Dispatch your trivially parallizable jobs with sharedmem.

To cite sharedmem use the DOI below

Now also supports Python 3.

• sharedmem.empty creates numpy arrays shared by child processes.
• sharedmem.MapReduce dispatches work to child processes, allowing work functions defined in nested scopes.
• sharedmem.MapReduce.ordered and sharedmem.MapReduce.critical implements the equivelant concepts as OpenMP ordered and OpenMP critical sections.
• Exceptions are properly handled, including unpicklable exceptions. Unexpected death of child processes (Slaves) is handled in a graceful manner.

Functions and variables are inherited from a fork syscall and the copy-on-write mechanism, except sharedmem variables which are writable from both child processes or the main process. Pickability of objects is not a concern.

Usual limitations of fork do apply. sharedmem.MapReduce is easier to use than multiprocessing.Pool, at the cost of not supporting Windows.

For documentation, please refer to http://rainwoodman.github.io/sharedmem .

Here we provide two simple examples to illustrate the usage: