翻译12.1节

tylinux · tylinux · commit c0be80f29385 · 2015-08-20T08:39:20.000+08:00
diff --git a/source/c12/p01_start_stop_thread.rst b/source/c12/p01_start_stop_thread.rst
@@ -5,148 +5,134 @@
 ----------
 问题
 ----------
-You want to create and destroy threads for concurrent execution of code.
-
-|
+你要为需要并发执行的代码创建/销毁线程
 
 ----------
 解决方案
 ----------
-The threading library can be used to execute any Python callable in its own thread. To
-do this, you create a Thread instance and supply the callable that you wish to execute
-as a target. Here is a simple example:
-
-# Code to execute in an independent thread
-import time
-def countdown(n):
-    while n > 0:
-        print('T-minus', n)
-        n -= 1
-        time.sleep(5)
-
-# Create and launch a thread
-from threading import Thread
-t = Thread(target=countdown, args=(10,))
-t.start()
-
-When you create a thread instance, it doesn’t start executing until you invoke its start()
-method (which invokes the target function with the arguments you supplied).
-Threads are executed in their own system-level thread (e.g., a POSIX thread or Windows
-threads) that is fully managed by the host operating system. Once started, threads run
-independently until the target function returns. You can query a thread instance to see
-if it’s still running:
-
-if t.is_alive():
-    print('Still running')
-else:
-    print('Completed')
-
-You can also request to join with a thread, which waits for it to terminate:
-
-    t.join()
-
-The interpreter remains running until all threads terminate. For long-running threads
-or background tasks that run forever, you should consider making the thread daemonic.
-For example:
-
-t = Thread(target=countdown, args=(10,), daemon=True)
-t.start()
-
-Daemonic threads can’t be joined. However, they are destroyed automatically when the
-main thread terminates.
-Beyond the two operations shown, there aren’t many other things you can do with
-threads. For example, there are no operations to terminate a thread, signal a thread,
-adjust its scheduling, or perform any other high-level operations. If you want these
-features, you need to build them yourself.
-If you want to be able to terminate threads, the thread must be programmed to poll for
-exit at selected points. For example, you might put your thread in a class such as this:
-
-class CountdownTask:
-    def __init__(self):
-        self._running = True
-
-    def terminate(self):
-        self._running = False
-
-    def run(self, n):
-        while self._running and n > 0:
-            print('T-minus', n)
-            n -= 1
-            time.sleep(5)
-
-c = CountdownTask()
-t = Thread(target=c.run, args=(10,))
-t.start()
-...
-c.terminate() # Signal termination
-t.join()      # Wait for actual termination (if needed)
-
-Polling for thread termination can be tricky to coordinate if threads perform blocking
-operations such as I/O. For example, a thread blocked indefinitely on an I/O operation
-may never return to check if it’s been killed. To correctly deal with this case, you’ll need
-to carefully program thread to utilize timeout loops. For example:
-
-class IOTask:
-    def terminate(self):
-        self._running = False
-
-    def run(self, sock):
-        # sock is a socket
-        sock.settimeout(5)        # Set timeout period
-        while self._running:
-            # Perform a blocking I/O operation w/ timeout
-            try:
-                data = sock.recv(8192)
-                break
-            except socket.timeout:
-                continue
-            # Continued processing
-            ...
-        # Terminated
-        return
-
+``threading`` 库可以在单独的线程中执行任何的在 Python 中可以调用的对象。你可以创建一个 ``Thread`` 对象并将你要执行的对象以 target 参数的形式提供给该对象。
+下面是一个简单的例子：
+
+.. code-block:: python
+
+   # Code to execute in an independent thread
+   import time
+   def countdown(n):
+       while n > 0:
+       print('T-minus', n)
+       n -= 1
+       time.sleep(5)
+
+   # Create and launch a thread
+   from threading import Thread
+   t = Thread(target=countdown, args=(10,))
+   t.start()
+
+当你创建好一个线程对象后，该对象并不会立即执行，除非你调用它的 ``start()`` 方法（当你调用 ``start()`` 方法时，它会调用你传递进来的函数，并把你传递进来的参数传递给该函数）。Python中的线程会在一个单独的系统级线程中执行（比如说一个 POSIX 线程或者一个 Windows 线程），这些线程将由操作系统来全权管理。线程一旦启动，将独立执行直到目标函数返回。你可以查询一个线程对象的状态，看它是否还在执行：
+
+.. code-block:: python
+   
+   if t.is_alive():
+       print('Still running')
+   else:
+       print('Completed')
+
+你也可以将一个线程加入到当前线程，并等待它终止：
+
+.. code-block:: python
+
+   t.join()
+
+Python解释器在所有线程都终止后才继续执行代码剩余的部分。对于需要长时间运行的线程或者需要一直运行的后台任务，你应当考虑使用后台线程。
+例如：
+
+.. code-block:: python
+   
+   t = Thread(target=countdown, args=(10,), daemon=True)
+   t.start()
+
+后台线程无法等待，不过，这些线程会在主线程终止时自动销毁。
+除了如上所示的两个操作，并没有太多可以对线程做的事情。你无法结束一个线程，无法给它发送信号，无法调整它的调度，也无法执行其他高级操作。如果需要这些特性，你需要自己添加。比如说，如果你需要终止线程，那么这个线程必须通过编程在某个特定点轮询来退出。你可以像下边这样把线程放入一个类中：
+
+.. code-block:: python
+
+   class CountdownTask:
+       def __init__(self):
+           self._running = True
+
+       def terminate(self):
+           self._running = False
+
+       def run(self, n):
+           while self._running and n > 0:
+               print('T-minus', n)
+               n -= 1
+               time.sleep(5)
+
+       c = CountdownTask()
+       t = Thread(target=c.run, args=(10,))
+       t.start()
+       c.terminate() # Signal termination
+       t.join()      # Wait for actual termination (if needed)
+
+如果线程执行一些像I/O这样的阻塞操作，那么通过轮询来终止线程将使得线程之间的协调变得非常棘手。比如，如果一个线程一直阻塞在一个I/O操作上，它就永远无法返回，也就无法检查自己是否已经被结束了。要正确处理这些问题，你需要利用超时循环来小心操作线程。
+例子如下：
+
+.. code-block:: python
+   
+   class IOTask:
+       def terminate(self):
+           self._running = False
+
+       def run(self, sock):
+           # sock is a socket
+           sock.settimeout(5)        # Set timeout period
+           while self._running:
+               # Perform a blocking I/O operation w/ timeout
+               try:
+                   data = sock.recv(8192)
+                   break
+               except socket.timeout:
+                   continue
+               # Continued processing
+               ...
+           # Terminated
+           return
 |
 
 ----------
 讨论
 ----------
-Due to a global interpreter lock (GIL), Python threads are restricted to an execution
-model that only allows one thread to execute in the interpreter at any given time. For
-this reason, Python threads should generally not be used for computationally intensive
-tasks where you are trying to achieve parallelism on multiple CPUs. They are much
-better suited for I/O handling and handling concurrent execution in code that performs
-blocking operations (e.g., waiting for I/O, waiting for results from a database, etc.).
-Sometimes  you  will  see  threads  defined  via  inheritance  from  the  Thread  class.  For
-example:
-
-from threading import Thread
-
-class CountdownThread(Thread):
-    def __init__(self, n):
-        super().__init__()
-        self.n = 0
-    def run(self):
-        while self.n > 0:
-
-            print('T-minus', self.n)
-            self.n -= 1
-            time.sleep(5)
-
-c = CountdownThread(5)
-c.start()
-
-Although this works, it introduces an extra dependency between the code and the 
-threading library. That is, you can only use the resulting code in the context of threads,
-whereas the technique shown earlier involves writing code with no explicit dependency
-on threading. By freeing your code of such dependencies, it becomes usable in other
-contexts that may or may not involve threads. For instance, you might be able to execute
-your code in a separate process using the multiprocessing module using code like this:
-
-import multiprocessing
-c = CountdownTask(5)
-p = multiprocessing.Process(target=c.run)
-p.start()
-...
-
-Again, this only works if the CountdownTask class has been written in a manner that is
-neutral to the actual means of concurrency (threads, processes, etc.).
+由于全局解释锁（GIL）的原因，Python 的线程被限制到同一时刻只允许一个线程执行这样一个执行模型。所以，Python 的线程更适用于处理I/O和其他需要并发执行的阻塞操作（比如等待I/O、等待从数据库获取数据等等），而不是需要多处理器并行的计算密集型任务。
+
+有时你会看到下边这种通过继承 ``Thread`` 类来实现的线程：
+
+.. code-block:: python
+   
+   from threading import Thread
+
+   class CountdownThread(Thread):
+       def __init__(self, n):
+           super().__init__()
+           self.n = 0
+       def run(self):
+           while self.n > 0:
+
+               print('T-minus', self.n)
+               self.n -= 1
+               time.sleep(5)
+
+   c = CountdownThread(5)
+   c.start()
+
+尽管这样也可以工作，但这使得你的代码依赖于 ``threading`` 库，所以你的这些代码只能在线程上下文中使用。上文所写的那些代码、函数都是与 ``threading`` 库无关的，这样就使得这些代码可以被用在其他的上下文中，可能与线程有关，也可能与线程无关。比如，你可以通过 ``multiprocessing`` 模块在一个单独的进程中执行你的代码：
+
+.. code-block:: python
+   
+   import multiprocessing
+   c = CountdownTask(5)
+   p = multiprocessing.Process(target=c.run)
+   p.start()
+
+
+再次重申，这段代码仅适用于 CountdownTask 类是以独立于实际的并发手段（多线程、多进程等等）实现的情况。
