Concrete implementations of Var implement observe.
Concrete implementations of Var implement observe. This is called for each toplevel observe. Depths indicate the relative structural depth of the observation, from the frame of reference of the root call to observe. (Each Var derived via flatMap increases the depth.) Depths are used to order the invocation of update callbacks. This is used to ensure that updates proceed in topological order so that every input variable is fully resolved before recomputing a derived variable.
An Event where changes in Var are emitted.
An Event where changes in Var are emitted. The current value of this Var is emitted synchronously upon subscription.
All changes to this Var are guaranteed to be published to the Event.
Produce an Event reflecting the differences between each update to this Var.
Create a dependent Var which behaves as f
applied to the
current value of this Var.
Create a dependent Var which behaves as f
applied to the
current value of this Var. FlatMap manages a dynamic dependency
graph: the dependent Var is detached and recomputed whenever
the outer Var changes, but only if there are any observers. An
unobserved Var returned by flatMap will not invoke f
Create a derived variable by applying f
to the contained
value.
Vars are values that vary over time. To create one, you must give it an initial value.
A Var created this way can be sampled to retrieve its current value,
println(Var.sample(a)) // prints 1
or, invoked to assign it new values.
Vars can be derived from other Vars.
And, if the underlying is assigned a new value, the derived Var is updated. Updates are computed lazily, so while assignment is cheap, sampling is where we pay the cost of the computation required to derive the new Var.
A key difference between the derived Var and its underlying is that derived Vars can't be assigned new values. That's why
b
, from the example above, can't be invoked to assign it a new value, it can only be sampled.There are no well-defined error semantics for Var. Vars are computed lazily, and the updating thread will receive any exceptions thrown while computing derived Vars. Note: There is a Java-friendly API for this trait: com.twitter.util.AbstractVar.
,Vars do not always perform the minimum amount of re-computation.