---
title: "Customization"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Customization}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

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

```{r setup}
library(shinydataviewer)
library(shiny)
library(bslib)
library(reactable)
```

The module exposes a small set of customization hooks intended to balance
drop-in defaults with downstream flexibility.

## Table behavior

`data_viewer_server()` exposes first-class arguments for common table
controls:

- `searchable`
- `filterable`
- `sortable`
- `default_page_size`
- `page_size_options`

For lower-level `reactable()` overrides, use `reactable_args`.

`default_page_size` must be one of the values supplied in
`page_size_options`, and `page_size_options` must contain positive integers.

```{r eval = FALSE}
data_viewer_server(
  "viewer",
  data = reactive(mtcars),
  searchable = TRUE,
  filterable = FALSE,
  sortable = TRUE,
  default_page_size = 25,
  page_size_options = c(25, 50, 100),
  reactable_args = list(
    showPageInfo = FALSE
  )
)
```

## Table controls position

The UI helpers support top or bottom table controls:

```{r eval = FALSE}
data_viewer_card_ui(
  "viewer",
  table_controls_position = "bottom"
)
```

## Custom summary cards

Use `summary_card_fn` to replace the default variable card renderer while
keeping the module's summary computation and table logic.

The custom function must accept at least `summary_row` and `index`, where
`summary_row` is a one-row data frame produced by `summarize_columns()`.

```{r eval = FALSE}
custom_summary_card <- function(summary_row, index) {
  htmltools::tags$div(
    class = "custom-summary-card",
    htmltools::tags$strong(summary_row$var_name[[1]]),
    htmltools::tags$span(sprintf(" (%s)", summary_row$type[[1]]))
  )
}

data_viewer_server(
  "viewer",
  data = reactive(iris),
  summary_card_fn = custom_summary_card
)
```

A typical use case is treating identifier-like columns differently from ordinary
categorical fields, for example by suppressing the mini chart and showing a
"High cardinality" badge instead.

The module validates unsupported column classes early, so custom summary-card
logic can assume the incoming `summary_row` corresponds to one of the supported
viewer types.

## Theme integration

The module styles use Bootstrap variables, so they follow the active `bslib`
theme and `brand.yml` values automatically.

```{r eval = FALSE}
ui <- page_fillable(
  theme = bs_theme(version = 5, brand = "brand.yml"),
  data_viewer_card_ui("viewer")
)
```