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Tools to read, write, create, and manipulate DESCRIPTION files. It is intended for packages that create or manipulate other packages.
Collapse red-green or green-blue distinctions to simulate the effects of different types of color-blindness.
Implementation of a function 'digest()' for the creation of hash digests of arbitrary R objects (using the md5, sha-1, sha-256, crc32, xxhash and murmurhash algorithms) permitting easy comparison of R language objects, as well as a function 'hmac()' to create hash-based message authentication code. The md5 algorithm by Ron Rivest is specified in RFC 1321, the sha-1 and sha-256 algorithms are specified in FIPS-180-1 and FIPS-180-2, and the crc32 algorithm is described in ftp://ftp.rocksoft.com/cliens/rocksoft/papers/crc_v3.txt. For md5, sha-1, sha-256 and aes, this package uses small standalone implementations that were provided by Christophe Devine. For crc32, code from the zlib library is used. For sha-512, an implementation by Aaron D. Gifford is used. For xxHash, the implementation by Yann Collet is used. For murmurhash, an implementation by Shane Day is used. Please note that this package is not meant to be deployed for cryptographic purposes for which more comprehensive (and widely tested) libraries such as OpenSSL should be used.
Create disposable R packages for testing. You can create, install and load multiple R packages with a single function call, and then unload, uninstall and destroy them with another function call. This is handy when testing how some R code or an R package behaves with respect to other
Parsing and evaluation tools that make it easy to recreate the command line behaviour of R.
Efficient calculation of the exponential of a matrix. The package contains an R interface and a C API that package authors can use.
Package providing a fast match() replacement for cases that require repeated look-ups. It is slightly faster that R's built-in match() function on first match against a table, but extremely fast on any subsequent lookup as it keeps the hash table in memory.
Implements a simple key-value style database where character string keys are associated with data values that are stored on the disk. A simple interface is provided for inserting, retrieving, and deleting data from the database. Utilities are provided that allow 'filehash' databases to be treated much like environments and lists are already used in R. These utilities are provided to encourage interactive and exploratory analysis on large datasets. Three different file formats for representing the database are currently available and new formats can easily be incorporated by third parties for use in the 'filehash' framework.
A collection of fortunes from the R community.