Pigeon Rs

Open source email automation written in Rust

Digital Marketing & SEORustApache-2.0

Abstract

Pigeon Rs is an open-source Digital Marketing & SEO project. Open source email automation written in Rust. Pigeon is a command line tool for automating your email workflow in a cheap and efficient way. Utilize your most efficient dev tools you are already familiar with. It is built using Rust. The complete source code is publicly available on GitHub under the Apache License 2.0, making it a useful reference for students building a Digital Marketing & SEO mini project or final-year project.

1. Introduction

Pigeon is a command line tool for automating your email workflow in a cheap and efficient way. Utilize your most efficient dev tools you are already familiar with.

2. Objective

Open source email automation written in Rust

This project demonstrates how Rust can be applied to a real-world Digital Marketing & SEO problem.

4. Technology Stack

Rust

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

  • Rust toolchain (rustup / cargo)
  • Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/quambene/pigeon-rs.git
cd pigeon-rs
# Build and install pigeon binary to ~/.cargo/bin
cargo install pigeon-rs
# Clone repository
git clone git@github.com:quambene/pigeon-rs.git
cd pigeon-rs

# Build and install pigeon binary to ~/.cargo/bin
cargo install --path .
export PATH="$HOME/.cargo/bin:$PATH"
pigeon connect

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

  • Export reports to Google Sheets or PDF
  • Schedule weekly automated reports
  • Add competitor comparison

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

  1. Which marketing or SEO problem does this tool solve?
  2. Which data sources or APIs does it use (Search Console, Analytics, social platforms)?
  3. Which metrics or KPIs does it report and how are they calculated?
  4. How could the output help a business make decisions?
  5. How would you schedule it to run automatically?

9. Source Code & License

This project is developed by quambene and published on GitHub under the Apache License 2.0. Please follow the license terms and credit the original author when you use or modify this code.

Want to build this as your internship project?

Work on a Digital Marketing & SEO project like this with mentor guidance, weekly reviews and an internship certificate from Training Trains, Erode — online or offline.

Apply for Digital Marketing & SEO Internship