---
title: "Using web-hosted boards"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Using web-hosted boards}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  eval = rlang::is_installed("webfakes")
)
```

The pins package supports back-and-forth collaboration for publishing and consuming using, for example, `board_s3()`.
The goal of this vignette is to show how to publish a board of pins to a website, bringing your pins to a wider audience. How does this work?

- For consumers, `board_url()` offers **read-only** collaboration.
- For publishers, a helper function is provided, `write_board_manifest()`.
A manifest contains a list of pins and versions, enabling
a `board_url()` to read like a `board_s3()` or `board_folder()`.

## Publishing

The steps for publishing a board that can be read by consumers using `board_url()` are:

- create a board,
- write pins to the board,
- write a manifest file using `write_board_manifest()`, and
- publish your website.

The first and last steps will be specific to how you deploy your board on the web; we discuss options in the [Publishing platforms] section. Regardless of platform, you'll write the pins and the manifest the same way.

For this first demonstration, we'll start by creating a board, and finish by showing how the board works after being served.

```{r pin-mtcars}
library(pins)
board <- board_temp(versioned = TRUE)
```

We're using a temporary board for this demonstration, but in practice, you might use `board_folder()` in a project folder or GitHub repo, or perhaps `board_s3()`.

Let's make the `mtcars` dataset available as a JSON file:

```{r}
board %>% pin_write(mtcars, type = "json")
```

Let's make a new version of this data by adding a column: `lper100km`, consumption in liters per 100 km.
This could make our data friendlier to folks outside the United States.


```{r}
#| echo: false

# we need a short delay here to keep the versions in the right order
Sys.sleep(2)
```

```{r metric}
mtcars_metric <- mtcars
mtcars_metric$lper100km <- 235.215 / mtcars$mpg

board %>% pin_write(mtcars_metric, name = "mtcars", type = "json")
```

Let's check our board to ensure we have one pin named `"mtcars"`, with two versions:

```{r board-pin-list}
board %>% pin_list()

board %>% pin_versions("mtcars")
```

Because a `board_url()` is consumed over the web, it doesn't have access to a file system the way, for example, a `board_folder()` has; we can work around this by creating a manifest file.
When a `board_url()` is set up by a consumer for reading, the pins package uses this file to discover the pins and their versions.
The manifest file is the key to `board_url()`'s ability to discover pins as if it were a file-system-based board.

After writing pins but *before* publishing, call `write_board_manifest()`:

```{r}
board %>% write_board_manifest()
```

The maintenance of this manifest file is not automated; it is your responsibility as the board publisher to keep the manifest up to date.

Let's confirm that there is a file called `_pins.yaml`:

```{r}
withr::with_dir(board$path, fs::dir_ls())
```

We can inspect its contents to see each pin in the board, and each version of each pin:

```yaml
`r if (rlang::is_installed("webfakes")) paste(readLines(fs::path(board$path, "_pins.yaml")), collapse = "\n")`
```

At this point, we would publish the folder containing the board as a part of a web site.
Let's pretend that we have served the folder from our fake website, `https://not.real.website.co/pins/`.

```{r board-serve}
#| echo: false
board_server <- webfakes::new_app()
board_server$use(webfakes::mw_static(root = board$path))
board_process <- webfakes::new_app_process(board_server)

web_board <- board_url(board_process$url())
```

## Consuming

With an up-to-date manifest file, a `board_url()` can behave as a read-only version of a `board_folder()`.
Let's create a `board_url()` using our fake URL:

```{r}
#| eval: false
web_board <- board_url("https://not.real.website.co/pins/")
```

The `board_url()` function reads the manifest file to discover the pins and versions:

```{r}
#| message: false
web_board %>% pin_list()

versions <- web_board %>% pin_versions("mtcars")
versions
```

We can read the most-recent version of the `"mtcars"` pin:

```{r}
#| message: false
web_board %>% pin_read("mtcars") %>% head()
```

We can also read the first version:

```{r}
#| message: false
web_board %>% pin_read("mtcars", version = versions$version[[1]]) %>% head()
```

## Publishing platforms

The goal of this section is to illustrate ways to publish a board as a part of a website.


### pkgdown

Pins offers another way for package developers to share data associated with an R package. 
Publishing a package dataset as a pin can extend your data's "audience" to those who have not installed the package.

Using [pkgdown](https://pkgdown.r-lib.org/articles/customise.html#additional-html-and-files), any files you save in the directory `pkgdown/assets/` will be copied to the website's root directory when `pkgdown::build_site()` is run.

The [_R Packages_ book](https://r-pkgs.org/data.html#sec-data-data-raw) suggests using a folder called `data-raw` for working with datasets; this can be adapted to use pins. You would start with `usethis::use_data_raw()`.
In a file in your `/data-raw` directory, wrangle and clean your datasets in the same way as if you were going to use `usethis::use_data()`.
To offer such datasets on a web-based board instead of as a built-in package dataset, in your `/data-raw` file you would:

- Create a board: `board_folder(here::here("pkgdown/assets/pins-board"))` (you might use a different name than `"pins-board"`).
- Write your datasets to the board using `pin_write()`.
- At the end, call `write_board_manifest()`.

Now when you build your pkgdown site and serve it (perhaps via GitHub Pages at a URL like `https://user-name.github.io/repo-name/`), your datasets are available as pins.

The _R Packages_ book offers this observation on CRAN and package data:

> Generally, package data should be smaller than a megabyte - if it’s larger you’ll need to argue for an exemption.

Publishing a board on your pkgdown site provides a way to offer datasets too large for CRAN or extended versions of your data. A consumer can read your pins by setting up a board like:

```{r}
#| eval: false
board <- board_url("https://user-name.github.io/repo-name/pins-board/")
```


### S3

S3 buckets can be made available to different users using [permissions](https://docs.aws.amazon.com/config/latest/developerguide/s3-bucket-policy.html); buckets can even be made publicly accessible. Publishing data as a pin in an S3 bucket can allow your collaborators to read without dealing with the authentication required by `board_s3()`.

To offer datasets as a pin on S3 via `board_url()` you would:

- Create a board: `board_s3("your-existing-bucket")` (set the bucket's permissions to give appropriate people access).
- Write your datasets to the board using `pin_write()`.
- At the end, call `write_board_manifest()`.

S3 buckets typically have a URL like `https://your-existing-bucket.s3.us-west-2.amazonaws.com/`. For a person who has access to your bucket, they can read your pins by setting up a board like:

```{r}
#| eval: false
board <- board_url("https://your-existing-bucket.s3.us-west-2.amazonaws.com/")
```


