Package 'arcgisutils'

Description

Override the default user-agent set by httr2 to indicate that a request came from arcgisutils.

Usage

arc_agent(req)

Arguments

Value

an httr2 request object

Examples

req <- httr2::request("http://example.com")
arc_agent(req)

Description

This function takes a url and creates a basic httr2 request that adds the user-agent and adds an authorization token to the X-Esri-Authorization header.

Usage

arc_base_req(
  url,
  token = NULL,
  path = NULL,
  query = NULL,
  error_call = rlang::caller_env()
)

Arguments

Value

an httr2_request with the X-Esri-Authorization header and User-Agent set.

Examples

arc_base_req("https://arcgis.com")

Description

ArcGIS endpoints make extensive use of form encoded data for the body of http requests. Form requests require that each element has a name and is encoded as a single string—often as json.

Usage

arc_form_params(params = list())

as_form_params(x)

Arguments

Details

The arc_form_params class provides validation of form body parameters ensuring that each element is a scalar string. It uses a named list internally to store the parameters.

The helper function as_form_params() converts a named list to form parameters by automatically JSON-encoding each element using yyjsonr::write_json_str() with auto_unbox = TRUE.

Value

an object of class arc_form_params

See Also

Other geoprocessing: arc_gp_job, arc_job_status(), gp_job_from_url(), gp_params

Other geoprocessing: arc_gp_job, arc_job_status(), gp_job_from_url(), gp_params

Examples

arc_form_params(
  list(f = "json", outFields = "*", where = "1 = 1")
)

Description

The arc_gp_job class is used to interact with Geoprocessing Services in ArcGIS Online and Enterprise.

Usage

new_gp_job(base_url, params = list(), token = arc_token())

Arguments

Details

The arc_gp_job uses S7 classes for the job request parameters and job status via arc_form_params() and arc_job_status() respectively. Importantly, arc_form_params() ensures that parameters provided to a geoprocessing service are all character scalars as required by the form body.

Value

An object of class arc_gp_job.

Associated Functions

from_url(url, token = arc_token())

Create a GP Job object from an existing job URL

Public fields

Active bindings

Methods

Public methods

• arc_gp_job$new()

• arc_gp_job$start()

• arc_gp_job$cancel()

• arc_gp_job$await()

• arc_gp_job$clone()

Method new()

Usage

arc_gp_job$new(
  base_url,
  params = list(),
  result_fn = NULL,
  token = arc_token(),
  error_call = rlang::caller_call()
)

Arguments

Method start()

Starts the job by calling the ⁠/submitJob⁠ endpoint. This also sets the public field id.

Usage

arc_gp_job$start()

Method cancel()

Cancels a job by calling the ⁠/cancel⁠ endpoint.

Usage

arc_gp_job$cancel()

Method await()

Waits for job completion and returns results.

Usage

arc_gp_job$await(interval = 0.1, verbose = FALSE)

Arguments

Method clone()

The objects of this class are cloneable with this method.

Usage

arc_gp_job$clone(deep = FALSE)

Arguments

See Also

Other geoprocessing: arc_form_params(), arc_job_status(), gp_job_from_url(), gp_params

Examples

url <- paste0(
  "https://logistics.arcgis.com/arcgis/",
  "rest/services/World/ServiceAreas/",
  "GPServer/GenerateServiceAreas"
)
job <- new_gp_job(url, list(f = "json"))
job

# extract params S7 class
params <- job$params
params

# view underlying list
params@params

Description

Fetches metadata about a group based on a provided group_id.

Usage

arc_group(group_id, host = arc_host(), token = arc_token())

Arguments

Details

Value

a list with group metadata

See Also

Other portal organization: arc_user()

Examples

arc_group("2f0ec8cb03574128bd673cefab106f39")

Description

List all users in a given group.

Usage

arc_group_users(
  group,
  name = NULL,
  member_type = NULL,
  joined_before = NULL,
  joined_after = NULL,
  sort_field = c("username", "membertype", "joined"),
  sort_order = c("asc", "desc"),
  page_size = 50,
  max_pages = Inf,
  .progress = TRUE,
  host = arc_host(),
  token = arc_token()
)

Arguments

Value

a data.frame

References

API Reference

Examples

## Not run: 
set_arc_token(auth_user())
groups <- arc_user("r-bridge-docs")$groups
arc_group_users(groups$id[1])

## End(Not run)

Description

Returns a scalar character indicating the host to make requests to.

Usage

arc_host()

Details

By default, the host is ArcGIS Online <⁠https://www.arcgis.com⁠>. If the environment variable ARCGIS_HOST is set, it will be returned.

Value

A scalar character, "https://www.arcgis.com" by default.

Examples

arc_host()

Description

Given the unique ID of a content item, fetches the item's metadata from a portal.

Usage

arc_item(item_id, host = arc_host(), token = arc_token())

Arguments

Details

See API Reference for more information.

Value

an object of class PortalItem which is a list with the item's metadata.

See Also

Other portal item: arc_item_data()

Examples

arc_item("9df5e769bfe8412b8de36a2e618c7672")

Description

Download the data backing a portal item. This function always returns a raw vector as the type of the data that is downloaded cannot always be known.

Usage

arc_item_data(item, host = arc_host(), token = arc_token())

Arguments

Details

Value

a raw vector containing the bytes of the data associated with the item. If the response is application/json then the json string is returned without parsing.

See Also

Other portal item: arc_item()

Examples

arc_item_data("9df5e769bfe8412b8de36a2e618c7672")

Description

Represents the status of a geoprocessing job.

Usage

arc_job_status(status = character(0))

Arguments

Value

an object of class arc_job_status

See Also

Other geoprocessing: arc_form_params(), arc_gp_job, gp_job_from_url(), gp_params

Examples

arc_job_status("esriJobSubmitted")

Description

Many API endpoints provide common pagination properties. arc_paginate_request() automatically applies pagination to an input request.

Usage

arc_paginate_req(req, page_size = 10, max_pages = Inf, .progress = TRUE)

Arguments

Value

a list of httr2_response.

References

API Documentation

See Also

arc_base_req()

Description

The resources endpoint lists all file resources for the organization.

Usage

arc_portal_resources(
  id = arc_portal_self(token)[["id"]],
  page_size = 50,
  max_pages = Inf,
  .progress = TRUE,
  host = arc_host(),
  token = arc_token()
)

Arguments

Value

a data.frame of resources available to your portal.

References

API Reference

See Also

Other portal: arc_portal_urls(), arc_portal_users(), self

Examples

## Not run: 
  set_arc_token(auth_user())
  arc_portal_resources()

## End(Not run)

Description

The servers resource lists the ArcGIS Server sites that have been federated with the portal.

Usage

arc_portal_servers(
  id = arc_portal_self(token)[["id"]],
  host = arc_host(),
  token = arc_token()
)

Arguments

Value

a data.frame of servers

Examples

## Not run: 
set_arc_token(auth_user())
arc_portal_servers()

## End(Not run)

Description

Returns the URLs of an organizations services.

Usage

arc_portal_urls(host = arc_host(), token = arc_token())

Arguments

Details

See API Reference for more information.

Value

a data.frame

See Also

Other portal: arc_portal_resources(), arc_portal_users(), self

Examples

arc_portal_urls()

Description

This function lists all users in a portal.

Usage

arc_portal_users(
  id = arc_portal_self(token)[["id"]],
  sort_field = NULL,
  provider = NULL,
  sort_order = NULL,
  role = NULL,
  fullname = NULL,
  username = NULL,
  firstname = NULL,
  lastname = NULL,
  filter_intersection = NULL,
  page_size = 50,
  max_pages = Inf,
  .progress = TRUE,
  host = arc_host(),
  token = arc_token()
)

Arguments

Value

a data.frame of users.

References

API Reference

See Also

Other portal: arc_portal_resources(), arc_portal_urls(), self

Examples

## Not run: 
set_arc_token(auth_user())
arc_portal_users()

## End(Not run)

Description

These functions are used to set, fetch, and check authorization tokens.

Usage

arc_token(token = "ARCGIS_TOKEN")

set_arc_token(token, ...)

unset_arc_token(token = NULL)

obj_check_token(token, call = rlang::caller_env())

check_token_has_user(token, call = rlang::caller_env())

Arguments

Details

It is possible to have multiple authorization tokens in one session. These functions assist you in managing them.

arc_token() is used to fetch tokens by name. The default token is ARCGIS_TOKEN. However, they can be any valid character scalar. set_arc_token() will create store a token with the name ARCGIS_TOKEN. However, you can alternatively set the tokens by name using a key-value pair. The key is what you would pass to arc_token() to fetch the httr2_token object. To remove a token that has been set, use unset_arc_token().

obj_check_token() is a developer oriented function that can be used to check if an object is indeed an httr2_token. To check if a token has expired, validate_or_refresh_token() will do so.

check_token_has_user() is a developer oriented function that checks to see if a token has a username field associated with it.

For developers:

set_arc_token() uses a package level environment to store the tokens. The tokens are fetched from the environment using arc_token().

Examples

# create fake tokens
token_a <- httr2::oauth_token("1234", arcgis_host = arc_host())
token_b <- httr2::oauth_token("abcd", arcgis_host = arc_host())

# set token to the default location
set_arc_token(token_a)

# fetch token from the default location
arc_token()

# set token by name
set_arc_token(org_a = token_a, org_b = token_b)

# fetch token by name
arc_token("org_a")
arc_token("org_b")

# unset tokens
unset_arc_token()
unset_arc_token(c("org_a", "org_b"))

Description

Fetch a user's metadata based on username.

Usage

arc_user(username, host = arc_host(), token = arc_token())

Arguments

Details

Value

a list of class PortalUser

See Also

Other portal organization: arc_group()

Examples

arc_user("esri_en")

Description

Given an authentication token, return a list of user-specfic information such as the user ID, username, available credits, email, groups, last login date and more.

Usage

arc_user_self(
  host = arc_host(),
  token = arc_token(),
  error_call = rlang::caller_call()
)

Arguments

Value

a list of the authenticated user's metadata

References

API Reference

Examples

## Not run: 
if (interactive()) {
  arc_user_self(token = auth_user())
}

## End(Not run)

Description

as_esri_geometry() converts an sfg object to a EsriJSON Geometry object as a string.

Usage

as_esri_geometry(x, crs = NULL, call = rlang::caller_env())

Arguments

Details

See as_featureset() and as_features() for converting sfc and sf objects into EsriJSON.

Value

a scalar string

References

API Reference

Examples

library(sf)
# POINT
# create sfg points
xy <- st_point(c(1, 2))
xyz <- st_point(c(1, 2, 3))
xym <- st_point(c(1, 2, 3), dim = "XYM")
xyzm <- st_point(c(1, 2, 3, 4))

as_esri_geometry(xy)
as_esri_geometry(xyz)
as_esri_geometry(xym)
as_esri_geometry(xyzm)

# MULTIPOINT
# vector to create matrix points
set.seed(0)
x <- rnorm(12)

xy <- st_multipoint(matrix(x, ncol = 2))
xyz <- st_multipoint(matrix(x, ncol = 3))
xym <- st_multipoint(matrix(x, ncol = 3), dim = "XYM")
xyzm <- st_multipoint(matrix(x, ncol = 4), dim = "XYM")

as_esri_geometry(xy)
as_esri_geometry(xyz)
as_esri_geometry(xym)
as_esri_geometry(xyzm)

# LINESTRING
xy <- st_linestring(matrix(x, ncol = 2))
xyz <- st_linestring(matrix(x, ncol = 3))
xym <- st_linestring(matrix(x, ncol = 3), dim = "XYM")
xyzm <- st_linestring(matrix(x, ncol = 4), dim = "XYM")

as_esri_geometry(xy)
as_esri_geometry(xyz)
as_esri_geometry(xym)
as_esri_geometry(xyzm)

# MULTILINESTRING
as_esri_geometry(st_multilinestring(list(xy, xy)))
as_esri_geometry(st_multilinestring(list(xyz, xyz)))
as_esri_geometry(st_multilinestring(list(xym, xym)))
as_esri_geometry(st_multilinestring(list(xyzm, xyzm)))

# POLYGON
coords <- rbind(
  c(0, 0, 0, 1),
  c(0, 1, 0, 1),
  c(1, 1, 1, 1),
  c(1, 0, 1, 1),
  c(0, 0, 0, 1)
)

xy <- st_polygon(list(coords[, 1:2]))
xyz <- st_polygon(list(coords[, 1:3]))
xym <- st_polygon(list(coords[, 1:3]), dim = "XYM")
xyzm <- st_polygon(list(coords))

as_esri_geometry(xy)
as_esri_geometry(xyz)
as_esri_geometry(xym)
as_esri_geometry(xyzm)

# MULTIPOLYGON
as_esri_geometry(st_multipolygon(list(xy, xy)))
as_esri_geometry(st_multipolygon(list(xyz, xyz)))
as_esri_geometry(st_multipolygon(list(xym, xym)))
as_esri_geometry(st_multipolygon(list(xyzm, xyzm)))

Description

Given an sf or sfc object create a list that represents the extent of the object. The result of this function can be parsed directly into json using jsonify::to_json(x, unbox = TRUE) or included into a list as the extent component that will be eventually converted into json using the above function.

Usage

as_extent(x, crs = sf::st_crs(x), call = rlang::caller_env())

Arguments

Value

An extent json object. Use jsonify::to_json(x, unbox = TRUE) to convert to json.

Examples

nc <- sf::st_read(system.file("shape/nc.shp", package = "sf"), quiet = TRUE)
as_extent(nc)

Description

These functions create an array of Esri Feature objects. Each feature consists of a geometry and attribute field. The result of as_esri_features() is a JSON array of Features whereas as_features() is a list that represents the same JSON array. Using jsonify::to_json(as_features(x), unbox = TRUE) will result in the same JSON array.

Usage

as_features(x, crs = sf::st_crs(x), call = rlang::caller_env())

as_esri_features(x, crs = sf::st_crs(x), call = rlang::caller_env())

Arguments

Value

Either a scalar string or a named list.

References

API Reference

Examples

library(sf)
# POINT
# create sfg points
xy <- st_sfc(st_point(c(1, 2)))
xyz <- st_sfc(st_point(c(1, 2, 3)))
xym <- st_sfc(st_point(c(1, 2, 3), dim = "XYM"))

as_esri_features(xy)
as_esri_features(xyz)
as_esri_features(xym)

# MULTIPOINT
# vector to create matrix points
set.seed(0)
x <- rnorm(12)

xy <- st_sfc(st_multipoint(matrix(x, ncol = 2)))
xyz <- st_sfc(st_multipoint(matrix(x, ncol = 3)))
xym <- st_sfc(st_multipoint(matrix(x, ncol = 3), dim = "XYM"))

as_esri_features(xy)
as_esri_features(xyz)
as_esri_features(xym)

# LINESTRING
xy <- st_sfc(st_linestring(matrix(x, ncol = 2)))
xyz <- st_sfc(st_linestring(matrix(x, ncol = 3)))
xym <- st_sfc(st_linestring(matrix(x, ncol = 3), dim = "XYM"))

as_esri_features(xy)
as_esri_features(xyz)
as_esri_features(xym)

# MULTILINESTRING
as_esri_features(st_sfc(st_multilinestring(list(xy[[1]], xy[[1]]))))
as_esri_features(st_sfc(st_multilinestring(list(xyz[[1]], xyz[[1]]))))
as_esri_features(st_sfc(st_multilinestring(list(xym[[1]], xym[[1]]))))

# POLYGON
coords <- rbind(
  c(0, 0, 0, 1),
  c(0, 1, 0, 1),
  c(1, 1, 1, 1),
  c(1, 0, 1, 1),
  c(0, 0, 0, 1)
)

xy <- st_sfc(st_polygon(list(coords[, 1:2])))
xyz <- st_sfc(st_polygon(list(coords[, 1:3])))
xym <- st_sfc(st_polygon(list(coords[, 1:3]), dim = "XYM"))

as_esri_features(xy)
as_esri_features(xyz)
as_esri_features(xym)

# MULTIPOLYGON
as_esri_features(st_sfc(st_multipolygon(list(xy[[1]], xy[[1]]))))
as_esri_features(st_sfc(st_multipolygon(list(xyz[[1]], xyz[[1]]))))
as_esri_features(st_sfc(st_multipolygon(list(xym[[1]], xym[[1]]))))

Description

These functions create an Esri FeatureSet object. A FeatureSet contains an inner array of features as well as additional metadata about the the collection such as the geometry type, spatial reference, and object ID field.

Usage

as_featureset(x, crs = sf::st_crs(x), call = rlang::caller_env())

as_esri_featureset(x, crs = sf::st_crs(x), call = rlang::caller_env())

Arguments

Value

a list or a json string

References

API Reference

Examples

library(sf)
# POINT
# create sfg points
xy <- st_sfc(st_point(c(1, 2)))
xyz <- st_sfc(st_point(c(1, 2, 3)))
xym <- st_sfc(st_point(c(1, 2, 3), dim = "XYM"))

as_esri_featureset(xy)
as_esri_featureset(xyz)
as_esri_featureset(xym)

# MULTIPOINT
# vector to create matrix points
set.seed(0)
x <- rnorm(12)

xy <- st_sfc(st_multipoint(matrix(x, ncol = 2)))
xyz <- st_sfc(st_multipoint(matrix(x, ncol = 3)))
xym <- st_sfc(st_multipoint(matrix(x, ncol = 3), dim = "XYM"))

as_esri_featureset(xy)
as_esri_featureset(xyz)
as_esri_featureset(xym)

# LINESTRING
xy <- st_sfc(st_linestring(matrix(x, ncol = 2)))
xyz <- st_sfc(st_linestring(matrix(x, ncol = 3)))
xym <- st_sfc(st_linestring(matrix(x, ncol = 3), dim = "XYM"))

as_esri_featureset(xy)
as_esri_featureset(xyz)
as_esri_featureset(xym)

# MULTILINESTRING
as_esri_featureset(st_sfc(st_multilinestring(list(xy[[1]], xy[[1]]))))
as_esri_featureset(st_sfc(st_multilinestring(list(xyz[[1]], xyz[[1]]))))
as_esri_featureset(st_sfc(st_multilinestring(list(xym[[1]], xym[[1]]))))

# POLYGON
coords <- rbind(
  c(0, 0, 0, 1),
  c(0, 1, 0, 1),
  c(1, 1, 1, 1),
  c(1, 0, 1, 1),
  c(0, 0, 0, 1)
)

xy <- st_sfc(st_polygon(list(coords[, 1:2])))
xyz <- st_sfc(st_polygon(list(coords[, 1:3])))
xym <- st_sfc(st_polygon(list(coords[, 1:3]), dim = "XYM"))

as_esri_featureset(xy)
as_esri_featureset(xyz)
as_esri_featureset(xym)

# MULTIPOLYGON
as_esri_featureset(st_sfc(st_multipolygon(list(xy[[1]], xy[[1]]))))
as_esri_featureset(st_sfc(st_multipolygon(list(xyz[[1]], xyz[[1]]))))
as_esri_featureset(st_sfc(st_multipolygon(list(xym[[1]], xym[[1]]))))

Description

Infers Esri field types from R objects. Use as_fields() to create a data.frame of valid Esri Field Types from an sf object or data.frame.

Usage

as_fields(.data, arg = rlang::caller_arg(.data), call = rlang::caller_env())

infer_esri_type(
  .data,
  arg = rlang::caller_arg(.data),
  call = rlang::caller_env()
)

fields_as_ptype_df(fields, n = 0, call = rlang::caller_env())

ptype_tbl(fields, n = 0, call = rlang::caller_env())

Arguments

Details

• as_fields() takes a data frame-like object and infers the Esri field type from it.

• fields_as_pytpe_df() takes a list with type and name and creates an empty data.frame with the corresponding column names and types.

• get_ptype() takes a scalar character containing the Esri field type and returns a prototype of the pertinent R type

Field type mapping:

Esri field types are mapped as

• esriFieldTypeSmallInteger: integer

• esriFieldTypeSingle: double

• esriFieldTypeGUID: integer

• esriFieldTypeOID: integer

• esriFieldTypeInteger: integer

• esriFieldTypeBigInteger: double

• esriFieldTypeDouble: double

• esriFieldTypeString: character

• esriFieldTypeDate: date

R types are mapped as

• double: esriFieldTypeDouble

• integer: esriFieldTypeInteger

• character: esriFieldTypeString

• date: esriFieldTypeDate

• raw: esriFieldTypeBlob

Value

• fields_as_ptype_df() takes a data.frame with columns name and type and creates an empty data.frame with the corresponding columns and R types

• as_fields() returns a data.frame with columns name, type, alias, nullable, and editable columns

  • This resembles that of the fields returned by a FeatureService

Examples

inferred <- as_fields(iris)
inferred

fields_as_ptype_df(inferred)

Description

These functions are used to generate list objects that can be converted into json objects that are used in REST API requests. Notably they are used for adding R objects as items to a portal.

Usage

as_layer(
  x,
  name,
  title,
  layer_definition = as_layer_definition(x, name, "object_id", infer_esri_type(x)),
  id = NULL,
  layer_url = NULL,
  legend_url = NULL,
  popup_info = NULL,
  call = rlang::caller_env()
)

as_layer_definition(
  x,
  name,
  object_id_field,
  fields = infer_esri_type(x),
  display_field = NULL,
  drawing_info = NULL,
  has_attachments = FALSE,
  max_scale = 0,
  min_scale = 0,
  templates = NULL,
  type_id_field = NULL,
  types = NULL,
  call = rlang::caller_env()
)

as_feature_collection(
  layers = list(),
  show_legend = TRUE,
  call = rlang::caller_env()
)

Arguments

Details

A featureCollection defines a layer of features that will be stored on a web map. It consists of an array of layers. The layer contains the features (attributes and geometries) as a featureSet (see as_esri_featureset()) and additional metadata which is stored in the layerDefinitionobject. The layerDefinition most importantly documents the fields in the object, the object ID, and additional metadata such as name, title, and display scale.

Additional documentation for these json object:

• layer

• layerDefinition

• featureCollection

Value

A list object containing the required fields for each respective json type. The results can be converted to json using jsonify::to_json(x, unbox = TRUE)

Examples

ld <- as_layer_definition(iris, "iris", "objectID")
l <- as_layer(iris, "iris name", "Iris Title")
fc <- as_feature_collection(layers = list(l))

Description

Authorize your R session to connect to an ArcGIS Portal. See details.

Usage

auth_code(client = Sys.getenv("ARCGIS_CLIENT"), host = arc_host())

auth_client(
  client = Sys.getenv("ARCGIS_CLIENT"),
  secret = Sys.getenv("ARCGIS_SECRET"),
  host = arc_host(),
  expiration = 120
)

auth_binding()

auth_user(
  username = Sys.getenv("ARCGIS_USER"),
  password = Sys.getenv("ARCGIS_PASSWORD"),
  host = arc_host(),
  expiration = 60
)

auth_key(api_key = Sys.getenv("ARCGIS_API_KEY"), host = arc_host())

refresh_token(token, client = Sys.getenv("ARCGIS_CLIENT"), host = arc_host())

validate_or_refresh_token(
  token,
  client = Sys.getenv("ARCGIS_CLIENT"),
  host = arc_host(),
  refresh_threshold = 10,
  call = rlang::caller_env()
)

Arguments

Details

ArcGIS Online and Enterprise Portals utilize OAuth2 authorization via their REST APIs.

• auth_code() is the recommend OAuth2 workflow for interactive sessions

• auth_client() is the recommended OAuth2 workflow for non-interactive sessions

• auth_user() uses legacy username and password authorization using the generateToken endpoint. It is only recommended for legacy systems that do not implement OAuth2.

• auth_binding() fetches a token from the active portal set by arcgisbinding. Uses arcgisbinding::arc.check_portal() to extract the authorization token. Recommended if using arcgisbinding.

Value

an httr2_token

Examples

## Not run: 
auth_code()
auth_client()
auth_user()
auth_key()
auth_binding()

## End(Not run)

Description

oath_provider_arcgis() and auth_shiny() provide an integrated authentication experience for {shiny} applications via the package shinyOAuth. Applications that use auth_shiny() will enable user-specific behavior and authentications.

Usage

oauth_provider_arcgis(host = arc_host())

auth_shiny(
  client = Sys.getenv("ARCGIS_CLIENT"),
  secret = Sys.getenv("ARCGIS_SECRET"),
  redirect_uri = Sys.getenv("ARCGIS_REDIRECT_URI"),
  host = arc_host(),
  ...
)

Arguments

Details

Authentication with auth_shiny() requires the package shinyOAuth. When creating an OAuth app in ArcGIS Online / Enterprise, ensure that the app has a valid redirect URI. This must be the same redirect URI that is used by shinyOAuth and must be the same port as the shiny application is served on.

oauth_provider_arcgis() is a low-level provider function that mimics other ⁠oauth_provider_*()⁠ functions from shinyOAuth. Use auth_shiny() to create an OAuth client.

Important: The client object returned by auth_shiny() must be created outside of the server function to ensure a shared state across the OAuth flow. Creating the client inside the server function will result in authentication failures.

The user info returned from auth$token@userinfo has the same structure as arc_portal_self(). See that function's documentation for available fields.

The below example is derived from the shinyOAuth documentation.

library(shiny)
library(shinyOAuth)
library(arcgisutils)

# Simple UI
ui <- fluidPage(
  use_shinyOAuth(),
  uiOutput("login_information")
)

client <- auth_shiny()

server <- function(input, output, session) {
  # Set auto_redirect = FALSE for manual login
  auth <- shinyOAuth::oauth_module_server(
    "AGOL",
    client,
    auto_redirect = FALSE
  )

  output$login_information <- renderUI({
    if (auth$authenticated) {
      user_info <- auth$token@userinfo
      tagList(
        tags$p("You are logged in! Your details:"),
        tags$pre(paste(capture.output(str(user_info)), collapse = "\n"))
      )
    } else {
      tagList(
        tags$p("You are not logged in."),
        actionButton("login_btn", "Login with ArcGIS")
      )
    }
  })

  # Trigger login when button is clicked
  observeEvent(input$login_btn, {
    auth$request_login()
  })
}

runApp(
  shinyApp(ui, server),
  port = 8100,
  launch.browser = FALSE
)

# Open the app in your regular browser at http://localhost:8100

Description

General utility functions

Usage

compact(.x)

a %||% b

check_dots_named(dots, call = rlang::caller_env())

data_frame(x, call = rlang::caller_call())

Arguments

Details

• compact() removes any NULL list elements

• ⁠%||%⁠ is a special pipe operator that returns b if a is NULL

Value

• compact() a list

• ⁠%||%⁠ the first non-null item or NULL if both are NULL

Examples

# remove null elements
compact(list(a = NULL, b = 1))

# if NULL return rhs
NULL %||% 123

# if not NULL return lhs
123 %||% NULL

Description

For a given user or group, returns a data.frame of all content items owned by them.

Usage

arc_group_content(group, host = arc_host(), token = arc_token())

arc_user_content(user, host = arc_host(), token = arc_token())

Arguments

Value

a data.frame of content item metadata

References

• Group Content API Reference

• User Content API Reference

Examples

## Not run: 
library(arcgis)

# authenticate
set_arc_token(auth_user())

# get your own content items
self <- arc_user_self()
arc_user_content(self$username)

# get a specific group's items
arc_group_content("2f0ec8cb03574128bd673cefab106f39")

## End(Not run)

Description

The requests responses from ArcGIS don't return the status code in the response itself but rather from the body in the json. This function checks for the existence of an error. If an error is found, the contents of the error message are bubbled up.

Usage

detect_errors(response, error_call = rlang::caller_env())

catch_error(response, error_call = rlang::caller_env())

Arguments

Value

Nothing. Used for it's side effect. If an error code is encountered in the response an error is thrown with the error code and the error message.

Examples

## Not run: 
response <- list(
  error = list(
    code = 400L,
    message = "Unable to generate token.",
    details = "Invalid username or password."
  )
)

detect_errors(response)

## End(Not run)

Description

Given an sfc or sfg object determine what dimensions are represented.

Usage

determine_dims(x)

has_m(x)

has_z(x)

Arguments

Value

determine_dims() returns a scalar character of the value "xy", "xyz", or "xyzm" depending on what dimensions are represented.

has_m() and has_z() returns a logical scalar of TRUE or FALSE if the geometry has a Z or M dimension.

Examples

geo <- sf::st_read(system.file("shape/nc.shp", package="sf"), quiet = TRUE)[["geometry"]]

determine_dims(geo)
has_z(geo)
has_m(geo)

Description

Takes an sf or sfc object and returns the appropriate Esri geometry type.

Usage

determine_esri_geo_type(x, call = rlang::caller_env())

Arguments

Details

Geometry type mapping

• POINT: esriGeometryPoint

• MULTIPOINT: esriGeometryMultipoint

• LINESTRING: esriGeometryPolyline

• MULTILINESTRING: esriGeometryPolyline

• POLYGON: esriGeometryPolygon

• MULTIPOLYGON: esriGeometryPolygon

Value

returns a character scalar of the corresponding Esri geometry type

Examples

determine_esri_geo_type(sf::st_point(c(0, 0)))

Description

Utility functions for feature service metadata.

Usage

fetch_layer_metadata(url, token = NULL, call = rlang::caller_env())

Arguments

Details

• fetch_layer_metadata() given a request, fetches the metadata by setting the query parameter f=json

Value

returns a list object

Examples

# url is broken into parts to fit within 100 characters to avoid CRAN notes
url_parts <- c(
  "https://services.arcgis.com/P3ePLMYs2RVChkJx/ArcGIS/rest/services",
  "/USA_Counties_Generalized_Boundaries/FeatureServer/0"
)

furl <- paste0(url_parts, collapse = "")
meta <- fetch_layer_metadata(furl)
head(names(meta))

Description

Create GP Job from existing URL

Usage

gp_job_from_url(url, token = arc_token())

Arguments

See Also

Other geoprocessing: arc_form_params(), arc_gp_job, arc_job_status(), gp_params

Examples

if (interactive()) {
job_url <- paste0(
  "https://hydro.arcgis.com/arcgis/rest/services/Tools/Hydrology/",
  "GPServer/TraceDownstream/jobs/jfde67910074649e4a567f0adbb8af870"
)

gp_job_from_url(
  job_url,
  token = auth_user()
)
}

Description

Functions for converting R objects to and from ArcGIS geoprocessing parameter types. These functions handle the serialization and parsing of various data types used in ArcGIS geoprocessing services.

Usage

parse_gp_feature_record_set(json)

as_gp_feature_record_set(x)

parse_gp_record_set(json)

as_record_set(x)

as_gp_raster_layer(x)

gp_linear_unit(distance = integer(0), units = character(0))

as_gp_linear_unit(x)

parse_gp_linear_unit(json)

gp_areal_unit(area = integer(0), units = character(0))

as_gp_areal_unit(x)

parse_gp_areal_unit(json)

as_gp_date(x)

parse_gp_date(json)

as_spatial_reference(x)

from_spatial_reference(sr, error_call = rlang::caller_call())

parse_spatial_reference(json)

from_envelope(x, error_call = rlang::caller_call())

Arguments

Details

This package provides support for the following geoprocessing parameter types:

Implemented Types

• GPFeatureRecordSetLayer: Feature collections with geometry and attributes

• GPRecordSet: Tabular data without geometry

• GPRasterDataLayer: Raster datasets from Portal items, Image Servers, or URLs

• GPLinearUnit: Linear distance measurements with units

• GPArealUnit: Area measurements with units

• GPDate: Date/time values in milliseconds since epoch

• GPSpatialReference: Coordinate reference systems

Not Yet Implemented

The following types are planned for future implementation:

• GPField: Field definitions with name, type, and properties

• GPMultiValue: Arrays of values for a single data type

• GPValueTable: Flexible table-like objects with rows and columns

• GPComposite: Parameters that accept multiple data types

• GPEnvelope: Bounding box extents (use as_extent() for GPExtent)

Usage Patterns

Most functions follow a consistent pattern:

• ⁠as_gp_*()⁠: Convert R objects to geoprocessing parameter JSON

• ⁠parse_gp_*()⁠: Parse geoprocessing response JSON to R objects

• Constructor functions (e.g., gp_linear_unit(), gp_areal_unit()) create typed S7 objects

Examples

# Create a linear unit
distance <- gp_linear_unit(distance = 100, units = "esriMeters")

# Convert spatial data to feature record set
as_gp_feature_record_set(my_sf_data)

# Parse a geoprocessing response
parse_gp_feature_record_set(response_json)

References

API Documentation

See Also

Other geoprocessing: arc_form_params(), arc_gp_job, arc_job_status(), gp_job_from_url()

Examples

# create a feature record set
fset <- as_gp_feature_record_set(iris[1,])
fset

# create fake gp feature record set to parse
fset_list <- list(
  list(
    dataType = "GPFeatureRecordSetLayer",
    paramName = "example",
    value = as_featureset(iris[1,])
  )
)

# create the json
json <- yyjsonr::write_json_str(fset_list, auto_unbox = TRUE)

# parse the record set json
parse_gp_feature_record_set(json)

# linear units
lu <- gp_linear_unit(10, "esriMeters")
lu
as_gp_linear_unit(lu)

# areal units
au <- gp_areal_unit(10, "esriSquareMeters")
au

as_gp_areal_unit(au)

# dates
json <- r"({
  "paramName": "Output_Date",
  "dataType": "GPDate",
  "value": 1199145600000
})"

parse_gp_date(json)
sr <- list(wkid = 4326L)
from_spatial_reference(sr)
x <- list(
  xmin = -122.4195,
  ymin = 37.330219000000056,
  xmax = -122.030757,
  ymax = 37.77650360000007,
  spatialReference = list(wkid = 4326L, latestWkid = 4326L)
)

from_envelope(x)

Description

Esri date fields are represented as milliseconds from the Unix Epoch.

Usage

is_date(x, tz)

date_to_ms(x, tz = "UTC")

from_esri_date(x)

Arguments

Details

• is_date(): checks if an object is a Date or POSIXt class object.

• date_to_ms() converts a date object to milliseconds from the Unix Epoch in the specified time zone.

Value

• is_date() returns a logical scalar

• date_to_ms() returns a numeric vector of times in milliseconds from the Unix Epoch in the specified time zone.

Examples

today <- Sys.Date()

is_date(today)

date_to_ms(today)

Description

Parses an Esri FeatureSet JSON object into an R object. If there is no geometry present, a data.frame is returned. If there is geometry, an sf object is returned.

Usage

parse_esri_json(string, ..., call = rlang::caller_env())

Arguments

Value

A data.frame. If geometry is found, returns an sf object.

Examples

esri_json <- '{
    "geometryType": "esriGeometryPolygon",
    "spatialReference": {
        "wkid": 4326
    },
    "hasZ": false,
    "hasM": false,
    "features": [
        {
            "attributes": {
                "id": 1
            },
            "geometry": {
                "rings": [
                    [
                        [0.0, 0.0],
                        [1.0, 0.0],
                        [1.0, 1.0],
                        [0.0, 1.0],
                        [0.0, 0.0]
                    ]
                ]
            }
        }
    ]
}'

parse_esri_json(esri_json)

Description

Every portal item has an associated item type. Each of those item types have keywords which cna be used to help narrow down search further.

Usage

item_type(item_type = character(0))

item_keyword(keyword = character(0))

portal_item_keywords()

portal_item_types()

Arguments

References

REST API Documentation

Description

A general function that takes a list of data.frames and returns a single and combines them into a single object. It will use the fastest method available. In order this is collapse::rowbind(), data.table::rbindlist(), vctrs::list_unchop(), then do.call(rbind.data.frame, x).

Usage

rbind_results(x, call = rlang::current_env(), .ptype = data.frame())

Arguments

Details

If all items in the list are data.frames, then the result will be a data.frame. If all elements are an sf object, then the result will be an sf object. If the items are mixed, the result will be a data.frame.

If any items are NULL, then an attribute null_elements will be attached to the result. The attribute is an integer vector of the indices that were NULL.

Value

see details.

Examples

x <- head(iris)
res <- rbind_results(list(x, NULL, x))
attr(res, "null_elements")

Description

Perform full text search or use parameters to programamatically query your portal for content items.

Usage

search_items(
  query = NULL,
  filter = NULL,
  title = NULL,
  description = NULL,
  snippet = NULL,
  tags = NULL,
  owner = NULL,
  orgid = NULL,
  item_type = NULL,
  type_keywords = NULL,
  created = NULL,
  modified = NULL,
  categories = NULL,
  category_filters = NULL,
  sort_field = NULL,
  sort_order = NULL,
  count_fields = NULL,
  count_size = NULL,
  display_sublayers = FALSE,
  filter_logic = "and",
  bbox = NULL,
  page_size = 50,
  max_pages = Inf,
  .progress = TRUE,
  host = arc_host(),
  token = arc_token()
)

Arguments

Details

Search is quite nuanced and should be handled with care as you may get unexpected results.

• Most arguments are passed as filter parameters to the API endpoint.

• If multiple values are passed to an argument such as tags, the search will use an "OR" statement.

• When multiple arguments are provided, for example tags, owner, and item_type, the search will use "AND" logic—i.e. results shown match the tags and owner and item_type.

  • Note: you can change this to "OR" behavior by setting filter_logic = "or"

• If the filter argument is provided, all other arguments except query are ignored.

Value

a data.frame.

References

API Documentation

Examples

crime_items <- search_items(
  query = "crime",
  item_type = "Feature Service",
  max_pages = 1
)
crime_items

Description

The function returns the ⁠/self⁠ resource from the ArcGIS REST API. The ⁠/self⁠ endpoint returns the view of the portal as seen by the current user, whether anonymous or signed in.

Usage

arc_self_meta(token = arc_token(), error_call = rlang::current_call())

arc_portal_self(token = arc_token(), error_call = rlang::current_call())

Arguments

Details

See the endpoint documentation for more details.

The Portal Self response can vary based on whether it's called by a user, an app, or both.

The response includes user and appinfo properties, and the variations in responses are primarily related to these two properties. As the names indicate, the user property includes information about the user making the call, and the appinfo property includes information pertaining to the app that made the call.

Value

A named list.

See Also

Other portal: arc_portal_resources(), arc_portal_urls(), arc_portal_users()

Examples

## Not run: 
set_arc_token(auth_code())
self <- arc_self_meta()
names(self)

## End(Not run)

Description

arc_url_parse() uses httr2::url_parse() to parse URL components and combine the components with a service or content URL type and a layer number if applicable. A layer component is only included if the type is "MapServer" or "FeatureServer" and the URL includes a trailing digit. A full url value is also included in the returned list. The url, type, and layer components are not part of the httr2_url class object returned by httr2::url_parse().

Usage

arc_url_parse(url, base_url = NULL, error_call = rlang::caller_call())

arc_url_type(url, error_call = rlang::caller_call())

is_url(url, error_call = rlang::caller_call())

Arguments

Details

Value

A named list with the following components: scheme, hostname, username, password, port, path, query, fragment, url, type, and layer.

Examples

arc_url_parse(
  "https://services.arcgisonline.com/arcgis/rest/services/USA_Topo_Maps/MapServer/0"
)
arc_url_parse(
  "https://geocode.arcgis.com/arcgis/rest/services/World/GeocodeServer"
)
arc_url_parse(
  "https://services.arcgisonline.com/arcgis/rest/services/WorldElevation3D/Terrain3D/ImageServer"
)

Description

Takes a representation of a CRS and ensures that it is a valid one. The CRS is validated using sf::st_crs() if it cannot be validated, a null CRS is returned.

Usage

validate_crs(crs, arg = rlang::caller_arg(crs), call = rlang::caller_env())

Arguments

Details

See sf::st_crs() for more details on valid representations.

Value

Returns a list of length 1 with an element named spatialReference which is itself a named list.

If the provided CRS returns a valid well-known ID (WKID) spatialReference contains a named element called wkid which is the integer value of the WKID. If the WKID is not known but the CRS returned is a valid well-known text representation the wkid field is NA and another field wkt contains the valid wkt.

Examples

# using epsg code integer or string representation
validate_crs(3857)
validate_crs("EPSG:4326")

# using a custom proj4 string
proj4string <- "+proj=longlat +datum=WGS84 +no_defs"

crs <- validate_crs(proj4string)

# using wkt2 (from above result)
crs <- validate_crs(crs$spatialReference$wkt)