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Tools for 'CRAN'-Like Repositories
A set of functions to manage 'CRAN'-like repositories efficiently.
Create Disposable R Packages for Testing
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 packages.
Stack Data Type as an 'R6' Class
An extremely simple stack data type, implemented with 'R6' classes. The size of the stack increases as needed, and the amortized time complexity is O(1). The stack may contain arbitrary objects.
Lightweight Portable Message Queue Using 'SQLite'
Temporary and permanent message queues for R. Built on top of 'SQLite' databases. 'SQLite' provides locking, and makes it possible to detect crashed consumers. Crashed jobs can be automatically marked as "failed", or put in the queue again, potentially a limited number of times.
Simple Graph Data Types and Basic Algorithms
Simple classic graph algorithms for simple graph classes. Graphs may possess vertex and edge attributes. 'simplegraph' has no dependencies and it is written entirely in R, so it is easy to install.
Dynamic 'R' Prompt
Set the 'R' prompt dynamically, from a function. The package contains some examples to include various useful dynamic information in the prompt: the status of the last command (success or failure); the amount of memory allocated by the current 'R' process; the name of the R package(s) loaded by 'pkgload' and/or 'devtools'; various 'git' information: the name of the active branch, whether it is dirty, if it needs pushes pulls. You can also create your own prompt if you don't like the predefined examples.
R and C/C++ Wrappers to Run the Leiden find_partition() Function
An R to C/C++ interface that runs the Leiden community
detection algorithm to find a basic partition (). It runs the
equivalent of the 'leidenalg' find_partition() function, which is
given in the 'leidenalg' distribution file
'leiden/src/functions.py'. This package includes the
required source code files from the official 'leidenalg'
distribution and functions from the R 'igraph'
package. The 'leidenalg' distribution is available from
< https://github.com/vtraag/leidenalg/>
and the R 'igraph' package is available from
< https://igraph.org/r/>.
The Leiden algorithm is described in the article by
Traag et al. (2019)
Illustrate the Flow of Information or Material
Plots that illustrate the flow of information or material.
Implements the Leiden Algorithm via an R Interface
An R interface to the Leiden algorithm, an iterative community detection algorithm on networks. The algorithm is designed to converge to a partition in which all subsets of all communities are locally optimally assigned, yielding communities guaranteed to be connected. The implementation proves to be fast, scales well, and can be run on graphs of millions of nodes (as long as they can fit in memory). The original implementation was constructed as a python interface "leidenalg" found here: < https://github.com/vtraag/leidenalg>. The algorithm was originally described in Traag, V.A., Waltman, L. & van Eck, N.J. "From Louvain to Leiden: guaranteeing well-connected communities". Sci Rep 9, 5233 (2019)
'WebDriver' Client for 'PhantomJS'
A client for the 'WebDriver' 'API'. It allows driving a (probably headless) web browser, and can be used to test web applications, including 'Shiny' apps. In theory it works with any 'WebDriver' implementation, but it was only tested with 'PhantomJS'.