This allows the implementer of the GAPI to specify three parameters for
every Next message sent on the channel. The Fast parameter tells the
agent if it should do the pause quickly or if it should finish the
sequence. A quick pause means that it will cause a pause immediately
after the currently running resources finish, where as a slow (default)
pause will allow the wave of execution to finish. This is usually
preferred in scenarios where complex graphs are used where we want each
step to complete. The Exit parameter tells the engine to exit, and the
Err parameter tells the engine that an error occurred.
Since the pgraph graph can store arbitrary pointers, we don't need a
special method to create the vertices or edges as long as they implement
the String() string method. This cleans up the library and some of the
examples which I let rot previously.
The graph of dependencies in golang is a DAG, and as such doesn't allow
cycles. Clean up this lib so that it eventually doesn't import our
resources module or anything else which might want to import it.
This patch makes adjacency private, and adds a generalized key store to
the graph struct.
This puts the generation of the initial event into the Next method of
the GAPI. If it does not happen, then we will never get a graph. This is
important because this notifies the GAPI when we're actually ready to
try and generate a graph, rather than blocking on the Graph method if we
have a long compile for example.
This is also required for the etcd watch cleanup.
There was a race condition that would sometimes occur in that if we
stopped reading from the gapiChan (on shutdown) but then a new message
was available before we managed to close the GAPI, then we would wait
forever to finish the close because the channel never sent, and the
WaitGroup wouldn't let us exit.
This fixes this horrible, horrible race.
This is the initial base of what will hopefully become a powerful API
that machines will use to communicate. It will be the basis of the
stateful data store that can be used for exported resources, fact
exchange, state machine flags, locks, and much more.
This polishes the password resource so that it can actually avoid
writing the password to disk, and so that the work actually happens in
CheckApply where it can properly interact with the graph. This resource
now re-generates the password when it receives a notification.
The send/recv plumbing has been extended so that receivers can detect
when they're receiving new values. This is particularly important if
they might otherwise not expect those values to change and cache them
for efficiency purposes.
Resources can send "refresh" notifications along edges. These messages
are sent whenever the upstream (initiating vertex) changes state. When
the changed state propagates downstream, it will be paired with a
refresh flag which can be queried in the CheckApply method of that
resource.
Future work will include a stateful refresh tracking mechanism so that
if a refresh event is generated and not consumed, it will be saved
across an interrupt (shutdown) or a crash so that it can be re-applied
on the subsequent run. This is important because the unapplied refresh
is a form of hysteresis which needs to be tracked and remembered or we
won't be able to determine that the state is wrong!
Still to do:
* Update the autogrouping code to handle the edge notify properties!
* Actually finish the stateful bool code
This is a new design idea which I had. Whether it stays around or not is
up for debate. For now it's a rough POC.
The idea is that any resource can _produce_ data, and any resource can
_consume_ data. This is what we call send and recv. By linking the two
together, data can be passed directly between resources, which will
maximize code re-use, and allow for some interesting logical graphs.
For example, you might have an HTTP resource which puts its output in a
particular file. This avoids having to overload the HTTP resource with
all of the special behaviours of the File resource.
For our POC, I implemented a `password` resource which generates a
random string which can then be passed to a receiver such as a file. At
this point the password resource isn't recommended for sensitive
applications because it caches the password as plain text.
Still to do:
* Statically check all of the type matching before we run the graph
* Verify that our autogrouping works correctly around this feature
* Verify that appropriate edges exist between send->recv pairs
* Label the password as generated instead of storing the plain text
* Consider moving password logic from Init() to CheckApply()
* Consider combining multiple send values (list?) into a single receiver
* Consider intermediary transformation nodes for value combining
