openstack/deb-python-eventlet
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dagpool: improved documentation

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nat-goodspeed
2016-09-28 13:22:21 -04:00
committed by Sergey Shepelev
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doc/modules/dagpool.rst
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@@ -1,6 +1,493 @@
:mod:`dagpool` -- Dependency-Driven Greenthreads
================================================
Rationale
*********
The dagpool module provides the :class:`DAGPool <eventlet.dagpool.DAGPool>`
class, which addresses situations in which the value produced by one
greenthread might be consumed by several others -- while at the same time a
consuming greenthread might depend on the output from several different
greenthreads.
If you have a tree with strict many-to-one dependencies -- each producer
greenthread provides results to exactly one consumer, though a given consumer
may depend on multiple producers -- that could be addressed by recursively
constructing a :class:`GreenPool <eventlet.greenpool.GreenPool>` of producers
for each consumer, then :meth:`waiting <eventlet.greenpool.GreenPool.waitall>`
for all producers.
If you have a tree with strict one-to-many dependencies -- each consumer
greenthread depends on exactly one producer, though a given producer may
provide results to multiple consumers -- that could be addressed by causing
each producer to finish by launching a :class:`GreenPool
<eventlet.greenpool.GreenPool>` of consumers.
But when you have many-to-many dependencies, a tree doesn't suffice. This is
known as a
`Directed Acyclic Graph <https://en.wikipedia.org/wiki/Directed_acyclic_graph>`_,
or DAG.
You might consider sorting the greenthreads into dependency order
(`topological sort <https://en.wikipedia.org/wiki/Topological_sorting>`_) and
launching them in a GreenPool. But the concurrency of the GreenPool must be
strictly constrained to ensure that no greenthread is launched before all its
upstream producers have completed -- and the appropriate pool size is
data-dependent. Only a pool of size 1 (serializing all the greenthreads)
guarantees that a topological sort will produce correct results.
Even if you do serialize all the greenthreads, how do you pass results from
each producer to all its consumers, which might start at very different points
in time?
One answer is to associate each greenthread with a distinct key, and store its
result in a common dict. Then each consumer greenthread can identify its
direct upstream producers by their keys, and find their results in that dict.
This is the essence of DAGPool.
A DAGPool instance owns a dict, and stores greenthread results in that dict.
You :meth:`spawn <eventlet.dagpool.DAGPool.spawn>` *all* greenthreads in the
DAG, specifying for each its own key -- the key with which its result will be
stored on completion -- plus the keys of the upstream producer greenthreads on
whose results it directly depends.
Keys need only be unique within the DAGPool instance; they need not be UUIDs.
A key can be any type that can be used as a dict key. String keys make it
easier to reason about a DAGPool's behavior, but are by no means required.
The DAGPool passes to each greenthread an iterable of (key, value) pairs.
The key in each pair is the key of one of the greenthread's specified upstream
producers; the value is the value returned by that producer greenthread. Pairs
are delivered in the order results become available; the consuming greenthread
blocks until the next result can be delivered.
Tutorial
*******
Example
-------
Consider a couple of programs in some compiled language that depend on a set
of precompiled libraries. Suppose every such build requires as input the
specific set of library builds on which it directly depends.
::
a zlib
| / |
|/ |
b c
| /|
| / |
| / |
|/ |
d e
We can't run the build for program d until we have the build results for both
b and c. We can't run the build for library b until we have build results for
a and zlib. We can, however, immediately run the builds for a and zlib.
So we can use a DAGPool instance to spawn greenthreads running a function such
as this:
::
def builder(key, upstream):
for libname, product in upstream:
# ... configure build for 'key' to use 'product' for 'libname'
# all upstream builds have completed
# ... run build for 'key'
return build_product_for_key
:meth:`spawn <eventlet.dagpool.DAGPool.spawn>` all these greenthreads:
::
pool = DAGPool()
# the upstream producer keys passed to spawn() can be from any iterable,
# including a generator
pool.spawn("d", ("b", "c"), builder)
pool.spawn("e", ["c"], builder)
pool.spawn("b", ("a", "zlib"), builder)
pool.spawn("c", ["zlib"], builder)
pool.spawn("a", (), builder)
As with :func:`eventlet.spawn() <eventlet.spawn>`, if you need to pass special
build flags to some set of builds, these can be passed as either positional or
keyword arguments:
::
def builder(key, upstream, cflags="", linkflags=""):
...
pool.spawn("d", ("b", "c"), builder, "-o2")
pool.spawn("e", ["c"], builder, linkflags="-pie")
However, if the arguments to each builder() call are uniform (as in the
original example), you could alternatively build a dict of the dependencies
and call :meth:`spawn_many() <eventlet.dagpool.DAGPool.spawn_many>`:
::
deps = dict(d=("b", "c"),
e=["c"],
b=("a", "zlib"),
c=["zlib"],
a=())
pool.spawn_many(deps, builder)
From outside the DAGPool, you can obtain the results for d and e (or in fact
for any of the build greenthreads) in any of several ways.
:meth:`pool.waitall() <eventlet.dagpool.DAGPool.waitall>` waits until the last of the spawned
greenthreads has completed, and returns a dict containing results for *all* of
them:
::
final = pool.waitall()
print("for d: {0}".format(final["d"]))
print("for e: {0}".format(final["e"]))
waitall() is an alias for :meth:`wait() <eventlet.dagpool.DAGPool.wait>` with no arguments:
::
final = pool.wait()
print("for d: {0}".format(final["d"]))
print("for e: {0}".format(final["e"]))
Or you can specifically wait for only the final programs:
::
final = pool.wait(["d", "e"])
The returned dict will contain only the specified keys. The keys may be passed
into wait() from any iterable, including a generator.
You can wait for any specified set of greenthreads; they need not be
topologically last:
::
# returns as soon as both a and zlib have returned results, regardless of
# what else is still running
leaves = pool.wait(["a", "zlib"])
Suppose you want to wait specifically for just *one* of the final programs:
::
final = pool.wait(["d"])
dprog = final["d"]
The above wait() call will return as soon as greenthread d returns a result --
regardless of whether greenthread e has finished.
:meth:`__getitem()__ <eventlet.dagpool.DAGPool.__getitem__>` is shorthand for
obtaining a single result:
::
# waits until greenthread d returns its result
dprog = pool["d"]
In contrast, :meth:`get() <eventlet.dagpool.DAGPool.get>` returns immediately,
whether or not a result is ready:
::
# returns immediately
if pool.get("d") is None:
...
Of course, your greenthread might not include an explicit return statement and
hence might implicitly return None. You might have to test some other value.
::
# returns immediately
if pool.get("d", "notdone") == "notdone":
...
Suppose you want to process each of the final programs in some way (upload
it?), but you don't want to have to wait until they've both finished. You
don't have to poll get() calls -- use :meth:`wait_each()
<eventlet.dagpool.DAGPool.wait_each>`:
::
for key, result in pool.wait_each(["d", "e"]):
# key will be d or e, in completion order
# process result...
As with :meth:`wait() <eventlet.dagpool.DAGPool.wait>`, if you omit the
argument to wait_each(), it delivers results for all the greenthreads of which
it's aware:
::
for key, result in pool.wait_each():
# key will be a, zlib, b, c, d, e, in whatever order each completes
# process its result...
Introspection
-------------
Let's say you have set up a :class:`DAGPool <eventlet.dagpool.DAGPool>` with
the dependencies shown above. To your consternation, your :meth:`waitall()
<eventlet.dagpool.DAGPool.waitall>` call does not return! The DAGPool instance
is stuck!
You could change waitall() to :meth:`wait_each()
<eventlet.dagpool.DAGPool.wait_each>`, and print each key as it becomes
available:
::
for key, result in pool.wait_each():
print("got result for {0}".format(key))
# ... process ...
Once the build for a has completed, this produces:
::
got result for a
and then stops. Hmm!
You can check the number of :meth:`running <eventlet.dagpool.DAGPool.running>`
greenthreads:
::
>>> print(pool.running())
4
and the number of :meth:`waiting <eventlet.dagpool.DAGPool.waiting>`
greenthreads:
::
>>> print(pool.waiting())
4
It's often more informative to ask *which* greenthreads are :meth:`still
running <eventlet.dagpool.DAGPool.running_keys>`:
::
>>> print(pool.running_keys())
('c', 'b', 'e', 'd')
but in this case, we already know a has completed.
We can ask for all available results:
::
>>> print(pool.keys())
('a',)
>>> print(pool.items())
(('a', result_from_a),)
The :meth:`keys() <eventlet.dagpool.DAGPool.keys>` and :meth:`items()
<eventlet.dagpool.DAGPool.items>` methods only return keys and items for
which results are actually available, reflecting the underlying dict.
But what's blocking the works? What are we :meth:`waiting for
<eventlet.dagpool.DAGPool.waiting_for>`?
::
>>> print(pool.waiting_for("d"))
set(['c', 'b'])
(waiting_for()'s optional argument is a *single* key.)
That doesn't help much yet...
::
>>> print(pool.waiting_for("b"))
set(['zlib'])
>>> print(pool.waiting_for("zlib"))
KeyError: 'zlib'
Aha! We forgot to even include the zlib build when we were originally
configuring this DAGPool!
(For non-interactive use, it would be more informative to omit waiting_for()'s
argument. This usage returns a dict indicating, for each greenthread key,
which other keys it's waiting for.)
::
from pprint import pprint
pprint(pool.waiting_for())
{'b': set(['zlib']), 'c': set(['zlib']), 'd': set(['b', 'c']), 'e': set(['c'])}
In this case, a reasonable fix would be to spawn the zlib greenthread:
::
pool.spawn("zlib", (), builder)
Even if this is the last method call on this DAGPool instance, it should
unblock all the rest of the DAGPool greenthreads.
Posting
-------
If we happen to have zlib build results in hand already, though, we could
instead :meth:`post() <eventlet.dagpool.DAGPool.post>` that result instead of
rebuilding the library:
::
pool.post("zlib", result_from_zlib)
This, too, should unblock the rest of the DAGPool greenthreads.
Preloading
----------
If rebuilding takes nontrivial realtime, it might be useful to record partial
results, so that in case of interruption you can restart from where you left
off rather than having to rebuild everything prior to that point.
You could iteratively :meth:`post() <eventlet.dagpool.DAGPool.post>` those
prior results into a new DAGPool instance; alternatively you can
:meth:`preload <eventlet.dagpool.DAGPool.__init__>` the :class:`DAGPool
<eventlet.dagpool.DAGPool>` from an existing dict:
::
pool = DAGPool(dict(a=result_from_a, zlib=result_from_zlib))
Any DAGPool greenthreads that depend on either a or zlib can immediately
consume those results.
It also works to construct DAGPool with an iterable of (key, result) pairs.
Exception Propagation
---------------------
But what if we spawn a zlib build that fails? Suppose the zlib greenthread
terminates with an exception? In that case none of b, c, d or e can proceed!
Nor do we want to wait forever for them.
::
dprog = pool["d"]
eventlet.dagpool.PropagateError: PropagateError(d): PropagateError: PropagateError(c): PropagateError: PropagateError(zlib): OriginalError
DAGPool provides a :class:`PropagateError <eventlet.dagpool.PropagateError>`
exception specifically to wrap such failures. If a DAGPool greenthread
terminates with an Exception subclass, the DAGPool wraps that exception in a
PropagateError instance whose *key* attribute is the key of the failing
greenthread and whose *exc* attribute is the exception that terminated it.
This PropagateError is stored as the result from that greenthread.
Attempting to consume the result from a greenthread for which a PropagateError
was stored raises that PropagateError.
::
pool["zlib"]
eventlet.dagpool.PropagateError: PropagateError(zlib): OriginalError
Thus, when greenthread c attempts to consume the result from zlib, the
PropagateError for zlib is raised. Unless the builder function for greenthread
c handles that PropagateError exception, that greenthread will itself
terminate. That PropagateError will be wrapped in another PropagateError whose
*key* attribute is c and whose *exc* attribute is the PropagateError for zlib.
Similarly, when greenthread d attempts to consume the result from c, the
PropagateError for c is raised. This in turn is wrapped in a PropagateError
whose *key* is d and whose *exc* is the PropagateError for c.
When someone attempts to consume the result from d, as shown above, the
PropagateError for d is raised.
You can programmatically chase the failure path to determine the original
failure if desired:
::
orig_err = err
key = "unknown"
while isinstance(orig_err, PropagateError):
key = orig_err.key
orig_err = orig_err.exc
Scanning for Success / Exceptions
---------------------------------
Exception propagation means that we neither perform useless builds nor wait for
results that will never arrive.
However, it does make it difficult to obtain *partial* results for builds that
*did* succeed.
For that you can call :meth:`wait_each_success()
<eventlet.dagpool.DAGPool.wait_each_success>`:
::
for key, result in pool.wait_each_success():
print("{0} succeeded".format(key))
# ... process result ...
a succeeded
Another problem is that although five different greenthreads failed in the
example, we only see one chain of failures. You can enumerate the bad news
with :meth:`wait_each_exception() <eventlet.dagpool.DAGPool.wait_each_exception>`:
::
for key, err in pool.wait_each_exception():
print("{0} failed with {1}".format(key, err.exc.__class__.__name__))
c failed with PropagateError
b failed with PropagateError
e failed with PropagateError
d failed with PropagateError
zlib failed with OriginalError
wait_each_exception() yields each PropagateError wrapper as if it were the
result, rather than raising it as an exception.
Notice that we print :code:`err.exc.__class__.__name__` because
:code:`err.__class__.__name__` is always PropagateError.
Both wait_each_success() and wait_each_exception() can accept an iterable of
keys to report:
::
for key, result in pool.wait_each_success(["d", "e"]):
print("{0} succeeded".format(key))
(no output)
for key, err in pool.wait_each_exception(["d", "e"]):
print("{0} failed with {1}".format(key, err.exc.__class__.__name__))
e failed with PropagateError
d failed with PropagateError
Both wait_each_success() and wait_each_exception() must wait until the
greenthreads for all specified keys (or all keys) have terminated, one way or
the other, because of course we can't know until then how to categorize each.
Module Contents
===============
.. automodule:: eventlet.dagpool
:members:

245
eventlet/dagpool.py
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@@ -1,9 +1,7 @@
"""\
@file dagpool.py
@author Nat Goodspeed
@date 2016-08-08
@brief Provide DAGPool class
"""
# @file dagpool.py
# @author Nat Goodspeed
# @date 2016-08-08
# @brief Provide DAGPool class
from eventlet.event import Event
from eventlet import greenthread
@@ -32,8 +30,12 @@ class PropagateError(Exception):
PropagateError.
Attributes:
key: the key of the greenthread which raised the exception
exc: the exception object raised by the greenthread
key
the key of the greenthread which raised the exception
exc
the exception object raised by the greenthread
"""
def __init__(self, key, exc):
self.key = key
@@ -51,9 +53,10 @@ class DAGPool(object):
This is a way to implement general DAG dependencies. A simple dependency
tree (flowing in either direction) can straightforwardly be implemented
using recursion and (e.g.) GreenThread.imap(). What gets complicated is
when a given node depends on several other nodes as well as contributing
to several other nodes.
using recursion and (e.g.)
:meth:`GreenThread.imap() <eventlet.greenthread.GreenThread.imap>`.
What gets complicated is when a given node depends on several other nodes
as well as contributing to several other nodes.
With DAGPool, you concurrently launch all applicable greenthreads; each
will proceed as soon as it has all required inputs. The DAG is implicit in
@@ -65,34 +68,41 @@ class DAGPool(object):
The greenthread callable must accept (key, results), where:
key is its own key
results is an iterable of (key, value) pairs.
key
is its own key
results
is an iterable of (key, value) pairs.
A newly-launched DAGPool greenthread is entered immediately, and can
perform any necessary setup work. At some point it will iterate over the
(key, value) pairs from the passed 'results' iterable. Doing so blocks the
greenthread until a value is available for each of the keys specified in
its initial dependencies iterable. These (key, value) pairs are delivered
in chronological order, NOT the order in which they are initially
in chronological order, *not* the order in which they are initially
specified: each value will be delivered as soon as it becomes available.
The value returned by a DAGPool greenthread becomes the value for its
key, which unblocks any other greenthreads waiting on that key.
If a DAGPool greenthread terminates with an exception instead of returning
a value, attempting to retrieve the value raises PropagateError, which
binds the key of the original greenthread and the original exception.
Unless the greenthread attempting to retrieve the value handles
a value, attempting to retrieve the value raises :class:`PropagateError`,
which binds the key of the original greenthread and the original
exception. Unless the greenthread attempting to retrieve the value handles
PropagateError, that exception will in turn be wrapped in a PropagateError
of its own, and so forth. The code that ultimately handles PropagateError
can follow the chain of PropagateError.exc attributes to discover the flow
of that exception through the DAG of greenthreads.
External greenthreads may also interact with a DAGPool. See wait_each(),
waitall(), post().
External greenthreads may also interact with a DAGPool. See :meth:`wait_each`,
:meth:`waitall`, :meth:`post`.
It is not recommended to constrain external DAGPool producer greenthreads
in a GreenPool: it may be hard to provably avoid deadlock.
in a :class:`GreenPool <eventlet.greenpool.GreenPool>`: it may be hard to
provably avoid deadlock.
.. automethod:: __init__
.. automethod:: __getitem__
"""
_Coro = collections.namedtuple("_Coro", ("greenthread", "pending"))
@@ -123,47 +133,47 @@ class DAGPool(object):
def waitall(self):
"""
waitall() blocks the calling greenthread until there is a value for
every DAGPool greenthread launched by spawn(). It returns a dict
containing all preload data, all data from post() and all values
returned by spawned greenthreads.
every DAGPool greenthread launched by :meth:`spawn`. It returns a dict
containing all :class:`preload data <DAGPool>`, all data from
:meth:`post` and all values returned by spawned greenthreads.
See also wait().
See also :meth:`wait`.
"""
# waitall() is an alias for compatibility with GreenPool
return self.wait()
def wait(self, keys=_MISSING):
"""
keys is an optional iterable of keys. If you omit the argument, it
waits for all the keys from preload data, from post() calls and from
spawn() calls: in other words, all the keys of which this DAGPool is
aware.
*keys* is an optional iterable of keys. If you omit the argument, it
waits for all the keys from :class:`preload data <DAGPool>`, from
:meth:`post` calls and from :meth:`spawn` calls: in other words, all
the keys of which this DAGPool is aware.
wait() blocks the calling greenthread until all of the relevant keys
have values. wait() returns a dict whose keys are the relevant keys,
and whose values come from the preload data, from values returned by
DAGPool greenthreads or from post() calls.
and whose values come from the *preload* data, from values returned by
DAGPool greenthreads or from :meth:`post` calls.
If a greenthread terminates with an exception, wait() will raise
PropagateError wrapping that exception. If more than one greenthread
terminates with an exception, it is indeterminate which one wait()
will raise.
If a DAGPool greenthread terminates with an exception, wait() will
raise :class:`PropagateError` wrapping that exception. If more than
one greenthread terminates with an exception, it is indeterminate
which one wait() will raise.
If a greenthread posts a PropagateError instance, wait() will raise
that PropagateError. If more than one greenthread posts
PropagateError, it is indeterminate which one wait() will raise.
If an external greenthread posts a :class:`PropagateError` instance,
wait() will raise that PropagateError. If more than one greenthread
posts PropagateError, it is indeterminate which one wait() will raise.
See also wait_each_success(), wait_each_exception().
See also :meth:`wait_each_success`, :meth:`wait_each_exception`.
"""
# This is mostly redundant with wait_each() functionality.
return dict(self.wait_each(keys))
def wait_each(self, keys=_MISSING):
"""
keys is an optional iterable of keys. If you omit the argument, it
waits for all the keys from preload data, from post() calls and from
spawn() calls: in other words, all the keys of which this DAGPool is
aware.
*keys* is an optional iterable of keys. If you omit the argument, it
waits for all the keys from :class:`preload data <DAGPool>`, from
:meth:`post` calls and from :meth:`spawn` calls: in other words, all
the keys of which this DAGPool is aware.
wait_each() is a generator producing (key, value) pairs as a value
becomes available for each requested key. wait_each() blocks the
@@ -177,11 +187,13 @@ class DAGPool(object):
each of the ready ones in arbitrary order before blocking again.
The DAGPool does not distinguish between a value returned by one of
its own greenthreads and one provided by a post() call or preload data.
its own greenthreads and one provided by a :meth:`post` call or *preload* data.
The wait_each() generator terminates (raises StopIteration) when all
specified keys have been delivered. Thus, typical usage might be:
::
for key, value in dagpool.wait_each(keys):
# process this ready key and value
# continue processing now that we've gotten values for all keys
@@ -189,10 +201,10 @@ class DAGPool(object):
By implication, if you pass wait_each() an empty iterable of keys, it
returns immediately without yielding anything.
If the value to be delivered is a PropagateError exception object, the
If the value to be delivered is a :class:`PropagateError` exception object, the
generator raises that PropagateError instead of yielding it.
See also wait_each_success(), wait_each_exception().
See also :meth:`wait_each_success`, :meth:`wait_each_exception`.
"""
# Build a local set() and then call _wait_each().
return self._wait_each(self._get_keyset_for_wait_each(keys))
@@ -200,12 +212,12 @@ class DAGPool(object):
def wait_each_success(self, keys=_MISSING):
"""
wait_each_success() filters results so that only success values are
yielded. In other words, unlike wait_each(), wait_each_success() will
not raise PropagateError. Not every provided (or defaulted) key will
necessarily be represented, though naturally the generator must wait
until all have completed.
yielded. In other words, unlike :meth:`wait_each`, wait_each_success()
will not raise :class:`PropagateError`. Not every provided (or
defaulted) key will necessarily be represented, though naturally the
generator will not finish until all have completed.
In all other respects, wait_each_success() behaves like wait_each().
In all other respects, wait_each_success() behaves like :meth:`wait_each`.
"""
for key, value in self._wait_each_raw(self._get_keyset_for_wait_each(keys)):
if not isinstance(value, PropagateError):
@@ -215,13 +227,13 @@ class DAGPool(object):
"""
wait_each_exception() filters results so that only exceptions are
yielded. Not every provided (or defaulted) key will necessarily be
represented, though naturally the generator must wait until all have
completed.
represented, though naturally the generator will not finish until
all have completed.
Unlike other DAGPool methods, wait_each_exception() simply yields
PropagateError instances as values rather than raising them.
:class:`PropagateError` instances as values rather than raising them.
In all other respects, wait_each_exception() behaves like wait_each().
In all other respects, wait_each_exception() behaves like :meth:`wait_each`.
"""
for key, value in self._wait_each_raw(self._get_keyset_for_wait_each(keys)):
if isinstance(value, PropagateError):
@@ -289,31 +301,32 @@ class DAGPool(object):
def spawn(self, key, depends, function, *args, **kwds):
"""
Launch the passed function(key, results, ...) as a greenthread,
Launch the passed *function(key, results, ...)* as a greenthread,
passing it:
- the specified 'key'
- the specified *key*
- an iterable of (key, value) pairs
- whatever other positional args or keywords you specify.
Iterating over the 'results' iterable behaves like calling
wait_each(depends).
Iterating over the *results* iterable behaves like calling
:meth:`wait_each(depends) <DAGPool.wait_each>`.
Returning from function() behaves like post(key, return_value).
Returning from *function()* behaves like
:meth:`post(key, return_value) <DAGPool.post>`.
If function() terminates with an exception, that exception is wrapped
in PropagateError with the greenthread's key and (effectively) posted
If *function()* terminates with an exception, that exception is wrapped
in :class:`PropagateError` with the greenthread's *key* and (effectively) posted
as the value for that key. Attempting to retrieve that value will
raise that PropagateError.
Thus, if the greenthread with key 'a' terminates with an exception,
and greenthread 'b' depends on 'a', when greenthread 'b' attempts to
iterate through its 'results' argument, it will encounter
iterate through its *results* argument, it will encounter
PropagateError. So by default, an uncaught exception will propagate
through all the downstream dependencies.
If you pass spawn() a key already passed to spawn() or post(), spawn()
raises Collision.
If you pass :meth:`spawn` a key already passed to spawn() or :meth:`post`, spawn()
raises :class:`Collision`.
"""
if key in self.coros or key in self.values:
raise Collision(key)
@@ -359,12 +372,18 @@ class DAGPool(object):
def spawn_many(self, depends, function, *args, **kwds):
"""
spawn_many() accepts a single function whose parameters are the same
as for spawn().
spawn_many() accepts a single *function* whose parameters are the same
as for :meth:`spawn`.
The difference is that spawn_many() accepts a dependency dict. A new
greenthread is spawned for each key in the dict. That dict key's value
should be an iterable of other keys on which this greenthread depends.
The difference is that spawn_many() accepts a dependency dict
*depends*. A new greenthread is spawned for each key in the dict. That
dict key's value should be an iterable of other keys on which this
greenthread depends.
If the *depends* dict contains any key already passed to :meth:`spawn`
or :meth:`post`, spawn_many() raises :class:`Collision`. It is
indeterminate how many of the other keys in *depends* will have
successfully spawned greenthreads.
"""
# Iterate over 'depends' items, relying on self.spawn() not to
# context-switch so no one can modify 'depends' along the way.
@@ -373,7 +392,7 @@ class DAGPool(object):
def kill(self, key):
"""
Kill the greenthread that was spawned with the specified 'key'.
Kill the greenthread that was spawned with the specified *key*.
If no such greenthread was spawned, raise KeyError.
"""
@@ -384,25 +403,26 @@ class DAGPool(object):
def post(self, key, value, replace=False):
"""
post(key, value) stores the passed value for the passed key. It then
causes each greenthread blocked on its results iterable, or on
wait_each(keys), to check for new values. A waiting greenthread might
not literally resume on every single post() of a relevant key, but the
first post() of a relevant key ensures that it will resume eventually,
and when it does it will catch up with all relevant post() calls.
post(key, value) stores the passed *value* for the passed *key*. It
then causes each greenthread blocked on its results iterable, or on
:meth:`wait_each(keys) <DAGPool.wait_each>`, to check for new values.
A waiting greenthread might not literally resume on every single
post() of a relevant key, but the first post() of a relevant key
ensures that it will resume eventually, and when it does it will catch
up with all relevant post() calls.
Calling post(key, value) when there is a running greenthread with that
same 'key' raises Collision. If you must post(key, value) instead of
same *key* raises :class:`Collision`. If you must post(key, value) instead of
letting the greenthread run to completion, you must first call
kill(key).
:meth:`kill(key) <DAGPool.kill>`.
The DAGPool implicitly post()s the return value from each of its
greenthreads. But a greenthread may explicitly post() a value for its
own key, which will cause its return value to be discarded.
Calling post(key, value, replace=False) (the default 'replace') when a
Calling post(key, value, replace=False) (the default *replace*) when a
value for that key has already been posted, by any means, raises
Collision.
:class:`Collision`.
Calling post(key, value, replace=True) when a value for that key has
already been posted, by any means, replaces the previously-stored
@@ -410,13 +430,14 @@ class DAGPool(object):
behavior of greenthreads waiting on that key.
After a post(key, value1) followed by post(key, value2, replace=True),
it is unspecified which pending wait_each([key...]) calls (or
greenthreads iterating over 'results' involving that key) will observe
value1 versus value2. It is guaranteed that subsequent
wait_each([key...]) calls (or greenthreads spawned after that point)
will observe value2.
it is unspecified which pending :meth:`wait_each([key...]) <DAGPool.wait_each>`
calls (or greenthreads iterating over *results* involving that key)
will observe *value1* versus *value2*. It is guaranteed that
subsequent wait_each([key...]) calls (or greenthreads spawned after
that point) will observe *value2*.
A successful call to post(key, PropagateError(key, ExceptionSubclass))
A successful call to
post(key, :class:`PropagateError(key, ExceptionSubclass) <PropagateError>`)
ensures that any subsequent attempt to retrieve that key's value will
raise that PropagateError instance.
"""
@@ -452,7 +473,7 @@ class DAGPool(object):
def __getitem__(self, key):
"""
__getitem__(key) (aka dagpool[key]) blocks until 'key' has a value,
__getitem__(key) (aka dagpool[key]) blocks until *key* has a value,
then delivers that value.
"""
# This is a degenerate case of wait_each(). Construct a tuple
@@ -463,41 +484,41 @@ class DAGPool(object):
def get(self, key, default=None):
"""
get() returns the value for 'key'. If 'key' does not yet have a value,
get() returns 'default'.
get() returns the value for *key*. If *key* does not yet have a value,
get() returns *default*.
"""
return self._value_or_raise(self.values.get(key, default))
def keys(self):
"""
Return a tuple of keys for which we currently have values. Explicitly
return a copy rather than an iterator: don't assume our caller will
finish iterating before new values are posted.
Return a snapshot tuple of keys for which we currently have values.
"""
# Explicitly return a copy rather than an iterator: don't assume our
# caller will finish iterating before new values are posted.
return tuple(six.iterkeys(self.values))
def items(self):
"""
Return a snapshot tuple of currently-available (key, value) pairs.
Don't assume our caller will finish iterating before new values are
posted.
"""
# Don't assume our caller will finish iterating before new values are
# posted.
return tuple((key, self._value_or_raise(value))
for key, value in six.iteritems(self.values))
def running(self):
"""
Return number of running greenthreads. This includes greenthreads
blocked while iterating through their 'results' iterable, that is,
greenthreads waiting on values from other keys.
Return number of running DAGPool greenthreads. This includes
greenthreads blocked while iterating through their *results* iterable,
that is, greenthreads waiting on values from other keys.
"""
return len(self.coros)
def running_keys(self):
"""
Return keys for running greenthreads. This includes greenthreads
blocked while iterating through their 'results' iterable, that is,
greenthreads waiting on values from other keys.
Return keys for running DAGPool greenthreads. This includes
greenthreads blocked while iterating through their *results* iterable,
that is, greenthreads waiting on values from other keys.
"""
# return snapshot; don't assume caller will finish iterating before we
# next modify self.coros
@@ -505,9 +526,10 @@ class DAGPool(object):
def waiting(self):
"""
Return number of waiting greenthreads, that is, greenthreads still
waiting on values from other keys. This explicitly does NOT include
external greenthreads waiting on wait(), waitall(), wait_each().
Return number of waiting DAGPool greenthreads, that is, greenthreads
still waiting on values from other keys. This explicitly does *not*
include external greenthreads waiting on :meth:`wait`,
:meth:`waitall`, :meth:`wait_each`.
"""
# n.b. if Event would provide a count of its waiters, we could say
# something about external greenthreads as well.
@@ -519,18 +541,19 @@ class DAGPool(object):
# None as a supported key.
def waiting_for(self, key=_MISSING):
"""
waiting_for(key) returns a set() of the keys for which the greenthread
spawned with that key is still waiting. If you pass a key for which no
greenthread was spawned, waiting_for() raises KeyError.
waiting_for(key) returns a set() of the keys for which the DAGPool
greenthread spawned with that *key* is still waiting. If you pass a
*key* for which no greenthread was spawned, waiting_for() raises
KeyError.
waiting_for() without argument returns a dict. Its keys are the keys
of greenthreads still waiting on one or more values. In the returned
dict, the value of each such key is the set of other keys for which
that greenthread is still waiting.
of DAGPool greenthreads still waiting on one or more values. In the
returned dict, the value of each such key is the set of other keys for
which that greenthread is still waiting.
This method allows diagnosing a 'hung' DAGPool. If certain
This method allows diagnosing a "hung" DAGPool. If certain
greenthreads are making no progress, it's possible that they are
waiting on keys for which there is no greenthread and no post() data.
waiting on keys for which there is no greenthread and no :meth:`post` data.
"""
# We may have greenthreads whose 'pending' entry indicates they're
# waiting on some keys even though values have now been posted for