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Clarify worker limitations initial paragraph #208

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Clarify worker limitations initial paragraph #208

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7 changes: 4 additions & 3 deletions docs/user-guide/workers.md
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Expand Up @@ -251,9 +251,10 @@ computational tasks.

## Understanding limitations

Workers have separate memory spaces. Each worker has its own memory, and
you cannot share objects between workers or with the main thread. All
communication happens via function calls with serialised data.
Each worker is a separate Python interpreter, in a separate memory space,
with a separate virtual filesystem. You cannot share objects between workers,
nor with the main thread. All communication between them happens via function
calls with serialised data.

Only serialisable data can pass between threads. Function arguments and
return values must be JSON-serialisable: numbers, strings, lists,
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