Logs Analysis Udacity Project ⭐

This is my Logs Analysis project for Udacity's Full Stack Developer Nanodegree.

It is a Python script using psycopg2 to run queries on a mock PostgreSQL database for a fictional news website.

It generates a console output for three reports:

1. Top 3 articles, most viewed first.
2. Most popular authors, most viewed first.
3. Days above 1% request errors

Mock database structure

Table "authors"

Column	Type
name	text
bio	text
id	integer

Primary key:

• id

Table "articles"

Column	Type
author	integer
title	text
slug	text
lead	text
body	text
time	timestamp with time zone
id	integer

Primary key:

• id

Foreign-key:

• author REFERENCES authors(id)

Table "log"

Column	Type
path	text
ip	inet
method	text
status	text
time	timestamp with time zone
id	integer

Primary key:

• id

Installation ☕

Prerequisites: 🎮

• Installed VirtualBox
• Installed Vagrant
• Downloaded VM from Udacity
• Downloaded DB for news database (newsdata.sql)

Environment setup 💥

1. Unzup and copy the newsdata.sql file from newsdata.zip to your vagrant directory
2. Start the VM using your console in the downloaded Vagrant VM's directory using vagrant up
3. SSH into your VM using vagrant ssh
4. To load the data, cd into the vagrant directory and use the command psql -d news -f newsdata.sql

Application setup 👋

1. Create a new directory in vagrant's shared directory (i.e.: ../vagrant/logs_analysis/)
2. Clone the repository and put it into the previously created directory. (i.e.: ../vagrant/logs_analysis/)

Usage 💻

1. SSH into your VM using vagrant ssh
2. cd into the created folder (i.e.: /vagrant/logs_analysis)
3. Run ./reporting.py

An example of the output can be seen in output_example.txt

License

Copyright (c) 2017 Péter Szabó. All rights reserved.

This work is licensed under the terms of the MIT license.
For a copy, see https://opensource.org/licenses/MIT.