default_printer: builtin_function_or_method
InMainProcess: InMainProcess
InWorkerProcess: InWorkerProcess
mode_map: dict

__init__(self, logger=None, contract=None, uid=None): 

load_registry(): 

@property
parallelizer_registry(self): 

get_default(): 

For compat.

• :returns: _

lookup(key): 

Checks in the registry to see if a given parallelizer is there otherwise returns a SerialNonParallelizer.

• key: Any

• :returns: _

register(self, key): 

Checks in the registry to see if a given parallelizer is there otherwise returns a SerialNonParallelizer.

• key: Any

• :returns: _

@property
active(self): 

initialize(self): 

Initializes a parallelizer if necessary

• :returns: _

finalize(self, exc_type, exc_val, exc_tb): 

Finalizes a parallelizer (if necessary) if necessary

• :returns: _

__enter__(self): 

Allows the parallelizer context to be set using with

• :returns: _

__exit__(self, exc_type, exc_val, exc_tb): 

Allows the parallelizer context to be unset using with

• exc_type: Any

• exc_val: Any

• exc_tb: Any

• :returns: _

@property
on_main(self): 

Returns whether or not the executing process is the main process or not

• :returns: _

main_restricted(func): 

A decorator to indicate that a function should only be run when on the main process

• func: Any

• :returns: _

worker_restricted(func): 

A decorator to indicate that a function should only be run when on a worker process

• func: Any

• :returns: _

send(self, data, loc, **kwargs): 

Sends data to the process specified by loc

• data: Any

• kwargs: Any

• :returns: _

receive(self, data, loc, **kwargs): 

Receives data from the process specified by loc

• data: Any

• kwargs: Any

• :returns: _

broadcast(self, data, **kwargs): 

Sends the same data to all processes

• data: Any

• kwargs: Any

• :returns: _

scatter(self, data, **kwargs): 

Performs a scatter of data to the different available parallelizer processes. NOTE: unlike in the MPI case, data does not need to be evenly divisible by the number of available processes

• data: Any

• kwargs: Any

• :returns: _

gather(self, data, **kwargs): 

Performs a gather of data from the different available parallelizer processes

• data: Any

• kwargs: Any

• :returns: _

map(self, function, data, extra_args=None, extra_kwargs=None, **kwargs): 

Performs a parallel map of function over the held data on different processes

• function: Any

• data: Any

• kwargs: Any

• :returns: _

starmap(self, function, data, extra_args=None, extra_kwargs=None, **kwargs): 

Performs a parallel map with unpacking of function over the held data on different processes

• function: Any

• data: Any

• kwargs: Any

• :returns: _

apply(self, func, *args, main_kwargs=None, **kwargs): 

Runs the callable func in parallel

• func: Any

• args: Any

• kwargs: Any

• :returns: _

run(self, func, *args, comm=None, main_kwargs=None, **kwargs): 

Calls apply, but makes sure state is handled cleanly

• func: Any

• args: Any

• kwargs: Any

• :returns: _

from_config(mode=None, **kwargs): 

@property
nprocs(self): 

Returns the number of processes the parallelizer has to work with

• :returns: _

get_nprocs(self): 

Returns the number of processes

• :returns: _

@property
id(self): 

Returns some form of identifier for the current process

• :returns: _

@property
pid(self): 

get_id(self): 

Returns the id for the current process

• :returns: _

@property
printer(self): 

main_print(self, *args, **kwargs): 

Prints from the main process

• args: Any

• kwargs: Any

• :returns: _

worker_print(self, *args, **kwargs): 

Prints from a main worker process

• args: Any

• kwargs: Any

• :returns: _

print(self, *args, where='both', **kwargs): 

An implementation of print that operates differently on workers than on main processes

• args: Any

• kwargs: Any

• :returns: _

wait(self): 

Causes all processes to wait until they’ve met up at this point.

• :returns: _

__repr__(self): 

share(self, obj): 

Converts obj into a form that can be cleanly used with shared memory via a SharedObjectManager

• obj: Any

• :returns: _