## What Problem Does It Solve? First, we decided to build our SPA apps with ClojureScript, then we choose [Reagent], then we had a problem. For all its considerable brilliance, Reagent (+ React) delivers only the 'V' part of a traditional MVC framework. But apps involve much more than V. Where does the control logic go? How is state stored & manipulated? etc. We read up on [Pedestal App], [Flux], [Hoplon], [Om], early [Elm], etc and re-frame is the architecture that emerged. Since then, we've kept a close eye on further developments like the Elm Architecture, Om.Next, BEST, Cycle.js, Redux, etc. They have taught us much although we have often made different choices. re-frame does have M, V, and C parts but they aren't objects. It is sufficiently different in nature from (traditional, Smalltalk) MVC that calling it MVC would be confusing. I'd love an alternative. Perhaps it is a RACES framework - Reactive-Atom Component Event Subscription framework (I love the smell of acronym in the morning). Or, if we distill to pure essence, `DDATWD` - Derived Data All The Way Down. *TODO:* get acronym down to 3 chars! Get an image of stacked Turtles for `DDATWD` insider's joke, conference T-Shirt. ## Guiding Philosophy __First__, above all we believe in the one true [Dan Holmsand], creator of Reagent, and his divine instrument the `ratom`. We genuflect towards Sweden once a day. __Second__, we believe in ClojureScript, immutable data and the process of building a system out of pure functions. __Third__, we believe in the primacy of data, for the reasons previously given. re-frame implements an infinite loop of Derived data. __Fourth__, we believe that Reactive Programming is one honking great idea. It is a quite beautiful solution to one half of re-frame's data conveyance needs, but we don't take reactivity as far as, say, cycle.js. It doesn't take over everything in re-frame - it just does part of the job. __Finally__, many years ago I programmed briefly in Eiffel where I learned about [command-query separation](https://en.wikipedia.org/wiki/Command%E2%80%93query_separation). Each generation of programmers seems destined to rediscover this principle - CQRS is a recent re-rendering. And yet we still see read/write `cursors` and two way data binding being promoted as a good thing. Just say no. As programs get bigger, their use will encourage control logic into all the wrong places and you'll end up with a tire fire of an Architecture. IMHO. XXX I'll be using [Reagent] at an intermediate level, so you will need to have done some introductory Reagent tutorials before going on. Try: - [The Introductory Tutorial](http://reagent-project.github.io/) or - [this one](https://github.com/jonase/reagent-tutorial) or - [Building Single Page Apps with Reagent](http://yogthos.net/posts/2014-07-15-Building-Single-Page-Apps-with-Reagent.html). ## Flow Arguments from authority ... > Everything flows, nothing stands still. (Panta rhei) > No man ever steps in the same river twice for it's not the same river and he's not the same man. [Heraclitus 500 BC](http://en.wikiquote.org/wiki/Heraclitus). Who, being Greek, had never seen a frozen river. [alt version](http://farm6.static.flickr.com/5213/5477602206_ecb78559ed.jpg). > Think of an experience from your childhood. Something you remember clearly, something you can see, feel, maybe even smell, as if you were really there. After all you really were there at the time, weren’t you? How else could you remember it? But here is the bombshell: you weren’t there. Not a single atom that is in your body today was there when that event took place .... Matter flows from place to place and momentarily comes together to be you. Whatever you are, therefore, you are not the stuff of which you are made. If that does not make the hair stand up on the back of your neck, read it again until it does, because it is important. Steve Grand We'll get to the meat in a second, I promise, but first one final, useful diversion ... Terminology in the FRP world seems to get people hot under the collar. Those who believe in continuous-time semantics might object to me describing re-frame as having FRP-nature. They'd claim that it does something different from pure FRP, which is true. But, these days, FRP seems to have become a ["big tent"](http://soft.vub.ac.be/Publications/2012/vub-soft-tr-12-13.pdf) (a broad church?). Broad enough perhaps that re-frame can be in the far, top, left paddock of the tent, via a series of qualifications: re-frame has "discrete, dynamic, asynchronous, push FRP-ish-nature" without "glitch free" guarantees. (Surprisingly, "glitch" has specific meaning in FRP). **If you are new to FRP, or reactive programming generally**, browse these resources before going further (certainly read the first two): - [Creative Explanation](http://paulstovell.com/blog/reactive-programming) - [Reactive Programming Backgrounder](https://gist.github.com/staltz/868e7e9bc2a7b8c1f754) - [presentation (video)](http://www.infoq.com/presentations/ClojureScript-Javelin) by Alan Dipert (co-author of Hoplon) - [serious pants Elm thesis](https://www.seas.harvard.edu/sites/default/files/files/archived/Czaplicki.pdf) And for the love of all that is good, please watch this terrific [StrangeLoop presentation ](https://www.youtube.com/watch?v=fU9hR3kiOK0) (40 mins). Watch what happens when you re-imagine a database as a stream!! Look at all the problems that are solved. Think about that: shared mutable state (the root of all evil), re-imagined as a stream!! Blew my socks off. ### How Flow Happens In Reagent To implement FRP, Reagent provides a `ratom` and a `reaction`. re-frame uses both of these building blocks, so let's now make sure we understand them. `ratoms` behave just like normal ClojureScript atoms. You can `swap!` and `reset!` them, `watch` them, etc. From a ClojureScript perspective, the purpose of an atom is to hold mutable data. From a re-frame perspective, we'll tweak that paradigm slightly and **view a `ratom` as having a value that changes over time.** Seems like a subtle distinction, I know, but because of it, re-frame sees a `ratom` as a Signal. [Pause and read this](http://elm-lang.org:1234/guide/reactivity). The 2nd building block, `reaction`, acts a bit like a function. It's a macro which wraps some `computation` (a block of code) and returns a `ratom` holding the result of that `computation`. The magic thing about a `reaction` is that the `computation` it wraps will be automatically re-run whenever 'its inputs' change, producing a new output (return) value. Eh, how? Well, the `computation` is just a block of code, and if that code dereferences one or more `ratoms`, it will be automatically re-run (recomputing a new return value) whenever any of these dereferenced `ratoms` change. To put that yet another way, a `reaction` detects a `computation's` input Signals (aka input `ratoms`) and it will `watch` them, and when, later, it detects a change in one of them, it will re-run that computation, and it will `reset!` the new result of that computation into the `ratom` originally returned. So, the `ratom` returned by a `reaction` is itself a Signal. Its value will change over time when the `computation` is re-run. So, via the interplay between `ratoms` and `reactions`, values 'flow' into computations and out again, and then into further computations, etc. "Values" flow (propagate) through the Signal graph. But this Signal graph must be without cycles, because cycles cause mayhem! re-frame achieves a unidirectional flow. Right, so that was a lot of words. Some code to clarify: ```Clojure (ns example1 (:require-macros [reagent.ratom :refer [reaction]]) ;; reaction is a macro (:require [reagent.core :as reagent])) (def app-db (reagent/atom {:a 1})) ;; our root ratom (signal) (def ratom2 (reaction {:b (:a @app-db)})) ;; reaction wraps a computation, returns a signal (def ratom3 (reaction (condp = (:b @ratom2) ;; reaction wraps another computation 0 "World" 1 "Hello"))) ;; Notice that both computations above involve de-referencing a ratom: ;; - app-db in one case ;; - ratom2 in the other ;; Notice that both reactions above return a ratom. ;; Those returned ratoms hold the (time varying) value of the computations. (println @ratom2) ;; ==> {:b 1} ;; a computed result, involving @app-db (println @ratom3) ;; ==> "Hello" ;; a computed result, involving @ratom2 (reset! app-db {:a 0}) ;; this change to app-db, triggers re-computation ;; of ratom2 ;; which, in turn, causes a re-computation of ratom3 (println @ratom2) ;; ==> {:b 0} ;; ratom2 is result of {:b (:a @app-db)} (println @ratom3) ;; ==> "World" ;; ratom3 is automatically updated too. ``` So, in FRP-ish terms, a `reaction` will produce a "stream" of values over time (it is a Signal), accessible via the `ratom` it returns. Okay, that was all important background information for what is to follow. Back to the diagram ... ## Components Extending the diagram, we introduce `components`: ``` app-db --> components --> Hiccup ``` When using Reagent, your primary job is to write one or more `components`. This is the view layer. Think about `components` as `pure functions` - data in, Hiccup out. `Hiccup` is ClojureScript data structures which represent DOM. Here's a trivial component: ```Clojure (defn greet [] [:div "Hello ratoms and reactions"]) ``` And if we call it: ```Clojure (greet) ;; ==> [:div "Hello ratoms and reactions"] ``` You'll notice that our component is a regular Clojure function, nothing special. In this case, it takes no parameters and it returns a ClojureScript vector (formatted as Hiccup). Here is a slightly more interesting (parameterised) component (function): ```Clojure (defn greet ;; greet has a parameter now [name] ;; 'name' is a ratom holding a string [:div "Hello " @name]) ;; dereference 'name' to extract the contained value ;; create a ratom, containing a string (def n (reagent/atom "re-frame")) ;; call our `component` function, passing in a ratom (greet n) ;; ==> [:div "Hello " "re-frame"] returns a vector ``` So components are easy - at core they are a render function which turns data into Hiccup (which will later become DOM). Now, let's introduce `reaction` into this mix. On the one hand, I'm complicating things by doing this, because Reagent allows you to be ignorant of the mechanics I'm about to show you. (It invisibly wraps your components in a `reaction` allowing you to be blissfully ignorant of how the magic happens.) On the other hand, it is useful to understand exactly how the Reagent Signal graph is wired, because in a minute, when we get to `subscriptions`, we'll be directly using `reaction`, so we might as well bite the bullet here and now ... and, anyway, it is pretty easy... ```Clojure (defn greet ;; a component - data in, Hiccup out. [name] ;; name is a ratom [:div "Hello " @name]) ;; dereference name here, to extract the value within (def n (reagent/atom "re-frame")) ;; The computation '(greet n)' returns Hiccup which is stored into 'hiccup-ratom' (def hiccup-ratom (reaction (greet n))) ;; <-- use of reaction !!! ;; what is the result of the initial computation ? (println @hiccup-ratom) ;; ==> [:div "Hello " "re-frame"] ;; returns hiccup (a vector of stuff) ;; now change 'n' ;; 'n' is an input Signal for the reaction above. ;; Warning: 'n' is not an input signal because it is a parameter. Rather, it is ;; because 'n' is dereferenced within the execution of the reaction's computation. ;; reaction notices what ratoms are dereferenced in its computation, and watches ;; them for changes. (reset! n "blah") ;; n changes ;; The reaction above will notice the change to 'n' ... ;; ... and will re-run its computation ... ;; ... which will have a new "return value"... ;; ... which will be "reset!" into "hiccup-ratom" (println @hiccup-ratom) ;; ==> [:div "Hello " "blah"] ;; yep, there's the new value ``` So, as `n` changes value over time (via a `reset!`), the output of the computation `(greet n)` changes, which in turn means that the value in `hiccup-ratom` changes. Both `n` and `hiccup-ratom` are FRP Signals. The Signal graph we created causes data to flow from `n` into `hiccup-ratom`. Derived Data, flowing. ### Truth Interlude I haven't been entirely straight with you: 1. Reagent re-runs `reactions` (re-computations) via requestAnimationFrame. So a re-computation happens about 16ms after an input Signals change is detected, or after the current thread of processing finishes, whichever is the greater. So if you are in a bREPL and you run the lines of code above one after the other too quickly, you might not see the re-computation done immediately after `n` gets reset!, because the next animationFrame hasn't run (yet). But you could add a `(reagent.core/flush)` after the reset! to force re-computation to happen straight away. 2. `reaction` doesn't actually return a `ratom`. But it returns something that has ratom-nature, so we'll happily continue believing it is a `ratom` and no harm will come to us. On with the rest of my lies and distortions... ### Components Like Templates? A `component` such as `greet` is like the templates you'd find in Django, Rails, Handlebars or Mustache -- it maps data to HTML -- except for two massive differences: 1. you have the full power of ClojureScript available to you (generating a Clojure data structure). The downside is that these are not "designer friendly" HTML templates. 2. these templates are reactive. When their input Signals change, they are automatically rerun, producing new DOM. Reagent adroitly shields you from the details, but the renderer of any `component` is wrapped by a `reaction`. If any of the the "inputs" to that render change, the render is rerun. ### React etc. Okay, so we have some unidirectional, dynamic, async, discrete FRP-ish data flow happening here. Question: To which ocean does this river of data flow? Answer: The DOM ocean. The full picture: ``` app-db --> components --> Hiccup --> Reagent --> VDOM --> React --> DOM ``` Best to imagine this process as a pipeline of 3 functions. Each function takes data from the previous step, and produces (derived!) data for the next step. In the next diagram, the three functions are marked (f1, f2, f3). The unmarked nodes are derived data, produced by one step, to be input to the following step. Hiccup, VDOM and DOM are all various forms of HTML markup (in our world that's data). ``` app-db --> components --> Hiccup --> Reagent --> VDOM --> React --> DOM f1 f2 f3 ``` In abstract ClojureScript syntax terms, you could squint and imagine the process as: ```Clojure (-> app-db components ;; produces Hiccup Reagent ;; produces VDOM (virtual DOM that React understands) React ;; produces HTML (which magically and efficiently appears on the page). Browser ;; produces pixels Monitor) ;; produces photons? ``` Via the interplay between `ratom` and `reaction`, changes to `app-db` stream into the pipeline, where it undergoes successive transformations, until pixels colour the monitor you to see. Derived Data, flowing. Every step is acting like a pure function and turning data into new data. All well and good, and nice to know, but we don't have to bother ourselves with most of the pipeline. We just write the `components` part and Reagent/React will look after the rest. So back we go to that part of the picture ... ## Subscribe `components` render the app's state as hiccup. ``` app-db --> components ``` `components` (view layer) need to query aspects of `app-db` (data layer). But how? Let's pause to consider **our dream solution** for this part of the flow. `components` would: * obtain data from `app-db` (their job is to turn this data into hiccup). * obtain this data via a (possibly parameterised) query over `app-db`. Think database kind of query. * automatically recompute their hiccup output, as the data returned by the query changes, over time * use declarative queries. Components should know as little as possible about the structure of `app-db`. SQL? Datalog? re-frame's `subscriptions` are an attempt to live this dream. As you'll see, they fall short on the declarative query part, but they comfortably meet the other requirements. As a re-frame app developer, your job will be to write and register one or more "subscription handlers" - functions that do a named query. Your subscription functions must return a value that changes over time (a Signal). I.e. they'll be returning a reaction or, at least, the `ratom` produced by a `reaction`. Rules: - `components` never source data directly from `app-db`, and instead, they use a subscription. - subscriptions are only ever used by components (they are never used in, say, event handlers). Here's a component using a subscription: ```Clojure (defn greet ;; outer, setup function, called once [] (let [name-ratom (subscribe [:name-query])] ;; <---- subscribing happens here (fn [] ;; the inner, render function, potentially called many times. [:div "Hello" @name-ratom]))) ``` First, note this is a [Form-2](https://github.com/Day8/re-frame/wiki/Creating-Reagent-Components#form-2--a-function-returning-a-function) `component` ([there are 3 forms](https://github.com/Day8/re-frame/wiki/Creating-Reagent-Components)). Previously in this document, we've used the simplest, `Form-1` components (no setup was required, just render). With `Form-2` components, there's a function returning a function: - the returned function is the render function. Behind the scenes, Reagent will wrap this render function in a `reaction` to make it produce new Hiccup when its input Signals change. In our example above, that means it will rerun every time `name-ratom` changes. - the outer function is a setup function, called once for each instance of the component. Notice the use of 'subscribe' with the parameter `:name-query`. That creates a Signal through which new values are supplied over time; each new value causing the returned function (the actual renderer) to be run. >It is important to distinguish between a new instance of the component versus the same instance of a component reacting to a new value. Simplistically, a new component is returned for every unique value the setup function (i.e. the outer function) is called with. This allows subscriptions based on initialisation values to be created, for example: ``` Clojure (defn my-cmp [row-id] (let [row-state (subscribe [row-id])] (fn [row-id] [:div (str "Row: " row-id " is " @row-state)]))) ``` In this example, `[my-cmp 1][my-cmp 2]` will create two instances of `my-cmp`. Each instance will re-render when its internal `row-state` signal changes. `subscribe` is always called like this: ```Clojure (subscribe [query-id some optional query parameters]) ``` There is only one (global) `subscribe` function and it takes one parameter, assumed to be a vector. The first element in the vector (shown as `query-id` above) identifies/names the query and the other elements are optional query parameters. With a traditional database a query might be: ``` select * from customers where name="blah" ``` In re-frame, that would be done as follows: `(subscribe [:customer-query "blah"])` which would return a `ratom` holding the customer state (a value which might change over time!). So let's now look at how to write and register the subscription handler for `:customer-query` ```Clojure (defn customer-query ;; a query over 'app-db' which returns a customer [db, [sid cid]] ;; query fns are given 'app-db', plus vector given to subscribe (assert (= sid :customer-query)) ;; subscription id was the first element in the vector (reaction (get-in @db [:path :to :a :map cid]))) ;; re-runs each time db changes ;; register our query handler (register-sub :customer-query ;; the id (the name of the query) customer-query) ;; the function which will perform the query ``` Notice how the handler is registered to handle `:customer-query` subscriptions. **Rules and Notes**: - you'll be writing one or more handlers, and you will need to register each one. - handlers are functions which take two parameters: the db atom, and the vector given to subscribe. - `components` tend to be organised into a hierarchy, often with data flowing from parent to child via parameters. So not every component needs a subscription. Very often the values passed in from a parent component are sufficient. - subscriptions can only be used in `Form-2` components and the subscription must be in the outer setup function and not in the inner render function. So the following is **wrong** (compare to the correct version above) ```Clojure (defn greet ;; a Form-1 component - no inner render function [] (let [name-ratom (subscribe [:name-query])] ;; Eek! subscription in renderer [:div "Hello" @name-ratom])) ``` Why is this wrong? Well, this component would be re-rendered every time `app-db` changed, even if the value in `name-ratom` (the result of the query) stayed the same. If you were to use a `Form-2` component instead, and put the subscription in the outer functions, then there'll be no re-render unless the value queried (i.e. `name-ratom`) changed. ### Just A Read-Only Cursor? Subscriptions are different to read-only cursors. Yes, `subscriptions` abstract away (hide) the data source, like a Cursor, but they also allow for computation. To put that another way, they can create derived data from `app-db` (a Materialised View of `app-db`). Imagine that our `app-db` contained `:items` - a vector of maps. And imagine that we wanted to display these items sorted by one of their attributes. And that we only want to display the top 20 items. This is the sort of "derived data" which a subscription can deliver. (And as we'll see, more efficiently than a Cursor). ## The Signal Graph Let's sketch out the situation described above ... `app-db` would be a bit like this (`items` is a vector of maps): ```Clojure (def L [{:name "a" :val 23 :flag "y"} {:name "b" :val 81 :flag "n"} {:name "c" :val 23 :flag "y"}]) (def app-db (reagent/atom {:items L :sort-by :name})) ;; sorted by the :name attribute ``` The subscription-handler might be written: ```Clojure (register-sub :sorted-items ;; the query id (the name of the query) (fn [db [_]] ;; the handler for the subscription (reaction (let [items (get-in @db [:items]) ;; extract items from db sort-attr (get-in @db [:sort-by])] ;; extract sort key from db (sort-by sort-attr items))))) ;; return them sorted ``` Subscription handlers are given two parameters: 1. `app-db` - that's a reagent/atom which holds ALL the app's state. This is the "database" on which we perform the "query". 2. the vector originally supplied to `subscribe`. In our case, we ignore it. In the example above, notice that the `reaction` depends on the input Signal: `db`. If `db` changes, the query is re-run. In a component, we could use this query via `subscribe`: ```Clojure (defn items-list ;; Form-2 component - outer, setup function, called once [] (let [items (subscribe [:sorted-items]) ;; <-- subscribe called with name num (reaction (count @items)) ;; Woh! a reaction based on the subscription top-20 (reaction (take 20 @items))] ;; Another dependent reaction (fn [] [:div (str "there's " @num " of these suckers. Here's top 20") ;; rookie mistake to leave off the @ (into [:div ] (map item-render @top-20))]))) ;; item-render is another component, not shown ``` There's a bit going on in that `let`, most of it tortuously contrived, just so I can show off chained reactions. Okay, okay, all I wanted really was an excuse to use the phrase "chained reactions". The calculation of `num` is done by a `reaction` which has `items` as an input Signal. And, as we saw, `items` is itself a reaction over two other signals (one of them the `app-db`). So this is a Signal Graph. Data is flowing through computation into renderer, which produce Hiccup, etc. ## A More Efficient Signal Graph But there is a small problem. The approach above might get inefficient, if `:items` gets long. Every time `app-db` changes, the `:sorted-items` query is going to be re-run and it's going to re-sort `:items`. But `:items` might not have changed. Some other part of `app-db` may have changed. We don't want to perform this computationally expensive re-sort each time something unrelated in `app-db` changes. Luckily, we can easily fix that up by tweaking our subscription function so that it chains `reactions`: ```Clojure (register-sub :sorted-items ;; the query id (fn [db [_]] (let [items (reaction (get-in @db [:some :path :to :items]))] ;; reaction #1 sort-attr (reaction (get-in @db [:sort-by]))] ;; reaction #2 (reaction (sort-by @sort-attr @items))))) ;; reaction #3 ``` The original version had only one `reaction` which would be re-run completely each time `app-db` changed. This new version, has chained reactions. The 1st and 2nd reactions just extract from `db`. They will run each time `app-db` changes. But they are cheap. The 3rd one does the expensive computation using the result from the first two. That 3rd, expensive reaction will be re-run when either one of its two input Signals change, right? Not quite. `reaction` will only re-run the computation when one of the inputs has **changed in value**. `reaction` compares the old input Signal value with the new Signal value using `identical?`. Because we're using immutable data structures (thank you ClojureScript), `reaction` can perform near instant checks for change on even deeply nested and complex input Signals. And `reaction` will then stop unneeded propagation of `identical?` values through the Signal graph. In the example above, reaction #3 won't re-run until `:items` or `:sort-by` are different (do not test `identical?` to their previous value), even though `app-db` itself has changed (presumably somewhere else). Hideously contrived example, but I hope you get the idea. It is all screamingly efficient. Summary: - you can chain reactions. - a reaction will only be re-run when its input Signals test not `identical?` to previous value. - As a result, unnecessary Signal propagation is eliminated using highly efficient checks, even for large, deep nested data structures. ## The 2nd Flow ## Event Flow Events are what flow in the opposite direction. In response to user interaction, a DOM will generate events like "clicked delete button on item 42" or "unticked the checkbox for 'send me spam'". These events have to be "handled". The code doing this handling might mutate app state (in `app-db`), or request more data from the server, or POST somewhere and wait for a response, etc. In fact, all these actions ultimately result in changes to the `app-db`. An application has many handlers, and collectively they represent the **control layer of the application**. In re-frame, the backwards data flow of events happens via a conveyor belt: ``` app-db --> components --> Hiccup --> Reagent --> VDOM --> React --> DOM ^ | | v handlers <------------------- events ----------------------------------------- a "conveyor belt" takes events from the DOM to the handlers ``` Generally, when the user manipulates the GUI, the state of the application changes. In our case, that means the `app-db` will change. After all, it **is** the state. And the DOM presented to the user is a function of that state. So that tends to be the cycle: 1. the user clicks something which causes an event to be dispatched 2. a handler manages the event 3. and causes `app-db` to change (mutation happens here!) 4. which then causes a re-render 5. the user sees something different 6. goto #1 That's our water cycle. Because handlers are that part of the system which does `app-db` mutation, you could almost imagine them as a "stored procedures" on a database. Almost. Stretching it? We do like our in-memory database analogies. ### Dispatching Events ### Event Handlers Collectively, event handlers provide the control logic in a re-frame application. An event handler is a pure function of two parameters: 1. current value in `app-db`. Note: that's the map **in** `app-db`, not the atom itself. 2. an event (represented as a vector) It returns the new value which should be reset! into `app-db`. An example handler: ```Clojure (defn handle-delete [app-state [_ item-id]] ;; notice how event vector is destructured -- 2nd parameter (dissoc-in app-state [:some :path item-id])) ;; return a modified version of 'app-state' ``` Handling an event invariably involves mutating the value in `app-db` (which is provided as the first parameter). An item is added here, or one is deleted there. So, often simple CRUD, but sometimes much more, and sometimes with async results. But the `app-db` mutation is ultimately handled by re-frame (it does the `reset!`). That leaves your event handlers pure. As a result, they tend to be easy to test and understand. Many are almost trivial. There's more to event handlers than can be covered here in this introductory tutorial. Read up on issues like Middleware [in the Wiki](https://github.com/Day8/re-frame/wiki#handler-middleware). ### Control Via FSM Above, I commented that event handlers collectively represent the "control layer" of the application. They contain logic which interprets arriving events and they "step" the application "forward" via mutations to `app-db`. Our `delete-handler` above is trivial, but as an application grows more features, the logic in many handlers will become more complicated, and they will have to query BOTH the current state of the app AND the arriving event vector to determine what action to take. If the app is in logical State A, and event X arrives, then the handler will move the app to logical state B (by changing values in `app-db`). Sound like anything you learned in those [Theory Of Computation](https://www.youtube.com/watch?v=Pt6GBVIifZA) lectures? That's right - as an app becomes more complex, the handlers are likely to be collectively implementing a [Finite State Machine](http://en.wikipedia.org/wiki/Finite-state_machine): - your app is in a certain logical state (defined by the current values in `app-db`) - the arriving event vector represents a `trigger`. - the event handler implements "a transition", subject to BOTH the current logical state and the arriving trigger. - after the handler has run, the transition may have moved the app into a new logical state. - Repeat. Not every app has lots of logical `states`, but many do, and if you are implementing one of them, then formally recognising it and using a technique like [state charts](http://www.amazon.com/Constructing-User-Interface-Statecharts-Horrocks/dp/0201342782) will help greatly in getting a clean design and a nice datamodel. The beauty of re-frame from a FSM point of view is that all the data is in one place - unlike OO systems where the data is distributed (and synchronized) across many objects. So implementing your control logic as a FSM is both possible and natural in re-frame, whereas it is often difficult and contrived to do so in other kinds of architecture (in my experience). ### As A Reduce So here's another way of thinking about what's happening with this data flow - another useful mental model. First, imagine that all the events ever dispatched by a certain running app were stored in a collection. So, if when the app started, the user clicked on button X then the first item in this collection would be the event generated by that button, and then, if next the user moved a slider, the associated event would be the next item in the collection, and so on and so on. We'd end up with a collection of event vectors. Second, remind yourself that the `combining function` of a `reduce` takes two parameters: 1. the current state of the reduction and 2. the next collection member to fold in. Then notice that event handlers take two parameters too: 1. the current state of `app-db` 2. the next item to fold in. Which is the same as a `combining function` in a `reduce`!! So now we can introduce the new mental model: at any point in time, the value in `app-db` is the result of performing a `reduce` over the entire `collection` of events dispatched in the app up until that time. The combining function for this reduce is the set of handlers. It is almost like `app-db` is the temporary place where this imagined `perpetual reduce` stores its on-going reduction. ### Derived Data, Everywhere, flowing Have you watched that [StrangeLoop presentation ](https://www.youtube.com/watch?v=fU9hR3kiOK0) yet? I hope so. Database as a stream, right? If you have then, given the explanation above, you might twig to the idea that `app-db` is really a derived value (of the `perpetual reduce`). And yet, it acts as the authoritative source of state in the app. And yet, it isn't, it is simply a piece of derived state. And yet, it is the source. Hmm. This is an infinite loop of sorts. **Derived data is flowing around the loop, reactively, through pure functions.** There is a pause in the loop whenever we wait for a new event, but the moment we get it, it's another iteration of the "derived data" FRP loop. Derived values, all the way down, forever. Good news. If you've read this far, your insiders T-shirt will be arriving soon - it will feature turtles and [xkcd](http://xkcd.com/1416/). We're still working on the hilarious caption bit. Open a repo issue with a suggestion. Back to the more pragmatic world ... ### Logging And Debugging How did that exception happen, you wonder, shaking your head? What did the user do immediately prior to the exception? What state was the app in that this event was so disastrous? To debug it, you need to know this information: 1. the state of the app immediately before the exception 2. What final event then caused your app to fall in a screaming mess. Well, with re-frame you need to record (have available): 1. A recent checkpoint of the app state in `app-db` (perhaps the initial state) 2. all the events `dispatch`ed since the last checkpoint, up to the point where the exception occurred. Note: that's all just data. **Pure, lovely loggable data.** If you have that data, then you can reproduce the exception. re-frame allows you to time travel. Install the "checkpoint" state into `app-db` and then "play forward" through the collection dispatched events. The only way the app "moves forwards" is via events. "Replaying events" moves you step by step towards the exception causing problem. This is utterly, utterly perfect for debugging assuming, of course, you are in a position to capture a checkpoint, and the events since then. [SPAs]:http://en.wikipedia.org/wiki/Single-page_application [SPA]:http://en.wikipedia.org/wiki/Single-page_application [Reagent]:http://reagent-project.github.io/ [Dan Holmsand]:https://twitter.com/holmsand [Flux]:http://facebook.github.io/flux/docs/overview.html#content [Hiccup]:https://github.com/weavejester/hiccup [FRP]:https://gist.github.com/staltz/868e7e9bc2a7b8c1f754 [Elm]:http://elm-lang.org/ [OM]:https://github.com/swannodette/om [Prismatic Schema]:https://github.com/Prismatic/schema [Hoplon]:http://hoplon.io/ [Pedestal App]:https://github.com/pedestal/pedestal-app