/logs_analysis

Udacity Full Stack Web Developer Nanodegree Program - Project 1

Primary LanguagePython

Project 1: Logs Analysis

This project uses Python and psycopg2 to query a mock PostgreSQL database for a fictional news website. The database has the following three tables:

  • articles: Data on articles' author, title, slug, lead, body, time, and id.
  • authors: Data on authors' names, bios, and id.
  • log: Logged data of every instance of users' calls to the news website, including path, ip, method, status code, timestamp, and log id.

When executing the analayze.py script, queries are run that answer 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?

The results are printed to stdout in the terminal.

Requirements

To run this program, you will need Python >=3.6, along with psycopg2 and PostgreSQL.

Program design

The general design of this program (analyze.py) is as follows:

  • Import statements
  • SQL queries for each question
  • Functions to run each query and format the output in Python

How to run

  1. Create and activate an environment (I recommend conda) with the following:
  • python >=3.6
  • psycopg2
  • postgresql (if you don't already have this installed on your system)

  1. Clone this repo and cd into it.

  2. From the repo directory, download the newsdata.zip file that will create your mock database.

  3. Unzip the newsdata.zip file. Afterwards, you should have a newsdata.sql file.

  4. Run this postgres command to create your database using the newsdata.sql file:

psql -d news -f newsdata.sql
  1. Now run the Python script, which queries the database:
python analyze.py