CHANGES

CHANGES
-------
01/08/2017 Some refinements to the abide() function.   You can now have it
           reserve a dedicated thread.  This allows it to work with things
           like Condition variables.   For example::

               cond = threading.Condition()    # Foreign condition variable

               ...
               async with abide(code, reserve_thread=True) as c:
                   # c is an async-wrapper around (code)
                   # The following operation uses the same thread that was
                   # used to acquire the lock.
                   await c.wait()             
               ...

           abide() also prefers to use the block_in_thread() function that
           makes it much more efficient when synchronizing with basic locks
           and events.
 
01/08/2017 Some reworking of internals related to thread/process workers and 
           task cancellation. One issue with launching work into a thread
           worker is that threads have no mechanism for cancellation.  They
           run fully to completion no matter what.  Thus, if you perform some
           work like this:

                await run_in_thread(callable, args)

           and the calling task gets cancelled, it's impossible to find out
           what happened with the thread.  Basically, it's lost to the sands
           of time.   However, you can now supply an optional call_on_cancel
           argument to the function and use it like this:

                def cancelled_result(future):
                    result = future.result()
                    ...
                    
                await run_in_thread(callable, args, call_on_cancel=cancelled_result)

           The call_on_cancel function is a normal synchronous
           function. It receives the Future instance that was being used
           to receive the result of the threaded operation.  This
           Future is guaranteed to have the result/exception set.

	   Be aware that there is no way to know when the call_on_cancel 
           function might be triggered.  It might be far in the future.
           The Curio kernel might not even be running.   Thus, it's 
           generally not safe to make too many assumptions about it.
           The only guarantee is that the call_on_cancel function is
           called after a result is computed and it's called in the
           same thread.

           The main purpose of this feature is to have better support
           for cleanup of failed synchronization operations involving
           threads.

01/06/2017 New function.  block_in_thread().   This works like run_in_thread()
           except that it's used with the expectation that whatever operation
           is being performed is likely going to block for an undetermined
           time period.  The underlying operation is handled more efficiently.
           For each unique callable, there is at most 1 background thread
           being used regardless of how many tasks might be trying to
           perform the same operation.  For example, suppose you were
           trying to synchronize with a foreign queue:

               import queue
               
               work_q = queue.Queue()     # Standard thread queue

               async def worker():
                   while True:
                       item = await block_in_thread(work_q.get)
                       ...

               # Spin up a huge number of workers
               for n in range(1000):
                   await spawn(worker())

           In this code, there is one queue and 1000 worker tasks trying to
           read items.  The block_in_thread() function only uses 1 background
           thread to handle it.   If you used run_in_thread() instead, it
           consume all available worker threads and you'd probably deadlock.

01/05/2017 Experimental new feature--asynchronous threads!  An async thread
           is an actual real-life thread where it is safe to call Curio
           coroutines and use its various synchronization features. 
           As an example, suppose you had some code like this:

               async def handler(client, addr):
                   async with client:
                       async for data in client.as_stream():
                           n = int(data)
                           time.sleep(n)
                           await client.sendall(b'Awake!\n')
                   print('Connection closed')

               run(tcp_server('', 25000, handler))

           Imagine that the time.sleep() function represents some kind of
           synchronous, blocking operation.  In the above code, it would
           block the Curio kernel, prevents all other tasks from running.

           Not a problem, change the handler() function to an async thread
           and use the await() function like this:

               from curio.thread import await, async_thread

               @async_thread
               def handler(client, addr):
                   with client:
                       for data in client.as_stream():
                           n = int(data)
                           time.sleep(n)
                           await(client.sendall(b'Awake!\n'))
                   print('Connection closed')

              run(tcp_server('', 25000, handler))


           You'll find that the above code works fine and doesn't block
           the kernel.

           Asynchronous threads only work in the context of Curio.  They
           may use all of Curio's features.  Everywhere you would normally
           use await, you use the await() function. with and for statements
           will work with objects supporting asynchronous operation. 

01/04/2017 Modifed enable_cancellation() and disable_cancellation() so that
           they can also be used as functions.  This makes it easier to
           shield a single operation. For example:

              await disable_cancellation(coro())

           Functionally, it is the same as this:

              async with disable_cancellation():
                  await coro()

           This is mostly a convenience feature.  

01/04/2017 Two tasks that attempt to wait on the same file descriptor
           now results in an exception.  Closes issue #104.

01/04/2017 Modified the monitor so that killing the Curio process also
           kills the monitor thread and disconnects any connected clients.
           Addresses issue #108.

01/04/2017 Modified task.cancel() so that it also cancels any pending
           timeout. This prevents the delivery of a timeout exception
           (if any) in code that might be executing to cleanup from
           task cancellation.

01/03/2017 Added a TaskCancelled exception.  This is now what gets 
           raised when tasks are cancelled using the task.cancel()
           method.  It is a subclass of CancelledError.   This change 
	   makes CancelledError more of an abstract exception class
           for cancellation.  The TaskCancelled, TaskTimeout, and 
           TimeoutCancellationError exceptions are more specific
           subclasses that indicates exactly what has happened.

01/02/2017 Major reorganization of how task cancellation works. There
	   are two major parts to it.

	   Kernel:

           Every task has a boolean flag "task.allow_cancel" that
           determines whether or not cancellation exceptions (which
           includes cancellation and timeouts) can be raised in the
           task or not.  The flag acts as a simple mask. If set True,
           a cancellation results in an exception being raised in the
           task.  If set False, the cancellation-related exception is
           placed into "task.cancel_pending" instead.  That attribute
           holds onto the exception indefinitely, waiting for the task
           to reenable cancellations.  Once reenabled, the exception
           is raised immediately the next time the task performs a 
	   blocking operation.

	   Coroutines:

	   From coroutines, control of the cancellation flag is
	   performed by two functions which are used as context
	   managers:

	   To disable cancellation, use the following construct:

               async def coro():
                   async with disable_cancellation():
                       ...
                       await something1()
                       await something2()
                       ...

                   await blocking_op()   # Cancellation raised here (if any)
           
           Within a disable_cancellation() block, it is illegal for
           a CancelledError exception to be raised--even manually. Doing
           so causes a RuntimeError.  

	   To reenable cancellation in specific regions of code, use 
	   enable_cancellation() like this:

               async def coro():
                   async with disable_cancellation():
                       while True:
                           await something1()
                           await something2()
                           async with enable_cancellation() as c:
                               await blocking_op()

                           if c.cancel_pending:
                               # Cancellation is pending right now. Must bail out.
      			       break

                   await blocking_op()   # Cancellation raised here (if any)

           Use of enable_cancellation() is never allowed outside of an
           enclosing disable_cancellation() block.  Doing so will
           cause a RuntimeError exception. Within an
           enable_cancellation() block, all of the normal cancellation
           rules apply.  This includes raising of exceptions,
           timeouts, and so forth.  However, CancelledError exceptions
           will never escape the block.  Instead, they turn back into
           a pending exception which can be checked as shown above.

	   Normally cancellations are are only delivered on blocking 
           operations.   If you want to force a check, you can use
           check_cancellation() like this:

                if await check_cancellation():
                    # Cancellation is pending, but not allowed right now
                    ...

           Depending on the setting of the allow_cancel flag, 
           check_cancellation() will either raise the cancellation 
           exception immediately or report that it is pending.
           
12/27/2016 Modified timeout_after(None) so that it leaves any prior timeout
           setting in place (if any).  However, if a timeout occurs, it
           will appear as a TimeoutCancellationError instead of the usual
           TaskTimeout exception.  This is subtle, but it means that the
           timeout occurred to due to an outer timeout setting.   This
           change makes it easier to write functions that accept optional
           timeout settings.  For example:

              async def func(args, timeout=None):
                  try:
                      async with timeout_after(timeout):
                          statements
                          ...
                  except TaskTimeout as e:
                       # Timeout specifically due to timeout setting supplied
                       ...
                  except CancelledError as e:
                       # Function cancelled for some other reason
                       # (possibly an outer timeout)
                       ...
           
12/23/2016 Added further information to cancellation/timeout exceptions
           where partial I/O may have been performed. For readall() and
           read_exactly() methods, the bytes_read attribute contains
           all data read so far.  The readlines() method attaches a 
           lines_read attribute.  For write() and writelines(), a bytes_written
           attribute is added to the exception.   For example:

               try:
                  data = timeout_after(5, s.readall())
               except TimeoutError as e:
                  data = e.bytes_read     # Data received prior to timeout

           Here is a sending example:

               try:
                   timeout_after(5, s.write(data))
               except TimeoutError as e:
                   nwritten = e.bytes_written

           The primary purpose of these attributes is to allow more
           robust recovery in the event of cancellation. 

12/23/2016 The timeout arguments to subprocess related functions have been
           removed.  Use the curio timeout_after() function instead to deal
           with this case.  For example:

               try:
                   out = timeout_after(5, subprocess.check_output(args))
               except TaskTimeout as e:
                   # Get the partially read output
                   partial_stdout = e.stdout
                   partial_stderr = e.stderr
                   ... other recovery ...

           If there is an exception, the stdout and stderr
           attributes contain any partially read data on standard output
           and standard error.  These attributes mirror those present
           on the CalledProcessError exception raised if there is an error.

12/03/2016 Added a parentid attribute to Task instances so you can find parent
	   tasks.   Nothing else is done with this internally.

12/03/2016 Withdrew the pdb and crash_handler arguments to Kernel() and the
           run() function.  Added a pdb() method to tasks that can be used
	   to enter the debugger on a crashed task.  High-level handling
	   of crashed/terminated tasks is being rethought.   The old
	   crash_handler() callback was next to useless since no useful
	   actions could be performed (i.e., there was no ability to respawn
	   tasks or execute any kind of coroutine in response to a crash).

11/05/2016 Pulled time related functionality into the kernel as a new call.
           Use the following to get the current value of the kernel clock:
            
                await curio.clock()

           Timeout related functions such as timeout_after() and ignore_after()
           now rely on the kernel clock instead of using time.monotonic().
           This changes consolidates all use of the clock into one place
           and makes it easier (later) to reconfigure timing should it be
           desired.  For example, perhaps changing the scale of the clock
           to slow down or speed up time handling (for debugging, testing, etc.)

10/29/2016 If the sendall() method of a socket is aborted with a CancelledError,
           the resulting exception object now gets a bytes_sent attribute set to
           indicate how much progress was made.   For example:

           try:
               await sock.sendall(data)
           except CancelledError as e:
               print(e.bytes_sent, 'bytes sent')

10/29/2016 Added timeout_at() and ignore_at() functions that allow timeouts
           to be specified at absolute clock values.  The usage is the
           same as for timeout_after() and ignore_after().
           
10/29/2016 Modified TaskTimout exception so that it subclasses CancelledError.
           This makes it easier to write code that handles any kind of 
	   cancellation (explicit cancellation, cancellation by timeout, etc.)

10/17/2016 Added shutdown() method to sockets.  It is an async function
           to mirror async implementation of close()

           await sock.shutdown(how)

10/17/2016 Added writeable() method to sockets.  It can be used to
           quickly test if a socket will accept more data before
           doing a send().  See Issue #83.

           await sock.writeable()
           nsent = await sock.send(data)

10/17/2016 More precisely defined the semantics of nested timeouts
           and exception handling.  Consider the following arrangement
           of timeout blocks:

           # B1
           async with timeout_after(time1):
                # B2
                async with timeout_after(time2):
                    await coro()

           Here are the rules:

           1. If time2 expires before time1, then block B2 receives
              a TaskTimeout exception.

           2. If time1 expires before time2, then block B2 receives
              a TimeoutCancellationError exception and block B1
              receives a TaskTimeout exception.  This reflects the
              fact that the inner timeout didn't actually occur
              and thus it shouldn't be reported as such.  The inner
              block is still cancelled however in order to satisfy
              the outer timeout.

           3. If time2 expires before time1 and the resulting
              TaskTimeout is NOT caught, but allowed to propagate out
              to B1, then block B1 receives an UncaughtTimeoutError
              exception.  A block should never report a TaskTimeout
              unless its specified time interval has actually expired.
              Reporting a timeout early because of an uncaught 
              exception in an inner block should be considered to be
              an operational error. This exception reflects that.

           4. If time1 and time2 both expire simultaneously, the
              outer timeout takes precedence and time1 is considered
              to have expired first.

           See Issue #82 for further details about the rationale for
           this change. https://github.com/dabeaz/curio/issues/82
           
           
08/16/2016 Modified the Queue class so that the put() method can be used from either
           synchronous or asynchronous code.  For example:

              from curio import Queue
              queue = Queue()

              def spam():
                  # Create some item
                  ...
                  queue.put(item)

              async def consumer():
                  while True:
                       item = await queue.get()
                       # Consume the item
                       ...

              async def coro():
                    ...
                    spam()       # Note: Normal synchronous function call
                    ...

              async def main():
                  await spawn(coro())
                  await spawn(consumer())

              run(main())

           The main purpose of adding this is to make it easier for normal
           synchronous code to communicate to async tasks without knowing
           too much about what they are.  Note:  The put() method is never
           allowed to block in synchronous mode.  If the queue has a bounded
           size and it fills up, an exception is raised.

08/16/2016 Modified the Event class so that events can also be set from synchronous
           code.  For example:

               from curio import Event
               evt = Event()

               async def coro():
                   print('Waiting for something')
                   await evt.wait()
                   print('It happened')

               # A normal synchronous function. No async/await here.
               def spam():
                   print('About to signal')
                   evt.set()

               async def main():
                   await spawn(coro())
                   await sleep(5)
                   spam()         # Note: Normal synchronous function call

               run(main())

           The main motivation for adding this is that is very easy for
           control flow to escape the world of "async/await".  However,
           that code may still want to signal or coordinate with async
           tasks in some way.   By allowing a synchronous set(), it
           makes it possible to do this.    It should be noted that within
           a coroutine, you have to use await when triggering an event.
           For example:

               evt = Event()

               def foo():
                   evt.set()           # Synchronous use

               async def bar():
                   await evt.set()     # Asynchronous use

08/04/2016 Added a new KernelExit exception that can be used to 
           make the kernel terminate execution.  For example:

              async def coro():
                  ...
                  if something_bad:
                      raise KernelExit('Something bad')

           This causes the kernel to simply stop, aborting the
           currently executing task.   The exception will propagate
           out of the run() function so if you need to catch it, do
           this:

               try:
                   run(coro())
               except KernelExit as e:
                   print('Going away because of:', e)

           KernelExit by itself does not do anything to other 
	   running tasks.  However, the run() function will
           separately issue a shutdown request causing all
           remaining tasks to cancel.

08/04/2016 Added a new TaskExit exception that can be used to make a 
           single task terminate.  For example:

               async def coro():
                   ...
                   if something_bad:
                       raise TaskExit('Goodbye')
                   ...

           Think of TaskExit as a kind of self-cancellation. 

08/04/2016 Some refinements to kernel shutdown.   The shutdown process is
           more carefully supervised and fixes a few very subtle errors
           related to task scheduling. 

07/22/2016 Added support for asynchronous access to files as might be
           opened by the builtin open() function.  Use the new aopen()
           function with an async-context manager like this:

             async with aopen(filename, 'r') as f:
                 data = await f.read()

           Note: a file opened in this manner provides an asynchronous API
           that will prevent the Curio kernel from blocking on things
           like disk seeks.  However, the underlying implementation is
           not specified.  In the initial version, thread pools are
           used to carry out each I/O operation.
           
07/18/2016 Some changes to Kernel cleanup and resource management.  The
           proper way to shut down the kernel is to use Kernel.run(shutdown=True).
           Alternatively, the kernel can now been used as a context manager:

             with Kernel() as kern:
                  kern.run(coro())

           Note: The plain run() method properly shuts down the Kernel
           if you're only running a single coroutine.

           The Kernel.__del__() method now raises an exception if the
           kernel is deleted without being properly shut down. 

06/30/2016 Added alpn_protocols keyword argument to open_connection()
           function to make it easier to use TLS ALPN with clients.  For 
           example to open a connection and have it negotiate HTTP/2 
           or HTTP/1.1 as a protocol, you can do this:

           sock = await open_connection(host, port, ssl=True, 
                                        server_hostname=host,
                                        alpn_protocols=['h2', 'http/1.1'])

           print('selected protocol:', sock.selected_alpn_protocol())

06/30/2016 Changed internal clock handling to use absolute values of
           the monotonic clock.  New wakeat() function utilizes this
           to allow more controlled sleeping for periodic timers
           and other applications.  For example, here is a loop that
           precisely wakes up on a specified time interval:

           import time
           from curio import wakeat

           async def pulse(interval):
               next_wake = time.monotonic()
               while True:
                    await wake_at(next_wake)
                    print('Tick', time.asctime())
                    next_wake += interval
                
06/16/2016 Fixed Issue #55.  Exceptions occuring in code executed by 
           run_in_process() now include a RemoteTraceback exception 
           that shows the traceback from the remote process. This
           should make debugging a big easier. 

06/11/2016 Fixed Issue #53.  curio.run() was swallowing all exceptions.  It now
           reports a TaskError exception if the given coroutine fails.  This is
           a chained exception where __cause__ contains the actual cause of
           failure.   This is meant to be consistent with the join() method 
           of Tasks.

06/09/2016 Experimental new wait() function added.  It can be used to wait for
           more than one task at a time and to return them in completion order.
           For example:

           task1 = await spawn(coro())
           task2 = await spawn(coro())
           task3 = await spawn(coro())

           # Get results from all tasks as they complete
           async for task in wait([task1, task2, task3]):
               result = await task.join()

           # Get the first result and cancel remaining tasks
           async with wait([task1, task2, task3]) as w:
               task = await w.next_done()
               result = await task.join()
               # Other tasks cancelled here

06/09/2016 Refined the behavior of timeouts.  First, a timeout is not allowed
           to extend the time expiration of a previously set timeout. For
           example, if code previously set a 5 second timeout, an attempt
           to now set a 10 second timeout still results in a 5 second timeout.
           Second, when restoring a previous timeout, if the timeout period has
           expired, Curio arranges for a TaskTimeout exception to be raised on
           the next blocking call.   Without this, it's too easy for timeouts
           to disappear or not have any effect.   Setting a timeout of None
           disables timeouts regardless of any prior setting.

06/07/2016 Changed trap names (e.g., '_trap_io') to int enums. This is
           low-level change that shouldn't affect existing code.

05/23/2016 Fixed Issue #52 (Problem with ignore_after context manager).
           There was a possibility that a task would be marked for
           timeout at precisely the same time some other operation had
           completed and the task was sitting on the ready queue. To fix,
           the timeout is deferred and retried the next time the kernel
           blocks. 

05/20/2016 Added asyncobject class to curio/meta.py.  This allows you
           to write classes with an asynchronous __init__ method. For example:

           from curio.meta import asyncobject
           class Spam(asyncobject):
               async def __init__(self):
                   ...
                   self.value = await coro()
                   ...

           Instances can only be created via await.  For example:

              s = await Spam()

05/15/2016 Fixed Issue #50. Undefined variable n in io.py 
	   Reported by Wolfgang Langner

Version 0.4 : May 13, 2016
--------------------------
05/13/2016 Fixed a subtle bug with futures/cancellation.

Version 0.3 : May 13, 2016
--------------------------
05/13/2016 Bug fixes to the run_in_process() and run_in_thread() 
           functions so that exceptions are reported properly.
           Also fixed logic bug on related to kernel task initialization.

05/13/2016 Modification to the abide() function to allow it to work
           with RLocks from the threading module.  One caveat: Such
	   locks are NOT reentrant from within curio itself. 

Version 0.2 : May 11, 2016
--------------------------
05/05/2016 Refactoring of stream I/O classes. There is now FileStream
           and SocketStream.   The old Stream class is gone.

04/30/2016 The run_blocking() and run_cpu_bound() calls are now
           called run_in_thread() and run_in_process().

04/23/2016 Changed the new_task() function to spawn().

04/22/2016 Removed parent/child task relationship and associated
           tracking.  It's an added complexity that's not really
	   needed in the kernel and it can be done easily enough by
	   the user in cases where it might be needed.

04/18/2016 Major refactoring of timeout handling.  Virtually all
           operations in curio support cancellation and timeouts.
           However, putting an explicit "timeout" argument on
           every API function/method greatly complicates the 
           underlying implementation (and introduces performance
           overhead in cases where timeouts aren't used). To
           put a timeout on an operation, use the timeout_after()
           function instead.  For example:

               await timeout_after(5, sock.recv(1024))

           This will cause a timeout to be raised after the
           specified time interval.  

04/01/2016 Improved management of the I/O selector.  The number of
           register/unregister operations are reduced for tasks 
           that constantly perform I/O on the same resources.  This
           could offer a nice performance boost in certain cases.

03/31/2016 Switched test suite to py.test. All of the tests are in the
           top-level tests directory.  Use 'python3 -m pytest' to test.

03/30/2016 Improved the curio monitor.  Instead of relying on the
           console TTY (and invoked via Ctrl-C), it now uses a socket
           to which you must connect via a different session. To
           enable the monitor either use:

               kernel = Kernel(with_monitor=True)

           or run with an environment variable

               env CURIOMONITOR=TRUE python3 yourprogram.py

           To connect to the monitor, use the following command:

               python3 -m curio.monitor
          
02/15/2016 Fixed Issue #37 where scheduling multiple tasks for sleeping
           could potentially cause a crash in rare circumstances.

Version 0.1 : October 31, 2015
------------------------------
Initial version