On 28Jun2017 09:54, Paul Moore <p.f.mo...@gmail.com> wrote:
On 28 June 2017 at 05:30, Terry Reedy <tjre...@udel.edu> wrote:
On 6/27/2017 10:47 PM, Nick Coghlan wrote:
While I haven't been following this thread closely, I'd like to note
that arguing for a "chain()" builtin has the virtue that would just be
arguing for the promotion of the existing itertools.chain function
into the builtin namespace.
Such an approach has a lot to recommend it:
1. It has precedent, in that Python 3's map(), filter(), and zip(),
are essentially Python 2's itertools.imap(), ifilter(), and izip()
2. There's no need for a naming or semantics debate, as we'd just be
promoting an established standard library API into the builtin
namespace
A counter-argument is that there are other itertools that deserve promotion,
by usage, even more. But we need to see comparisons from more that one
limited corpus.
Indeed. I don't recall *ever* using itertools.chain myself. I'd be
interested in seeing some usage stats to support this proposal. As an
example, I see 8 uses of itertools.chain in pip and its various
vendored packages, as opposed to around 30 uses of map (plus however
many list comprehensions are used in place of maps). On a very brief
scan, it looks like the various other itertools are used less than
chain, but with only 8 uses of chain, it's not really possible to read
anything more into the relative frequencies.
I don't use it often, but when I do it is very handy. While I'm not arguing for
making it a builtin on the basis of my own use (though I've no objections
either), a quick grep shows:
My maildb kit uses chain to assemble multiple related header values:
*chain( msg.get_all(hdr, [])
for hdr
in ('to', 'cc', 'bcc', 'resent-to', 'resent-cc') )
Two examples where I use it to insert items in front of an iterable:
chunks = chain( [data], chunks )
blocks = indirect_blocks(chain( ( topblock, nexttopblock ), blocks ))
Neither of these is amenable to list rephrasings because the tail iterables
("chunks" and "blocks") are of unknown and potentially large size.
And a few other cases whose uses are harder to succinctly describe, but
generally "iterable flattening".
So it is uncommon for me, but very useful when I want it.
Just some (small) data points.
Cheers,
Cameron Simpson <c...@zip.com.au>
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