ebay_research's Introduction

Genius Bidding

Web App to analyze market places on eBay

Functionality:

Explore eBay market places using 9 item filters to get a variety of statistics, plots, datasets as well as photos and links to the most popular items.
Set specific searches to run at regular intervals to track statistics over time.
Track prices and market indicators through customized and automated search results.
Gain insights into top sellers, how they're marketing their products, and important trends.
Download unique data sets with 50+ variables.
User registration, authentication, and automated email notifications.

Note: if you are going to use Genius Bidding, make sure you abide by eBay's API terms and conditions.

About Genius Bidding:

I built Genius Bidding in 2019 as a personal project and hosted it on AWS elastic beanstalk for a couple of months. Backend is written in Python with vanilla JS, HTML, and CSS on the front.

When hosted, Genius Bidding used the following technologies:

Flask, sqlAlchemy
PostgreSQL
AWS: S3, Elastic Beanstalk, Route 53, RDS
cron - for running recurring searches
Sentry

The UI

Landing Page

Search Page

Search Page w/ Results

Account Page w/ search history

Trends Page

Login Page

To run locally:

Set the following ENV variables:

export APP_SETTINGS=development
export EBAY_API="YOUR_EBAY_API_KEY"
export FLASK_ENV=development
export SECRET_KEY="A_SECRET_KEY_FOR_FLASE"
export DATABASE_URL="postgresql://localhost/ebay_research" # set up your local DB
export FLASK_APP=run.py
export [email protected]
export MAIL_PASSWORD=email_password
export MAIL_SERVER=smtp.gmail.com
export MAIL_USE_TLS=1
export MAIL_PORT=587
export [email protected]
export AWS_SECRET_ACCESS_KEY=SECRET_KEY_IF_USING_AWS
export AWS_ACCESS_KEY_ID=AWS_ACCESS_KEY_IF_USING
export S3_DIRECTORY=S3_DIRECTORY_IF_USING

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