Re: [Python-ideas] PEP 380 close and contextmanagers?

28 Oct 2010


      On Wed, Oct 27, 2010 at 9:18 AM, Ron Adam  wrote:
...
On 10/27/2010 10:01 AM, Ron Adam wrote:
It looks like No context managers return values in the finally or __exit__
part of a context manager.  Is there way to do that?
How would that value be communicated to the code containing the with-clause?
...
Here's a context manager version of the min/max with nested coroutines, but
it doesn't return a value from close.
######
from contextlib import contextmanager
# New close function that enables returning a
# value.
def gclose(gen):
  try:
    gen.throw(GeneratorExit)
  except StopIteration as err:
    if err.args:
      return err.args[0]
  except GeneratorExit:
    pass
  return None
# Showing  both the class and geneator based
# context managers for comparison and to better
# see how these things may work.
class Consumer:
   def __init__(self, cofunc):
       next(cofunc)
       self.cofunc = cofunc
   def __enter__(self):
       return self.cofunc
   def __exit__(self, *exc_info):
       gclose(self.cofunc)
@contextmanager
def consumer(cofunc):
   next(cofunc)
   try:
       yield cofunc
   finally:
       gclose(cofunc)
class MultiConsumer:
   def __init__(self, cofuncs):
       for c in cofuncs:
           next(c)
       self.cofuncs = cofuncs
   def __enter__(self):
       return self.cofuncs
   def __exit__(self, *exc_info):
       for c in self.cofuncs:
           gclose(c)
@contextmanager
def multiconsumer(cofuncs):
   for c in cofuncs:
       next(c)
   try:
       yield cofuncs
   finally:
       for c in cofuncs:
           gclose(c)
So far so good.
...
# Min/max coroutine example slpit into
# nested coroutines for testing these ideas
# in a more complex situation that may arise
# when working with cofunctions and generators.
# Question:
#    How to rewrite this so close returns
#    a final value?
Change the function to catch GeneratorExit and when it catches that,
raise StopIteration(<returnvalue>).
...
def reduce_i(f):
    i = yield
    while True:
        i = f(i, (yield i))
Unfortunately from here on till the end of your example my brain exploded.
...
def reduce_it_to(funcs):
   with multiconsumer([reduce_i(f) for f in funcs]) as mc:
       values = None
       while True:
           i = yield values
           values = [c.send(i) for c in mc]
Maybe you could have picked a better name than 'i' for this variable...
...
def main():
   with consumer(reduce_it_to([min, max])) as c:
       for i in range(100):
           value = c.send(i)
       print(value)
I sort of get what you are doing here but I think you left one
abstraction out. Something like this:

def blah(it, funcs):
  with consumer(reduce_it_to(funcs) as c:
    for i in it:
      value = c.send(i)
    return value

def main():
  print(blah(range(100), [min, max]))
...
if __name__ == '__main__':
   main()
-- 
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