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future.apply (version 1.20.1)

Apply Function to Elements in Parallel using Futures

Description

Implementations of apply(), by(), eapply(), lapply(), Map(), .mapply(), mapply(), replicate(), sapply(), tapply(), and vapply() that can be resolved using any future-supported backend, e.g. parallel on the local machine or distributed on a compute cluster. These future_*apply() functions come with the same pros and cons as the corresponding base-R *apply() functions but with the additional feature of being able to be processed via the future framework .

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Install

install.packages('future.apply')

Monthly Downloads

278,621

Version

1.20.1

License

GPL (>= 2)

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Maintainer

Henrik Bengtsson

Last Published

December 9th, 2025

Functions in future.apply (1.20.1)

future_by

Apply a Function to a Data Frame Split by Factors via Futures
future_apply

Apply Functions Over Array Margins via Futures
future.apply

future.apply: Apply Function to Elements in Parallel using Futures
future.apply.options

Options used for future.apply
future_kernapply

Apply Smoothing Kernel in Parallel
makeChunks

Create Chunks of Index Vectors
fold

Efficient Fold, Reduce, Accumulate, Combine of a Vector
future_eapply

Apply a Function over a List or Vector via Futures
future_Filter

Apply a Function to Multiple List or Vector Arguments