Web-Server-Logs-Analysis

By Narotam Singh

An internal reporting tool that will use information from the database ( contains newspaper articles, as well as the web server log for the site) to discover what kind of articles the site's readers like. The log has a database row for each time a reader loaded a web page.

Output of code:

Using above information, this code will answer following questions:

1. What are the most popular three articles of all time?
2. Who are the most popular article authors of all time?
3. On which days did more than 1% of requests lead to errors?

Requirements:

Python
Vagrant
Virtual Box
PostgreSQL

How to install and use:

• Install Virtual Box, Vagrant.
• Clone the VM configuration vm
• Download this repo Or Clone this repo into the /vagrant directory.
• Launch the VM:
  • $ vagrant up
• SSH into the VM:
  • $ vagrant ssh
• In the VM navigate to the /vagrant folder:
  • vagrant@vagrant:~$ cd /vagrant
• Download Data. The file inside is called newsdata.sql, put this file into the vagrant directory, which is shared with your virtual machine.
• Load the data into the news database already in the VM:
  • vagrant@vagrant:~$ psql -d news -f newsdata.sql
• Run application:
  • vagrant@vagrant:~$ python wlogs_analysis.py

Output: