libgstreamermm-0.10-dbg
C++ wrapper library for the multimedia library GStreamer (debug symbols)
python3-wdlparse
Workflow Description Language (WDL) parser for Python
A Python package that provides the generated Hermes and Antlr4 WDL parsers for
Python.
revolt
better desktop integration for Element
Revolt is a small application which wraps the Element webapp to provide better
integration with desktop environments in general, and GNOME in particular:
librobottestingframework2
Robot Testing Framework - RTF library
It is a generic and multi-platform testing framework for the test
driven development (TDD) which is initially designed for the robotic
systems.
However, it can be used for any TDD system. The framework provides
functionalities for developing and running unit tests in a language and
middleware independent manner. The test cases are developed as
independent plug-ins (i.e., using scripting languages or built as
dynamically loadable libraries) to be loaded and executed by an
automated test runner.
Moreover, a fixture manager prepares the setup (e.g., running robot
interfaces, simulator) and actively monitors that all the requirements
for running the tests are satisfied during the execution of the tests.
These functionalities along with other facilities such as the test
result collector, result formatter and remote interface allow for rapid
development of test units to cover different levels of system testing.
libreactivedata-ocaml
FRP with incremental changes in data structures (runtime)
ReactiveData is an OCaml module for functional reactive programming
(FRP) based on React. It adds support to incremental changes in data
structures by reasoning on patches instead of absolute values.
libann0
Approximate Nearest Neighbor Searching library
ANN is a library written in C++, which supports data structures and
algorithms for both exact and approximate nearest neighbor searching
in arbitrarily high dimensions. ANN assumes that distances
are measured using any class of distance functions called Minkowski
metrics. These include the well known Euclidean distance, Manhattan
distance, and max distance. ANN performs quite efficiently for point
sets ranging in size from thousands to hundreds of thousands, and in
dimensions as high as 20.