Search Results for "website using python"
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Showing 9 open source projects for "website using python"
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Exchange Server SMTP Logs Viewer
Read Exchange Server SMTP Send and Receive Logs
The Exchange Server SMTP Log Viewer is a graphical tool developed using Python. It is designed to help system administrators and developers analyze SMTP server logs efficiently. -
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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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LogCrawler is an ANT task for automatic testing of web applications. Using a HTTP crawler it visits all pages of a website and checks the server logfiles for errors. Use it as a "smoketest" with your CI system like CruiseControl.
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WebStats dotNet generates website statistics and analytics from IIS http log files. Best of all, it's all free and licensed under the LGPL. Gui is webbased written in C# using ASP.NET. The core of the software is designed in C# as a class library.
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RRFiller provides an easy-to-use solution for logging statistics into an RRDTool database. Designed to complement RRGrapher, the project also provides configurations for creation and updating RRD databases using standard tools like vmstat and netstat.
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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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Probe is a website-usage analysis tool. It 'probes' (logs) certain pages being viewed by a visitor, without needing access to log-files from the web-server and produces a web-page with statistics using bargraphs.
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This is my Master Degree project, I am trying to improve the movie prediction by using machine learning techniques, for the Netflix data set. This project is done under guidance of Dr. Richard Maclin, at University of Minnesota Duluth.
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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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