tladeras’s avatartladeras’s Twitter Archive—№ 1,899

                        1. Joe Cheng talking about using Shiny in production by looking at “whales” who download lots at RStudio CRAN mirror #Rstudioconf
                          oh my god twitter doesn’t include alt text from images in their API
                      1. …in reply to @tladeras
                        Production environments: relied on by real users with real consequences if they go wrong. Goals are uptime, security, correctness, responsiveness. #Rstudioconf
                    1. …in reply to @tladeras
                      Can shiny be used in production? Yes, possible and now easy. Challenges are organizational, culural and technical. #Rstudioconf
                  1. …in reply to @tladeras
                    Cultural: many app designers are users and don’t necessarily know best practices, performance and scale testing, security testing. #Rstudioconf
                1. …in reply to @tladeras
                  Organizational: IT/management are skeptical, credibility gap. Engineering department may be biased against R. #Rstudioconf
              1. …in reply to @tladeras
                Technical: hard to debug and profile , single threaded execution. #Rstudioconf
            1. …in reply to @tladeras
              shinytest, shinyloadtest for testing and profiling apps, profvis (R Profiler), plot caching, async are tools to tackle technical challenges #Rstudioconf
          1. …in reply to @tladeras
            shinyloadtest to see how fast apps are. Use profvis to improve R processes. Improve by moving work out of shiny, make code faster, caching, async. Recheck in shinyloadtest. #Rstudioconf
        1. …in reply to @tladeras
          Shinyloadtest: record average app use case, run concurrent load tests on shiny app. shinycannon runs concurrent load tests, produce report to understand performance. #Rstudioconf
      1. …in reply to @tladeras
        How to improve? Use profvis to id bottlenecks in your app. Cranwhales spends too much time on loading in app. Load/process data ahead of time. Save as feather files for quick loading. Automate this using scheduling. #Rstudioconf
    1. …in reply to @tladeras
      Good candiates are slow plots, and plots that users frequently request. Add caching in renderPlot and tell shiny what input variables matter #rstudioconf
  1. …in reply to @tladeras
    Er, renderCahchedPlot #rstudiocomf
    1. …in reply to @tladeras
      I can’t spell or my thimbs are too large. #rstudioconf
      1. …in reply to @tladeras
        @kellrstats working on shiny in production book! bit.ly/shiny-prod-book #rstudioconf