README.Rmd

---
output: github_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE, message = FALSE, warning = FALSE)
```

# RStudio Connect Usage Data

This repository illustrates several examples for getting started with the
RStudio Connect usage data. The examples:

- [./examples/last_30_days](./examples/last_30_days)
- [./examples/interactive_app](./examples/interactive_app)
- [./examples/realtime](./examples/realtime)
- [./examples/connectAnalytics](./examples/connectAnalytics)
- [./examples/connectViz](./examples/connectViz)

The examples are generated using the [RStudio Connect Server
API](https://docs.rstudio.com/connect/api). The API and data collection are both
available as of RStudio Connect 1.7.0. The API contains data to help answer
questions like:

- What content is most visited?
- Who is visiting my content?
- What reports are most common?
- Has viewership increased over time?
- Did my CEO actually visit this app?

**A data science team's time is precious, this data will help you focus and justify your efforts.**

## Basic example

The following code should work as-is if copied into your R session. NOTE that it
uses the [`connectapi`](https://github.com/rstudio/connectapi) package, which
can be installed from GitHub with
`remotes::install_github("rstudio/connectapi")`. You just need to replace the
server name, and have your API key ready.

```{r connect_creds, eval=FALSE}
## ACTION REQUIRED: Change the server URL below to your server's URL
Sys.setenv("CONNECT_SERVER"  = "https://connect.example.com/rsc") 
## ACTION REQUIRED: Make sure to have your API key ready
Sys.setenv("CONNECT_API_KEY" = rstudioapi::askForPassword("Enter Connect Token:")) 
```

This will use the `get_usage_shiny()` function to pull the latest activity of
the Shiny apps you are allowed to see within your server.

```{r shiny_usage}
library(ggplot2)
library(dplyr)
library(connectapi)

client <- connect()

# Get and clean the Shiny usage data
shiny_rsc <- get_usage_shiny(
  client,
  from = lubridate::today() - lubridate::ddays(7), 
  limit = Inf
  ) %>%
  filter(!is.na(ended)) %>%
  mutate(session_duration = ended - started)

glimpse(shiny_rsc)
```

The identifiers used for the content in RStudio Connect are GUIDs. We can
retrieve content names using the API. The API handles only one GUID at a time,
so `purrr`'s `map_dfr()` is used to iterate through all of the unique GUIDs in
order to get every Shiny app's title.

```{r shiny_content_names}
# Get the title of each Shiny app
shiny_rsc_titles <- shiny_rsc %>%
  count(content_guid) %>% 
  pull(content_guid) %>%
  purrr::map_dfr(
    ~tibble(content_guid = .x, content_name = content_title(client, .x))
    )

glimpse(shiny_rsc_titles)
```

The new `shiny_rsc_titles` table, and the `shiny_rsc` can be joined to return
the "user readable" title. Using standard `dplyr` and `ggplot2` functions, we
can now determine things such as the top 10 apps based on how long their average
sessions are.

```{r analyze_data}
# Calculate the average session duration and sort
app_sessions <- shiny_rsc %>%
  inner_join(shiny_rsc_titles, by = "content_guid") %>%
  group_by(content_name) %>%
  summarise(avg_session = mean(session_duration)) %>%
  ungroup() %>%
  arrange(desc(avg_session)) %>%
  head(10)
  
# Plot the top 10 used content
app_sessions %>%
  ggplot(aes(content_name, avg_session)) +
  geom_col() +
  scale_y_continuous() +
  geom_text(aes(y = (avg_session + 200), label = round(avg_session)), size = 3) +
  coord_flip() +
  theme_bw() +
  labs(
    title = "RStudio Connect - Top 10", 
    subtitle = "Shiny Apps", 
    x = "", 
    y = "Average session time (seconds)"
    )
```

Learn more about programmatic deployments, calling the server API, and custom emails [here](https://docs.rstudio.com/user).