From 91c6e5b48dd8ae4ff8e210608e87f6eca800ec31 Mon Sep 17 00:00:00 2001 From: Akshay Khadse Date: Fri, 2 Dec 2016 02:20:43 +0530 Subject: [PATCH] Delete params.json --- params.json | 6 ------ 1 file changed, 6 deletions(-) delete mode 100644 params.json diff --git a/params.json b/params.json deleted file mode 100644 index a4cb3b1..0000000 --- a/params.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "name": "Matlab-usage-stats", - "tagline": "This is the repository for second course project of SDES course.", - "body": "# Matlab Usage Statistics\r\n[![Build Status](https://travis-ci.org/akshaykhadse/matlab-usage-stats.svg?branch=master)](https://travis-ci.org/akshaykhadse/matlab-usage-stats)\r\n[![Coverage Status](https://coveralls.io/repos/github/akshaykhadse/matlab-usage-stats/badge.svg?branch=master)](https://coveralls.io/github/akshaykhadse/matlab-usage-stats?branch=master)\r\n[![Documentation Status](https://readthedocs.org/projects/matlab-usage-stats/badge/?version=latest)](http://matlab-usage-stats.readthedocs.io/en/latest/?badge=latest)\r\n\r\nIntroduction\r\n============\r\n\r\nMatlab Usage Stats is a django based project to aggregate statistics FlexLM based MATLAB License Server logs.\r\n\r\nMATLAB License Server does not provide and option to track users IP addresses. So, there is no way in which one can analyse usage in terms of users departments or category.\r\n\r\nThis project provides a way to analyse the originally produced MATLAB debug logs along with port activity log and login portal log.\r\n\r\nThis Django project has two apps, parser and reports.\r\n\r\nThe parser app takes care of processing the logs and creating database entries which will then be processed by the reports app to generate different graphs based on the toolboxes that matlab provides and the departments.\r\n\r\nThere are four types of reports:\r\n\r\n- `/reports/list/` - List view of all entries\r\n- `/reports/graphs/` - Stacked Bar view of all entries\r\n- `/reports/departments/` - Bar Graph view of all entries from selected departments\r\n- `/reports/time/` - Stacked Bar Graph view of all entries from selected time frame\r\n\r\nHow to Use\r\n==========\r\n\r\n- Setup the project using **`$ python3 setup.py install`**\r\n- Download or Clone the source code from [here](https://github.com/akshaykhadse/matlab-usage-stats/)\r\n- Copy the data files to **`data/`** folder. Data files should be as follows:\r\n\r\n - **`LM_TMW.log`** - MATLAB Debug Log file\r\n - **`src_ip_log`** - Port activity log file with timestamp and IP coloumns\r\n - **`matlab_DB_active.csv`** - CSV file genrated from database `active` table\r\n - **`matlab_DB_archive.csv`** - CSV file generated from database `archive` table\r\n\r\n Sample data files can be downloaded [here](https://drive.google.com/drive/folders/0B8bbv1FqBgBVZ1NBdWE4VGd2Zlk?usp=sharing)\r\n\r\n- Create database by **`$ make migrate`**\r\n- To update entries use **`$ make update`**\r\n\r\n (This command needs to be run whenever log files are changed)\r\n\r\n- To start web interface **`$ make run`**\r\n\r\nDocumentation\r\n=============\r\nDocs for this project can be found [here](https://matlab-usage-stats.readthedocs.io/)\r\n\r\nRequirements\r\n============\r\n\r\n- flake8>=3.2.0\r\n- ldap3>=1.4.0\r\n- django>=1.10\r\n- coverage>=4.2\r\n- coveralls>=1.1\r\n- plotly>=1.12.9\r\n- sphinx>=1.4.8\r\n", - "note": "Don't delete this file! It's used internally to help with page regeneration." -} \ No newline at end of file