Path: csiph.com!usenet.pasdenom.info!gegeweb.org!de-l.enfer-du-nord.net!feeder1.enfer-du-nord.net!feeds.phibee-telecom.net!newsfeed.xs4all.nl!newsfeed6.news.xs4all.nl!xs4all!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 0.007 X-Spam-Evidence: '*H*': 0.99; '*S*': 0.00; 'ascii': 0.07; 'dict': 0.09; 'eof': 0.09; 'from:addr:python': 0.09; 'subject:file': 0.13; 'code?': 0.16; 'from:addr:mrabarnett.plus.com': 0.16; 'from:name:mrab': 0.16; 'message-id:@mrabarnett.plus.com': 0.16; 'received:84.92': 0.16; 'received:84.92.122': 0.16; 'received:84.92.122.60': 0.16; 'received:84.93': 0.16; 'received:84.93.230': 0.16; 'reply-to:addr:python-list': 0.16; 'sqlite3': 0.16; 'stokes': 0.16; 'wrote:': 0.18; 'file,': 0.21; 'header:In-Reply-To:1': 0.22; 'subject:data': 0.25; 'position.': 0.28; 'module.': 0.29; 'retrieval': 0.29; 'lines': 0.30; 'subject:?': 0.31; 'file.': 0.31; 'that,': 0.32; 'there': 0.33; 'header:User-Agent:1': 0.33; 'file': 0.34; 'received:84': 0.34; 'rather': 0.34; 'reply-to:addr:python.org': 0.34; 'structured': 0.34; 'probably': 0.35; 'to:addr:python-list': 0.35; '...': 0.35; 'sets': 0.35; 'offset': 0.37; 'could': 0.38; 'several': 0.38; 'data': 0.38; 'header': 0.39; 'put': 0.40; 'to:addr:python.org': 0.40; 'alphanumeric': 0.67; 'header:Reply-To:1': 0.70; 'reply- to:no real name:2**0': 0.72; 'database.': 0.74; 'thousand': 0.74; 'subject:Fast': 0.84 X-CM-Score: 0.00 X-CNFS-Analysis: v=2.0 cv=ZZifx7pA c=1 sm=1 a=0nF1XD0wxitMEM03M9B4ZQ==:17 a=qePWxsfFzlIA:10 a=HHWZFyI3HAYA:10 a=OUOv7kDek9cA:10 a=8nJEP1OIZ-IA:10 a=KWwk8Mge0Q1A-kRXCDoA:9 a=wPNLvfGTeEIA:10 a=0nF1XD0wxitMEM03M9B4ZQ==:117 X-AUTH: mrabarnett:2500 Date: Mon, 12 Mar 2012 20:31:35 +0000 From: MRAB User-Agent: Mozilla/5.0 (Windows NT 5.1; rv:10.0.2) Gecko/20120216 Thunderbird/10.0.2 MIME-Version: 1.0 To: python-list@python.org Subject: Re: Fast file data retrieval? References: <4F5E50F6.9070309@it.uu.se> In-Reply-To: <4F5E50F6.9070309@it.uu.se> Content-Type: text/plain; charset=ISO-8859-1; format=flowed Content-Transfer-Encoding: 7bit X-BeenThere: python-list@python.org X-Mailman-Version: 2.1.12 Precedence: list Reply-To: python-list@python.org List-Id: General discussion list for the Python programming language List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , Newsgroups: comp.lang.python Message-ID: Lines: 28 NNTP-Posting-Host: 2001:888:2000:d::a6 X-Trace: 1331584145 news.xs4all.nl 6877 [2001:888:2000:d::a6]:37489 X-Complaints-To: abuse@xs4all.nl Xref: csiph.com comp.lang.python:21544 On 12/03/2012 19:39, Virgil Stokes wrote: > I have a rather large ASCII file that is structured as follows > > header line > 9 nonblank lines with alphanumeric data > header line > 9 nonblank lines with alphanumeric data > ... > ... > ... > header line > 9 nonblank lines with alphanumeric data > EOF > > where, a data set contains 10 lines (header + 9 nonblank) and there can > be several thousand > data sets in a single file. In addition,*each header has a* *unique ID > code*. > > Is there a fast method for the retrieval of a data set from this large > file given its ID code? > Probably the best solution is to put it into a database. Have a look at the sqlite3 module. Alternatively, you could scan the file, recording the ID and the file offset in a dict so that, given an ID, you can seek directly to that file position.