PoliAgg

the goal is to create a website to aggregates information of all federal congressmen and congresswoman including their past positions in the federal

Django

The main framework for the website run with Python3

• generated a MySQL database
• dynamic webpages using JavaScript and custom CSS
• Separate modules for different services
• integrated twitter API
• integrated Django backend to interact with AWS services

AWS

Server Diagram

Acquired AWS Cloud Practitioner Certification

EC2

• Managed Configurations through userdata.sh shell script
• Briefly touched Autoscaling groups for PoliAgg webserver
• Strong grasp on differences between AWS Instance Types

S3

stores more static information concerning the website such as images and the code repository.

• used to host git repository for PoliAgg
• configured to save static information in PoliAgg

RDS

Holds all the tables concerning the people in congress and the data presented in the website with initial population using python web-scraper script

• MySQL / Aurora

Lambda

• Pulled down info from congress.gov and updated RDS instance
• Updated relevant info when certain item was called in Django by

VPC

• Secured private and public subnets in order for RDS and server to communicate without exposing RDS to public internet
• Generated route table to allow communication between subnets and internet

IAM

• Created IAM policies and roles to allow access from various AWS resources to other AWS resources

CodeDeploy / Code Pipeline (CI/CD Pipeline)

• Automatically updates/creates web server when git repository is updated

Scripts

• Bash script to download latest districts maps from government convert them into JSON files then separate the JSON into individual States for each of the districts
• Python webscraper that handles dynamic calling of resources from both congress.gov and clerk.house.gov compiled into zip files to run in AWS Lambda