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authorGeorg Brandl <georg@python.org>2008-09-29 06:43:45 (GMT)
committerGeorg Brandl <georg@python.org>2008-09-29 06:43:45 (GMT)
commit4970215bb544977f958c189ffcc440c0647d52b8 (patch)
tree2f7511e248582675c41bd6e1f6d6ee50c5814559 /Doc/library/multiprocessing.rst
parent58e74c6e0a94a8260a13329cac17548a2bff1961 (diff)
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#3993: fix old-style print statements.
Diffstat (limited to 'Doc/library/multiprocessing.rst')
-rw-r--r--Doc/library/multiprocessing.rst86
1 files changed, 43 insertions, 43 deletions
diff --git a/Doc/library/multiprocessing.rst b/Doc/library/multiprocessing.rst
index dd816a0..7badbc3 100644
--- a/Doc/library/multiprocessing.rst
+++ b/Doc/library/multiprocessing.rst
@@ -6,7 +6,7 @@
Introduction
-----------------------
+------------
:mod:`multiprocessing` is a package that supports spawning processes using an
API similar to the :mod:`threading` module. The :mod:`multiprocessing` package
@@ -28,7 +28,7 @@ multiprocess program is ::
from multiprocessing import Process
def f(name):
- print 'hello', name
+ print('hello', name)
if __name__ == '__main__':
p = Process(target=f, args=('bob',))
@@ -62,7 +62,7 @@ processes:
q = Queue()
p = Process(target=f, args=(q,))
p.start()
- print q.get() # prints "[42, None, 'hello']"
+ print(q.get()) # prints "[42, None, 'hello']"
p.join()
Queues are thread and process safe.
@@ -82,7 +82,7 @@ processes:
parent_conn, child_conn = Pipe()
p = Process(target=f, args=(child_conn,))
p.start()
- print parent_conn.recv() # prints "[42, None, 'hello']"
+ print(parent_conn.recv()) # prints "[42, None, 'hello']"
p.join()
The two connection objects returned by :func:`Pipe` represent the two ends of
@@ -105,7 +105,7 @@ that only one process prints to standard output at a time::
def f(l, i):
l.acquire()
- print 'hello world', i
+ print('hello world', i)
l.release()
if __name__ == '__main__':
@@ -148,8 +148,8 @@ However, if you really do need to use some shared data then
p.start()
p.join()
- print num.value
- print arr[:]
+ print(num.value)
+ print(arr[:])
will print ::
@@ -195,8 +195,8 @@ However, if you really do need to use some shared data then
p.start()
p.join()
- print d
- print l
+ print(d)
+ print(l)
will print ::
@@ -224,10 +224,10 @@ For example::
return x*x
if __name__ == '__main__':
- pool = Pool(processes=4) # start 4 worker processes
- result = pool.applyAsync(f, [10]) # evaluate "f(10)" asynchronously
- print result.get(timeout=1) # prints "100" unless your computer is *very* slow
- print pool.map(f, range(10)) # prints "[0, 1, 4,..., 81]"
+ pool = Pool(processes=4) # start 4 worker processes
+ result = pool.applyAsync(f, [10]) # evaluate "f(10)" asynchronously
+ print(result.get(timeout=1)) # prints "100" unless your computer is *very* slow
+ print(pool.map(f, range(10))) # prints "[0, 1, 4,..., 81]"
Reference
@@ -371,13 +371,13 @@ The :mod:`multiprocessing` package mostly replicates the API of the
>>> import processing, time, signal
>>> p = processing.Process(target=time.sleep, args=(1000,))
- >>> print p, p.is_alive()
+ >>> print(p, p.is_alive())
<Process(Process-1, initial)> False
>>> p.start()
- >>> print p, p.is_alive()
+ >>> print(p, p.is_alive())
<Process(Process-1, started)> True
>>> p.terminate()
- >>> print p, p.is_alive()
+ >>> print(p, p.is_alive())
<Process(Process-1, stopped[SIGTERM])> False
>>> p.exitcode == -signal.SIGTERM
True
@@ -612,7 +612,7 @@ Miscellaneous
from multiprocessing import Process, freeze_support
def f():
- print 'hello world!'
+ print('hello world!')
if __name__ == '__main__':
freeze_support()
@@ -1011,13 +1011,13 @@ process::
p.start()
p.join()
- print n.value
- print x.value
- print s.value
- print [(a.x, a.y) for a in A]
+ print(n.value)
+ print(x.value)
+ print(s.value)
+ print([(a.x, a.y) for a in A])
-.. highlightlang:: none
+.. highlight:: none
The results printed are ::
@@ -1026,7 +1026,7 @@ The results printed are ::
HELLO WORLD
[(3.515625, 39.0625), (33.0625, 4.0), (5.640625, 90.25)]
-.. highlightlang:: python
+.. highlight:: python
.. _multiprocessing-managers:
@@ -1212,7 +1212,7 @@ However, when using a proxy for a namespace object, an attribute beginning with
>>> Global.x = 10
>>> Global.y = 'hello'
>>> Global._z = 12.3 # this is an attribute of the proxy
- >>> print Global
+ >>> print(Global)
Namespace(x=10, y='hello')
@@ -1240,8 +1240,8 @@ callables with the manager class. For example::
manager = MyManager()
manager.start()
maths = manager.Maths()
- print maths.add(4, 3) # prints 7
- print maths.mul(7, 8) # prints 56
+ print(maths.add(4, 3)) # prints 7
+ print(maths.mul(7, 8)) # prints 56
Using a remote manager
@@ -1300,9 +1300,9 @@ referent can::
>>> from multiprocessing import Manager
>>> manager = Manager()
>>> l = manager.list([i*i for i in range(10)])
- >>> print l
+ >>> print(l)
[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]
- >>> print repr(l)
+ >>> print(repr(l))
<ListProxy object, typeid 'list' at 0xb799974c>
>>> l[4]
16
@@ -1321,10 +1321,10 @@ itself. This means, for example, that one shared object can contain a second::
>>> a = manager.list()
>>> b = manager.list()
>>> a.append(b) # referent of a now contains referent of b
- >>> print a, b
+ >>> print(a, b)
[[]] []
>>> b.append('hello')
- >>> print a, b
+ >>> print(a, b)
[['hello']] ['hello']
.. note::
@@ -1529,18 +1529,18 @@ The following example demonstrates the use of a pool::
pool = Pool(processes=4) # start 4 worker processes
result = pool.applyAsync(f, (10,)) # evaluate "f(10)" asynchronously
- print result.get(timeout=1) # prints "100" unless your computer is *very* slow
+ print(result.get(timeout=1)) # prints "100" unless your computer is *very* slow
- print pool.map(f, range(10)) # prints "[0, 1, 4,..., 81]"
+ print(pool.map(f, range(10))) # prints "[0, 1, 4,..., 81]"
it = pool.imap(f, range(10))
- print it.next() # prints "0"
- print it.next() # prints "1"
- print it.next(timeout=1) # prints "4" unless your computer is *very* slow
+ print(next(it)) # prints "0"
+ print(next(it)) # prints "1"
+ print(it.next(timeout=1)) # prints "4" unless your computer is *very* slow
import time
result = pool.applyAsync(time.sleep, (10,))
- print result.get(timeout=1) # raises TimeoutError
+ print(result.get(timeout=1)) # raises TimeoutError
.. _multiprocessing-listeners-clients:
@@ -1670,7 +1670,7 @@ the client::
listener = Listener(address, authkey='secret password')
conn = listener.accept()
- print 'connection accepted from', listener.last_accepted
+ print('connection accepted from', listener.last_accepted)
conn.send([2.25, None, 'junk', float])
@@ -1690,13 +1690,13 @@ server::
address = ('localhost', 6000)
conn = Client(address, authkey='secret password')
- print conn.recv() # => [2.25, None, 'junk', float]
+ print(conn.recv()) # => [2.25, None, 'junk', float]
- print conn.recv_bytes() # => 'hello'
+ print(conn.recv_bytes()) # => 'hello'
arr = array('i', [0, 0, 0, 0, 0])
- print conn.recv_bytes_into(arr) # => 8
- print arr # => array('i', [42, 1729, 0, 0, 0])
+ print(conn.recv_bytes_into(arr)) # => 8
+ print(arr) # => array('i', [42, 1729, 0, 0, 0])
conn.close()
@@ -1957,7 +1957,7 @@ Safe importing of main module
from multiprocessing import Process
def foo():
- print 'hello'
+ print('hello')
p = Process(target=foo)
p.start()
@@ -1968,7 +1968,7 @@ Safe importing of main module
from multiprocessing import Process, freeze_support
def foo():
- print 'hello'
+ print('hello')
if __name__ == '__main__':
freeze_support()