COVID-19 is a worldwide pandemic that was first identified in late 2019 in Wuhan, China. As of August 2020, more than 20 million cases resulting in over 800,000 deaths have been documented worldwide. Information regarding the coronavirus is scattered and countless individuals have found it exceedingly difficult to scavenge for information while balancing their readjusted life due to the pandemic. COVID19 Stats Tracker acts as a haven of live information regarding the virus, incorporating various pandemic-related APIs as well as voice activated commands.
What it does
COVID19 Stats Tracker incorporates APIs that draw live data including total cases, total recovered and total deaths in order to inform the user of the severity and numbers of the COVID-19 pandemic. Furthermore, the user is able to filter results in accordance to their own country. COVID19 Stats Tracker also features commands that links the user to pandemic-related resources. Due to the fact that social media and the news are ingrained into the lives of our society, COVID19 Stats Tracker displays the most recent news articles and Reddit posts regarding COVID-19. Lastly, all of commands are activated via voice recognition, allowing easy access for each and every individual.
How we built it
COVID19 Stats Tracker was built using Python incorporating the libraries: requests, Tkinter, datetime, webbrowser, newsapi, speech_recognition and pyttsx3. The requests module was utilized in order to web scrape data for live stats of the pandemic. Datetime was used to display the current time while the webbrowser library was used to open links to COVID-19 resources. The newsapi was used to fetch the top pandemic-related news articles. Lastly, in conjunction with all the commands, speech_recognition allows the user to activate commands via voice while pyttsx3 reads out prompts.
Challenges we ran into
Focusing on the API calls was our main priority, first and foremost. In order to accomplish displaying live stats, we were required to learn how to draw data encapsulated in the .json formatted. Due to the large amount of data encapsulated within each other in the .json files, learning to sort the data was a challenge at first, one which we ultimately overcame.
Accomplishments that we're proud of
As a team, we are proud of the fact that we were able to come together and build a program that is able to contribute to the society’s efforts in mitigating damages done by COVID-19.
What we learned
Utilizing previous knowledge and incorporating newly learned concepts, we were able to come together as a team and finish implementation of COVID19 Stats Tracker. Within the span of the hackathon, we furthered our knowledge regarding the Tkinter library as well as enhanced our knowledge regarding API calls, including learning to draw data in the .json format.
What's next for COVID19 Stats Tracker
Given more time, we would have desired to incorporate an infographics portion to the program.