In this talk, we will delve into the exciting world of advanced hardware and its use for distributed computations. As the heterogeneous computing landscape evolves with the introduction of quantum computers, GPUs, and specialized hardware, we will explore the interesting patterns in Python that allow us to interact with this heterogeneity and maximize performance effectively. The talk will address the challenges of distributed computations in the heterogeneous computing era, including monitoring real-time calculations, rapid iteration, prototyping in complex experiments, and ensuring smooth production runs with long access queues in specialized hardware. However, we will not only highlight the difficulties but also share valuable strategies for overcoming these obstacles and achieving optimal performance in these environments using open-source tools.