Python vs. Ruby vs. RunMat vs. Rust Comparison Chart

The core of extensible programming is defining functions. Python allows mandatory and optional arguments, keyword arguments, and even arbitrary argument lists. Whether you're new to programming or an experienced developer, it's easy to learn and use Python. Python can be easy to pick up whether you're a first-time programmer or you're experienced with other languages. The following pages are a useful first step to get on your way to writing programs with Python! The community hosts conferences and meetups to collaborate on code, and much more. Python's documentation will help you along the way, and the mailing lists will keep you in touch. The Python Package Index (PyPI) hosts thousands of third-party modules for Python. Both Python's standard library and the community-contributed modules allow for endless possibilities.

RunMat (by Dystr) is a fast, free, open-source alternative for running MATLAB code. Users can run their existing MATLAB code with complete language grammar and core semantics. No license fees, no lock-in. RunMat is built with a modern compiler, which enables blazing-fast calculations. It boots in 5 milliseconds, GPU optimization is enabled by default, and it's a single, compact, cross-platform binary. Typical engineering use cases - Controls/signal processing & numerics: accelerate MATLAB-style loops plus heavy linear algebra; enjoy faster iteration due to instant startup and tiered JIT. - Batch/CI & serverless jobs: snapshots + compact binaries make it easy to run .m workloads in containers or ephemeral runners at scale. - Plot-heavy workflows: interactive GPU plots for exploratory analysis and reportable exports for stakeholders. - Education: remove license friction and start labs instantly; Jupyter kernel supports reproducible worksheets.