python contextvars

Context Variables

Python's contextvars module helps manage thread-local state in asynchronous deep learning pipelines. It allows you to create context-specific variables that persist across asynchronous calls, ensuring data integrity in complex workflows.

This approach prevents race conditions in parallel processing, maintains separate states for different execution contexts, and enables clean, modular code in asynchronous environments. It's especially useful in

Distributed ML scenarios or when handling multiple models concurrently for an

AI Server.


import contextvars
import asyncio

# Create a context variable
model_state = contextvars.ContextVar('model_state', default={})

async def update_model(data):
    state = model_state.get()
    # Update state with new data
    state.update(data)
    model_state.set(state)

async def process_batch(batch):
    await update_model(batch)
    # More processing...

async def main():
    batches = [{'batch1': 'data'}, {'batch2': 'data'}]
    await asyncio.gather(*(process_batch(b) for b in batches))
    print(model_state.get())

# For Jupyter notebooks, use this instead of asyncio.run(main())
await main()

contextvars — Context Variables

This module provides APIs to manage, store, and access context-local state. The ContextVar class is used to declare and work with Context Variables. The copy_context() function and the Context clas...

https://docs.python.org/3/library/contextvars.html

python `contextvars`

Context Variables

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