Path: csiph.com!x330-a1.tempe.blueboxinc.net!usenet.pasdenom.info!aioe.org!feeder.news-service.com!newsfeed.xs4all.nl!newsfeed5.news.xs4all.nl!xs4all!newsgate.cistron.nl!newsgate.news.xs4all.nl!post.news.xs4all.nl!not-for-mail Return-Path: X-Original-To: python-list@python.org Delivered-To: python-list@mail.python.org X-Spam-Status: OK 0.093 X-Spam-Evidence: '*H*': 0.82; '*S*': 0.00; 'operator': 0.05; 'python': 0.07; '3.2.': 0.16; 'caveat': 0.16; 'comparisons,': 0.16; 'cc:no real name:2**0': 0.20; 'subject:list': 0.22; 'header:In-Reply- To:1': 0.22; 'cc:addr:python-list': 0.22; 'received:209.85.213': 0.23; 'list': 0.30; 'cc:addr:python.org': 0.31; 'cc:addr:gmail.com': 0.31; 'tuples': 0.31; 'import': 0.32; 'initial': 0.32; 'header:User-Agent:1': 0.35; 'items.': 0.35; 'some': 0.37; 'received:209.85': 0.37; 'time:': 0.38; 'received:google.com': 0.38; 'cc:2**1': 0.38; 'under': 0.39; 'received:209': 0.39; '(3)': 0.64; '(4)': 0.65; 'to:addr:googlegroups.com': 0.69; 'reply-to:no real name:2**0': 0.72; 'header:Reply-To:1': 0.72; '(5)': 0.77; 'reply- to:addr:googlegroups.com': 0.93 Newsgroups: comp.lang.python Date: Tue, 26 Apr 2011 12:39:32 -0700 (PDT) In-Reply-To: Complaints-To: groups-abuse@google.com Injection-Info: glegroupsg2000goo.googlegroups.com; posting-host=207.229.149.157; posting-account=yjzYUgoAAAB_PKEzWUqDhDdSzxKMCeMa User-Agent: G2/1.0 MIME-Version: 1.0 Subject: Re: De-tupleizing a list From: Mark Niemczyk To: comp.lang.python@googlegroups.com Content-Type: text/plain; charset=ISO-8859-1 Cc: python-list@python.org, Gnarlodious X-BeenThere: python-list@python.org X-Mailman-Version: 2.1.12 Precedence: list Reply-To: comp.lang.python@googlegroups.com List-Id: General discussion list for the Python programming language List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , Message-ID: Lines: 23 NNTP-Posting-Host: 82.94.164.166 X-Trace: 1303847501 news.xs4all.nl 81482 [::ffff:82.94.164.166]:40502 X-Complaints-To: abuse@xs4all.nl Xref: x330-a1.tempe.blueboxinc.net comp.lang.python:4074 Some interesting performance comparisons, under Python 3.2. Times are relative, and are for an initial list of tuples with 500,000 items. (1) ans = [] #relative time: 298 for item in lst: ans += list(item) return ans (2) return [item[0] for item in lst] #relative time: 106 (3) from operator import itemgetter #relative time: 84 return list(map(itemgetter(0), lst)) (4) import itertools #relative time: 63 return list(itertools.chain.from_iterable(lst)) (5) return [x for (x,) in lst] #relative time: 52 With the caveat that 'your mileage may vary' Regards, Mark