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.