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A log analyzer to extract analytic reports of usage
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A log grinder to extract statistics and more

What it does

  1. A backend python log grinder to analyze, extract and compute information, generating JSON files with different content like:
  • a distinct list of URLs with a count visit number taken from the log files. See the algorithm here
  • a distinct list of URLs with the count visit number taking the list from a given URLs router map file and counting the occurrencies of those URLs within the log files. See the algorithm here
  • a from-to pattern pair of urls starting from the log files, extracting relevant URLs grouped by the same user/ip, and counting the occurrencies of each from-to pattern. See the algorithm here
  1. A web dashboard to view results from the backend analysis with some filtering options

How to use

Get the source project

git clone
cd logorator


You may want to configure parameters in the logorator.conf file first.


Important: changing location of files within this application, stats_file for instance, will make the dashboard web page unable to load data. Please make sure you will update the json source file name accordingly for each page.

Backend: python analyzer


The program makes an assumption about your log format expecting log lines with the request information containing the url wrapped between "", something like the following: - - [19/Oct/2017:11:00:16 +0200] "POST /my/url/path HTTP/1.1" 200 334

The relies on the output of and on the output it generates itself from a given .xml map files with

    <action path=""></action>

element tags for the list of known routes.

The relies on more than one assumption instead:

  • the ip address
  • the date and time format
  • the url


Everything in one shot

cd logorator
python backend/

*Note: in case you miss to populate some configuration parameter values, the related elaboration will not be executed"

Frontend: dashboard web page

Available pages:

  • Raw Stats - How many times your urls have been hitten?
  • Known route Stats - Which known routes have been hit the most, and which never?
  • Refined Patterns - Frequent patterns workflow


  1. Nodejs
  2. Yarn


cd logorator/dashboard
yarn install
yarn start
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