Enhance R Shiny App for Scalability
Budget: €30 – €250 EUR
I have an existing R Shiny app with approximately 800 lines of code. This app currently produces an interactive map using a dataset of around 20,000 entries. The app performs reasonably well for 1-2 users but is not equipped to handle larger loads or more extensive datasets. As the database expands to 6 million entries and user numbers rise into the hundreds, I need a professional to refine the app for speed, stability, and scalability.
Key Requirements:
- Preventing Infinite Loops: One of the critical issues with the current app is its tendency to enter infinite loops when selections are changed too rapidly. This needs to be addressed urgently.
- Server Scalability: The app must be optimized to handle more users without crashing or slowing down significantly.
- Optimized Data Queries: With the increase in database size, data queries need to be streamlined for efficiency.
Ideal Skills and Experience:
- Proficiency in R and Shiny with extensive experience in app development.
- Strong background in debugging, profiling, and code refactoring.
- Experience with scalable server solutions and load balancing techniques.
- Familiarity with designing interactive maps within Shiny apps.
I have already attempted some improvements with the help of AI tools like ChatGPT and Claude, but these solutions have proven insufficient. I'm looking for a professional with the technical skills and experience to deliver a robust, reliable Shiny app.
The person taking on this job needs to be comfortable in Bengali/Bangla - as this is the default language for the map. I am attaching the current code. The context is the tubewell arsenic problem in Bangladesh that is estimated to kill about 100,000 per year prematuraly. This is about mapping a new large government data set of well tests for arsenic and making the data more accessible to the public. Such access will point villagers and local government to solutions.
Key Requirements:
- Preventing Infinite Loops: One of the critical issues with the current app is its tendency to enter infinite loops when selections are changed too rapidly. This needs to be addressed urgently.
- Server Scalability: The app must be optimized to handle more users without crashing or slowing down significantly.
- Optimized Data Queries: With the increase in database size, data queries need to be streamlined for efficiency.
Ideal Skills and Experience:
- Proficiency in R and Shiny with extensive experience in app development.
- Strong background in debugging, profiling, and code refactoring.
- Experience with scalable server solutions and load balancing techniques.
- Familiarity with designing interactive maps within Shiny apps.
I have already attempted some improvements with the help of AI tools like ChatGPT and Claude, but these solutions have proven insufficient. I'm looking for a professional with the technical skills and experience to deliver a robust, reliable Shiny app.
The person taking on this job needs to be comfortable in Bengali/Bangla - as this is the default language for the map. I am attaching the current code. The context is the tubewell arsenic problem in Bangladesh that is estimated to kill about 100,000 per year prematuraly. This is about mapping a new large government data set of well tests for arsenic and making the data more accessible to the public. Such access will point villagers and local government to solutions.