Skip to content

treyyi/Data-Engineering

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 

Repository files navigation

Data Pipeline of Facebook Artist Chatbot (Spotify API)

※ The scripts are from the last section of Fastcampus Data Engineering course, yet I, of course, typed and reviewed all the scripts for my understanding.

Summary

This is my first data engineering project with data pipeline example of Facebook Artist Chatbot Application. The chatbot provides top tracks and genres of the global artists through Spotify API in real time.

Environment

Type Details
Language Python 3.7, Shell
Storage AWS S3, EC2
RDBMS AWS RDS (MySQL)
NoSQL AWS DynamoDB
OS Ubuntu 14.05 (AWS EC2), Windows 10
API Call AWS Lambda
Log Monitoring AWS Cloud Watch
API Service AWS API Gateway
Library Pymysql, boto3, json, etc
Data Source Spotify API

Data Pipeline

How It Works

  1. Facebook Chatbot (Client)
    • Artist 이름을 챗봇에 입력한다.
  2. AWS Lambda Function

Project Review

DynamoDB를 top tracks를 업데이트하는 테이블로 사용한 이유는 무엇인가?

  • RDS와 DynamoDB의 차이점

그 외의 issues

  • Due to Covid-19, Facebook currently has paused to review and approve the apps for individual uses.

About

Data Engineering projects

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published