in values, some want truncation, and
  some want a partially filled-in tuple. The alone is reason enough not
  to set one behavior in stone.

• There is an issue with having too many itertools. The module taken as
  a whole becomes more difficult to use as new tools are added.

[lieryan]

All implementations relying on zip or zip_longest breaks with infinite
iterable (e.g. itertools.count()).

And it is not impossible to define a clean, flexible, and familiar API
which will be similar to open()'s mode or unicode error mode. The modes
would be 'error' (default), 'pad', 'truncate', and 'partial' (maybe
should suggest a better name than 'partial')

There is an issue with having too many itertools.
The module taken as a whole becomes more
difficult to use as new tools are added.

It should also be weighed that a lot of people are expecting for this
kind of function in itertools. I think there are other functions in
itertools that have more questionable value than groupers, such as starmap.

[rhettinger]

All implementations relying on zip or zip_longest breaks
with infinite iterable (e.g. itertools.count()).

How is it broken?
Infinite in, infinite out.

>>> def grouper(n, iterable, fillvalue=None):
...    args = [iter(iterable)] * n
...    return zip_longest(*args, fillvalue=fillvalue)

>>> g = grouper(3, count())
>>> next(g)
(0, 1, 2)
>>> next(g)
(3, 4, 5)
>>> next(g)
(6, 7, 8)
>>> next(g)

And it is not impossible to define a clean, flexible,
and familiar API which will be similar to open()'s mode
or unicode error mode. The modes would be 'error'
(default), 'pad', 'truncate', and 'partial'

Of course, it's possible. I find that to be bad design. Generally, we
follow Guido's advice and create separate functions rather than overload
a single function with flags -- that is why we have filterfalse()
instead of a flag on filter(). When people suggest an API with multiple
flags, it can be a symptom of hyper-generalization where api complexity
gets substituted for writing a simple function that does what you want
in the first place. IMO, it is easier to learn the zip(g, g, g) idiom
and customize it to your own needs than to learn a new tool with four
flag options that control its output signature.