Avoiding the GIL in Data Pipelines: Parallel Execution of DAGs in Wpipe
Avoiding the GIL in Data Pipelines: Parallel Execution of DAGs in Wpipe Day 11 of the Wisrovi Open Source Architecture Series. When running complex directed acyclic graphs (DAGs) in Python, traditional orchestrators usually hit the Global Interpreter Lock (GIL) when running intensive numerical transformations, or suffer an astronomical memory cost when lifting...
Wisrovi's Wpipe is a data pipeline tool that solves issues with traditional orchestrators crashing due to the Global Interpreter Lock (GIL) when running complex directed acyclic graphs (DAGs) in Python. Wpipe uses a hybrid execution engine, running I/O-bound tasks asynchronously with asyncio threads and delegating heavy computations to worker processes with atomic memory and high-speed serialization.
The tool allows for parallel execution of DAGs, eliminating the need for manual blocking or complex multiprocessing queues. Wpipe is available on GitHub and PyPI.
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