Karabo constructs and executes radio astronomy data processing and simulation workflows in interactive environments such as Jupyter Notebooks. The package facilitates development, validation, and benchmarking of radio telescope processing methods for projects such as the Square Kilometer Array. It integrates existing tools for interferometer simulation, imaging, and source detection, enabling users to build custom pipelines that simulate instrument behavior, generate synthetic visibilities, perform imaging, and evaluate results with readily available modules. The code supports simulation of general interferometer observations, configuration and visualization of telescope models, and scriptable workflows for tasks such as SRCNet data generation and line emission studies. Karabo includes utilities for parallel processing and data handling, and its extensible design allows combination of third-party libraries and user code to prototype and benchmark radio astronomy algorithms.

CosmoHammer is a Python framework for the estimation of cosmological parameters. The software embeds the Python package emcee by Foreman-Mackey et al. (2012) and gives the user the possibility to plug in modules for the computation of any desired likelihood. The major goal of the software is to reduce the complexity when one wants to extend or replace the existing computation by modules which fit the user's needs as well as to provide the possibility to easily use large scale computing environments. CosmoHammer can efficiently distribute the MCMC sampling over thousands of cores on modern cloud computing infrastructure.