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Package Dependency Resolution and Downloads
Find recursive dependencies of 'R' packages from various sources. Solve the dependencies to obtain a consistent set of packages to install. Download packages, and install them. It supports packages on 'CRAN', 'Bioconductor' and other 'CRAN-like' repositories, 'GitHub', package 'URLs', and local package trees and files. It caches metadata and package files via the 'pkgcache' package, and performs all 'HTTP' requests, downloads, builds and installations in parallel. 'pkgdepends' is the workhorse of the 'pak' package.
Read Excel Files
Import excel files into R. Supports '.xls' via the embedded 'libxls' C library < https://github.com/libxls/libxls> and '.xlsx' via the embedded 'RapidXML' C++ library < https://rapidxml.sourceforge.net/>. Works on Windows, Mac and Linux without external dependencies.
File Cacher
The main functions in this package are with_cache() and cached_read(). The former is a simple way to cache an R object into a file on disk, using 'cachem'. The latter is a wrapper around any standard read function, but caches both the output and the file list info. If the input file list info hasn't changed, the cache is used; otherwise, the original files are re-read. This can save time if the original operation requires reading from many files, and/or involves lots of processing.
Simple R Cache
Simple result caching in R based on R.cache. The global environment is not considered when caching results simplifying moving files between multiple instances of R. Relies on more base functions than R.cache (e.g. cached results are saved using saveRDS() and readRDS()).
Application Directories: Determine Where to Save Data, Caches, and Logs
An easy way to determine which directories on the users computer you should use to save data, caches and logs. A port of Python's 'Appdirs' (< https://github.com/ActiveState/appdirs>) to R.
Function Mocking for Unit Testing
With the deprecation of mocking capabilities shipped with 'testthat' as of 'edition 3' it is left to third-party packages to replace this functionality, which in some test-scenarios is essential in order to run unit tests in limited environments (such as no Internet connection). Mocking in this setting means temporarily substituting a function with a stub that acts in some sense like the original function (for example by serving a HTTP response that has been cached as a file). The only exported function 'with_mock()' is modeled after the eponymous 'testthat' function with the intention of providing a drop-in replacement.
A General-Purpose Package for Dynamic Report Generation in R
Provides a general-purpose tool for dynamic report generation in R using Literate Programming techniques.
Cross-Platform File System Operations Based on 'libuv'
A cross-platform interface to file system operations, built on top of the 'libuv' C library.
Track R Package Downloads from RStudio's CRAN Mirror
Allows to get and cache R package download log files from RStudio's CRAN mirror for analyzing package usage.
Reproducible Data Embedding
Allows caching of raw data directly in R code. This allows R scripts and R Notebooks to be shared and re-run on a machine without access to the original data. Cached data is encoded into an ASCII string that can be pasted into R code. When the code is run, the data is automatically loaded from the cached version if the original data file is unavailable. Works best for small datasets (a few hundred observations).