RcppMsgPack 0.2.0

September 13, 2017

(This article was first published on Thinking inside the box , and kindly contributed to R-bloggers)

A new and much enhanced version of RcppMsgPack arrived on CRAN a couple of days ago. It came together following this email to the r-package-devel list which made it apparent that Travers Ching had been working on MessagePack converters for R which required the very headers I had for use from, inter alia, the RcppRedis package.

So we joined our packages. I updated the headers in RcppMsgPack to the current upstream version 2.1.5 of MessagePack, and Travers added his helper functions allow direct packing / unpacking of MessagePack objects at the R level, as well as tests and a draft vignette. Very exciting, and great to have a coauthor!

So now RcppMspPack provides R with both MessagePack header files for use via C++ (or C, if you must) packages such as RcppRedis — and direct conversion routines at the R prompt.

MessagePack itself is an efficient binary serialization format. It lets you exchange data among multiple languages like JSON. But it is faster and smaller. Small integers are encoded into a single byte, and typical short strings require only one extra byte in addition to the strings themselves.

Changes in version 0.2.0 (2017-09-07)

  • Added support for building on Windows

  • Upgraded to MsgPack 2.1.5 (#3)

  • New R functions to manipulate MsgPack objects: msgpack_format, msgpack_map, msgpack_pack, msgpack_simplify, mgspack_unpack (#4)

  • New R functions also available as msgpackFormat, msgpackMap, msgpackPack, msgpackSimplify, mgspackUnpack (#4)

  • New vignette (#4)

  • New tests (#4)

Courtesy of CRANberries, there is also a diffstat report for this release. More information is on the RcppRedis page.

More information may be on the RcppMsgPack page. Issues and bugreports should go to the GitHub issue tracker.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. Please report excessive re-aggregation in third-party for-profit settings.

To leave a comment for the author, please follow the link and comment on their blog: Thinking inside the box .

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Search R-bloggers


Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)