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Executes Python code on all workers in the pool. Useful for initializing shared state, importing modules, or defining functions across all workers.
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Add py:new_env/1,2 to create reusable Python environments with
initialization code. Environments can be named for global lookup
via persistent_term.
New API:
- py:new_env(Code) / py:new_env(Code, #{name => atom()})
- py:set_env(Name | Ref) - set current env for process
- py:get_env() / py:get_env(Name) - get current/named env
- py:list_envs() - list all named environments
- py:destroy_env(Ref) - remove from registry
When a named env is set, py:eval/exec and py_event_loop_pool:eval/exec
use it directly via NIF instead of routing through contexts.
Remove preload API from py_event_loop_pool in favor of named
environments which provide more flexibility.
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Summary
py:new_env/1,2to create reusable Python environments with initialization codepy:set_env/1,py:get_env/0,1,py:list_envs/0,py:destroy_env/1py:eval/execandpy_event_loop_pool:eval/execto use named env when setExample usage:
{ok, _} = py:new_env(<<"import numpy as np">>, #{name => numpy_env}), ok = py:set_env(numpy_env), {ok, Result} = py:eval(<<"np.array([1,2,3])">>).