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If "exc" is None then the current exception, if any, is used (but not cleared). The returned snapshot is the same as what _interpreters.exec() returns.whence(id) -> int Return an identifier for where the interpreter was created.get_config(id, *, restrict=False) -> types.SimpleNamespace Return a representation of the config used to initialize the interpreter.is_running(id, *, restrict=False) -> bool Return whether or not the identified interpreter is running.is_shareable(obj) -> bool Return True if the object's data may be shared between interpreters and False otherwise.run_func(id, func, shared=None, *, restrict=False) Execute the body of the provided function in the identified interpreter. Code objects are also supported. In both cases, closures and args are not supported. Methods and other callables are not supported either. (See _interpreters.exec().run_string(id, script, shared=None, *, restrict=False) Execute the provided string in the identified interpreter. (See _interpreters.exec().call(id, callable, args=None, kwargs=None, *, restrict=False) Call the provided object in the identified interpreter. Pass the given args and kwargs, if possible. "callable" may be a plain function with no free vars that takes no arguments. The function's code object is used and all its state is ignored, including its __globals__ dict.exec(id, code, shared=None, *, restrict=False) Execute the provided code in the identified interpreter. This is equivalent to running the builtin exec() under the target interpreter, using the __dict__ of its __main__ module as both globals and locals. "code" may be a string containing the text of a Python script. Functions (and code objects) are also supported, with some restrictions. The code/function must not take any arguments or be a closure (i.e. have cell vars). Methods and other callables are not supported. If a function is provided, its code object is used and all its state is ignored, including its __globals__ dict.set___main___attrs(id, ns, *, restrict=False) Bind the given attributes in the interpreter's __main__ module.get_main() -> (ID, whence) Return the ID of main interpreter.get_current() -> (ID, whence) Return the ID of current interpreter.list_all() -> [(ID, whence)] Return a list containing the ID of every existing interpreter.destroy(id, *, restrict=False) Destroy the identified interpreter. Attempting to destroy the current interpreter raises InterpreterError. So does an unrecognized ID.create([config], *, reqrefs=False) -> ID Create a new interpreter and return a unique generated ID. The caller is responsible for destroying the interpreter before exiting, typically by using _interpreters.destroy(). This can be managed automatically by passing "reqrefs=True" and then using _incref() and _decref()` appropriately. "config" must be a valid interpreter config or the name of a predefined config ("isolated" or "legacy"). The default is "isolated".new_config(name='isolated', /, **overrides) -> type.SimpleNamespace Return a representation of a new PyInterpreterConfig. The name determines the initial values of the config. Supported named configs are: default, isolated, legacy, and empty. Any keyword arguments are set on the corresponding config fields, overriding the initial values.;L(xh(JP`u,Ud32,hn:(Ht1I$ $Hd<pXh4hxxzRx $FJ w?;*3$"D (XZBAA RABP" $,ADG VGA. 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