Industrial control systems are producing vast amounts of data, but the Python tools used to process this data often face significant performance limitations. The traditional OPC UA libraries used in these systems are based on synchronous, polling-based architectures, which can lead to performance issues. When dealing with large-scale industrial networks that involve thousands of sensors broadcasting high-frequency data, these synchronous Python implementations can become overwhelmed. To address this issue, developers need a native Publisher and Subscriber solution that can handle the modern many-to-many topology without blocking the execution thread. This solution should be able to handle network packets without interrupting the execution thread, allowing for more efficient data processing. OPC UA PubSub is a standard that enables devices to broadcast telemetry via stateless middleware like UDP Multicast, decoupling data producers from consumers. This standard is particularly useful in industrial settings where data needs to be transmitted efficiently and reliably. For Python developers who are new to industrial protocols, OPC UA PubSub provides a solution that can handle the complexities of industrial data transmission. The asyncio library in Python provides a way to handle thousands of simultaneous network operations concurrently, making it an ideal tool for industrial engineers working with Python concurrency. By leveraging asyncio and OPC UA PubSub, developers can create more efficient and scalable industrial control systems that can handle the demands of modern industrial networks.