Pub/Sub driven {shiny} dashboard
Author: Andrea Dodet
Date: 2023-03-02

# Pub/Sub driven `{shiny}` dashboard

#### Andrea Dodet

#### 2023-03-02

## Resource setup

In order to run the shiny app in `inst/shiny/consumer_example/app.R` you’ll need to setup your `GCP_PROJECT` as an environment variable before running this example.
Run the app from the root of the package:

    shiny::runApp("inst/shiny/consumer_example/")

Upon startup, the `inst/shiny/consumer_example/app.Rinit.R` file will take care of creating the following resources:

- A pubsub topic named `shiny-topic`
- An associated pubsub subscription from where we’ll be polling and consuming messages, named `shiny-sub`

## Components

This app is composed by two main components:

A producer:

In this case, our producer will be an `actionButton` (on top of this readme) that will trigger a `PubsubMessage` to be generated and sent to the subscription, the message will contain the following fields:

    {
      "col_a": "int",    # A random integer
      "col_b": "int",    # A random integer
      "fired_at": "str"  # Timestamp at which the message was created
    }

A consumer:

This is the bulk of where the interesting things happen. The shiny app will check whether new messages have been published to the subscription every 2 seconds. In order not to block the user from sending new messages (or keep interacting with sliders, inputs, etc. in a more complex case), this will be done in a parallel R session using the `{promises}` and `{future}` packages.

    # Set up a message consumer in background sessions (poll messages every 2 seconds)
    observe({
      invalidateLater(20000, session)

      future_promise({
        pubsub_auth() # Authenticated session is not passed to futures' env
        get_data()
      }) %>%
        then(function(res) {
          # Notify the user if new messages have been received
          if (!is.null(res)) {
            showNotification(
              paste("Message received at", strftime(Sys.time()), sep = " "),
              duration = 3,
              type = "warning"
            )
          }

          # Append to the reactive dataframe
          out_df$df <- rbind(out_df$df, res)
        })

      # Hide the future, this is a fire and forget hack and allows avoid blocking
      # from https://stackoverflow.com/a/57922419/9046275
      return(NULL)
    })

The `get_data()` function takes care of:

1. Pulling the messages from the Pub/Sub topic
2. Convert the base64 encoded string and binding the results to a data frame
3. Acknowledge the subscription the messages where consumed (effectively removing them from the subscription).

The components described above interact according the behaviour described by the diagram below:

    +---------------+   +---------------+     +------------------+        +--------------------+
    | actionButton  |-->| Pub/Sub Topic |     |Observe({promise})|------> |Output dataframe    |
    | (producer)    |   |               |     |(consumer)        |        |(reactiveValues(df) |
    +---------------+   +---------------+     +------------------+        +--------------------+
                              |                     ^     |
                        +-----v---------+           |     |
                        |Pub/Sub        |-----------+     |
                        |Subscription   |<----------------+
                        +---------------+

### Todo

- It would be nice to have the time to profile the whole thing (an idea could be to observe memory usage inside a docker container as I am not sure `profviz` is capable to handle multi-session shiny apps).