High Rise is a full-stack web application for accessing a database of information about the tallest skyscrapers in the United States. It is a class project from CS257 (taught by Jeff Ondich at Carleton College), completed collaboratively with Ellie Mamantov. It consists of a normalized PostgreSQL database, accessible by API calls, and a clear and interactive user interface with advanced search, ranking, and sorting capabilities.
A rich dataset of skyscraper information stored in a normalized PostgreSQL database. This dataset includes the height, construction year, location, purpose, and materials used to build a given skyscraper, as extracted from the original dataset found at https://think.cs.vt.edu/corgis/csv/skyscrapers/skyscrapers.html. CSV files corresponding to the database tables can be found in the data folder, as well as a .sql dump file for the database, the original raw data in CSV form, and Python code for converting this raw data into separate CSV files for each table.
An HTTP-based API allows JSON access to the dataset. A detailed description of the API endpoints can be found in reference/APIservices.txt, and the Flask app for the API can be found in api.py.
An interactive web interface for easy user browsing of data. The user can see a ranking of skyscrapers based on their height, number of floors, year construction was started or completed, or alphabetical order. They can view all available information about a specific skyscraper by clicking on a skyscraper from the rankings page or any other page with listings of specific skyscrapers. They can also refine the ranking listing to show only skyscrapers in a certain city, built in a certain year, built of a specific material (e.g. steel), or used for a specific purpose (e.g. belltower). Users can browse the lists of cities, materials, and purposes, or search for a specific skyscraper.
The HTML layout files, stylesheets, and Javascript files for the webpages can be found in the templates and static folders.
(Unfortunately the server ports are no longer active for this project, but mockups showing rough visualizations of most of the features of the webapp are available in the reference/mockups folder.)
├── README.md : Description of this repository
├── api.py : Flask app for the HTTP-based API with JSON access to skyscraper data
├── website.py : Flask app linking API to website for user browsing of data
├── data : Raw data and postgreSQL table contents in CSV form, .sql dump file, and raw data converter .py file
├── reference : Reference files from database, API, and UI design planning stages
│ ├── mockups : Mockup drawings for primary webpages
│ ├── APIservices.txt : Detailed descriptions of API endpoints, corresponding query responses, and usage examples
│ ├── createstatements.txt : CREATE TABLE statements used to populate the PostgreSQL database tables
│ ├── improvements.txt : Reflections on bugs and imperfections remaining at the end of the project, to be improved in the future
│ └── userstories.txt : User stories describing possible use cases of the webapp
├── static : Static files (.css and .js)
├── templates : HTML layout files
└── .gitignore : Files and directories to be ignored by git
Access the webapp at: http://perlman.mathcs.carleton.edu:5203/ (port no longer active)
Access the API at: http://perlman.mathcs.carleton.edu:5103/ (port no longer active)
Jessie Baskauf
Ellie Mamantov
Some basic code stubs provided by Jeff Ondich
Original data from the following webpage: https://think.cs.vt.edu/corgis/csv/skyscrapers/skyscrapers.html