blocks|key|3405454|text|在新线程中运行它。了解java+here和python多线程here中的多线程技术|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|3405455|Java示例：|3405456|走错了路。通过将Thread子类化|3405457|new+Thread()+{
++++public+void+run()+{
++++++++YourFunction();//Call+your+function
++++}
}.start();|code-block|syntax|javascript|3405458|正确的方式。通过提供一个可运行的实例|3405459|Runnable+myrunnable+=+new+Runnable()+{
++++public+void+run()+{
++++++++YourFunction();//Call+your+function
++++}
}

new+Thread(myrunnable).start();//Call+it+when+you+need+to+run+the+function|3405460|entityMap|0|LINK|mutability|MUTABLE|url|http://www.tutorialspoint.com/java/java_multithreading.htm|1|http://www.tutorialspoint.com/python/python_multithreading.htm^0|G|4|0|U|4|1|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|10|8|@]|9|@$A|11|B|12|1|13]|$A|14|B|15|1|16]]|C|$]]|$1|D|3|E|5|6|7|17|8|@]|9|@]|C|$]]|$1|F|3|G|5|6|7|18|8|@]|9|@]|C|$]]|$1|H|3|I|5|J|7|19|8|@]|9|@]|C|$K|L]]|$1|M|3|N|5|6|7|1A|8|@]|9|@]|C|$]]|$1|O|3|P|5|J|7|1B|8|@]|9|@]|C|$K|L]]|$1|Q|3|-4|5|6|7|1C|8|@]|9|@]|C|$]]]|R|$S|$5|T|U|V|C|$W|X]]|Y|$5|T|U|V|C|$W|Z]]]]

Run it in a new thread. Learn about multithreading in java <a href="http://www.tutorialspoint.com/java/java_multithreading.htm" rel="nofollow noreferrer">here</a> and python multithreading <a href="http://www.tutorialspoint.com/python/python_multithreading.htm" rel="nofollow noreferrer">here</a>

Java example:

<h2>The WRONG way ... by subclassing Thread</h2>

<pre><code>new Thread() {
 public void run() {
 YourFunction();//Call your function
 }
}.start();
</code></pre>

<h2>The RIGHT way ... by supplying a Runnable instance</h2>

<pre><code>Runnable myrunnable = new Runnable() {
 public void run() {
 YourFunction();//Call your function
 }
}

new Thread(myrunnable).start();//Call it when you need to run the function
</code></pre>

blocks|key|3317689|text|在Java中，有一个标准习惯用法:创建一个线程并运行它：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3317690|new+Thread()+{
++++@Override
++++public+void+run()+{
++++++++callMyFunction();
++++}
}.start();|code-block|syntax|javascript|3317691|或者，您可以创建一个Runnable并将其传递给线程：|3317692|Runnable+caller+=+new+Runnable()+{
++++@Override
++++public+void+run()+{
++++++++callMyFunction();
++++}
}

new+Thread(caller).start();|3317693|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|N|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|O|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|P|8|@]|9|@]|A|$E|F]]|$1|K|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|L|$]]

In Java, there's a standard idiom: create a thread and run it:

<pre><code>new Thread() {
 @Override
 public void run() {
 callMyFunction();
 }
}.start();
</code></pre>

Or you can create a Runnable and pass it to the thread:

<pre><code>Runnable caller = new Runnable() {
 @Override
 public void run() {
 callMyFunction();
 }
}

new Thread(caller).start();
</code></pre>

blocks|key|1680644|text|在python中使用multiprocessing：|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1680645|from+multiprocessing+import+Process

def+b():
++++#+long+process

p+=+Process(target=b)+
p.start()|code-block|syntax|javascript|1680646|entityMap|0|LINK|mutability|MUTABLE|url|http://docs.python.org/library/multiprocessing.html^0|A|F|0|0|0^^$0|@$1|2|3|4|5|6|7|Q|8|@]|9|@$A|R|B|S|1|T]]|C|$]]|$1|D|3|E|5|F|7|U|8|@]|9|@]|C|$G|H]]|$1|I|3|-4|5|6|7|V|8|@]|9|@]|C|$]]]|J|$K|$5|L|M|N|C|$O|P]]]]

Using <a href="http://docs.python.org/library/multiprocessing.html" rel="nofollow">multiprocessing</a> in python:

<pre><code>from multiprocessing import Process

def b():
 # long process

p = Process(target=b) 
p.start()
</code></pre>

blocks|key|1680725|text|正如在其他答案中所指出的，在Python中，你可以将函数放在一个新的线程中(不是很好，因为CPython中的线程不会给你带来太多好处)，或者放在另一个使用多处理的进程中。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1680726|from+multiprocessing+import+Process

def+b():
++++#+long+process

def+a():
++++p+=+Process(target=b)+
++++p.start()
++++...
a()|code-block|syntax|javascript|1680727|(如monkut的答案所示)。|1680728|但是Python的装饰器允许将样板隐藏在地毯下，在调用时，您只“看到”一个普通的函数调用。在下面的示例中，我创建了“并行”装饰器--只需将其放在任何函数之前，当被调用时，它将自动在一个单独的进程中运行：|1680729|from+multiprocessing+import+Process
from+functools+import+partial

from+time+import+sleep

def+parallel(func):
++++def+parallel_func(*args,+**kw):
++++++++p+=+Process(target=func,+args=args,+kwargs=kw)
++++++++p.start()
++++return+parallel_func

@parallel
def+timed_print(x=0):
++++for+y+in+range(x,+x+%2B+10):
++++++++print+y
++++++++sleep(0.2)



def+example():
++++timed_print(100)
++++sleep(0.1)
++++timed_print(200)
++++for+z+in+range(10):
++++++++print+z
++++++++sleep(0.2)


if+__name__+==+"__main__":
++++example()|1680730|当运行这段代码时，会得到：|1680731|[gwidion@caylus+Documents]$+python+parallel.py+
100
0
200
101
1
201
102
2
202
103
3
203
104
4
204
105
5
205
106
6
206
107
7
207
108
8
208
109
9
209
[gwidion@caylus+Documents]$+|1680732|entityMap^0|0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|T|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|U|8|@]|9|@]|A|$]]|$1|I|3|J|5|6|7|V|8|@]|9|@]|A|$]]|$1|K|3|L|5|D|7|W|8|@]|9|@]|A|$E|F]]|$1|M|3|N|5|6|7|X|8|@]|9|@]|A|$]]|$1|O|3|P|5|D|7|Y|8|@]|9|@]|A|$E|F]]|$1|Q|3|-4|5|6|7|Z|8|@]|9|@]|A|$]]]|R|$]]

As noted in other answers, from Python you can either put the function in a new thread (not that good, since threads in CPython do not gain you much), or in another process using Multiprocessing - 

<pre><code>from multiprocessing import Process

def b():
 # long process

def a():
 p = Process(target=b) 
 p.start()
 ...
a()
</code></pre>

(As put in monkut's answer).

But Python's decorator allow one to hide the boilerplate under the carpet, in a way that at calling time, you "see" just a normal function call. In the example bellow,
I create the "parallel" decorator - just place it before any function, and it will authomatically run in a separate process when called:

<pre><code>from multiprocessing import Process
from functools import partial

from time import sleep

def parallel(func):
 def parallel_func(*args, **kw):
 p = Process(target=func, args=args, kwargs=kw)
 p.start()
 return parallel_func

@parallel
def timed_print(x=0):
 for y in range(x, x + 10):
 print y
 sleep(0.2)



def example():
 timed_print(100)
 sleep(0.1)
 timed_print(200)
 for z in range(10):
 print z
 sleep(0.2)


if __name__ == "__main__":
 example()
</code></pre>

When running this snippet, one gets:

<pre><code>[gwidion@caylus Documents]$ python parallel.py 
100
0
200
101
1
201
102
2
202
103
3
203
104
4
204
105
5
205
106
6
206
107
7
207
108
8
208
109
9
209
[gwidion@caylus Documents]$ 
</code></pre>

blocks|key|1680766|text|你最好从ExecutorService开始，而不是直接使用原始线程。它提供了池化，完成检测，还有一些子类也有一些调度。例如：|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1680767|...
//+Create+a+simple+instance+with+a+single+thread+in+the+pool
ExecutorService+executor+=+Executors.newFixedThreadPool(1);+
...
Future<Integer>+future+=+executor.submit(new+Callable<Integer>()+{
++++@Override
++++public+Integer+call()+{
++++++++return+YourFunction();
++++}
});
...

//+To+wait+for+YourFunction()+to+finish,+and+get+the+result:
Integer+result+=+future.get();|code-block|syntax|javascript|1680768|您可以向ExecutorService提交任意数量的异步任务；它们将并行执行，也可以按顺序执行，具体取决于您选择的实现、后备线程池中的线程数量等。|1680769|entityMap|0|LINK|mutability|MUTABLE|url|http://docs.oracle.com/javase/6/docs/api/java/util/concurrent/ExecutorService.html^0|4|F|0|0|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@]|9|@$A|T|B|U|1|V]]|C|$]]|$1|D|3|E|5|F|7|W|8|@]|9|@]|C|$G|H]]|$1|I|3|J|5|6|7|X|8|@]|9|@]|C|$]]|$1|K|3|-4|5|6|7|Y|8|@]|9|@]|C|$]]]|L|$M|$5|N|O|P|C|$Q|R]]]]

You'd better start with an <a href="http://docs.oracle.com/javase/6/docs/api/java/util/concurrent/ExecutorService.html" rel="nofollow">ExecutorService</a> instead of going directly with raw threads.
It provides pooling, completion detection, and there are subclasses which also have some scheduling. For instance:

<pre><code>...
// Create a simple instance with a single thread in the pool
ExecutorService executor = Executors.newFixedThreadPool(1); 
...
Future&lt;Integer&gt; future = executor.submit(new Callable&lt;Integer&gt;() {
 @Override
 public Integer call() {
 return YourFunction();
 }
});
...

// To wait for YourFunction() to finish, and get the result:
Integer result = future.get();
</code></pre>

You can submit as many asynchronous tasks to the ExecutorService as you like; they will be executed in parallel, or sequentially, depending on the implementation you choose, on the number of threads in the backing thread pool, etc.

blocks|key|1893381|text|由于jsbueno的答案并不适用于所有的windows系统，因为由于操作系统的限制，os.fork在那里不能高效地工作，所以你必须在那里使用多线程才能达到同样的效果。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1893382|请在jsbueno的答案中找到相同的代码，使用多线程而不是多处理(Python3版本)|1893383|from+threading+import+Thread

from+time+import+sleep

def+thread_parallel(func):
++++def+parallel_func(*args,+**kw):
++++++++p+=+Thread(target=func,+args=args,+kwargs=kw)
++++++++p.daemon+=+True
++++++++p.start()
++++return+parallel_func

@thread_parallel
def+timed_print(x=0):
++++for+y+in+range(x,+x+%2B+10):
++++++++print(y)
++++++++sleep(0.2)


def+example():
++++timed_print(100)
++++sleep(0.1)
++++timed_print(200)
++++for+z+in+range(10):
++++++++print(z)
++++++++sleep(0.2)


if+__name__+==+"__main__":
++++example()|code-block|syntax|javascript|1893384|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|K|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|L|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|M|8|@]|9|@]|A|$G|H]]|$1|I|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|J|$]]

Since jsbueno's answer will not work in all windows systems, as os.fork will not work efficiently there due to restrictions in the os, you will have to use multithreading there to achieve the same effect.

Please find the same code from jsbueno's answer with multithreading instead of multiprocessing (Python 3 version)

<pre><code>from threading import Thread

from time import sleep

def thread_parallel(func):
 def parallel_func(*args, **kw):
 p = Thread(target=func, args=args, kwargs=kw)
 p.daemon = True
 p.start()
 return parallel_func

@thread_parallel
def timed_print(x=0):
 for y in range(x, x + 10):
 print(y)
 sleep(0.2)


def example():
 timed_print(100)
 sleep(0.1)
 timed_print(200)
 for z in range(10):
 print(z)
 sleep(0.2)


if __name__ == "__main__":
 example()
</code></pre>

Hi I was wondering if there was a way of calling a function/method (preferably in Python or Java) and continue execution without waiting for it.

Example:

<pre><code>def a():
 b() #call a function, b()
 return "something"

def b():
 #something that takes a really long time
</code></pre>

Call a function without waiting for it

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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嗨，我想知道是否有一种方法可以调用函数/方法(最好是在Python或Java中)并继续执行，而不需要等待它。示例：def a():    b()  #call a function, b()    return "something"def b():    #something that takes a really ...

问无需等待即可调用函数
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问无需等待即可调用函数EN