# sklearn.utils.Parallel¶

Warning

DEPRECATED

class sklearn.utils.Parallel(**kwargs)

Methods

 __call__(iterable) Call self as a function. debug(msg) dispatch_next() Dispatch more data for parallel processing dispatch_one_batch(iterator) Prefetch the tasks for the next batch and dispatch them. format(obj[, indent]) Return the formatted representation of the object. print_progress() Display the process of the parallel execution only a fraction of time, controlled by self.verbose. retrieve() warn(msg)
__init__(**kwargs)

DEPRECATED: deprecated in version 0.20.1 to be removed in version 0.23. Please import this functionality directly from joblib, which can be installed with: pip install joblib.

dispatch_next()

Dispatch more data for parallel processing

This method is meant to be called concurrently by the multiprocessing callback. We rely on the thread-safety of dispatch_one_batch to protect against concurrent consumption of the unprotected iterator.

dispatch_one_batch(iterator)

Prefetch the tasks for the next batch and dispatch them.

The effective size of the batch is computed here. If there are no more jobs to dispatch, return False, else return True.

The iterator consumption and dispatching is protected by the same lock so calling this function should be thread safe.

format(obj, indent=0)

Return the formatted representation of the object.

print_progress()

Display the process of the parallel execution only a fraction of time, controlled by self.verbose.