Log Analysis

Overview

This is the project for Udacity Intro to Programing Nano Degree - Back-End Development. In this project, you will use PostgresSQL to build an internal reporting tool that will use information from a large database to discover what kind of articles the site's readers like. The database has the following 3 tables:

• articles - articles that has been posted so far
• authors - a list of the authors
• log - log records that sent to server (>1,000K rows)

Run the code from main.py you will find the answer of the 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?

Ton Run

What you need:

• Python 2.7
• Vagrent
• VirtualBox
• Git

Step by step:

1. Set up VirtualBox & Vagrant
2. Download or clone the FSND-VM repository
3. Download data
4. Unzip the file, move newsdata.sql into vagrant folder
5. Load the data into your local database with psql -d news -f newsdata.sql
6. Connect to your database using psql -d news, then you can explore the tables
7. Run the code python main.py
8. The output will be displayed in the bash

Launching virtual machine:

1. Go into the downloaded fullstack-nanodegree-vm repository enter command:

  $ vagrant up

2. Log in using command:

  $ vagrant ssh

3. Change directory to vagrant using command:

  $ cd /vagrant