[Python-ideas] Suggestion for a new thread API for Python (OpenMP inspired)

[Sturla Molden]

I have lately been using OpenMP to write parallel C and Fortran code. I 
must admit I am impressed. OpenMP is a much better abstraction for 
writing concurrent code than using Win32/posix threads directly (or 
similarly threading.Thread i Java or Python). What matters most is that 
code can be written as sequential, tested, and then parallelised using 
compiler pragmas. This is much easier than writing code intended to be 
parallel from the start.

Not only is the abstraction more easy to apply, it also leads to fewer 
problems with deadlocks, race conditions, livelocks, etc.

I was thinking something similar could be created for Python, e.g. on 
top of the existing thread or threading modules, and possibly 
multiprocessing. I believe a context manager could be used for this 
purpose. What I have in mind is an API that would look approximately 
like this (OpenMP pragmas for C on top, proposed Python equivalent below):


#pragma omp parallel
with pymp.Pool() as pool:

#pragma omp for
for item in pool.parallel(<iterable>):

#pragma omp for shedule(guided)
for item in pool.parallel(<iterable>, shed='guided'):

#pragma omp parallel for
with pymp.Pool() as pool:
    for item in pool.parallel(<iterable>):

#pragma omp barrier
pool.barrier()

#pragma omp section
pool.section(fun, *args, **kwargs)

#pragma omp parallel sections
with pymp.Pool() as pool:
    pool.section(fun1, *args, **kwargs)
    pool.section(fun2, *args, **kwargs)

#pragma omp master
if pool.master:

#pragma omp critical
#pragma omp atomic
with pool.lock:

#pragma omp single
with pool.single():

#pragma omp ordered
with pool.ordered():


This is all trivial to program, except for the context manager on top. 
It has somehow to get access to the code block below, spawn multiple 
threads, and execute that block in each of the threads. I am not sure 
how to grab the next executable block as a Python object (so I could 
pass it to eval or exec), so a little help would be appreciated :)


Regards,
Sturla Molden