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Yandex Cloud Functions
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    • Overview
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In this article:

  • Pre-installed packages
  • Installing additional packages
  • packages.R
  • Manual delivery of dependencies
  1. Developing in R
  2. Managing dependencies

Building and managing R function dependencies

Written by
Yandex Cloud
Updated at July 2, 2026
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  • Pre-installed packages
  • Installing additional packages
  • packages.R
  • Manual delivery of dependencies

Pre-installed packagesPre-installed packages

The runtime of a function in R includes the following pre-installed packages available for use in function code:
httr, logging, data.table, dplyr, paws, rjson, stringr, BiocManager, ggplot2, plotly, devtools, Rcpp, tidyr, lubridate, e1071, caret, mongolite, Rsamtools.

Installing additional packagesInstalling additional packages

When creating a new function version, Cloud Functions enables you to install all dependencies required for the function. To do this, place a file named packages.R that describes the installation process into the project root.

This service also supports manual delivery of dependencies along with the source code.

packages.Rpackages.R

This script is executed once when creating a function version.

Example of installing a package via packages.R:

install.packages("purrr", repo="http://cran.r-project.org")

Manual delivery of dependenciesManual delivery of dependencies

To configure dependencies manually, place the compiled packages in the usr/library/ subdirectory of the project archive.

Dependency installation is limited in terms of resources and execution time. For more information, see Quotas and limits in Cloud Functions. You can view the dependency installation log via the link displayed in the list of operations.

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