We present FastFlow-Python, a framework that brings parallelism to Python for stream-processing applications. FastFlow-Python enables developers to build high-throughput, low-latency data-flow networks by instantiating high-level, ready-to-use parallel building blocks. Built on the C++ FastFlow library, it leverages Python bindings via the C/Python API to efficiently manage parallel execution using both subinterpreters and multiprocessing, all abstracted by the framework. We demonstrate the performance benefits of FastFlow-Python through a comparative analysis with a pure Python stream-processing implementation, highlighting its effectiveness in overcoming the limitations imposed by the Global Interpreter Lock (GIL). Experimental results show almost linear scalability when increasing the number of workers.