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CONTRIBUTING.md

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Contributing to this package is easy. Just send a [pull request](https://help.github.com/articles/using-pull-requests/). When you send your PR, make sure `develop` is the destination branch on the [future.apply repository](https://github.com/futureverse/future.apply). Your PR should pass `R CMD check --as-cran`, which will also be checked by <a href="https://github.com/futureverse/future.apply/actions?query=workflow%3AR-CMD-check">GitHub Actions</a> and when the PR is submitted.
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We abide to the [Code of Conduct](https://www.contributor-covenant.org/version/2/0/code_of_conduct/) of Contributor Covenant.
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We abide by the [Code of Conduct](https://www.contributor-covenant.org/version/2/0/code_of_conduct/) of Contributor Covenant.

DESCRIPTION

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Package: future.apply
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Version: 1.20.1-9001
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Version: 1.20.1-9002
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Title: Apply Function to Elements in Parallel using Futures
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Depends:
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R (>= 3.2.0),

NEWS.md

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* Fix some HTML5 issues in help pages.
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# Version 1.9.0 [2022-04-24]
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## Signficant Changes
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## Significant Changes
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* `future_mapply()` and `future_Map()` was updated to match the new
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behavior of `mapply()` and `Map()` in R (>= 4.2.0), which follows
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# Version 1.6.0 [2020-06-30]
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## Signficant Changes
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## Significant Changes
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* `future_apply()` gained argument `simplify`, which is added to
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R-devel (to become R 4.1.0).
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# Version 1.1.0 [2019-01-16]
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## Signficant Changes
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## Significant Changes
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* Added argument `future.stdout` and `future.conditions` for
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controlling whether standard output and conditions (e.g. messages
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# Version 1.0.0 [2018-06-19]
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## Signficant Changes
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## Significant Changes
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* License changed from LGPL (>= 2.1) to GPL (>= 2) to make sure it is
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compatible with the source code adopted from R base's `apply()`,

R/future.apply-package.R

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#' future.apply: Apply Function to Elements in Parallel using Futures
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#'
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#' The \pkg{future.apply} packages provides parallel implementations of
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#' The \pkg{future.apply} package provides parallel implementations of
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#' common "apply" functions provided by base \R. The parallel processing
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#' is performed via the \pkg{future} ecosystem, which provides a large
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#' number of parallel backends, e.g. on the local machine, a remote cluster,

R/future_Filter.R

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#' @example incl/future_Filter.R
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#'
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#' @author
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#' The implementations of `future_Filter()` is adopted from the source code
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#' The implementation of `future_Filter()` is adopted from the source code
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#' of the corresponding base \R function `Filter()`, which is licensed under
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#' GPL (>= 2) with 'The R Core Team' as the copyright holder.
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#'

R/future_Map.R

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#' @export
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#'
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#' @author
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#' The implementations of `future_Map()` is adopted from the source code
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#' The implementation of `future_Map()` is adopted from the source code
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#' of the corresponding base \R function `Map()`, which is licensed under
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#' GPL (>= 2) with 'The R Core Team' as the copyright holder.
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#'

R/future_apply.R

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#' See [base::apply()] for details.
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#'
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#' @author
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#' The implementations of `future_apply()` is adopted from the source code
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#' The implementation of `future_apply()` is adopted from the source code
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#' of the corresponding base \R function, which is licensed under GPL (>= 2)
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#' with 'The R Core Team' as the copyright holder.
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#'

R/future_lapply.R

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#'
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#' @section Global variables:
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#' Argument `future.globals` may be used to control how globals
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#' should be handled similarly how the `globals` argument is used with
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#' should be handled similarly to how the `globals` argument is used with
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#' `future()`.
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#' Since all function calls use the same set of globals, this function can do
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#' any gathering of globals upfront (once), which is more efficient than if
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#'
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#' If `future.seed = FALSE`, it is expected that none of the
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#' `FUN(X[[ii]], ...)` function calls use random number generation.
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#' If they do, then an informative warning or error is produces depending
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#' If they do, then an informative warning or error is produced depending
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#' on settings. See [future::future()] for more details.
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#' Using `future.seed = NULL`, is like `future.seed = FALSE` but without
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#' the check whether random numbers were generated or not.
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#' be used to control the ordering the elements are iterated over, which
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#' only affects the processing order and _not_ the order values are returned.
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#' This attribute can take the following values:
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#' * index vector - an numeric vector of length `length(X)`
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#' * function - an function taking one argument which is called as
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#' * index vector - a numeric vector of length `length(X)`
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#' * function - a function taking one argument which is called as
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#' `ordering(length(X))` and which must return an
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#' index vector of length `length(X)`, e.g.
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#' `function(n) rev(seq_len(n))` for reverse ordering.

R/makeChunks.R

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#' be used to control the ordering the elements are iterated over, which
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#' only affects the processing order _not_ the order values are returned.
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#' This attribute can take the following values:
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#' * index vector - an numeric vector of length `nbrOfElements` specifying
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#' * index vector - a numeric vector of length `nbrOfElements` specifying
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#' how elements are remapped
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#' * function - an function taking one argument which is called as
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#' * function - a function taking one argument which is called as
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#' `ordering(nbrOfElements)` and which must return an
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#' index vector of length `nbrOfElements`, e.g.
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#' `function(n) rev(seq_len(n))` for reverse ordering.

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