tweets-docker-pipeline VS Airflow

First, I created an app on Twitter and got my credentials (API key and Access Token). Then, I wrote the Python code for streaming live tweets, using tweepy with my Twitter credentials. I chose to stream the hashtag #OnThisDay (thought it would be interesting to get a daily notification of what happened years ago) and collected the tweet text and user handle.

I was really excited, though also a bit overwhelmed by all the things I had to set up for this project. In total, I spent five days learning the tools, debugging, and building this pipeline with Python (including libraries like Tweepy, TextBlob, VADER, and SQLAlchemy), Postgres, MongoDB, Docker, and Airflow (most frustrating part...). If you're interested to see how I did this, you can check out the project on GitHub and read this blog post.

Contributing to Apache Airflow's open-source project immersed me in collaborative coding. Experienced maintainers rigorously reviewed my contributions, providing constructive feedback. This ongoing dialogue refined the codebase and honed my understanding of best practices.

In week Two, I contributed to the Apache Airflow repository.

Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. The platform features a web-based user interface and a command-line interface for managing and triggering workflows.

Airflow is the most widely used and well-known tool for orchestrating data workflows. It allows for efficient pipeline construction, scheduling, and monitoring.

AIRFLOW This is more of a library in my opinion, but Airflow has become an essential tool for scheduling in my work. All our ML training pipelines are ordered and scheduled with Airflow and it works seamlessly. The dashboard provided is also fantastic!

I agree there are many options in this space. Two others to consider:

- https://airflow.apache.org/

- https://github.com/spotify/luigi

There are also many Kubernetes based options out there. For the specific use case you specified, you might even consider a plain old Makefile and incrond if you expect these all to run on a single host and be triggered by a new file showing up in a directory…

You can try and contribute some new connectors/operators for workflow managers like Airflow or Airbyte