In frictionlessdata/frictionless-r: Read and Write Frictionless Data Packages

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

Data Resource is a simple format to describe a data resource such as an individual table or file, including its name, format, path, etc.

::: {.callout-info} In this document we use the terms "package" for Data Package, "resource" for Data Resource, "dialect" for Table Dialect, and "schema" for Table Schema. :::

General implementation

Frictionless supports reading, manipulating and writing resources, but much of its functionality is limited to Tabular Data Resources.

Read

resources() lists all resources in a package:

library(frictionless)
package <- example_package()

# List the resources
resources(package)

read_resource() reads data from a tabular resource to a data frame:

read_resource(package, "deployments")

Frictionless does not support reading data from non-tabular resources.

Manipulate

remove_resource() removes a resource (of any type):

remove_resource(package, "deployments")

# This and many other functions return "package", which you can update with
# package <- remove_resource(package, "deployments")

add_resource() adds or replaces a tabular resource. The provided data must be a data frame or a tabular data file (e.g. CSV):

# Add a resource with data from a data frame
add_resource(package, "iris", data = iris)

# Replace a resource with one where data is stored in a tabular file
path <- system.file("extdata", "v1", "deployments.csv", package = "frictionless")
add_resource(package, "deployments", data = path, replace = TRUE)

::: {.callout-info} You can pipe most functions (see vignette("data-package")). :::

Write

write_package() writes a package to disk as a datapackage.json file. This file includes the metadata of all the resources. write_package() also writes resource data to CSV files, unless the referred data are referred to be URL or inline. See the function documentation for details.

Properties implementation

name

name is required. It is used to identify a resource in read_resource(), add_resource() and remove_resource() (always as the second argument):

deployments <- read_resource(package, resource_name = "deployments")

add_resource() sets name to the provided resource_name:

add_resource(package, resource_name = "iris", data = iris)

path

path or data (see further) is required. Providing both is not allowed.

path is for data in files (e.g. a CSV file). It can be a local path or URL. Supported protocols are http, https, ftp, sftp and sftp. Absolute paths (/) or relative parent paths (../) are not allowed to avoid security vulnerabilities.

When multiple paths are provided ("path": ["myfile1.csv", "myfile2.csv"]), the files are expected to have the same structure. read_resource() merges these into a single data frame in the order the paths are provided (using dplyr::bind_rows()):

# The "observations" resource has multiple files in path
package$resources[[2]]$path
# These are combined into a single data frame when reading
read_resource(package, "observations")

add_resource() sets path to the path(s) provided in data:

path <- system.file("extdata", "v1", "deployments.csv", package = "frictionless")
add_resource(package, "deployments", data = path, replace = TRUE)

data

::: {.callout-warning} Support for inline data is currently limited, e.g. JSON object and string are not supported and schema, mediatype and format are ignored. :::

data is for inline data (included in the datapackage.json). read_resource() attempts to read data if it is provided as a JSON array:

# The "media" resource has inline data
str(package$resources[[3]]$data)
read_resource(package, "media")

add_resource() adds the provided data frame to data:

df <- data.frame("col_1" = c(1, 2), "col_2" = c("a", "b"))
package <- add_resource(package, "df", df)
package$resources[[4]]$data

write_package() writes that data frame to a CSV file, adds its path to path and removes data.

profile

profile is required to have the value "tabular-data-resource". add_resource() sets profile to that value.

schema

schema is required. It is used by read_resource() to parse data types and missing values. It can either be a JSON object or a path or URL referencing a JSON object. See vignette("table-schema") for details.

dialect

dialect is used by read_resource() to parse a tabular data file. It can either be a JSON object or a path or URL referencing a JSON object. See vignette("table-dialect") for details.

title

title is ignored by read_resource() and not set by add_resource(), unless provided:

add_resource(
  package,
  "iris",
  iris,
  title = "Edgar Anderson's Iris Data",
  replace = TRUE
)

description

description is ignored by read_resource() and not set by add_resource() unless provided (cf. title).

format

format is ignored by read_resource(). add_resource() sets format when data are provided as a file, based on the provided delim:

delim | format --- | --- "," (default) | "csv" "\t" | "tsv" any other value | "csv"

path <- system.file("extdata", "v1", "observations_1.tsv", package = "frictionless")
package <- add_resource(package, "observations", data = path, delim = "\t", replace = TRUE)
package$resources[[2]]$format

add_resource() leaves format undefined when data are provided as a data frame. write_package() sets it to "csv" when writing to disk.

mediatype

mediatype is ignored by read_resource(). add_resource() sets mediatype when data are provided as a file, based on the provided delim:

delim | mediatype --- | --- "," (default) | "text/csv" "\t" | "text/tab-separated-values" any other value | "text/csv"

path <- system.file("extdata", "v1", "observations_1.tsv", package = "frictionless")
package <- add_resource(package, "observations", data = path, delim = "\t", replace = TRUE)
package$resources[[2]]$mediatype

add_resource() leaves mediatype undefined when data are provided as a data frame. write_package() sets it to "text/csv" when writing to disk.

encoding

encoding (e.g. "windows-1252") is used by read_resource() to parse the file. It defaults to UTF-8 if no encoding is provided or if it cannot be recognized. The returned data frame is always UTF-8.

add_resource() guesses the encoding (using readr::guess_encoding()) when data are provided as file. It leaves the encoding undefined when data are provided as a data frame. write_package() sets it to "utf-8" when writing to disk.

path <- system.file("extdata", "v1", "deployments.csv", package = "frictionless")
package <- add_resource(package, "deployments", data = path, delim = ",", replace = TRUE)
package$resources[[2]]$encoding

bytes

bytes is ignored by read_resource() and not set by add_resource() unless provided (cf. title).

hash

hash is ignored by read_resource() and not set by add_resource() unless provided (cf. title).

sources

sources is ignored by read_resource() and not set by add_resource() unless provided (cf. title).

licenses

licenses is ignored by read_resource() and not set by add_resource() unless provided (cf. title).

compression

compression (a recipe) is ignored by read_resource() and not set by add_resource().

Compression is derived from the provided path instead. If the path ends in .gz, .bz2, .xz, or .zip, the files are automatically decompressed by read_resource() (using default readr::read_delim() functionality). Only .gz files can be read directly from URL paths.

frictionlessdata/frictionless-r documentation built on April 17, 2025, 11:45 a.m.