======
stopit

Raise asynchronous exceptions in other threads, control the timeout of
blocks or callables with two context managers and two decorators.

.. attention:: API Changes

Users of 1.0.0 should upgrade their source code:

stopit.Timeout is renamed stopit.ThreadingTimeout
stopit.timeoutable is renamed stopit.threading_timeoutable

Explications follow below...

.. contents::

Overview

This module provides:

a function that raises an exception in another thread, including the main
thread.
two context managers that may stop its inner block activity on timeout.
two decorators that may stop its decorated callables on timeout.

Developed and tested with CPython 2.6, 2.7, 3.3 and 3.4 on MacOSX. Should work
on any OS (xBSD, Linux, Windows) except when explicitly mentioned.

.. note::

Signal based timeout controls, namely SignalTimeout context manager and
signal_timeoutable decorator won't work in Windows that has no support
for signal.SIGALRM. Any help to work around this is welcome.

Installation

Using `stopit` in your application

Both work identically:

.. code:: bash

easy_install stopit
pip install stopit

Developing `stopit`

.. code:: bash

You should prefer forking if you have a Github account

git clone https://github.com/glenfant/stopit.git
cd stopit
python setup.py develop

Does it work for you ?

python setup.py test

Public API

Exception

stopit.TimeoutException
...........................

A stopit.TimeoutException may be raised in a timeout context manager
controlled block.

This exception may be propagated in your application at the end of execution
of the context manager controlled block, see the swallow_ex parameter of
the context managers.

Note that the stopit.TimeoutException is always swallowed after the
execution of functions decorated with xxx_timeoutable(...). Anyway, you
may catch this exception within the decorated function.

Threading based resources

.. warning::

Threading based resources will only work with CPython implementations
since we use CPython specific low level API. This excludes Iron Python,
Jython, Pypy, ...

Will not stop the execution of blocking Python atomic instructions that
acquire the GIL. In example, if the destination thread is actually
executing a time.sleep(20), the asynchronous exception is effective
after its execution.

stopit.async_raise
......................

A function that raises an arbitrary exception in another thread

async_raise(tid, exception)

tid is the thread identifier as provided by the ident attribute of a
thread object. See the documentation of the threading module for further
information.
exception is the exception class or object to raise in the thread.

stopit.ThreadingTimeout
...........................

A context manager that "kills" its inner block execution that exceeds the
provided time.

ThreadingTimeout(seconds, swallow_exc=True)

seconds is the number of seconds allowed to the execution of the context
managed block.
swallow_exc : if False, the possible stopit.TimeoutException will
be re-raised when quitting the context managed block. Attention: a
True value does not swallow other potential exceptions.

Methods and attributes

of a stopit.ThreadingTimeout context manager.

.. list-table::
:header-rows: 1

- Method / Attribute
- Description
- .cancel()
- Cancels the timeout control. This method is intended for use within the
  block that's under timeout control, specifically to cancel the timeout
  control. Means that all code executed after this call may be executed
  till the end.
- .state
- This attribute indicated the actual status of the timeout control. It
  may take the value of the EXECUTED, EXECUTING, TIMED_OUT,
  INTERRUPTED or CANCELED attributes. See below.
- .EXECUTING
- The timeout control is under execution. We are typically executing
  within the code under control of the context manager.
- .EXECUTED
- Good news: the code under timeout control completed normally within the
  assigned time frame.
- .TIMED_OUT
- Bad news: the code under timeout control has been sleeping too long.
  The objects supposed to be created or changed within the timeout
  controlled block should be considered as non existing or corrupted.
  Don't play with them otherwise informed.
- .INTERRUPTED
- The code under timeout control may itself raise explicit
  stopit.TimeoutException for any application logic reason that may
  occur. This intentional exit can be spotted from outside the timeout
  controlled block with this state value.
- .CANCELED
- The timeout control has been intentionally canceled and the code
  running under timeout control did complete normally. But perhaps after
  the assigned time frame.

A typical usage:

.. code:: python

import stopit

...

with stopit.ThreadingTimeout(10) as to_ctx_mgr:
assert to_ctx_mgr.state == to_ctx_mgr.EXECUTING
# Something potentially very long but which
# ...

OK, let's check what happened

if to_ctx_mgr.state == to_ctx_mgr.EXECUTED:
# All's fine, everything was executed within 10 seconds
elif to_ctx_mgr.state == to_ctx_mgr.EXECUTING:
# Hmm, that's not possible outside the block
elif to_ctx_mgr.state == to_ctx_mgr.TIMED_OUT:
# Eeek the 10 seconds timeout occurred while executing the block
elif to_ctx_mgr.state == to_ctx_mgr.INTERRUPTED:
# Oh you raised specifically the TimeoutException in the block
elif to_ctx_mgr.state == to_ctx_mgr.CANCELED:
# Oh you called to_ctx_mgr.cancel() method within the block but it
# executed till the end
else:
# That's not possible

Notice that the context manager object may be considered as a boolean
indicating (if True) that the block executed normally:

.. code:: python

if to_ctx_mgr:
# Yes, the code under timeout control completed
# Objects it created or changed may be considered consistent

stopit.threading_timeoutable
................................

A decorator that kills the function or method it decorates, if it does not
return within a given time frame.

stopit.threading_timeoutable([default [, timeout_param]])

default is the value to be returned by the decorated function or method of
when its execution timed out, to notify the caller code that the function
did not complete within the assigned time frame.

If this parameter is not provided, the decorated function or method will
return a None value when its execution times out.

.. code:: python

@stopit.threading_timeoutable(default='not finished')
def infinite_loop():
# As its name says...
result = infinite_loop(timeout=5)
assert result == 'not finished'
timeout_param: The function or method you have decorated may require a
timeout named parameter for whatever reason. This empowers you to change
the name of the timeout parameter in the decorated function signature to
whatever suits, and prevent a potential naming conflict.

.. code:: python

@stopit.threading_timeoutable(timeout_param='my_timeout')
def some_slow_function(a, b, timeout='whatever'):
# As its name says...
result = some_slow_function(1, 2, timeout="something", my_timeout=2)

About the decorated function
............................

or method...

As you noticed above, you just need to add the timeout parameter when
calling the function or method. Or whatever other name for this you chose with
the timeout_param of the decorator. When calling the real inner function
or method, this parameter is removed.

Signaling based resources

.. warning::

Using signaling based resources will not work under Windows or any OS
that's not based on Unix.

stopit.SignalTimeout and stopit.signal_timeoutable have exactly the
same API as their respective threading based resources, namely
stopit.ThreadingTimeout_ and stopit.threading_timeoutable_.

See the comparison chart_ that warns on the more or less subtle differences
between the Threading based resources_ and the Signaling based resources_.

Logging

The stopit named logger emits a warning each time a block of code
execution exceeds the associated timeout. To turn logging off, just:

.. code:: python

import logging
stopit_logger = logging.getLogger('stopit')
stopit_logger.seLevel(logging.ERROR)

.. _comparison chart:

Comparing thread based and signal based timeout control

.. list-table::
:header-rows: 1

- Feature
- Threading based resources
- Signaling based resources
- GIL
- Can't interrupt a long Python atomic instruction. e.g. if
  time.sleep(20.0) is actually executing, the timeout will take
  effect at the end of the execution of this line.
- Don't care of it
- Thread safety
- Yes : Thread safe as long as each thread uses its own ThreadingTimeout
  context manager or threading_timeoutable decorator.
- Not thread safe. Could yield unpredictable results in a
  multithreads application.
- Nestable context managers
- Yes : you can nest threading based context managers
- No : never nest a signaling based context manager in another one.
  The innermost context manager will automatically cancel the timeout
  control of outer ones.
- Accuracy
- Any positive floating value is accepted as timeout value. The accuracy
  depends on the GIL interval checking of your platform. See the doc on
  sys.getcheckinterval and sys.setcheckinterval for your Python
  version.
- Due to the use of signal.SIGALRM, we need provide an integer number
  of seconds. So a timeout of 0.6 seconds will ve automatically
  converted into a timeout of zero second!
- Supported platforms
- Any CPython 2.6, 2.7 or 3.3 on any OS with threading support.
- Any Python 2.6, 2.7 or 3.3 with signal.SIGALRM support. This
  excludes Windows boxes

Known issues

Timeout accuracy

Important: the way CPython supports threading and asynchronous features has
impacts on the accuracy of the timeout. In other words, if you assign a 2.0
seconds timeout to a context managed block or a decorated callable, the
effective code block / callable execution interruption may occur some
fractions of seconds after this assigned timeout.

For more background about this issue - that cannot be fixed - please read
Python gurus thoughts about Python threading, the GIL and context switching
like these ones:

This is the reason why I am more "tolerant" on timeout accuracy in the tests
you can read thereafter than I should be for a critical real-time application
(that's not in the scope of Python).

It is anyway possible to improve this accuracy at the expense of the global
performances decreasing the check interval which defaults to 100. See:

If this is a real issue for users (want a precise timeout and not an
approximative one), a future release will add the optional check_interval
parameter to the context managers and decorators. This parameter will enable
to lower temporarily the threads switching check interval, having a more
accurate timeout at the expense of the overall performances while the context
managed block or decorated functions are executing.

`gevent` support

Threading timeout control as mentioned in Threading based resources_ does not work as expected
when used in the context of a gevent worker.

See the discussion in Issue 13 <https://github.com/glenfant/stopit/issues/13>_ for more details.

Tests and demos

.. code:: pycon

import threading
from stopit import async_raise, TimeoutException

In a real application, you should either use threading based timeout resources:

.. code:: pycon

from stopit import ThreadingTimeout as Timeout, threading_timeoutable as timeoutable #doctest: +SKIP

Or the POSIX signal based resources:

.. code:: pycon

from stopit import SignalTimeout as Timeout, signal_timeoutable as timeoutable #doctest: +SKIP

Let's define some utilities:

.. code:: pycon

import time
def fast_func():
... return 0

def variable_duration_func(duration):
... t0 = time.time()
... while True:
... dummy = 0
... if time.time() - t0 > duration:
... break

exc_traces = []
def variable_duration_func_handling_exc(duration, exc_traces):
... try:
... t0 = time.time()
... while True:
... dummy = 0
... if time.time() - t0 > duration:
... break
... except Exception as exc:
... exc_traces.append(exc)

def func_with_exception():
... raise LookupError()

`async_raise` function raises an exception in another thread

Testing async_raise() with a thread of 5 seconds:

.. code:: pycon

five_seconds_threads = threading.Thread(
... target=variable_duration_func_handling_exc, args=(5.0, exc_traces))

start_time = time.time()
five_seconds_threads.start()
thread_ident = five_seconds_threads.ident
five_seconds_threads.is_alive()
True

We raise a LookupError in that thread:

.. code:: pycon

async_raise(thread_ident, LookupError)

Okay but we must wait few milliseconds the thread death since the exception is
asynchronous:

.. code:: pycon

while five_seconds_threads.is_alive():
... pass

And we can notice that we stopped the thread before it stopped by itself:

.. code:: pycon

time.time() - start_time < 0.5
True

len(exc_traces)
1

exc_traces[-1].class.name
'LookupError'

`Timeout` context manager

The context manager stops the execution of its inner block after a given time.
You may manage the way the timeout occurs using a try: ... except: ...
construct or by inspecting the context manager state attribute after the
block.

Swallowing Timeout exceptions
.............................

We check that the fast functions return as outside our context manager:

.. code:: pycon

with Timeout(5.0) as timeout_ctx:
... result = fast_func()

result
0

timeout_ctx.state == timeout_ctx.EXECUTED
True

And the context manager is considered as True (the block executed its last
line):

.. code:: pycon

bool(timeout_ctx)
True

We check that slow functions are interrupted:

.. code:: pycon

start_time = time.time()
with Timeout(2.0) as timeout_ctx:
... variable_duration_func(5.0)

time.time() - start_time < 2.2
True

timeout_ctx.state == timeout_ctx.TIMED_OUT
True

And the context manager is considered as False since the block did timeout.

.. code:: pycon

bool(timeout_ctx)
False

Other exceptions are propagated and must be treated as usual:

.. code:: pycon

try:
... with Timeout(5.0) as timeout_ctx:
... result = func_with_exception()
... except LookupError:
... result = 'exception_seen'

timeout_ctx.state == timeout_ctx.EXECUTING
True

result
'exception_seen'

Propagating TimeoutException
................................

We can choose to propagate the TimeoutException too. Potential exceptions
have to be handled:

.. code:: pycon

result = None
start_time = time.time()
try:
... with Timeout(2.0, swallow_exc=False) as timeout_ctx:
... variable_duration_func(5.0)
... except TimeoutException:
... result = 'exception_seen'

time.time() - start_time < 2.2
True

result
'exception_seen'

timeout_ctx.state == timeout_ctx.TIMED_OUT
True

Other exceptions must be handled too:

.. code:: pycon

result = None
start_time = time.time()
try:
... with Timeout(2.0, swallow_exc=False) as timeout_ctx:
... func_with_exception()
... except Exception:
... result = 'exception_seen'

time.time() - start_time < 0.1
True

result
'exception_seen'

timeout_ctx.state == timeout_ctx.EXECUTING
True

`timeoutable` callable decorator

This decorator stops the execution of any callable that should not last a
certain amount of time.

You may use a decorated callable without timeout control if you don't provide
the timeout optional argument:

.. code:: pycon

@timeoutable()
... def fast_double(value):
... return value * 2

fast_double(3)
6

You may specify that timeout with the timeout optional argument.
Interrupted callables return None:

.. code:: pycon

@timeoutable()
... def infinite():
... while True:
... pass
... return 'whatever'

infinite(timeout=1) is None
True

Or any other value provided to the timeoutable decorator parameter:

.. code:: pycon

@timeoutable('unexpected')
... def infinite():
... while True:
... pass
... return 'whatever'

infinite(timeout=1)
'unexpected'

If the timeout parameter name may clash with your callable signature, you
may change it using timeout_param:

.. code:: pycon

@timeoutable('unexpected', timeout_param='my_timeout')
... def infinite():
... while True:
... pass
... return 'whatever'

infinite(my_timeout=1)
'unexpected'

It works on instance methods too:

.. code:: pycon

class Anything(object):
... @timeoutable('unexpected')
... def infinite(self, value):
... assert type(value) is int
... while True:
... pass

obj = Anything()
obj.infinite(2, timeout=1)
'unexpected'

Links

Source code (clone, fork, ...)
https://github.com/glenfant/stopit

Issues tracker
https://github.com/glenfant/stopit/issues

PyPI
https://pypi.python.org/pypi/stopit

Credits

This is a NIH package which is mainly a theft of Gabriel Ahtune's recipe <http://gahtune.blogspot.fr/2013/08/a-timeout-context-manager.html>_ with
tests, minor improvements and refactorings, documentation and setuptools
awareness I made since I'm somehow tired to copy/paste this recipe among
projects that need timeout control.
Gilles Lenfant <gilles.lenfant@gmail.com>_: package creator and
maintainer.

License

This software is open source delivered under the terms of the MIT license. See the LICENSE file of this repository.

Changes log

1.1.2 - 2018-02-09

Changed license to MIT
Tested with Python 3.5 and 3.6

1.1.1 - 2015-03-22

Fixed bug of timeout context manager as bool under Python 2.x
Tested with Python 3.4

1.1.0 - 2014-05-02

Added support for TIMER signal based timeout control (Posix OS only)
API changes due to new timeout controls
An exhaustive documentation.

1.0.0 - 2014-02-09

Initial version

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stopit

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