Access services specified in OpenAPI (formerly Swagger) format.
  It is not a code generator. Client is generated dynamically as a list of R 
  functions.

Access to the C-level R date and 'datetime' code is provided for
 C-level API use by other packages via registration of native functions.
 Client packages simply include a single header 'RApiDatetime.h' provided
 by this package, and also 'import' it.  The R Core group is the original
 author of the code made available with slight modifications by this package.

Provides a high-performance interface for calculating string similarities and distances, leveraging the efficient library 'RapidFuzz' <https://github.com/rapidfuzz/rapidfuzz-cpp>. This package integrates the 'C++' implementation, allowing 'R' users to access cutting-edge algorithms for fuzzy matching and text analysis.

Provides JSON parsing capability through the 'Rapidjson' 'C++' header-only library.

A collection of 'HTML', 'JavaScript', 'CSS' and fonts
  assets that generate 'RapiDoc' documentation from an 'OpenAPI' Specification:
   <https://mrin9.github.io/RapiDoc/>.

Rapidly estimates tree-topology from large allele frequency
    data using Root Distances Method, under a Brownian Motion Model. See
    Peng et al. (2021) <doi:10.1016/j.ympev.2021.107142>.

Facilitates efficient polygon search using kd trees.
    Coordinate level spatial data can be aggregated to higher geographical
    identities like census blocks, ZIP codes or police district boundaries.
    This process requires mapping each point in the given data set to a
    particular identity of the desired geographical hierarchy. Unless efficient
    data structures are used, this can be a daunting task. The operation
    point.in.polygon() from the package sp is computationally expensive.
    Here, we exploit kd-trees as efficient nearest neighbor search algorithm
    to dramatically reduce the effective number of polygons being searched.

A 'Java' implementation of the RAKE algorithm ('Rose', S., 'Engel', D., 
  'Cramer', N. and 'Cowley', W. (2010) <doi:10.1002/9780470689646.ch1>), which can 
  be used to extract keywords from documents without any training data.