libadios2-serial-plugins
ADIOS2 Adaptable IO system for simulations - core libraries (serial)
The Adaptable IO System (ADIOS) provides a simple, flexible way for
scientists to describe the data in their code that may need to be
written, read, or processed outside of the running simulation. By
providing an external to the code XML file describing the various
elements, their types, and how you wish to process them this run, the
routines in the host code (either Fortran or C) can transparently
change how they process the data.
libnet-amazon-signature-v4-perl
module for the Amazon Web Services signature version 4
Net::Amazon::Signature::V4 signs an HTTP::Request to Amazon Web Services by
appending an Authorization header. Amazon Web Services signature version 4,
AWS4-HMAC-SHA256, is used.
libmodule-build-pluggable-cpanfile-perl
plugin for Module::Build::Pluggable to use cpanfiles
Module::Build::Pluggable::CPANfile is a plugin for Module::Build::Pluggable
to include dependencies from cpanfile into meta files.
python3-litestar
Powerful, flexible, highly performant, opinionated ASGI framework
LiteStar is a Python web framework (similar to FastAPI and Django) that is
designed to be simply but also very flexible. It is built with the goal of
being easy to learn and use, making it an excellent choice for both beginners
and experienced developers. LiteStar follows the WSGI (Web Server Gateway
Interface) standard, which means it can run on various web servers and is
compatible with popular Python web server gateways like Gunicorn and uWSGI.
r-cran-cvar
GNU R package to Computed Expected Shortfall and Value at Risk
Compute expected shortfall (ES) and Value at Risk (VaR) from a
quantile function, distribution function, random number generator or
probability density function. ES is also known as Conditional Value at
Risk (CVaR). Virtually any continuous distribution can be specified.
The functions are vectorized over the arguments. The computations are
done directly from the definitions, see e.g. Acerbi and Tasche (2002)
<doi:10.1111/1468-0300.00091>. Some support for GARCH models is provided,
as well.
r-cran-sftime
GNU R support for simple feature objects that have a time column
Classes and methods for spatial objects that have a registered time
column, in particular for irregular spatiotemporal data. The time column can
be of any type, but needs to be ordinal. Regularly laid out spatiotemporal
data (vector or raster data cubes) are handled by package 'stars'.