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Automated Monthly Rent Calculator

A simple AWS-powered service that automates the monthly calculation of rent for my apartment and sends an email report. This script can be run locally or deployed via AWS.

I like to automate things and I had to find an excuse to use my AWS Cloud Practitioner knowledge lol.

Table of Contents

1. About The Project
   • The Story
   • Built With
2. Getting Started
   • Prerequisites
   • Installation
3. Usage
4. What I Learned
5. Roadmap
6. Contact

About The Project

Every month, I used to manually enter rent details into a local Excel sheet and then send a group text to my roommates with the updated figures. This repetitive process was not only time-consuming but also error-prone.

After earning my AWS Cloud Practitioner Certification, I saw an opportunity to build a simple AWS service that automates this process. This project uses AWS Lambda (triggered by a monthly CRON schedule), CodeBuild, CodePipeline, and CodeDeploy to:

• Scrape my rent portal for the latest balance using Selenium.
• Calculate the rent share based on predefined parameters.
• Send an email with a detailed monthly rent calculation report.

The Story

I embarked on this project to solve a practical problem in my everyday life. Managing rent and splitting costs among roommates is just kinda annoying. I love automating tedious tasks and figured this would be a good way to actually make use of my Cloud Practitioner knowledge, so I hammered some AWS services in here.

Built With

• AWS Lambda – Serverless compute to run the monthly task.
• AWS CodeBuild – To package the project.
• AWS CodePipeline – To automate deployment from GitHub.
• AWS CodeDeploy – For updating the Lambda function.
• Python 3.10 – The programming language used.
• Selenium – For web scraping the rent portal.
• Boto3 – AWS SDK for Python.
• AWS SES – To send email reports.

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Getting Started

I will provide configuration steps on how to set up the project for deployment with AWS.

Prerequisites

• AWS Account with access to Lambda, CodeBuild, CodePipeline, CodeDeploy, and SES.
• Python 3.10 installed locally.
• Git installed.
• Download the Chrome Labs Chromium Binary to run Selenium here.
  • If you don't want to peruse the versions, here is version 1.33.0.6943.53 for Win64.
• Selenium WebDriver and appropriate binaries for headless Chrome (for local testing).
• AWS CLI configured with appropriate IAM permissions.

Installation

1. Clone the Repository

   git clone https://github.com/your_github_username/Automated-Monthly-Rent-Calculator.git
   cd Automated-Monthly-Rent-Calculator

2. Install Python Dependencies

   pip install -r requirements.txt

3. Refer to the deployment.md file for further instructions on AWS. I did not want to clutter this README with a vast amount of instructions.

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Usage

This project runs as a monthly CRON job on AWS Lambda. Here’s how it works:

1. Monthly Trigger:

   • The Lambda function is scheduled to run once a month using an AWS CRON expression (via CloudWatch Events/EventBridge).

2. Rent Data Collection:

   • When triggered, the Lambda function calls the Selenium scraper (rent_scraper.py), which logs into the rent portal, scrapes the current balance, and returns the data.

3. Calculation and Reporting:

   • The main handler in lambda_function.py combines the scraped data with static rent calculations and creates an email report.

4. Email Notification:

   • The report is sent to the designated email address using AWS SES.

5. CI/CD Pipeline:

   • CodePipeline and CodeBuild automatically update the Lambda function whenever code is pushed to GitHub.

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What I Learned

1. AWS Cloud Services Integration:

   • I gained hands-on experience with AWS Lambda, CodeBuild, CodePipeline, CodeDeploy by automating deployments from GitHub.

2. Serverless Architecture:

   • I learned how to build and deploy a serverless application that handles scheduled tasks and integrates multiple AWS services.

3. Selenium Web Scraping:

   • I improved my skills with Selenium for automating browser interactions and scraping dynamic web pages.

4. Problem Solving & Automation:

   • I transformed a tedious, manual process into an automated solution, showcasing an entrepreneurial mindset and efficient problem solving.

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Roadmap

1. Local Script Usage:

   • Add a separate directory with files to run this script locally instead of needing to rely on AWS, in the case of hitting free monthly usage limits like I currently have due to debugging.

2. Basic Automation:

   • Automate monthly rent calculation and email reporting using AWS Lambda, SES, and scheduled CRON jobs. I am currently waiting for my AWS monthly free usage limits to reset for AWS CodeBuild and AWS CodePipeline.

3. Complete CI/CD Integration:

   • Fully integrate CodePipeline and CodeBuild to automatically update the Lambda function.

4. Secure Credential Management:

   • Integrate AWS Secrets Manager for secure handling of login credentials.

5. Enhanced Error Handling:

   • Improve logging and error notifications for the Selenium scraper.

6. Portfolio Documentation:

   • Expand documentation and add examples to better showcase this project in my personal portfolio.

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Contact

• Feel free to reach me at [email protected]

• Project Link: https://github.com/Defconn4/RentAutoCalculator

• LinkedIn: https://www.linkedin.com/in/frank-costantino-a4a61b133/

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