Type: Package
Title: Efficient Wrapper for the 'Airtable' API
Version: 0.1.2
Maintainer: Matthew Rogers <matthew.rogers09@gmail.com>
Description: Efficient CRUD interface for the 'Airtable' API https://airtable.com/developers/web/api, supporting batch requests and parallel encoding of large data sets.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.1.2
Imports: httr, jsonlite, tibble, dplyr, cli, crayon, rlang, parallel, progress
URL: https://matthewjrogers.github.io/rairtable/
BugReports: https://github.com/matthewjrogers/rairtable/issues
NeedsCompilation: no
Packaged: 2023-04-02 15:16:50 UTC; MJR
Author: Matthew Rogers [aut, cre]
Repository: CRAN
Date/Publication: 2023-04-02 15:40:02 UTC

Create a new airtable object

Description

Creates an S3 airtable object, which serves as a pointer for rairtable functions

Usage

airtable(
  table,
  base,
  view = NULL,
  api_url = "https://api.airtable.com",
  api_version = 0
)

Arguments

table

Table name in Airtable

base

Airtable base containing table. A base functions like a schema in a traditional database. You can retrieve the base ID from the API documentation.

view

Optional view of data to read

api_url

API endpoint to connect to. Can be changed for API integrations that require custom endpoint

api_version

Version of API to use. Defaults to 0 (the current version as of Fall 2021)

Value

An airtable object

Examples

## Not run: 
table <- airtable("Table 1", "appXXXXXXXXXXXXX")

## End(Not run)

Delete airtable records

Description

Delete records in an Airtable table based on their Airtable record ID.

Usage

delete_records(
  data,
  airtable,
  airtable_id_col = "airtable_record_id",
  safely = TRUE,
  batch_size = 10
)

Arguments

data

A data frame containing records to delete

airtable

An airtable object

airtable_id_col

Column containing Airtable record IDs. Not required if record IDs are stored in row names as returned from read_airtable.

safely

If TRUE, ask for confirmation before executing DELETE request

batch_size

Number of requests to send at a time. Maximum of 10.

Value

A vector of IDs deleted

Insert records into an Airtable table

Description

Insert rows into an Airtable table. Requires that data names and types exactly match column names and types in Airtable. Violating this assumption will return a 422 Unprocessable Entity error. Supports batch insert and parallel JSON encoding (recommended for large tables).

Usage

insert_records(
  data,
  airtable,
  typecast = FALSE,
  parallel = FALSE,
  batch_size = 10
)

Arguments

data

A dataframe containing records to insert

airtable

An airtable object

typecast

If TRUE, values will be converted to match the base if possible. Set to TRUE to add new values to a multi select field.

parallel

If TRUE, use parallel processing for encoding large tables

batch_size

Number of records per request to insert. Maximum of 10

Value

A dataframe (invisibly) of the input data, to be stored as an object or piped into further 'dplyr' functions

Read table from Airtable

Description

Connect to and read values from an Airtable table.

Usage

read_airtable(airtable, fields = NULL, id_to_col = TRUE, max_rows = 50000)

Arguments

airtable

An airtable object

fields

An optional list of fields to select.

id_to_col

If TRUE, store airtable ID as a column rather than as row names

max_rows

Optional maximum number of rows to read

Value

A dataframe containing the data read from the specified 'Airtable' table

Set or install Airtable API key

Description

Set Airtable API key as an environment variable, and optionally install the API key to your .Renviron file for future use.

Usage

set_airtable_api_key(key, install = FALSE)

Arguments

key

A valid Airtable API key

install

Add your API key to .Renviron for future sessions. Optionally overwrite an existing Airtable API key.

Value

No return value, called for side effects

Examples

## Not run: 
airtable_api_key("XXXXXXXXXX", install = TRUE)

## End(Not run)

Update Airtable records

Description

Update one or more columns of data in an Airtable table. Supports batch updates and parallel JSON encoding (recommended for large tables).

Usage

update_records(
  data,
  airtable,
  columns = dplyr::everything(),
  airtable_id_col = "airtable_record_id",
  safely = TRUE,
  parallel = FALSE,
  batch_size = 10
)

Arguments

data

A dataframe containing the records and fields to update

airtable

An airtable object

columns

Columns in the data to update on Airtable. Can be a vector of character strings, unquoted column names, or a dplyr tidyselect helper like starts_with(), ends_with() or everything(). Defaults to dplyr::everything()

airtable_id_col

Column containing Airtable record IDs. Not required if record IDs are stored in row names as returned from read_airtable

safely

If TRUE, confirm number and names of columns to update and number of rows before executing update.

parallel

If TRUE use parallel processing for encoding large tables

batch_size

Number of records to update per request. Maximum of 10

Value

A dataframe (invisibly) of the input data, to be stored as an object or piped into further 'dplyr' functions