Search Results for "apache log analyzer"
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Showing 8 open source projects for "apache log analyzer"
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apache-logs-to-mysql
Apache Log Parser and Data Normalization Application
...Database system designed to accommodate unlimited domains. Step-by-step guide for easy installation. Web interface with Drill Down Capability and apache/echarts Log Visualization integration in development. MySQL apache_logs schema currently has 49 Tables, 853 Columns, 168 Indexes, 66 Views, 7 Stored Procedures and 43 Functions to process Apache Access log in 4 formats & Apache Error log in 2 formats. Database normalization at work! -
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PynDora
Python WebServer Log File Analyzer
This is a web log file analyzer we are making using python. First the IIS parsing engine wil be built and then Apache and possibly other servers. It is going to support multiple log files from any date and output the statistics in html formatted files, incorporating automatically build charts. It will be a pure python solution which is going to be self contained, ie no installation will be required other from the standard python modules. -
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FileZilla Log Analyzer
Project's new home: https://github.com/Stunner/FileZilla-Log-Analyzer
Python scripts that filter, parse, mask, and analyze FileZilla Server Log files. Works on Windows, Linux, and Mac systems. WARNING: NEW VERSIONS ARE BEING POSTED TO GITHUB HERE: https://github.com/Stunner/FileZilla-Log-Analyzer -
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Find out where your website visitors are from: generates statistics on hits per top level domain (e.g. .com, .org, .uk, .se, .fr). Currently works with apache log format, but can easily be extended to understand other formats. Written in vanilla Python.
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PyLogAlyzer is a Web Log Analyzer in Pure Python (a clone of Awstats). PyLogAlyzer produces a XML result and uses XSLT to generate the HTML files.
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A python based adaptive network analyzer. The aim of the project is to identify illegitimate uses of bandwidth in a network. Uses tshark for network data gathering.
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This is a collection of REST specifications, and implementations of those specs, for very low-level information sharing and workflow operations using REST actions over HTTP. Implementations are in various languages, mainly Java, Python, and Ruby.
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