uqfoundation / multiprocess Goto Github PK

I tried to install pathos using miniconda + py3.4. I get the following errors:

Complete output from command python setup.py egg_info:
Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "/private/var/folders/d0/kxzh7pwd4c10bzx7wffq8s740000gn/T/pip-build-dw9bfq7k/pathos/setup.py", line 66
    exec setup_code
                  ^
SyntaxError: Missing parentheses in call to 'exec'

From looking around it seems that pathos can only be used on Py2, is that correct? If so, then is there an alternative for Py3?

Hi, this is my codes:

from multiprocess import Queue
q = Queue()
BaseManager.register('getq',callable=lambda:q)
server=BaseManager(address=('127.0.0.1',5009),authkey=b'abc')
server.start()
x=server.getq() # Here I got an error

RemoteError:

Traceback (most recent call last):
File "E:\Anaconda3\lib\site-packages\multiprocess\managers.py", line 195, in handle_request
result = func(c, *args, **kwds)
File "E:\Anaconda3\lib\site-packages\multiprocess\managers.py", line 351, in create
obj = callable(*args, **kwds)
File "", line 1, in
NameError: name 'q' is not defined

If lib is before lib/site-packages in your PYTHONPATH, then the stdlib version of multiprocessing will be found and not the fork. This points to installing as multiprocess as a better option (as in #2).

I was trying to add typing to a function that can take either an integer or a multiprocess.Pool().
in the case of the integer it would star a Pool itself.

from typing import Union
import multiprocess

def foo( procs : Union[int, multiprocess.pool.Pool]):
    pass

This however fails with
AttributeError: module 'multiprocess' has no attribute 'pool'

if I either run import multiprocess.pool

import multiprocess.pool
multiprcess.pool

or if I use multiprocess.Pool()

import multiprocess
multiprocess.Pool()
multiprcess.pool

They work.
but

import multiprocess
multiprcess.pool
>> AttributeError: module 'multiprocess' has no attribute 'pool'

gives the error.

My question is this the expected behavior?

Hi,

I am working on a non-blocking I/O gevent-powered web application that is required to launch a child process to handle a CPU-intensive task which can be crashed randomly because of bugs in the underlying C/C++ code.

However, Python's standard multiprocessing has defined its own socket that makes it incompatible with gevent's patch. As a result, the following code does not work

from gevent.monkey import patch_all
patch_all()
from multiprocessing import Process, Pipe

def test_document(conn, local_path):
    try:
        file_utils.test_document(local_path)
    except BaseException as e:
        conn.send(e)
    else:
        conn.send("done")
    conn.close()

parent_conn, child_conn = Pipe()
p = Process(target=test_document, args=(child_conn, local_path,))
p.start()
try:
    message = None
    # Broken because of gevent
    message = parent_conn.recv() # An IOError (Resource temporarily unavailable) will be thrown
except:
    # Always get a IOError, message will be never returned
   pass

The solution to this issue is to unpatch it which makes multiprocessing code work.

https://github.com/liujingchen/fixgevent

However, it forces my application to be blocked on I/O again.

What about multiprocess? Can it handle the issue or I need to implement a work-around?

Thanks

Has anyone worked to have pytest coverage statistics follow multiprocess processes?

• Coverage as specific support for collecting coverage statistics from tasks using threads, greenlists, and multiprocessor. The multiprocessor specific code:

def multiprocessing_start(_):
    cov = init()
    if cov:
        multiprocessing.util.Finalize(None, cleanup, args=(cov,), exitpriority=1000)


try:
    import multiprocessing.util
except ImportError:
    pass
else:
    multiprocessing.util.register_after_fork(multiprocessing_start, multiprocessing_start)

multiprocessing_finish = cleanup  # in case someone dared to use this internal

• Generating coverage for portions of code under multiprocess, especially in PyCharm, would be helpful.

Is there any guidance on this? Or any experience?

From time to time I find myself writing something like this (I removed all insignificant parts):

    def sometask(self, n, jobs=1):

        if not isinstance(jobs, int) or jobs < 1:
            raise ValueError("`jobs` must be a positive integer")

        def foo(...):
            output1 = workers.starmap(spam, ...)
            outpu2 = workers.map(ham, ...)
            return  zip(output1, output2)

        workers = Workers(jobs)
        foo(...)
        workers.terminate()

When jobs >= 1 you get the overhead of de/serialising stuff, but it shouldn't be the case when jobs == 1. Why waste resources? So far I've been doing something like this

from itertools import starmap

class MyPool(Pool):

    @property
    def processes(self):
        return self._processes

    def map(self, func, iterable, chunksize=None):
        if self.processes == 1:
            return list(map(func, iterable))
        return super().map(func, iterable, chunksize=chunksize)

    def starmap(self, func, iterable, chunksize=None):
        if self.processes == 1:
            return list(starmap(func, iterable))
        return super().starmap(func, iterable, chunksize=chunksize)

Have you thought about adding something like this to your package?

Hi,

Since the new Python 3.5 release the setup script fail to work.
I have done the (obvious) following at the root of the repository:

$ cp -rf py3.4 py3.5
$ sudo python setup.py install

And it works perfectly.
I think it will be great that the setup script fallback to the last version supported by Multiprocess.
I have not yet experimented issue with Python 3.5 and Multiprocess, but I do not use the entire module.

Best regards,

Hi,

We are attempting to replace multiprocessing with your package after hitting a bug in our project (Axelrod-Python/Axelrod#518). However, we are hitting exactly the same error and, somewhat unexpectedly, it arises within the standard pickle.py.

Assuming our library is installed using pip install axelrod here is the minimum code which reproduces the problem:

import dill
import axelrod as axl
player = axl.BackStabber()
dill.dumps(player)

Any idea where we are going wrong?

On windows dill is a problem.

Would it be easy to replace it with cloudpickle, as did the "dask" package ?
dask/dask#865

Migrate relevant tickets at http://trac.mystic.cacr.caltech.edu/project/pathos/query.html to the list of issues here.

update copyright and license

I'm trying to call a function which uses a numpy function in its body, with Pool.map and Pool.map_async, however each time, I get an error saying 'name "numpy" is not defined. I then had a look at the Python 3.5 examples, which use the time module in the body of a function, but this also fails for me. The following are the lines of code I'm executing line by line in Spyder->IPython on Windows 7 x64:

from multiprocess import Pool, TimeoutError
from multiprocess import cpu_count as cpuCount, current_process as currentProcess, freeze_support as freezeSupport, active_children as activeChildren

import time, random, sys

def calculate(func, args):
    result = func(*args)
    return '%s says that %s%s = %s' % \
        (currentProcess()._name, func.__name__, args, result)

def mul(a, b):
    time.sleep(0.5*random.random())
    return a * b

pool = Pool(4)
TASKS = [(mul, (i, 7)) for i in range(10)]
results = [pool.apply_async(calculate, t) for t in TASKS]

for r in results:
    print('\t', r.get())

That last for loop gives me an error: NameError: name 'time' is not defined

I'm guessing this is because the function mul uses time.sleep, however, the time module is not being loaded in the child pseudo-fork process on Windows. However, this code is straight from the multiprocess github examples, so I'm not sure why this isn't working for me.

Could anyone please help me out? How can you use a function in Pool which uses external modules like time or numpy in that function's body?

Observed this behavior when Pool.maping a callback that either returned a value or a custom exception type. Returning certain types of exceptions will cause the Pool.map call to never return (hang), and in the case of Python 2.7, you are unable to SIGINT the process (possibly because something handles KeyboardInterrupt).

I believe that the mishandling of these custom exceptions is caused by pickle internally, but there is still the issue that Pool.map does not return when this occurs.

I have written some Nose tests in a Gist to reproduce this issue, and to determine exactly which cases trigger this issue. The tests that are decorated with @skip will cause the tests to hang if they are run.

I am using Python version 2.7.10/3.5.2, and multiprocess version 0.70.5.

TLDR; If, from a Pool.map callback, you return a custom exception whose constructor is of arity n, but you pass n + 1 arguments to that exception's parent constructor, Pool.map will never return, and you may need to kill Python to regain control.

Need to add a travis.yml file. The issue is that for each different version of python, there's a different tests (and optionally, examples) folder. Thus, there needs to be something like an environment variable that captures the version of python being used, so if can be passed into the script block.

Suppose we've got a project:

test/
     test.py
     pkg/
         __init__.py
         lib/
             __init__.py
             workers.py
         test/
             __init__.py
             workers.py

In pkg/lib/workers we have:

import multiprocess.pool as mp


class Test:
    def __init__(self, f):
        self.f = f

    def method(self, data):
        return workers.map(self.f, data)


if __name__ == "__main__":
    raise RuntimeError
else:
    workers = mp.Pool(processes=2)

in pkg/test/workers.py

from ..lib.workers import *


print(Test(max).method([[1,2,3], [1,2,3]]))

in test.py

print("Hello")

import pkg.test.workers

print("Goobye")

When I run test.py I get:

$ python test.py 
Hello
[3, 3]
Goobye

If I change the second line of code in pkg/test/workers.py from print(Test(max).method([[1,2,3], [1,2,3]])) to print(Test(lambda x: max(x)).method([[1,2,3], [1,2,3]])), I get

$ python test.py 
Hello

And the process freezes. Nothing happens for hours. No errors, no messages.

P.S.

This is a stripped down version of my real project, where I use the pool of workers inside a bound method of an instance and pass an attribute to the pool as a function to use. I believe this example reproduces the exact same problem.

P.P.S.

I've also asked the question on Stack Overflow (link)

I'm using the concurrent.futures ProcessPoolExecutor option.

Installed multiprocess to solve the "Can't pickle <class 'module'>: attribute lookup module on builtins failed" but it didn't work either.

The data is a static keras model which isn't pickable - see https://keras.io/getting-started/faq/#how-can-i-save-a-keras-model.

I have enough memory for each process to hold a copy of the data model or for it to be placed in shared memory for all processes to access. But, how to solve the not pickable problem for a keras model?

This, ultimately, should be a patch submitted to python.

freeze_support is required on windows, is it possible to remove the need to use it?

With multiprocessing.reducer.register, multiprocessing can register a custom pickler. How does this impact the use of dill in multiprocess?

Build sphinx docs for multiprocess.

This is a little weird, as the docs are overwhelmingly the same as the python standard library multiprocessing... and in addition, multiprocess has a slightly different version for each minor version of python.

(this happens every time)

Process: Python [39974]
Path: /System/Library/Frameworks/Python.framework/Versions/2.7/Resources/Python.app/Contents/MacOS/Python
Identifier: Python
Version: 2.7.10 (2.7.10)
Code Type: X86-64 (Native)
Parent Process: Python [39965]
Responsible: Terminal [258]
User ID: 501

Date/Time: 2016-02-19 12:05:12.981 +0000
OS Version: Mac OS X 10.10.5 (14F27)
Report Version: 11
Anonymous UUID: 36B6C9B8-4E1D-FCD0-677F-7B3719CA910C

Sleep/Wake UUID: B6BE108A-FCFD-460C-8778-4DB9AED9AB21

Time Awake Since Boot: 970000 seconds
Time Since Wake: 3300 seconds

Crashed Thread: 0 Dispatch queue: com.apple.main-thread

Exception Type: EXC_BAD_ACCESS (SIGSEGV)
Exception Codes: KERN_INVALID_ADDRESS at 0x0000000000000110

VM Regions Near 0x110:
-->
__TEXT 000000010e700000-000000010e701000 [ 4K] r-x/rwx SM=COW /System/Library/Frameworks/Python.framework/Versions/2.7/Resources/Python.app/Contents/MacOS/Python

Application Specific Information:
*** multi-threaded process forked ***
crashed on child side of fork pre-exec

Thread 0 Crashed:: Dispatch queue: com.apple.main-thread
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Thread 0 crashed with X86 Thread State (64-bit):
rax: 0x0000000000000000 rbx: 0x00007f81785d43e0 rcx: 0x0000000000000100 rdx: 0x0000000000000003
rdi: 0x00007f817ac03240 rsi: 0x0000000000000001 rbp: 0x00007fff514f9a30 rsp: 0x00007fff514f9a00
r8: 0x0000000000000006 r9: 0x00000000ffffffe0 r10: 0x000000000000000d r11: 0x00007f8178500000
r12: 0x0000000000000001 r13: 0x00007f817ac03240 r14: 0x0000000000001000 r15: 0x00007fff7c42fbc0
rip: 0x00007fff9709e5d2 rfl: 0x0000000000010206 cr2: 0x0000000000000110

Logical CPU: 6
Error Code: 0x00000006
Trap Number: 14

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0x7fff99996000 - 0x7fff99a2afff com.apple.ink.framework (10.9 - 213) <8E029630-1530-3734-A446-13353F0E7AC5> /System/Library/Frameworks/Carbon.framework/Versions/A/Frameworks/Ink.framework/Versions/A/Ink
0x7fff99a2b000 - 0x7fff99a63fff com.apple.RemoteViewServices (2.0 - 99) /System/Library/PrivateFrameworks/RemoteViewServices.framework/Versions/A/RemoteViewServices
0x7fff99a64000 - 0x7fff99a67fff com.apple.xpc.ServiceManagement (1.0 - 1) /System/Library/Frameworks/ServiceManagement.framework/Versions/A/ServiceManagement
0x7fff99acc000 - 0x7fff99acefff com.apple.loginsupport (1.0 - 1) /System/Library/PrivateFrameworks/login.framework/Versions/A/Frameworks/loginsupport.framework/Versions/A/loginsupport
0x7fff99acf000 - 0x7fff99ae8ff7 com.apple.CFOpenDirectory (10.10 - 187) <3FCEE6F7-A8C6-3222-B22D-8AD290E477E2> /System/Library/Frameworks/OpenDirectory.framework/Versions/A/Frameworks/CFOpenDirectory.framework/Versions/A/CFOpenDirectory
0x7fff99ae9000 - 0x7fff99aeafff com.apple.TrustEvaluationAgent (2.0 - 25) <2D61A2C3-C83E-3A3F-8EC1-736DBEC250AB> /System/Library/PrivateFrameworks/TrustEvaluationAgent.framework/Versions/A/TrustEvaluationAgent
0x7fff99af0000 - 0x7fff99af3ff7 libdyld.dylib (353.2.3) /usr/lib/system/libdyld.dylib
0x7fff99af4000 - 0x7fff99af5fff libffi.dylib (18.1) <0F6C6A4D-1210-3585-8DA1-B8A94B9924A5> /usr/lib/libffi.dylib
0x7fff99af6000 - 0x7fff99b98fff com.apple.Bluetooth (4.3.6 - 4.3.6f3) /System/Library/Frameworks/IOBluetooth.framework/Versions/A/IOBluetooth
0x7fff99b99000 - 0x7fff99b9afff libDiagnosticMessagesClient.dylib (100) <2EE8E436-5CDC-34C5-9959-5BA218D507FB> /usr/lib/libDiagnosticMessagesClient.dylib
0x7fff99c35000 - 0x7fff99d19fff libcrypto.0.9.8.dylib (52.40.1) /usr/lib/libcrypto.0.9.8.dylib
0x7fff99ebd000 - 0x7fff9a1eefff com.apple.Foundation (6.9 - 1154) <49EE64E1-9F53-35D1-A481-2EFE2789B254> /System/Library/Frameworks/Foundation.framework/Versions/C/Foundation

External Modification Summary:
Calls made by other processes targeting this process:
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Calls made by this process:
task_for_pid: 0
thread_create: 0
thread_set_state: 0
Calls made by all processes on this machine:
task_for_pid: 47694102
thread_create: 1
thread_set_state: 0

VM Region Summary:
ReadOnly portion of Libraries: Total=188.5M resident=177.1M(94%) swapped_out_or_unallocated=11.4M(6%)
Writable regions: Total=126.6M written=4856K(4%) resident=44.0M(35%) swapped_out=0K(0%) unallocated=82.6M(65%)

REGION TYPE VIRTUAL
=========== =======
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Model: MacBookPro11,3, BootROM MBP112.0138.B15, 4 processors, Intel Core i7, 2.5 GHz, 16 GB, SMC 2.19f12
Graphics: Intel Iris Pro, Intel Iris Pro, Built-In
Graphics: NVIDIA GeForce GT 750M, NVIDIA GeForce GT 750M, PCIe, 2048 MB
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AirPort: spairport_wireless_card_type_airport_extreme (0x14E4, 0x134), Broadcom BCM43xx 1.0 (7.15.166.24.3)
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apparently some changes were made in 3.6.2 (and likely 3.6.1) that cause failures in the 3.6.0-based test suite. Some changes were made to utils in e290d4c, and a few tests were commented out in the proceeding commits. However, it's probably a better approach to migrate multiprocess to a more recent version (3.6.4 or greater).

Nearly all tests in the native multiprocessing unit test suite pass. However, there were a very few failures… like test_unpicklable_object that failed. List the tests here, and determine if action needs to be taken.

At least locally, tox fails unless it is run with a tox built for the specified python version, and the envlist does not contain any other python versions.

So, tox-2.7 -e py27 works, and tox-3.5 -e py35 works -- however, tox-3.5 -e py34 and tox-3.5 -e py35,py34 both hang on the build of the mismatched version's extension code.

Actually, there are several 'issues' (on windows, python2.7):

• when installing with pip install . (from the repo directory), no warning about missing C compiler is issued.
• when installing with pip install . (and having no C compiler) it is impossible to import multiprocess because it complains about missing _multiprocess
• when installing via python setup.py install it does warn about missing C compiler, but promises that most functionality will be available. import multiprocess still raises ImportError missing _multiprocess

So, if not having C compiler makes it impossible to import multiprocess, then may be it should be an error, not a warning?

What free (open) C compiler can I install on windows so multiprocess can build its extensions?

I may be doing something wrong here, so please correct me if the problem is actually very simple.

The problem here is that setting dill.settings['recurse'] = True doesn't seem to prevent the same issues that are present in Issue #155 of dill while using multiprocess.

To give a minimal test code, running the code below,

import dill
from sympy import Symbol, lambdify
dill.detect.trace(False) # Let me know if you'd like to see this output.
dill.settings['recurse'] = True

x = Symbol('x', real=True)
H = lambdify(x, x**2, 'numpy')

print(dill.loads(dill.dumps(H)))

yields an expected result of printing

<function _lambdifygenerated at 0x7f81f0e79510>

While the following code

import multiprocess as mp
import dill
from sympy import Symbol, lambdify
dill.detect.trace(True)
dill.settings['recurse'] = True

x = Symbol('x', real=True)
H = lambdify(x, x**2, 'numpy')

pool = mp.Pool(mp.cpu_count())
res = pool.map(H, (2,3,))
print(res.get())

throws the exception:

  File "/usr/lib/python3.7/site-packages/dill/_dill.py", line 1321, in save_type
    StockPickler.save_global(pickler, obj)
  File "/usr/lib/python3.7/pickle.py", line 962, in save_global
    (obj, module_name, name))
_pickle.PicklingError: Can't pickle <class 'numpy.int64'>: it's not the same object as numpy.int64

with the full output posted here.

I'm running Python 3.7.1 with

>>> dill.__version__
'0.2.8.2'
>>> mp.__version__
'0.70.5'

Oh, and running the first script with

dill.settings['recurse'] = False

yields the same error as in the multiprocess script.

I got the following error in python 3.5:

>>> import multiprocess
>>> multiprocess.__version__
'0.70.4'
>>> from multiprocess import Pool
>>> p = Pool(4)
>>> p.map(lambda x: (lambda y:y**2)(x) + x, range(10))
Traceback (most recent call last):
  File "<input>", line 1, in <module>
    p.map(lambda x: (lambda y:y**2)(x) + x, range(10))
  File "/home/zhou13/.local/lib/python3.5/site-packages/multiprocess/pool.py", line 260, in map
    return self._map_async(func, iterable, mapstar, chunksize).get()
  File "/home/zhou13/.local/lib/python3.5/site-packages/multiprocess/pool.py", line 608, in get
    raise self._value
  File "/home/zhou13/.local/lib/python3.5/site-packages/multiprocess/pool.py", line 385, in _handle_tasks
    put(task)
  File "/home/zhou13/.local/lib/python3.5/site-packages/multiprocess/connection.py", line 206, in send
    self._send_bytes(ForkingPickler.dumps(obj))
  File "/home/zhou13/.local/lib/python3.5/site-packages/multiprocess/reduction.py", line 53, in dumps
    cls(buf, protocol).dump(obj)
  File "/usr/lib/python3.5/pickle.py", line 408, in dump
    self.save(obj)
  File "/usr/lib/python3.5/pickle.py", line 475, in save
    f(self, obj) # Call unbound method with explicit self
  File "/usr/lib/python3.5/pickle.py", line 740, in save_tuple
    save(element)
  File "/usr/lib/python3.5/pickle.py", line 475, in save
    f(self, obj) # Call unbound method with explicit self
  File "/usr/lib/python3.5/pickle.py", line 725, in save_tuple
    save(element)
  File "/usr/lib/python3.5/pickle.py", line 475, in save
    f(self, obj) # Call unbound method with explicit self
  File "/usr/lib/python3.5/pickle.py", line 725, in save_tuple
    save(element)
  File "/usr/lib/python3.5/pickle.py", line 475, in save
    f(self, obj) # Call unbound method with explicit self
  File "/home/zhou13/.local/lib/python3.5/site-packages/dill/dill.py", line 793, in save_function
    obj.__dict__), obj=obj)
  File "/usr/lib/python3.5/pickle.py", line 599, in save_reduce
    save(args)
  File "/usr/lib/python3.5/pickle.py", line 475, in save
    f(self, obj) # Call unbound method with explicit self
  File "/usr/lib/python3.5/pickle.py", line 740, in save_tuple
    save(element)
  File "/usr/lib/python3.5/pickle.py", line 475, in save
    f(self, obj) # Call unbound method with explicit self
  File "/home/zhou13/.local/lib/python3.5/site-packages/dill/dill.py", line 835, in save_module_dict
    StockPickler.save_dict(pickler, obj)
  File "/usr/lib/python3.5/pickle.py", line 810, in save_dict
    self._batch_setitems(obj.items())
  File "/usr/lib/python3.5/pickle.py", line 836, in _batch_setitems
    save(v)
  File "/usr/lib/python3.5/pickle.py", line 495, in save
    rv = reduce(self.proto)
  File "/home/zhou13/.local/lib/python3.5/site-packages/multiprocess/pool.py", line 492, in __reduce__
    'pool objects cannot be passed between processes or pickled'
NotImplementedError: pool objects cannot be passed between processes or pickled

The critical change in 3.x is very self contained (for 2.x, it also includes two lines in C). Could dill be injected into multiprocessing proper at runtime?

Support for tox should be added. One issue is that the tests are different for each version of python, and currently need to be aware of which version of python is being executed.

I tried running:

from multiprocess import Process, Queue
q = Queue()

which works fine in py2.7 but in py3.5 i get an error:

SystemError: initialization of _multiprocess raised unreported exception

This is different from #10 because the error occurs after importing (so importing seems to work fine). If I try to use the regular queue module, it looks like multiprocess tries to use the pickle method instead of dill to serialize.

Hi, I am replacing the multiprocessing with multiprocess module, and while my target function consist enum, it return pickling error. If the enum is removed, the function will run without issue.

My target function is a simple loop as I tried to troubleshoot the source of can't pickling:
def ExecuteMultiprocess(self):
list = []
i = States.DetectingShots
count = 0
while i is States.DetectingShots:
list.append(i)
print(i)
count = count+1
if count > 10:
break

Error
Traceback (most recent call last):
File "", line 1, in
File "C:\Gk\Pf\Gk\source\XShot\XShot\env\lib\site-packages\multiprocess\spawn.py", line 105, in spawn_main
exitcode = _main(fd)
File "C:\Gk\Pf\Gk\source\XShot\XShot\env\lib\site-packages\multiprocess\spawn.py", line 115, in _main
self = reduction.pickle.load(from_parent)
File "C:\Gk\Pf\Gk\source\XShot\XShot\env\lib\site-packages\dill_dill.py", line 304, in load
obj = pik.load()
EOFError: Ran out of input

Building wheels should reduce the need for people to install a C compiler. Not having a C compiler or Python.h is one of the most common issues that is experienced for pathos and multiprocess.

It should be fairly trivial to support pypy. I expect it will either require a fork, as done with python, or possibly could be done with a extend.

I installed multiprocess via pip (python 2.7 on Win10). The installation seemed to be successful.

But when I use the example code

    from multiprocess import Process, Queue

    def f(q):
        q.put('hello world')

    if __name__ == '__main__':
        q = Queue()
        p = Process(target=f, args=[q])
        p.start()
        print q.get()
        p.join()

I get an error message:
Traceback (most recent call last):
File "C:\Users\mdk\Desktop\test_process.py", line 1, in
from multiprocess import Process, Queue
File "C:\Python27\lib\site-packages\multiprocess__init_.py", line 84, in
import _multiprocess as _multiprocessing
ImportError: No module named multiprocess

Need to fork python 3.6 multiprocessing and add new directory in multiprocess.

Have you thought about including a citation file in your repo?

This idea is based on: http://www.software.ac.uk/blog/2013-09-02-encouraging-citation-software-introducing-citation-files

Here is an example:

https://github.com/DRMacIver/hypothesis/blob/master/CITATION

I know you have instructions but a standard CITATION file is helpful. If this is of interest I could submit a PR.

Ensure all tests can run with nosetests or pytest, or at least with a run_all that can be run with python -m multiprocess.tests or something like that.

$ python -V
Python 2.7.13
$ python py2.7/tests/__init__.py
…

======================================================================
FAIL: test_no_import_lock_contention (__main__.WithManagerTestQueue)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "__init__.py", line 641, in test_no_import_lock_contention
    self.fail("Probable regression on import lock contention;"
AssertionError: Probable regression on import lock contention; see Issue #22853

This failure does not occur for other supported versions of python 2.x and 3.x.

My program seems to not proceed further beyond the docs = poolObj.map(nlp,textStr) statement. I am using python 3.6 on windows server, 64 bit virtual machine with 8 virtual CPU's. Its on Azure Cloud.

I installed tcc and put it under C:/Apps/tcc and added it to to the system path. Downloaded the multiprocess source from GitHub, build and installed it.
I am able to call import _multiprocess

My code is as below

import spacy
import pandas as pd
import numpy as np
from multiprocess import Pool
from multiprocess import freeze_support as freezeSupport

def getEntitiesByChunk(textList):   
    
    path="C:/Apps/Anaconda3/model"
    nlp= spacy.load(path,disable=['tokenizer','parser', 'textcat','tagger']) 
    textList = np.array(textList)
    if(len(textList)<400):
        n=2
    else:    
        n=int(len(textList)/400)
    textChunks = np.array_split(textList,n)
    textStr = [(' ').join(textChunks[i].tolist()) for i in range(n)]
    
    entitiesfinal=[]
    entities = []
   
    freezeSupport()
    poolObj = Pool(5)
    
    docs = poolObj.map(nlp,textStr)
    for doc in docs: 
	entities =[{'text':ent.text,'type': ent.label_} for ent in doc.ents] 
        entitiesfinal.extend(entities)	

    return pd.DataFrame(df) 

In [2]: import multiprocess as mp
---------------------------------------------------------------------------
ImportError                               Traceback (most recent call last)
/cs/work/home/hxiao/code/lst/<ipython-input-2-e802685ea588> in <module>()
----> 1 import multiprocess as mp

/cs/home/hxiao/.local/lib/python2.7/site-packages/multiprocess/__init__.py in <module>()
     63
     64 from multiprocess.process import Process, current_process, active_children
---> 65 from multiprocess.util import SUBDEBUG, SUBWARNING
     66
     67 #


/cs/home/hxiao/.local/lib/python2.7/site-packages/multiprocess/util.py in <module>()
     39 import threading        # we want threading to install it's
     40                         # cleanup function before multiprocessing does

---> 41 from subprocess import _args_from_interpreter_flags
     42
     43 from multiprocess.process import current_process, active_children

ImportError: cannot import name _args_from_interpreter_flags

Python version:

Python 2.7.3 (default, Jun 22 2015, 19:33:41)
[GCC 4.6.3] on linux2

it seems the docs have broken. see: https://multiprocess.readthedocs.io/

maybe overwriting the standard library isn't a great idea -- so an alternate install could be provided as the default (with option to overload?)

I'm trying to install multiprocess into an ubuntu linux 14.04 anaconda environment on an aws ec2 instance.

Using pip install multiprocess executes successfully and installs 0.70.4

However, in ipython:

import multiprocess

generates the folllowing:

ImportError Traceback (most recent call last)
in ()
----> 1 import multiprocess

/home/ubuntu/anaconda/envs/roa/lib/python2.7/site-packages/multiprocess/init.py in ()
82
83 # This is down here because _multiprocessing uses BufferTooShort
---> 84 import _multiprocess as _multiprocessing
85
86 #

ImportError: No module named _multiprocess

I'm using the same environment on the AWS EC2 instance as on my stand alone ubuntu 14.04 box where the same version was installed via cvxpy successfully (ie no import error).

Using which c++ generates

/usr/bin/c++

Using which g++ generates

/usr/bin/g++

Using which gcc generates

/usr/bin/gcc

on both the AWS EC2 instance and my box where there is no issue.

Anything else I can try?

Thanks,

Rob

update multiprocess to match python versions 3.4.9, 3.5.6, 3.6.8, and 3.7.2

Greetings. Programmed myself into a corner by getting something to work with fork on posix then realizing spawn was going to be a nightmare on windows. I have typically been subclassing Process directly and performing communication between processes with Events, Queues, and so on. Upon trying a drop in replacement with multiprocess, i.e.

import multiprocess as mp
class Filter(mp.Process):
    def __init__(self):
        super(Filter, self).__init__()
        # Other stuff
        self.exit = mp.Event()
        # Other stuff

I see problems with creating the event. This ultimately traces to:

~/anaconda/lib/python3.6/site-packages/multiprocess/semaphore_tracker.py in ensure_running(self)
     59                 args = [exe] + util._args_from_interpreter_flags()
     60                 args += ['-c', cmd % r]
---> 61                 util.spawnv_passfds(exe, args, fds_to_pass)
     62             except:
     63                 os.close(w)

~/anaconda/lib/python3.6/site-packages/multiprocess/util.py in spawnv_passfds(path, args, passfds)
    393             args, [os.fsencode(path)], True, passfds, None, None,
    394             -1, -1, -1, -1, -1, -1, errpipe_read, errpipe_write,
--> 395             False, False, None)
    396     finally:
    397         os.close(errpipe_read)

TypeError: fork_exec() argument 4 must be tuple, not list

Which seems like a simple tuple/list confusion.

Connection objects, such as those created by a Pipe are not pickled correctly in python 2.x. There is a known patch, which has been applied to python 3.x. See: uqfoundation/dill#177 for details.

all tests in test_multiprocessing_main_handling fail for py3.4, py3.5, py3.6, and py3.7.

$ python py3.5/tests/test_multiprocessing_main_handling.py 
FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF
======================================================================
FAIL: test_basic_script (__main__.ForkCmdLineTest)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "py3.5/tests/test_multiprocessing_main_handling.py", line 161, in test_basic_script
    self._check_script(script_name)
  File "py3.5/tests/test_multiprocessing_main_handling.py", line 155, in _check_script
    rc, out, err = assert_python_ok(*run_args, __isolated=False)
  File "/opt/local/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/test/support/script_helper.py", line 135, in assert_python_ok
    return _assert_python(True, *args, **env_vars)
  File "/opt/local/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/test/support/script_helper.py", line 121, in _assert_python
    err))
AssertionError: Process return code is 1
command line: ['/opt/local/bin/python3.5', '-X', 'faulthandler', '-E', '/private/var/folders/t2/nsd68bs92ys2q1qbjnqf4s6c0000gn/T/tmpbp5kt9jk/script.py', 'fork']

stdout:
---

---

stderr:
---
Traceback (most recent call last):
  File "/private/var/folders/t2/nsd68bs92ys2q1qbjnqf4s6c0000gn/T/tmpbp5kt9jk/script.py", line 10, in <module>
    from multiprocess import Pool, set_start_method
ImportError: No module named 'multiprocess'
---

…

Can you tag and release a new version to pypi? The new Python 3.5 support will be very helpful.

>>> import multiprocess as mp
>>> import time
>>> 
>>> def sleepy_squared(x):
…     time.sleep(0.2)
…     return x**2
…
>>> mp.Pool().map(sleepy_squared, range(2))

On Windows, this fails with a NameError -- global name time not defined.

However, it can be avoided by using:
dill.settings['trace'] = True
Results then are as expected.