The thread module has been renamed to _thread in Python 3.0. The 2to3 tool will automatically adapt imports when converting your sources to 3.0; however, you should consider using the high-level threading module instead.
This module provides low-level primitives for working with multiple threads (also called light-weight processes or tasks) — multiple threads of control sharing their global data space. For synchronization, simple locks (also called mutexes or binary semaphores) are provided. The threading module provides an easier to use and higher-level threading API built on top of this module.
The module is optional. It is supported on Windows, Linux, SGI IRIX, Solaris 2.x, as well as on systems that have a POSIX thread (a.k.a. “pthread”) implementation. For systems lacking the thread module, the dummy_thread module is available. It duplicates this module’s interface and can be used as a drop-in replacement.
It defines the following constant and functions:
Raise a KeyboardInterrupt exception in the main thread. A subthread can use this function to interrupt the main thread.
New in version 2.3.
Return the thread stack size used when creating new threads. The optional size argument specifies the stack size to be used for subsequently created threads, and must be 0 (use platform or configured default) or a positive integer value of at least 32,768 (32kB). If changing the thread stack size is unsupported, the error exception is raised. If the specified stack size is invalid, a ValueError is raised and the stack size is unmodified. 32kB is currently the minimum supported stack size value to guarantee sufficient stack space for the interpreter itself. Note that some platforms may have particular restrictions on values for the stack size, such as requiring a minimum stack size > 32kB or requiring allocation in multiples of the system memory page size - platform documentation should be referred to for more information (4kB pages are common; using multiples of 4096 for the stack size is the suggested approach in the absence of more specific information). Availability: Windows, systems with POSIX threads.
New in version 2.5.
Lock objects have the following methods:
In addition to these methods, lock objects can also be used via the with statement, e.g.:
import thread a_lock = thread.allocate_lock() with a_lock: print "a_lock is locked while this executes"
It is not possible to interrupt the acquire() method on a lock — the KeyboardInterrupt exception will happen after the lock has been acquired.
When the main thread exits, it is system defined whether the other threads survive. On SGI IRIX using the native thread implementation, they survive. On most other systems, they are killed without executing try ... finally clauses or executing object destructors.