Containerlab vs QuNetSim

Containerlab is a command-line tool for orchestrating container-based networking labs. Users describe nodes, links and lab settings in topology files, then use lifecycle commands to deploy, destroy, save, inspect or graph a lab. Supported nodes include containerized and virtual-machine network operating systems from Nokia, Cisco, Juniper, Arista and other vendors and projects. The project lists platforms such as Nokia SR Linux and SR OS, Cisco XRd and Nexus 9000v, Juniper cRPD and vMX, Arista, SONiC, Cumulus VX, VyOS, FRR, VPP, FreeBSD, OpenBSD, OpenWRT, Linux containers and generic VMs. It can launch VM routers through vrnetlab or boxen, and Clabernetes can run Containerlab-style topologies on Kubernetes. Optional interfaces include a VS Code extension, desktop app and web app; desktop and web connect to a reachable clab-api-server on a Linux host. Its single binary and topology definitions can start labs in CI systems such as GitLab CI and GitHub Actions. Containerlab is free and open source. Documented prerequisites include a Linux server or VM, Docker and sudo privileges for some operations.

QuNetSim is a free, MIT-licensed Python framework for developing and testing quantum networking applications and protocols. It includes built-in exercises for qubit teleportation, entanglement distribution, superdense coding, and quantum key distribution. Multi-hop networks use entanglement swapping to create links between distant hosts. You can define routing functions from classical and quantum network states, represented with NetworkX graphs. The event-driven model gives packets sequence numbers and lets them wait for acknowledgements. Host, Protocols, and Network components correspond to application, transport, and network layers. Supported backends include SimulaQron, ProjectQ, and EQSN, with SimulaQron listed as the default; custom network and qubit backends can also be imported. Installation uses pip and includes an example-generating template. Linux, macOS, and Windows setup instructions require Python 3.5 or newer. It is intended for students and instructors, especially newcomers, and is described as educational rather than a full quantum-physics simulator.