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submitting cpu-bound tasks to processes and io-bound tasks to threads

Project description

Convert a classic sequential program into a parallel one.

Why?

It runs faster.

What if not?

Don’t use it.

How?

for image in images:
    create_thumbnail(image)       # original

for image in images:
    fork(create_thumbnail, image) # parallelized explicitly

for image in images:
    create_thumbnail(image)       # parallelized implicitly (read below)

What about return values?

As usual:

result = fork(my_func, *args, **kwargs)

It’s a proxy object that behaves almost exactly like the real return value of my_func.

Furthermore, it evaluates only if needed; also in combination with operators (like +, - etc.).

What happens to exceptions?

Their original (sequential) tracebacks are preserved. That should make debugging easier.

Speaking of threads …

and processes? fork will take care of that for you.

You can assist fork by decorating your functions (not decorating defaults to cpu_bound):

@io_bound
def call_remote_webservice():
    # implementation

@cpu_bound
def fib(n):
    # naive implementation of Fibonacci numbers

@unsafe # don't fork; run sequentially
def weird_side_effects(*args, **kwargs):
    # implementation

Parallelize implicitly?

If you don’t like the fork calling syntax, you can convert certain functions into stand-alone forks.

Use with caution.

@io_bound_fork
def create_thumbnail_by_webservice(image):
    # implementation

@cpu_bound_fork
def create_thumbnail_by_bare_processing_power(image):
    # implementation

# the following two lines spawn two forks
create_thumbnail_by_webservice(image1)
create_thumbnail_by_bare_processing_power(image2)

Conclusion

Good

  • easy to give it a try / easy way from sequential to parallel and back

  • results evaluate lazily

  • sequential tracebacks are preserved

  • cascading forks possible / it’s thread-safe

  • compatible with Python 2 and 3

Bad

  • weird calling syntax (no syntax support)

  • type(result) == ResultProxy

  • not working with lambdas due to PickleError

  • needs fix:

    • not working with coroutines (asyncio) yet

Project details


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