libjdns2t64
Simple DNS queries library
JDNS is a simple DNS implementation that can perform normal DNS
queries of any record type (notably SRV), as well as Multicast DNS
queries and advertising. Multicast support is based on Jeremie
Miller's "mdnsd" implementation.
libjsonrpccpp-client0t64
library implementing json-rpc C++ clients
This library provides classes to easily implement JSON-RPC C++ clients.
It comes with a built in HTTP-Client connector (based on libcurl)
for easy data exchange. It is fully JSON-RPC 2.0 and JSON-RPC
1.0 compatible, including:
libkiwix12t64
library of common code for Kiwix
Kiwix is an offline Wikipedia reader. libkiwix provides the
software core for Kiwix, and contains the code shared by all
Kiwix ports (Windows, Linux, OSX, Android, etc.).
libkmlbase1t64
Library to manipulate KML 2.2 OGC standard files - libkmlbase
This is a library for use with applications that want to parse,
generate and operate on KML, a geo-data XML variant. It is an
implementation of the OGC KML 2.2 standard. It is written in C++ and
bindings are available via SWIG to Java and Python.
libkmldom1t64
Library to manipulate KML 2.2 OGC standard files - libkmldom
This is a library for use with applications that want to parse,
generate and operate on KML, a geo-data XML variant. It is an
implementation of the OGC KML 2.2 standard. It is written in C++ and
bindings are available via SWIG to Java and Python.
r-cran-collapse
GNU R advanced and fast data transformation
A C/C++ based package for advanced data transformation and statistical
computing in R that is extremely fast, flexible and parsimonious to code
with, class-agnostic and programmer friendly. It is well integrated with
base R, 'dplyr' / (grouped) 'tibble', 'data.table', 'plm' (panel-series
and data frames), 'sf' data frames, and non-destructively handles other
matrix or data frame based classes (such as 'ts', 'xts' / 'zoo',
'timeSeries', 'tsibble', 'tibbletime' etc.) --- Key Features: ---
(1) Advanced statistical programming: A full set of fast statistical
functions supporting grouped and weighted computations on vectors,
matrices and data frames. Fast and programmable grouping, ordering,
unique values / rows, factor generation and interactions. Fast and
flexible functions for data manipulation and data object
conversions.
(2) Advanced aggregation: Fast and easy multi-data-type, multi-function,
weighted, parallelized and fully customized data aggregation.
(3) Advanced transformations: Fast row / column arithmetic, (grouped)
replacing and sweeping out of statistics, (grouped, weighted)
scaling / standardizing, between (averaging) and (quasi-)within
(centering / demeaning) transformations, higher-dimensional
centering (i.e. multiple fixed effects transformations), linear
prediction / partialling-out, linear model fitting and testing.
(4) Advanced time-computations: Fast (sequences of) lags / leads, and
(lagged / leaded, iterated, quasi-, log-) differences, (compounded)
growth rates, and cumulative sums on (unordered, irregular) time
series and panel data. Multivariate auto-, partial- and cross-
correlation functions for panel data. Panel data to (ts-)array
conversions.
(5) List processing: (Recursive) list search / identification,
splitting, extraction / subsetting, data-apply, and generalized
recursive row-binding / unlisting in 2D.
(6) Advanced data exploration: Fast (grouped, weighted, panel-
decomposed) summary statistics for complex multilevel / panel data.