The third project into the Udacity's Full Stack Developer Nanodegree.
This isn't a commercial project and has only academic purposes.
This is an internal reporting tool that uses information from a database to discover specific informations about users and they preference.
It analyzes a fictional newspaper site that is already running on and creating logs in a database when some page get accessed.
The solution was written using Python and PostgreSQL.
It explores basics concepts about:
- Connections between an application and a database server
- Querying and manipulating data (filtering, grouping, parsing)
- Use of imports, native modules of Python
- Isolation between application and the database server
- Formatting data to a better application's output
- Error handling
These are the questions the reporting tool should answer:
- What are the most popular three articles of all time?
- Who are the most popular article authors of all time?
- On which days did more than 1% of requests lead to errors?
The project will run inside a virtual machine provided by VirtualBox and managed by Vagrant
The Vagrantfile will be used to set the VM configuration.
With the VM built with this file and running up, we are ready to go.
The Python language can be used with versions 2 and 3.
The PostgreSQL relational database can be used in the most recent versions.
The newsdata.sql file provided by Udacity. Download link.
1- Clone the repo to a folder on your local machine:
$ git clone https://github.com/reismatheus97/log-analysis-project.git
2- Get into the project's folder:
$ cd log-analysis-project
3- Copy log-analysis-project.py and newsdata.sql and paste both into the vagrant shared directory inside your virtual machine.
4- Connect to your VM and get into the vagrant shared directory:
$ cd / & cd /vagrant
5- Set the data:
psql -d news -f newsdata.sql
6- Then, run:
$ python log-analysis-project.py