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.

Miscellaneous Tools for Reproducible Research

Tools to load 'R' packages and automatically generate BibTeX files citing them as well as load and cache plain-text and 'Excel' formatted data stored on 'GitHub', and from other sources.

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.

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.

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()).

Export Data Frames to Excel 'xlsx' Format

Zero-dependency data frame to xlsx exporter based on 'libxlsxwriter' < https://libxlsxwriter.github.io>. Fast and no Java or Excel required.

Read, Write and Edit xlsx Files

Simplifies the creation of Excel .xlsx files by providing a high level interface to writing, styling and editing worksheets. Through the use of 'Rcpp', read/write times are comparable to the 'xlsx' and 'XLConnect' packages with the added benefit of removing the dependency on Java.

A Simpler Way to Find Your Files

Constructs paths to your project's files. Declare the relative path of a file within your project with 'i_am()'. Use the 'here()' function as a drop-in replacement for 'file.path()', it will always locate the files relative to your project root.

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.