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Process is a library inspired by Prismatic's Graph

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# process

Process is a library inspired by the core idea of Prismatic's
[Graph](http://blog.getprismatic.com/blog/2012/10/1/prismatics-graph-at-strange-loop.html)
library. For that reason it also has a lot of goals in common with
Stuart Sierra's [Flow](https://github.com/stuartsierra/flow) library.
You should read Prismatic's [blog
post](http://blog.getprismatic.com/blog/2012/10/1/prismatics-graph-at-strange-loop.html)
about Graph to get an idea what benefits you can leverage if you use
this fine-grained, composable abstraction
([FCA](http://blog.getprismatic.com/blog/2012/4/5/software-engineering-at-prismatic.html)).

What it comes down to is, that you can compose different steps of a
computation in a more flexible way than using a let for that
purpose. In a real life system these computations or rather processes
often involve a lot of steps. Normally you end up with a function that
contains a huge let statement (kind of a 'monster'-let) that composes
all these steps. This construct is totally inflexible, if you like to
do anything more than to execute this ball of mud. Especially, if you
have discovered a bug that is caused by some of the composed steps or
maybe just by some missing data. Most often the fastest way is to add
some `println` statements in between the steps of the 'monster'-let to
do some ad-hoc debugging.  
The FCA of the process library helps you to compose all these steps in
a flexible way, so that you can access each and every interim result
of the computation. It even allows you to evaluate the computation
only up to a certain point or to predefine the output of a step. The
latter is especially useful if the corresponding step represents a
side effect that you like to "mock out". In terms of the simplicity
notion you could say the FCA of the process library helps you to
separate the declarative part of how the steps of a process depend on
each other from the part of how the process is executed in the
end. You could choose to just execute the steps of a process
sequentially like a let statement or you can write an execution
strategy that figures out which steps can be calculated in parallel.  
Among other things we use the process library to split up some complex
event processing code into simple steps. A lot of steps produces
interim results that are needed by different computations to calculate
their end result. By using process the interim results can easily be
shared between the different computations and the execution strategy
can be adapted to higher performance demands independently from the
actual implementation of the calculation. There are a whole lot of
other benefits like transparently enhancing the execution of a process
with performance monitoring stuff and so on, that are all described in
the aforementioned blog post by Prismatic about their Graph
library. One last point I like to mention is that this FCA really
helps a lot to separate the pure functional parts of a process from
the impure parts or rather steps with side effects.

## Releases

The latest release is 0.1.2

[Leiningen](https://github.com/technomancy/leiningen) dependency information:

[net.doo/process "0.1.2"]

## Usage

To define a step or rather component of a process you can use the
`fnc` macro that just adds a `:process.definition/dependencies` entry
(a vector of keywords) to the metadata of the function. So `(def f
(fnc [alpha beta] (+ alpha beta)))` just states that the function `f`
depends on two outputs named `alpha` and `beta` as inputs to do its
calculation. `alpha` or `beta` could either be an output of another
process component or they can be inputs for the process itself. Here
the example that is also used for the Flow library:

(use 'process.definition)

(def process-definition
     {:result (fnc [gamma delta epsilon] (+ gamma delta epsilon))
      :gamma (fnc [alpha beta] (+ alpha beta))
      :delta (fnc [alpha gamma] (+ alpha gamma))
      :epsilon (fnc [gamma delta] (+ gamma delta))})

(use 'process.execution.sequential)
 
    > (execute-sequential process-definition {:alpha 1 :beta 2} :result)
    {:result 14, :epsilon 7, :delta 4, :gamma 3, :alpha 1, :beta 2}

In the example above `alpha` and `beta` are both inputs for the
process. The component `gamma` just depends on `alpha` and `beta`,
while the component `delta` needs the output of gamma to perform its
calculation. Therefore it is clear that `gamma` needs to be calculated
first before the `delta` component function can be invoked. The
`execute-sequential` function uses the dependency graph from the
org.clojure/tools.namespace library and a level order traversal to
find a sequence to execute the process, so that all outputs of the
component's dependencies are available when a component function is
invoked. Through the second parameter of the `execute-sequential`
function you define the 'existing' outputs of the process execution,
here we just say that the outputs of `alpha` and `beta` are already
calculated. The remaining arguments of the function define which
outputs you like to calculate. Here we just want to know what the
result is. However you could also only execute the process partially:

> (execute-sequential process-definition {:alpha 1 :beta 2} :delta)
    {:delta 4, :gamma 3, :alpha 1, :beta 2}

As you can see above only the outputs are calculated to perform the
computation of the delta component. Furthermore you also can predefine
the output of components:

> (execute-sequential process-definition {:alpha 1 :beta 2 :gamma 1} :delta)
    {:delta 2, :alpha 1, :beta 2, :gamma 1}

If gamma would perform some side effect - for example querying a
database - you can easily predefine the output to avoid the execution
of the side effect (e.g. in your test scenario).

To become more similar to a let the process macro has been added to
the library (still alpha):

(def process-definition
      (process
       [alpha nil
        beta 2
        gamma (+ alpha beta)
        delta (+ alpha gamma)
        epsilon (+ gamma delta)
        result (+ gamma delta epsilon)]))

> (execute-sequential process-definition {:alpha 1} :result)
    {:result 14, :epsilon 7, :delta 4, :gamma 3, :beta 2, :alpha 1}

In comparison to our first process-definition this version has much
less boilerplate code. The `process` macro needs to be aware of the
inputs so that it can figure out if you mean a dependency or just a
symbol from the context (a var defined in the current namespace or a
binding in a surrounding let). Here we define `alpha` as nil while
`beta` has a default value of `2`. Like any other component `beta`
can also be predefined via the existing-outputs parameter of the
`execute-sequential` function.

## License

Distributed under the Eclipse Public License, the same as Clojure.

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