The Tracing API is currently private and unstable. Use it for local debugging, but if you think you need to commit code that references it, you should either pin your dependency on the current version of Automat, or at least be prepared for your application to break when this API is changed or removed.
The tracing API lets you assign a callback function that will be invoked each time an input event causes the state machine to move from one state to another. This can help you figure out problems caused by events occurring in the wrong order, or not happening at all. Your callback function can print a message to stdout, write something to a logfile, or deliver the information in any application-specific way you like. The only restriction is that the function must not touch the state machine at all.
To prepare the state machine for tracing, you must assign a name to the “_setTrace” method in your class. In this example, we use setTheTracingFunction, but the name can be anything you like:
class Sample(object): mm = MethodicalMachine() @mm.state(initial=True) def begin(self): "initial state" @mm.state() def end(self): "end state" @mm.input() def go(self): "event that moves us from begin to end" @mm.output() def doThing1(self): "first thing to do" @mm.output() def doThing2(self): "second thing to do" setTheTracingFunction = mm._setTrace begin.upon(go, enter=end, outputs=[doThing1, doThing2])
Later, after you instantiate the Sample object, you can set the tracing callback for that particular instance by calling the setTheTracingFunction() method on it:
s = Sample() def tracer(oldState, input, newState): pass s.setTheTracingFunction(tracer)
Note that you cannot shortcut the name-assignment step: s.mm._setTrace(tracer) will not work, because Automat goes to great lengths to hide that mm object from external access. And you cannot set the tracing function at class-definition time (e.g. a class-level mm._setTrace(tracer)) because the state machine has merely been defined at that point, not instantiated (you might eventually have multiple instances of the Sample class, each with their own independent state machine), and each one can be traced separately.
Since this is a private API, consider using a tolerant getattr when retrieving the _getTrace method. This way, if you do commit code which references it, but you only call that code during debugging, then at least your application or tests won’t crash when the API is removed entirely:
mm = MethodicalMachine() setTheTracingFunction = getattr(mm, "_setTrace", lambda self, f: None)
The Tracer Callback Function¶
When the input event is received, before any transitions are made, the tracer function is called with three positional arguments:
- oldState: a string with the name of the current state
- input: a string with the name of the input event
- newState: a string with the name of the new state
If your tracer function returns None, then you will only be notified about the input events. But, if your tracer function returns a callable, then just before each output function is executed (if any), that callable will be executed with a single output argument (as a string).
So if you only care about the transitions, your tracing function can just do:
>>> s = Sample() >>> def tracer(oldState, input, newState): ... print("%s.%s -> %s" % (oldState, input, newState)) >>> s.setTheTracingFunction(tracer) >>> s.go() begin.go -> end
But if you want to know when each output is invoked (perhaps to compare against other log messages emitted from inside those output functions), you can do:
>>> s = Sample() >>> def tracer(oldState, input, newState): >>> def traceOutputs(output): ... print("%s.%s -> %s: %s()" % (oldState, input, newState, output)) ... print("%s.%s -> %s" % (oldState, input, newState)) ... return traceOutputs >>> s.setTheTracingFunction(tracer) >>> s.go() begin.go -> end begin.go -> end: doThing1() begin.go -> end: doThing2()
Tracing Multiple State Machines¶
If you have multiple state machines in your application, you will probably want to pass a different tracing function to each, so your logs can distinguish between the transitions of MachineFoo vs those of MachineBar. This is particularly important if your application involves network communication, where an instance of MachineFoo (e.g. in a client) is in communication with a sibling instance of MachineFoo (in a server). When exercising both sides of this connection in a single process, perhaps in an automated test, you will need to clearly mark the first as “foo1” and the second as “foo2” to avoid confusion.
s1 = Sample() s2 = Sample() def tracer1(oldState, input, newState): print("S1: %s.%s -> %s" % (oldState, input, newState)) s1.setTheTracingFunction(tracer1) def tracer2(oldState, input, newState): print("S2: %s.%s -> %s" % (oldState, input, newState)) s2.setTheTracingFunction(tracer2)