nautilus-font-manager

Nautilus extension for Font Manager

Font Manager is intended to provide a way for average users to easily manage desktop fonts, without having to resort to command line tools or editing configuration files by hand. While designed primarily with the GNOME Desktop Environment in mind, it should work well with other Gtk+ desktop environments.

php-async-aws-sns

AsyncAws Sns - AsyncAws component

SNS client, part of the AWS SDK provided by AsyncAws.

python3-iminuit

Robust Python minimisation library based around MINUIT2

iminuit is a Jupyter-friendly Python frontend to the MINUIT2 C++ library. It can be used as a general robust function minimisation method, but is most commonly used for likelihood fits of models to data, and to get model parameter error estimates from likelihood profile analysis.

libminini1t64

minimal INI file parser

minIni is a programmer's library to read and write "INI" files in embedded systems. minIni takes little resources, has a deterministic memory footprint and can be configured for various kinds of file I/O libraries. The principal purpose for minIni is to be used on embedded systems that run on an RTOS (or even without any operating system). minIni requires that such a system provides a kind of storage and file I/O system, but it does not require that this file I/O system is compatible with the standard C/C++ library.

python3-pytest

Simple, powerful testing in Python3

This testing tool has for objective to allow the developers to limit the boilerplate code around the tests, promoting the use of built-in mechanisms such as the `assert` keyword.

python3-pycuda

Python 3 module to access Nvidia‘s CUDA parallel computation API

PyCUDA lets you access Nvidia‘s CUDA parallel computation API from Python. Several wrappers of the CUDA API already exist–so what’s so special about PyCUDA? * Object cleanup tied to lifetime of objects. This idiom, often called RAII in C++, makes it much easier to write correct, leak- and crash-free code. PyCUDA knows about dependencies, too, so (for example) it won’t detach from a context before all memory allocated in it is also freed. * Convenience. Abstractions like pycuda.driver.SourceModule and pycuda.gpuarray.GPUArray make CUDA programming even more convenient than with Nvidia’s C-based runtime. * Completeness. PyCUDA puts the full power of CUDA’s driver API at your disposal, if you wish. * Automatic Error Checking. All CUDA errors are automatically translated into Python exceptions. * Speed. PyCUDA’s base layer is written in C++, so all the niceties above are virtually free. * Helpful Documentation.