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项目描述

ScanErrLog is a Python module that allows you to
parse Apache error_log files and present their
data in decreasing order of occurences of error
messages. This is particularly useful if you want
to quickly solve the most annoying problems Web
visitors encounter on your site. You can use it
directly from the command line, import it into
another Python program and use the classes it
defines, or use it as a CGI script. You can
produce reports in HTML, PDF, XML, or Plain Text
formats.

系统要求

System requirement is not defined
Information regarding Project Releases and Project Resources. Note that the information here is a quote from Freecode.com page, and the downloads themselves may not be hosted on OSDN.

2002-05-02 03:40
2.01

版权字符串已被更新。
标签: Minor feature enhancements
Copyright strings have been updated.

2001-04-23 21:43
2.00

过时的jahtml模块不再需要。此版本现在需要jaxml模块,版本2.22或更高,它工作正常的ReportLab 1.06。
标签: Major feature enhancements
The obsolete jahtml module is no longer needed. This release now requires the
jaxml module, version 2.22 or higher, and it works fine with ReportLab 1.06.

2001-01-30 15:13
1.9

阿失踪import语句导致程序崩溃立即(至少在Solaris)上一版本。这个版本修复了这个问题。
A missing import statement caused the previous release of the program to crash immediately (at least under Solaris). This version fixes this problem.

2001-01-30 15:13
1.8

当使用-继续选择,非法寻求错误是可能的,并坠毁在某些情况下的程序。此版本修正该错误。
When using the --continue option, an illegal seek error was possible, and crashed the program under certain circumstances. This release fixes that bug.

2001-01-30 15:13
1.7

一个新的选项(- ç | -继续)被添加到缓存统计之间在同一scanerrlog的许多运行文件,可能越来越高,文件。这一变化极大地提高分析性能,如果你解析多次相同的文件(如每天或每周)。这是不完全测试,但似乎运作良好。输入文件中读取的优化也做,大大提高对大文件的性能。
A new option (-c | --continue) was added to cache statistics in a file between many runs of ScanErrLog on the same, possibly ever growing, file. This change dramatically improves the parsing performance if you parse the same file many times (e.g. every day or week). This is not fully tested but seems to work well. Input file reading optimisations were also done, which greatly improve performance on big files.

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