Defining Data-Streaming Simulations in YAML, Without Writing Python

Tue, 06 Oct 2026 00:00:00 +0000

A pipeline is easier to test when its input behaves like production: orders arrive at random, queues grow, a machine slows down. A simulation can produce that data, but when the simulation is a Python program, every change is a code change. Someone who only wants to double an arrival rate has to read and edit code, and a reviewer has to check that nothing else moved. A file that holds only settings is easier to read, to compare in a pull request and to run in CI.

dynamic-des 0.16.0 adds that file. A YAML blueprint describes the whole simulation, and the ddes command runs it. Each of the seven examples in the repository now has a YAML version in plain YAML. The documentation was rebuilt around the three ways to write a simulation.

YAML on Jaehyeon Kim

Defining Data-Streaming Simulations in YAML, Without Writing Python