Local Distributed Python Framework Delivers Enterprise Performance Without Complexity

This project demonstrates that distributed computing across local networks doesn't require complex frameworks like Dask or Ray for simple parallel workloads. By matching enterprise-grade performance with minimal setup (just a few lines of code), it reveals that framework overhead is negligible when the CPU is the bottleneck. For developers running parallel tasks on WiFi-connected machines, this approach offers a pragmatic middle ground between no distribution and full cloud infrastructure.