Add modification buttons as a column

Description

Add modification buttons as a column

Usage

addButtons(
  df,
  columnName,
  ns,
  iCol = "i",
  canEditRow = TRUE,
  canDeleteRow = TRUE,
  canCloneRow = TRUE,
  statusCol = "_editbl_status"
)

Arguments

Value

df with extra column containing buttons

Author(s)

Jasper Schelfhout

Start a transaction for a tibble

Description

Start a transaction for a tibble

Usage

beginTransaction(tbl)

Arguments

Author(s)

Jasper Schelfhout

Re-usable documentation

Description

Re-usable documentation

Usage

canXXXRowTemplate(canEditRow, canCloneRow, canDeleteRow)

Arguments

Cast columns in data.frame to editable types in datatable

Description

Cast columns in data.frame to editable types in datatable

Usage

castForDisplay(data, cols = colnames(data))

Arguments

Value

data.frame with some columns cast to another type

Author(s)

Jasper Schelfhout

Cast tbl to class of template

Description

Cast tbl to class of template

Usage

castFromTbl(tbl, template)

Arguments

Value

tbl cast to the type of template

Author(s)

Jasper Schelfhout

Cast all columns that exist in a foreignTbl to factor

Description

Cast all columns that exist in a foreignTbl to factor

Usage

castToFactor(data, foreignTbls)

Arguments

Details

Can be used to fixate possible options when editing.

Value

data.frame

Author(s)

Jasper Schelfhout

Cast the data type to something supported by SQL.

Description

Cast the data type to something supported by SQL.

Usage

castToSQLSupportedType(x)

Arguments

Value

x, possibly cast to different type

Author(s)

Jasper Schelfhout

Cast data to tbl

Description

Cast data to tbl

Usage

castToTbl(data)

Arguments

Value

tbl

Author(s)

Jasper Schelfhout

Cast tbl or data.frame x to the types of the template

Description

Cast tbl or data.frame x to the types of the template

Usage

castToTemplate(x, template)

Arguments

Details

If template is a tbl with database source, convert to an in-memory tibble with same data types instead.

Rownames might differ or get lost.

Value

object containing data of x in the class and structure of the template.

Author(s)

Jasper Schelfhout

Check if all rows in tbl fufill foreignTbl constraints

Description

Check if all rows in tbl fufill foreignTbl constraints

Usage

checkForeignTbls(tbl, foreignTbls)

Arguments

Value

logical stating if tbl fufills all constraints imposed by all foreign tbls.

Author(s)

Jasper Schelfhout

Return first non NULL argument

Description

Return first non NULL argument

Usage

coalesce(...)

Arguments

Author(s)

Jasper Schelfhout

Cast columns to the type of the template

Description

Cast columns to the type of the template

Usage

coerceColumns(template, x)

Arguments

Details

only affects columns in both the template and x

DT::coerceValue with better POSIXct support

Description

DT::coerceValue with better POSIXct support

Usage

coerceValue(val, old)

Arguments

Details

Will assume UTC in case no timezone is specified.

Author(s)

Jasper Schelfhout

Start a transaction for a tibble

Description

Start a transaction for a tibble

Usage

commitTransaction(tbl)

Arguments

Author(s)

Jasper Schelfhout

Connect to a database.

Description

Connect to a database.

Usage

connectDB(
  dbname = system.file("extdata", "chinook.sqlite", package = utils::packageName()),
  drv = RSQLite::SQLite(),
  ...
)

Arguments

Details

Connects by default to a test SQLite database originally obtained here: chinook_git

Value

database connection

Examples

conn <- connectDB()
DBI::dbDisconnect(conn)

Create buttons to modify the row.

Description

Create buttons to modify the row.

Usage

createButtons(
  row,
  suffix,
  ns,
  canEditRow = TRUE,
  canDeleteRow = TRUE,
  canCloneRow = TRUE,
  statusCol = "_editbl_status"
)

Arguments

Details

buttons used per row in the app.

Value

character(1) HTML

Generate HTML for an in-row clone button

Description

Generate HTML for an in-row clone button

Usage

createCloneButtonHTML(ns = "%1$s", suffix = "%2$s", disabled = FALSE)

Arguments

Value

character(1) HTML

Helper function to write HTML

Description

Helper function to write HTML

Usage

createCloneButtonHTML_shiny(ns = "%1$s", suffix = "%2$s", disabled = FALSE)

Arguments

Details

only to be used interactively. sprintf() implementation is faster.

See Also

createCloneButtonHTML

Generate HTML for an in-row delete button

Description

Generate HTML for an in-row delete button

Usage

createDeleteButtonHTML(ns = "%1$s", suffix = "%2$s", disabled = FALSE)

Arguments

Value

character(1) HTML

Helper function to write HTML

Description

Helper function to write HTML

Usage

createDeleteButtonHTML_shiny(ns = "%1$s", suffix = "%2$s", disabled = FALSE)

Arguments

Details

only to be used interactively. sprintf() implementation is faster.

See Also

createEditButtonHTML

Generate HTML for an in-row edit button

Description

Generate HTML for an in-row edit button

Usage

createEditButtonHTML(ns, suffix, disabled = FALSE)

Arguments

Value

character(1) HTML

Helper function to write HTML

Description

Helper function to write HTML

Usage

createEditButtonHTML_shiny(ns = "%1$s", suffix = "%2$s", disabled = FALSE)

Arguments

Details

only to be used interactively. sprintf() implementation is faster.

See Also

createEditButtonHTML

Generate a custom button for eDT

Description

Generate a custom button for eDT

Usage

customButton(id, label, icon = "", disabled = FALSE)

Arguments

Details

Combines elements of shiny::actionButton and datatable options

Value

list to be used in eDT(options = list(buttons = xxx))

Author(s)

Jasper Schelfhout

Examples

if(interactive()){

  ui <- eDTOutput("data")
  server <- function(input,output,session){
    b <- customButton('print', label = 'print')
    eDT_result <- eDT(id = "data", mtcars, options = list(buttons = list("save", b)))
    observeEvent(input$print,{
          print(eDT_result$state())
    })
  }
  shinyApp(ui,server)
}

Server of the DB demo app

Description

Server of the DB demo app

Usage

demoServer_DB(id, conn)

Arguments

Value

NULL, just executes the module server.

Author(s)

Jasper Schelfhout

Server of the mtcars demo app

Description

Server of the mtcars demo app

Usage

demoServer_custom(id, x)

Arguments

Value

NULL, just executes the module server.

Author(s)

Jasper Schelfhout

Server of the mtcars demo app

Description

Server of the mtcars demo app

Usage

demoServer_mtcars(id)

Arguments

Value

NULL, just executes the module server.

Author(s)

Jasper Schelfhout

UI of the DB demo app

Description

UI of the DB demo app

Usage

demoUI_DB(id, conn)

Arguments

Value

HTML

Author(s)

Jasper Schelfhout

UI of the demo mtcars app

Description

UI of the demo mtcars app

Usage

demoUI_custom(id)

Arguments

Value

HTML

Author(s)

Jasper Schelfhout

UI of the demo mtcars app

Description

UI of the demo mtcars app

Usage

demoUI_mtcars(id)

Arguments

Value

HTML

Author(s)

Jasper Schelfhout

Server of the development app

Description

Server of the development app

Usage

devServer(id, conn)

Arguments

Value

NULL, just executes the module server.

Author(s)

Jasper Schelfhout

UI of the development app

Description

UI of the development app

Usage

devUI(id, conn)

Arguments

Value

HTML

Author(s)

Jasper Schelfhout

Function to generate CSS to disable clicking events on a column

Description

Function to generate CSS to disable clicking events on a column

Usage

disableDoubleClickButtonCss(id)

Arguments

Details

https://stackoverflow.com/questions/60406027/how-to-disable-double-click-reactivity-for-specific-columns-in-r-datatable

https://stackoverflow.com/questions/75406546/apply-css-styling-to-a-single-dt-datatable

Value

character CSS

Create a modifieable datatable.

Description

Create a modifieable datatable.

Usage

eDT(
  data,
  options = list(dom = "Bfrtlip", keys = TRUE, ordering = FALSE, autoFill = list(update =
    FALSE, focus = "focus"), buttons = list("add", "undo", "redo", "save")),
  class = "display",
  callback = NULL,
  rownames = FALSE,
  colnames = NULL,
  container,
  caption = NULL,
  filter = c("none", "bottom", "top"),
  escape = TRUE,
  style = "auto",
  width = NULL,
  height = NULL,
  elementId = NULL,
  fillContainer = getOption("DT.fillContainer", NULL),
  autoHideNavigation = getOption("DT.autoHideNavigation", NULL),
  selection = "none",
  extensions = c("KeyTable", "AutoFill", "Buttons"),
  plugins = NULL,
  editable = list(target = "cell"),
  id,
  keys = NULL,
  in_place = FALSE,
  format = function(x) {
     x
 },
  foreignTbls = list(),
  columnOrder = c(),
  statusColor = c(insert = "#e6e6e6", update = "#32a6d3", delete = "#e52323"),
  inputUI = editbl::inputUI,
  defaults = tibble(),
  cloneDefaults = tibble(),
  env = environment(),
  canEditRow = TRUE,
  canDeleteRow = TRUE,
  canCloneRow = TRUE,
  utilityColumns = NULL
)

Arguments

c(
  status = '_editbl_status',
  buttons = '_editbl_buttons',
  identity = '_editbl_identity',
  deleted = '_editbl_deleted'
 )

Details

Works the same as datatable. This function is however a shiny module and comes with additional arguments and different defaults. Instead of having output$id = renderDT(DT::datatable(iris)), eDT(id = 'id', data = iris) should be used on the server side. On the UI side eDTOutput should be used instead of DTOutput.

Can also be used as standalone app when not ran in reactive context.

All arguments except 'id' and 'env' can be normal objects or reactive objects.

Value

list

• result reactive modified version of data (saved)

• state reactive current state of the data (unsaved)

• selected reactive selected rows of the data (unsaved)

Author(s)

Jasper Schelfhout

Examples

## Only run this example in interactive R sessions
if(interactive()){
  # tibble support
  modifiedData <- editbl::eDT(tibble::as_tibble(mtcars))

  # data.table support
  modifiedData <- editbl::eDT(dtplyr::lazy_dt(data.table::data.table(mtcars)))

  # database support
  tmpFile <- tempfile(fileext = ".sqlite")
  file.copy(system.file("extdata", "chinook.sqlite", package = 'editbl'), tmpFile)

  conn <- editbl::connectDB(dbname = tmpFile)
  modifiedData <- editbl::eDT(dplyr::tbl(conn, "Artist"), in_place = TRUE)
  DBI::dbDisconnect(conn)

  unlink(tmpFile)

  # Within shiny
  library(shiny)
  library(editbl)
  shinyApp(
    ui = fluidPage(fluidRow(column(12, eDTOutput('tbl')))),
    server = function(input, output) {
      eDT('tbl',iris,)
    }
  )

  # Custom inputUI
  editbl::eDT(mtcars, inputUI = function(id, data){
    ns <- NS(id)
    textInput(
    ns("mpg"),
    label = "mpg",
    value = data$mpg)})

  # Do not allow delete
  editbl::eDT(mtcars, canDeleteRow = FALSE)
}

UI part of eDT

Description

UI part of eDT

Usage

eDTOutput(id, ...)

Arguments

Details

Works exactly like DTOutput apart from the fact that instead of the outputId argument, id is requested. Reason being that this function is a UI to a shiny module. This means that the datatable can be found under the id '{namespace}-{id}-DT' instead of '{namespace}-{outputId}'.

Also some minor CSS and javascript is executed for functional puposes.

Value

HTML

Author(s)

Jasper Schelfhout

Examples

## Only run this example in interactive R sessions
if(interactive()){
  # tibble support
  modifiedData <- editbl::eDT(tibble::as_tibble(mtcars))

  # data.table support
  modifiedData <- editbl::eDT(dtplyr::lazy_dt(data.table::data.table(mtcars)))

  # database support
  tmpFile <- tempfile(fileext = ".sqlite")
  file.copy(system.file("extdata", "chinook.sqlite", package = 'editbl'), tmpFile)

  conn <- editbl::connectDB(dbname = tmpFile)
  modifiedData <- editbl::eDT(dplyr::tbl(conn, "Artist"), in_place = TRUE)
  DBI::dbDisconnect(conn)

  unlink(tmpFile)

  # Within shiny
  library(shiny)
  library(editbl)
  shinyApp(
    ui = fluidPage(fluidRow(column(12, eDTOutput('tbl')))),
    server = function(input, output) {
      eDT('tbl',iris,)
    }
  )

  # Custom inputUI
  editbl::eDT(mtcars, inputUI = function(id, data){
    ns <- NS(id)
    textInput(
    ns("mpg"),
    label = "mpg",
    value = data$mpg)})

  # Do not allow delete
  editbl::eDT(mtcars, canDeleteRow = FALSE)
}

Open interactive app to explore and modify data

Description

Open interactive app to explore and modify data

Usage

eDT_app(...)

Arguments

Details

When eDT is not used within the server of a shiny app, it will call this function to start up a shiny app itself. Just as DT::datatable() displays a table in the browser when called upon interactively.

Value

data (or a modified version thereof) once you click 'close'

Server of eDT_app

Description

Server of eDT_app

Usage

eDT_app_server(moduleId = "nevergonnagiveyouup", ...)

Arguments

Value

moduleServer which on application stop returns version of x with made changes

Author(s)

Jasper Schelfhout

UI of eDT_app

Description

UI of eDT_app

Usage

eDT_app_ui(moduleId = "nevergonnagiveyouup", eDTId = "nevergonnaletyoudown")

Arguments

Value

HTML

Author(s)

Jasper Schelfhout

Insert rows into a tibble

Description

Insert rows into a tibble

Usage

e_rows_insert(
  x,
  y,
  by = NULL,
  ...,
  conflict = c("error", "ignore"),
  copy = FALSE,
  in_place = FALSE
)

Arguments

Details

Mainly a wrapper around rows_insert. Allows for specific implementations should the behavior differ from what's needed by editbl. Reason for separate method is to avoid conflicts on package loading.

Value

An object of the same type as x. The order of the rows and columns of x is preserved as much as possible. The output has the following properties:

• rows_update() and rows_patch() preserve the number of rows; rows_insert(), rows_append(), and rows_upsert() return all existing rows and potentially new rows; rows_delete() returns a subset of the rows.

• Columns are not added, removed, or relocated, though the data may be updated.

• Groups are taken from x.

• Data frame attributes are taken from x.

If in_place = TRUE, the result will be returned invisibly.

Insert rows into a tibble

Description

Insert rows into a tibble

Usage

## Default S3 method:
e_rows_insert(
  x,
  y,
  by = NULL,
  ...,
  conflict = c("error", "ignore"),
  copy = FALSE,
  in_place = FALSE
)

Arguments

Details

Mainly a wrapper around rows_insert. Allows for specific implementations should the behavior differ from what's needed by editbl. Reason for separate method is to avoid conflicts on package loading.

Value

An object of the same type as x. The order of the rows and columns of x is preserved as much as possible. The output has the following properties:

• rows_update() and rows_patch() preserve the number of rows; rows_insert(), rows_append(), and rows_upsert() return all existing rows and potentially new rows; rows_delete() returns a subset of the rows.

• Columns are not added, removed, or relocated, though the data may be updated.

• Groups are taken from x.

• Data frame attributes are taken from x.

If in_place = TRUE, the result will be returned invisibly.

rows_insert implementation for data.table backends.

Description

rows_insert implementation for data.table backends.

Usage

## S3 method for class 'dtplyr_step'
e_rows_insert(x, y, by = NULL, ..., copy = FALSE, in_place = FALSE)

Arguments

Details

Mainly a wrapper around rows_insert. Allows for specific implementations should the behavior differ from what's needed by editbl. Reason for separate method is to avoid conflicts on package loading.

Value

An object of the same type as x. The order of the rows and columns of x is preserved as much as possible. The output has the following properties:

• rows_update() and rows_patch() preserve the number of rows; rows_insert(), rows_append(), and rows_upsert() return all existing rows and potentially new rows; rows_delete() returns a subset of the rows.

• Columns are not added, removed, or relocated, though the data may be updated.

• Groups are taken from x.

• Data frame attributes are taken from x.

If in_place = TRUE, the result will be returned invisibly.

Author(s)

Jasper Schelfhout

rows_insert implementation for DBI backends.

Description

rows_insert implementation for DBI backends.

Usage

## S3 method for class 'tbl_dbi'
e_rows_insert(x, y, by = NULL, ..., copy = FALSE, in_place = FALSE)

Arguments

Details

Mainly a wrapper around rows_insert. Allows for specific implementations should the behavior differ from what's needed by editbl. Reason for separate method is to avoid conflicts on package loading.

Value

An object of the same type as x. The order of the rows and columns of x is preserved as much as possible. The output has the following properties:

• rows_update() and rows_patch() preserve the number of rows; rows_insert(), rows_append(), and rows_upsert() return all existing rows and potentially new rows; rows_delete() returns a subset of the rows.

• Columns are not added, removed, or relocated, though the data may be updated.

• Groups are taken from x.

• Data frame attributes are taken from x.

If in_place = TRUE, the result will be returned invisibly.

Author(s)

Jasper Schelfhout

Examples

library(dplyr)

# Set up a test table
conn <- DBI::dbConnect(RSQLite::SQLite(), ":memory:")
artists_df <- data.frame(
         ArtistId = c(1,2),
         Name = c("AC/DC", "The Offspring")
)
DBI::dbWriteTable(conn, "Artist", artists_df)     
 
# Insert new row
artists <- tbl(conn, "Artist")
DBI::dbBegin(conn)
e_rows_insert(artists,
 data.frame(ArtistId = 999, Name = "testArtist"),
 in_place = TRUE)

DBI::dbRollback(conn)
DBI::dbDisconnect(conn)

Update rows of a tibble

Description

Update rows of a tibble

Usage

e_rows_update(
  x,
  y,
  by = NULL,
  ...,
  match,
  unmatched = c("error", "ignore"),
  copy = FALSE,
  in_place = FALSE
)

Arguments

Details

Mainly a wrapper around rows_update. Allows for specific implementations should the behavior differ from what's needed by editbl. Reason for separate method is to avoid conflicts on package loading.

Value

An object of the same type as x. The order of the rows and columns of x is preserved as much as possible. The output has the following properties:

• rows_update() and rows_patch() preserve the number of rows; rows_insert(), rows_append(), and rows_upsert() return all existing rows and potentially new rows; rows_delete() returns a subset of the rows.

• Columns are not added, removed, or relocated, though the data may be updated.

• Groups are taken from x.

• Data frame attributes are taken from x.

If in_place = TRUE, the result will be returned invisibly.

rows_update implementation for data.frame backends.

Description

rows_update implementation for data.frame backends.

Usage

## S3 method for class 'data.frame'
e_rows_update(
  x,
  y,
  by = NULL,
  match = NULL,
  ...,
  copy = FALSE,
  in_place = FALSE
)

Arguments

Details

Mainly a wrapper around rows_update. Allows for specific implementations should the behavior differ from what's needed by editbl. Reason for separate method is to avoid conflicts on package loading.

Value

An object of the same type as x. The order of the rows and columns of x is preserved as much as possible. The output has the following properties:

• rows_update() and rows_patch() preserve the number of rows; rows_insert(), rows_append(), and rows_upsert() return all existing rows and potentially new rows; rows_delete() returns a subset of the rows.

• Columns are not added, removed, or relocated, though the data may be updated.

• Groups are taken from x.

• Data frame attributes are taken from x.

If in_place = TRUE, the result will be returned invisibly.

Author(s)

Jasper Schelfhout

Update rows of a tibble

Description

Update rows of a tibble

Usage

## Default S3 method:
e_rows_update(
  x,
  y,
  by = NULL,
  ...,
  match = match,
  unmatched = c("error", "ignore"),
  copy = FALSE,
  in_place = FALSE
)

Arguments

Details

Mainly a wrapper around rows_update. Allows for specific implementations should the behavior differ from what's needed by editbl. Reason for separate method is to avoid conflicts on package loading.

Value

An object of the same type as x. The order of the rows and columns of x is preserved as much as possible. The output has the following properties:

• rows_update() and rows_patch() preserve the number of rows; rows_insert(), rows_append(), and rows_upsert() return all existing rows and potentially new rows; rows_delete() returns a subset of the rows.

• Columns are not added, removed, or relocated, though the data may be updated.

• Groups are taken from x.

• Data frame attributes are taken from x.

If in_place = TRUE, the result will be returned invisibly.

rows_update implementation for data.table backends.

Description

rows_update implementation for data.table backends.

Usage

## S3 method for class 'dtplyr_step'
e_rows_update(
  x,
  y,
  by = NULL,
  match = NULL,
  ...,
  copy = FALSE,
  in_place = FALSE
)

Arguments

Details

Mainly a wrapper around rows_update. Allows for specific implementations should the behavior differ from what's needed by editbl. Reason for separate method is to avoid conflicts on package loading.

Value

An object of the same type as x. The order of the rows and columns of x is preserved as much as possible. The output has the following properties:

• rows_update() and rows_patch() preserve the number of rows; rows_insert(), rows_append(), and rows_upsert() return all existing rows and potentially new rows; rows_delete() returns a subset of the rows.

• Columns are not added, removed, or relocated, though the data may be updated.

• Groups are taken from x.

• Data frame attributes are taken from x.

If in_place = TRUE, the result will be returned invisibly.

Author(s)

Jasper Schelfhout

rows_update implementation for DBI backends.

Description

rows_update implementation for DBI backends.

Usage

## S3 method for class 'tbl_dbi'
e_rows_update(
  x,
  y,
  by = NULL,
  match = NULL,
  ...,
  copy = FALSE,
  in_place = FALSE
)

Arguments

Details

Mainly a wrapper around rows_update. Allows for specific implementations should the behavior differ from what's needed by editbl. Reason for separate method is to avoid conflicts on package loading.

Value

An object of the same type as x. The order of the rows and columns of x is preserved as much as possible. The output has the following properties:

• rows_update() and rows_patch() preserve the number of rows; rows_insert(), rows_append(), and rows_upsert() return all existing rows and potentially new rows; rows_delete() returns a subset of the rows.

• Columns are not added, removed, or relocated, though the data may be updated.

• Groups are taken from x.

• Data frame attributes are taken from x.

If in_place = TRUE, the result will be returned invisibly.

Author(s)

Jasper Schelfhout

Examples

library(dplyr)

# Set up a test table
conn <- DBI::dbConnect(RSQLite::SQLite(), ":memory:")
artists_df <- data.frame(
         ArtistId = c(1,2),
         Name = c("AC/DC", "The Offspring")
)
DBI::dbWriteTable(conn, "Artist", artists_df)     

# Update rows without changing the key.
artists <- tbl(conn, "Artist")
DBI::dbBegin(conn)
y <- data.frame(ArtistId = 1, Name = "DC/AC")
e_rows_update(
     x = artists,
     y = y,
     by = "ArtistId",
     in_place = TRUE)
DBI::dbRollback(conn)

# Update key values of rows.
DBI::dbBegin(conn)
y <- data.frame(ArtistId = 999, Name = "DC/AC")
match <- list(
   x = data.frame("ArtistId" = 1),
   y = data.frame("ArtistId" = 999)
)
e_rows_update(
    x = artists,
    y = y,
    match = match,
    by = "ArtistId",
    in_place = TRUE)
DBI::dbRollback(conn)
DBI::dbDisconnect(conn)

Determine if a row can be cloned

Description

Determine if a row can be cloned

Usage

evalCanCloneRow(row, canCloneRow = TRUE, statusCol = "_editbl_status")

Arguments

Details

calling this around the user passed on function ensures that newly inserted rows are being excempt from the logic. Moreover, the output of the function can be checked.

Value

boolean

Author(s)

Saar Junius

Determine if a row can be deleted

Description

Determine if a row can be deleted

Usage

evalCanDeleteRow(row, canDeleteRow = TRUE, statusCol = "_editbl_status")

Arguments

Details

calling this around the user passed on function ensures that newly inserted rows are being excempt from the logic. Moreover, the output of the function can be checked.

Value

boolean

Author(s)

Jasper Schelfhout

Determine if a row can be edited

Description

Determine if a row can be edited

Usage

evalCanEditRow(row, canEditRow = TRUE, statusCol = "_editbl_status")

Arguments

Details

calling this around the user passed on function ensures that newly inserted rows are being excempt from the logic. Moreover, the output of the function can be checked.

Value

boolean

Author(s)

Jasper Schelfhout

Fill data columns based on foreignTbls

Description

Fill data columns based on foreignTbls

Usage

fillDeductedColumns(tbl, foreignTbls)

Arguments

Details

When a combination of columns is not found in the foreignTbl, fill the deductedColumns with NA.

on foreignTbls suggesting conflicting data, an arbitrary choice is made. It is best to afterwards check with checkForeignTbls to see if a valid result is obtained.

Value

tbl

Author(s)

Jasper Schelfhout

Replace instances of integer64 with actual NA values instead of weird default 9218868437227407266

Description

Replace instances of integer64 with actual NA values instead of weird default 9218868437227407266

Usage

fixInteger64(x)

Arguments

Details

github issue

Value

x with integer64 columns set to bit64::as.integer64(NA)

Author(s)

Jasper Schelfhout

Create a foreign tibble

Description

Create a foreign tibble

Usage

foreignTbl(
  x,
  y,
  by = intersect(dplyr::tbl_vars(x), dplyr::tbl_vars(y)),
  naturalKey = dplyr::tbl_vars(y),
  allowNew = FALSE
)

Arguments

Details

This is a tibble that can be passed onto eDT as a referenced table.

It is the equivalent of a database table to which the data tbl of eDT has a foreign key.

It will be merged with the tbl passed onto the data argument allowing to provide restrictions for certain columns.

Note that row uniqueness for the columns used in by and naturalKey is assumed. This assumption will however not be checked since it is an expensive operation on big datasets. However, if violated, it might give errors or unexpected results during usage of the eDT module.

Value

List with unmodified arguments. However, they have now been checked for validity.

• y, see argument y.

• by, see argument by.

• naturalKey, see argument naturalKey.

• allowNew, see argument allowNew

Author(s)

Jasper Schelfhout

Examples

a <- tibble::tibble(
   first_name = c("Albert","Donald","Mickey"),
   last_name_id = c(1,2,2)
 )

b <-  foreignTbl(
 a,
 tibble::tibble(
     last_name = c("Einstein", "Duck", "Mouse"),
     last_name_id = c(1,2,3)
   ),
 by = "last_name_id",
 naturalKey = "last_name"
)

## Only run this in interactive R sessions
if(interactive()){
  eDT(a,
   foreignTbls = list(b),
   options = list(columnDefs = list(list(visible=FALSE, targets="last_name_id")))
  )
 }

Get types of columns in a tbl

Description

Get types of columns in a tbl

Usage

getColumnTypeSums(tbl)

Arguments

Value

named list with types of the colums

Author(s)

Jasper Schelfhout

Get all columns that are not natural keys

Description

Get all columns that are not natural keys

Usage

getNonNaturalKeyCols(foreignTbls)

Arguments

Value

character

Author(s)

Jasper Schelfhout

Get name of the tbl in the database

Description

Get name of the tbl in the database

Usage

get_db_table_name(x)

Arguments

Value

SQL, the table name as used in the database

Add some extra columns to data to allow for / keep track of modifications

Description

Add some extra columns to data to allow for / keep track of modifications

Usage

initData(
  data,
  ns,
  buttonCol = "buttons",
  statusCol = "_editbl_status",
  deleteCol = "_editbl_deleted",
  iCol = "i",
  canDeleteRow = TRUE,
  canEditRow = TRUE,
  canCloneRow = TRUE
)

Arguments

Value

data with extra columns buttons, status, i.

Author(s)

Jasper Schelfhout

An input server for a data.frame

Description

An input server for a data.frame

Usage

inputServer(id, data, ...)

Arguments

Details

A new method for this can be added if you wish to alter the default behavior of the pop-up modals in eDT.

Value

modified version of data

Author(s)

Jasper Schelfhout

Examples

if(interactive()){
  library(shiny)
  ui <- inputUI('id')
  server <- function(input,output,session){
    input <- inputServer("id", mtcars[1,])
    observe({print(input())})
  }
shinyApp(ui, server)
}

An input server for a data.frame

Description

An input server for a data.frame

Usage

## Default S3 method:
inputServer(id, data, colnames, notEditable, foreignTbls, ...)

Arguments

Details

Reads all inputs ids that are identical to column names of the data and updates the data.

Value

reactive modified version of data

Author(s)

Jasper Schelfhout

An input UI for a data.frame

Description

An input UI for a data.frame

Usage

inputUI(id, ...)

Arguments

Details

A new method for this can be added if you wish to alter the default behavior of the pop-up modals in eDT.

Value

HTML. A set of input fields corresponding to the given row.

Author(s)

Jasper Schelfhout

Examples

if(interactive()){
  library(shiny)
  ui <- inputUI('id')
  server <- function(input,output,session){
    input <- inputServer("id", mtcars[1,])
    observe({print(input())})
  }
shinyApp(ui, server)
}

UI part for modal with input fields for editing

Description

UI part for modal with input fields for editing

Usage

## Default S3 method:
inputUI(id, ...)

Arguments

Details

The UI elements that have an id identical to a column name are used for updating the data.

Value

HTML. A set of input fields corresponding to the given row.

Author(s)

Jasper Schelfhout

Merge a tbl with it a foreignTbl

Description

Merge a tbl with it a foreignTbl

Usage

joinForeignTbl(
  tbl,
  foreignTbl,
  keepNA = TRUE,
  by = foreignTbl$by,
  copy = TRUE,
  type = c("inner", "left")[1]
)

Arguments

Details

see also dplyr join functions, for example dplyr::left_join.

Value

tbl, containing both columns from argument tbl and argument foreignTbl.

Author(s)

Jasper Schelfhout

Overwrite default settings with provided settings

Description

Overwrite default settings with provided settings

Usage

overwriteDefaults(defaults, settings)

Arguments

Value

named character vector

Author(s)

Jasper Schelfhout

Start a transaction for a tibble

Description

Start a transaction for a tibble

Usage

rollbackTransaction(tbl)

Arguments

Author(s)

Jasper Schelfhout

Add a row to a table in the database.

Description

Add a row to a table in the database.

Usage

rowInsert(conn, table, values)

Arguments

Value

integer number of affected rows.

Update rows in the database.

Description

Update rows in the database.

Usage

rowUpdate(conn, table, values, where)

Arguments

Value

integer number of affected rows.

rows_delete implementation for data.table backends.

Description

rows_delete implementation for data.table backends.

Usage

## S3 method for class 'dtplyr_step'
rows_delete(x, y, by = NULL, ..., unmatched, copy = FALSE, in_place = FALSE)

Arguments

Value

An object of the same type as x. The order of the rows and columns of x is preserved as much as possible. The output has the following properties:

• rows_update() and rows_patch() preserve the number of rows; rows_insert(), rows_append(), and rows_upsert() return all existing rows and potentially new rows; rows_delete() returns a subset of the rows.

• Columns are not added, removed, or relocated, though the data may be updated.

• Groups are taken from x.

• Data frame attributes are taken from x.

If in_place = TRUE, the result will be returned invisibly.

Author(s)

Jasper Schelfhout

Run a demo app

Description

Run a demo app

Usage

runDemoApp(app = "database", ...)

Arguments

Details

These apps are for illustrative purposes.

Value

An object that represents the app. Printing the object or passing it to runApp() will run the app.

Examples

## Only run this example in interactive R sessions
if(interactive()){
 
  # Database
  tmpFile <- tempfile(fileext = ".sqlite")
  file.copy(system.file("extdata", "chinook.sqlite", package = 'editbl'), tmpFile)

  conn <- connectDB(dbname = tmpFile)

  runDemoApp(app = "database", conn = conn)
  DBI::dbDisconnect(conn)

  unlink(tmpFile)

  # mtcars
  runDemoApp(app = "mtcars")

  # Any tibble of your liking
  runDemoApp(app = "custom", dplyr::tibble(iris))
}

Run a demo app

Description

Run a demo app

Usage

runDemoApp_DB()

Value

An object that represents the app. Printing the object or passing it to runApp() will run the app.

Run a custom demo app

Description

Run a custom demo app

Usage

runDemoApp_custom(x)

Arguments

Value

An object that represents the app. Printing the object or passing it to runApp() will run the app.

Run a demo app

Description

Run a demo app

Usage

runDemoApp_mtcars()

Value

An object that represents the app. Printing the object or passing it to runApp() will run the app.

Run a development app

Description

Run a development app

Usage

runDevApp()

Details

This app prints some of the server objects and has a button to interactively browse the code. This is useful for debugging and experimenting with new features.

Value

An object that represents the app. Printing the object or passing it to runApp() will run the app.

Server part to use a datatable as select input

Description

Server part to use a datatable as select input

Usage

selectInputDT_Server(
  id,
  label = "",
  choices,
  selected = NULL,
  multiple = FALSE
)

Arguments

Value

A selection of rows from the data.frame provided under choices.

Author(s)

Jasper Schelfhout

See Also

shiny::selectInput. This function can be more convenient for selecting rows with multiple columns.

Examples

## Only run this example in interactive R sessions
if(interactive()){
  ui <- selectInputDT_UI('id')
  data <- data.frame(id = 1:3, name = letters[1:3])
  server <- function(input,output, session){
    selected = selectInputDT_Server('id', choices = data, selected = data[1,] )
    observe({print(selected())})
  }
  shiny::shinyApp(ui, server)

}

UI part of a DT select input

Description

UI part of a DT select input

Usage

selectInputDT_UI(id)

Arguments

Value

HTML

Author(s)

Jasper Schelfhout

Examples

## Only run this example in interactive R sessions
if(interactive()){
  ui <- selectInputDT_UI('id')
  data <- data.frame(id = 1:3, name = letters[1:3])
  server <- function(input,output, session){
    selected = selectInputDT_Server('id', choices = data, selected = data[1,] )
    observe({print(selected())})
  }
  shiny::shinyApp(ui, server)

}

Get a shiny input for a column of a tbl

Description

Get a shiny input for a column of a tbl

Usage

shinyInput(x, inputId, label, selected)

Arguments

Value

shiny input

Author(s)

Jasper Schelfhout

Standardize colnames argument to the format of named character vector

Description

Standardize colnames argument to the format of named character vector

Usage

standardizeArgument_colnames(colnames, data)

Arguments

Value

named character vector

Author(s)

Jasper Schelfhout

Standardized editable argument to be in the form of a list

Description

Standardized editable argument to be in the form of a list

Usage

standardizeArgument_editable(editable, data)

Arguments

Value

list of the form list(target = foo, ...)

Author(s)

Jasper Schelfhout

Generate where sql

Description

Generate where sql

Usage

whereSQL(conn, table, column, operator = "in", values = NULL)

Arguments

Value

character sql

Author(s)

Jasper Schelfhout