A Dockerized Data Pipeline for Sentiment Analysis on tweets

There are 5 steps in the data pipeline:

• Extract tweets with Tweepy API
• Loaded the tweets in a MongoDB
• Extracted the tweets from MongoDB, performed sentiment analysis on the tweets, and loaded the transformed data in a PostgresDB (ETL job)
• Loaded the tweets and corresponding sentiment assessment in a PostgresDB
• Extracted the data from the PostgresDB and posted it in a slack channel with a Slack bot

Usage

• Install Docker on your machine
• Clone the repository: git clone https://github.com/miladbehrooz/Dockerized_Data_Pipeline.git
• Get credentials for Twitter API and insert them in tweet_collector/credentials.py
• Get credentials for Slack bot and insert them in slack_bot/credentials.py
• Run docker-compose build, then docker-compose up in terminal