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Our Software Engineering Web Application Project

Home Page: sweatshop.tech

HTML 68.99% CSS 4.80% Python 16.72% API Blueprint 6.31% Makefile 0.42% Shell 0.02% JavaScript 2.74%
flask jinja2 python html5 css3 travis-ci api website postgresql ec2

idb's Introduction

sweatshop.tech Build Status  Code Climate Test Coverage Issue Count

The Problem

Have you ever had a brilliant idea and wanted to create your own company but didn’t know if a similar business already existed? Have you ever wanted to quickly find potential investors to fund your idea? Have you ever been curious about which schools had the most notable graduates from which you could recruit employees? SWEatshop aims to aggregate, organize, and display helpful data about companies, people, investors, and schools in order to ease the process from having an idea to getting your startup up and running!

Use Cases

A potential user of SWEatshop could be a college student who comes up with the idea of a new social network for pets and pet owners. Unfortunately, she doesn’t know if there already exists such a company. Google is too vast, not specific enough, and too daunting for such a task. She can then go on sweatshop.tech, click on our companies tab and sort the companies by category. She could also look for companies with the keyword “pet” to begin her research.

Another user could be the founder of a small startup company who is in need of more investors. The founder can simply go to SWEatshop’s investor tab and start looking for investors. He could filter by categories to find companies that are similar to his, then check who invested in them. He could also search for investors by the amount of funding or even their location to find some that might best suit his business.

Say there is a company recruiter who is tasked with finding potential new interns for the summer. If he had no information to specify where to start looking, he could use SWEatshop to find schools from which his company has already recruited by filtering schools by company. He could also filter companies to find similar businesses, then check what schools they have commonly recruited from already. He could even search people to find schools from which successful employees have graduated from and start his recruiting from there.

Another use case is a CEO of a new startup in Austin who needs advice on how to run the financial aspects of his new company. Perhaps he would like to ask some advice from a peer who has experience in his business field. In SWEatshop, he can search for all sorts of people by job title, location, name, etc. In this example he could filter for CFOs who are located in Austin, TX. He then would be able to contact CFOs around Austin and be able to set up a meeting with one of them to give him some advice or maybe even meet hiring prospects.

How about a college senior from the University of Texas at Austin with several job offers from big companies and startup companies? Said student wants do further research on the companies to help him make a final decision. If the student is unsure about the stability of his job at a startup company, he can search for the company he is interested in, see how much funding that company has and who the investors are. He can also learn more about the background of the CEO and other people who work at that company.

Another test case is that of a well established company who has started to see a decline in their sales. They assign someone to research why this is happening. This employee wants to find out if there are growing companies in the same field as their own business that could be creating competition. The employee can visit SWEatshop.tech and filter companies by categories. Furthermore, they can know exactly what they do through the description that is provided and can even research some of the people that work for the company.

idb's People

Contributors

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idb's Issues

Card links ordering

Card link orders in template files seems arbitrary. Figure out why and fix.

Scrape Crunchbase

Models: Company

  • Location
  • Size
  • Category
  • Public/Private
  • Description
  • Funding
  • CEO
  • Investors
  • Logo
    (Connected to People and Investors)

People

  • Job Title
  • Company
  • Gender
  • Location
  • DOB
  • Website
  • Profile Picture
  • Social Links
  • Schools
    (Connected to Companies and Schools)

Investors

  • Name
  • CEO
  • Invested in (Companies)
  • Money Invested
  • Location
  • Logo
  • Website
  • Description
    (Connected to Companies and People)

Schools

  • Name
  • Location
  • Logo
  • Website
  • Notable Graduates (People)
  • Investors
    (Connected to People and Investors)

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