A Simple S3 Class for Representing Vectors of Binary Data ('BLOBS')

R's raw vector is useful for storing a single binary object. What if you want to put a vector of them in a data frame? The 'blob' package provides the blob object, a list of raw vectors, suitable for use as a column in data frame.

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The goal of blob is to provide a simple S3 class to represent a vector of binary objects, aka blobs. The blob class is a lightweight wrapper around a list of raw vectors, suitable for inclusion in a data frame.

In most cases you will not need to use this package explicitly: it will be used transparently by packages that need to load BLOB columns from databases or binary file formats.


You can install blob from github with:



To create a blob, use blob(), new_blob() or as.blob():

x1 <- charToRaw("Good morning")
x2 <- as.raw(c(0x48, 0x65, 0x6c, 0x6c, 0x6f))
new_blob(list(x1, x2))
#> [1] blob[12 B] blob[5 B]
blob(x1, x2)
#> [1] blob[12 B] blob[5 B]
as.blob(c("Good morning", "Good evening"))
#> [1] blob[12 B] blob[12 B]


blob 1.1.1 (2018-03-24)

  • Now suggesting pillar instead of importing tibble, and using colored formatting with the prettyunits package with B instead of b as units (#7, #9).

  • The blob class can now be used for S4 dispatch.

  • Calling c() on blob objects returns a blob.

blob 1.1.0 (2017-06-17)

  • New maintainer: Kirill Müller.

  • Added as.blob.blob()and as.data.frame.blob() methods (#3).

  • Size of very large blobs is displayed correctly.

blob 1.0.0

  • Initial release.

Reference manual

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1.2.2 by Kirill Müller, 6 months ago

https://blob.tidyverse.org, https://github.com/tidyverse/blob

Report a bug at https://github.com/tidyverse/blob/issues

Browse source code at https://github.com/cran/blob

Authors: Hadley Wickham [aut] , Kirill Müller [cre] , RStudio [cph]

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports methods, rlang, vctrs

Suggests covr, crayon, pillar, testthat

Imported by DBItest, RMariaDB, RPostgres, RSQLite, dbflobr, dbplyr, flobr, odbc, sparklyr.

Suggested by DBI, bigrquery, dbx, dplyr.teradata, ipaddress, sf, tibble.

See at CRAN