Consumption app (cons_app)

Author

Manu García, MSc in Data Science and Data Scientist.

Introduction

This app has the aim of deploying the social media consumption index into a server and visualize it.

Technologies used

• Python and postgresSQL.
• Docker.
• json backups format.

Repository structure

SMI_0_database folder

Docker container service that mounts and fills a postgres database. It creates all the database structure, schema, tables and variables.

More explanation about the process is explained in the readme of the SMI_0_database folder.

SMI_1_users folder

Docker container service that retrieves friends and followers from a users list. Given a user list, it retrieves all its friends and followers and it stores them in the database.

SMI_2_tweets folder

Docker container service that retrieves all the tweets from a user list. Given a period range, it retrieves all the tweets and stores them in the database.

SMI_3_model folder

Docker container service to train a classification supervised model. Given a labeled dataset, it executes a machine learning modelling pipeline.

SMI_4_visual folder

(to think about...)