__         __     ______     ______        ______   ______     ______     __  __    
/\ \       /\ \   /\  ___\   /\  __ \      /\  == \ /\  ___\   /\  ___\   /\ \/ /    
\ \ \____  \ \ \  \ \___  \  \ \  __ \     \ \  _-/ \ \  __\   \ \ \____  \ \  _"-.  
 \ \_____\  \ \_\  \/\_____\  \ \_\ \_\     \ \_\    \ \_____\  \ \_____\  \ \_\ \_\ 
  \/_____/   \/_/   \/_____/   \/_/\/_/      \/_/     \/_____/   \/_____/   \/_/\/_/ 
               

Project: Companion Twitter Bots - @snowinginithaca and @snowedinithaca

Description: This project is from INFO 664 Programming for Cultural Heritage with Matt Miller in Fall 2020 (attended virtually). Our final projects were open ended, but we were encouraged to utilize specific python skills we learned throughout the course. I worked with APIs and created two companion Twitter bots.

Role: This project was completed individually.

Method: Snowing in Ithaca tweets whether or not it is snowing based on current conditions. For this project, I used the OpenWeather API to source current weather data in Ithaca, NY and automated tweets with Tweepy and Amazon Web Services.

Snowed in Ithaca replies to its companion with the last year it snowed on that date. It calls on the NOAA Web Services v2 API alongside crvaden's NOAA API module and also tweets with Tweepy and AWS. This bot also uses the python packages pytz and dateutil to navigate timezones and dates. NOAA data is sourced from Cornell University's weather station, with data from 1893-present.

Please note: I have made adjustments to the bots after the course ended, including the addition of historical max. snowfall values to Snowed in Ithaca.

Rationale: This project directly exemplifies an application of technology in information — using python and related APIs & packages, these Twitter bots access, parse and present information to the public. Much of their development and testing relied on the randomness of the weather, presenting certain challenges in programming.