re-frame
re-frame is a tiny reagent framework for writing SPAs using ClojureScript.
It proposes a pattern for structuring an app, and provides a small library implementing one version of this pattern.
In another context, re-frame might be called an MVC framework, except it is instead a functional RACES framework - Reactive-Atom Component Event Subscription (I love the smell of acronym in the morning).
Claims
Nothing about re-frame is the slightest bit original or clever. You'll find no ingenious use of functional zippers, transducers or core.async. This is a good thing (although, for the record, one day I'd love to develop something original and clever).
Using re-frame, you will be able to break your application code into distinct pieces. Each of these pieces can be easily described, understood and tested independently. These pieces will (mostly) be pure functions.
At small scale, any framework seems like pesky overhead. The explanatory examples in here are small scale, so you'll need to squint a little to see the benefit.
Core Beliefs
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 that FRP is a honking great idea. We think you only really "get" Reagent once you view it as an FRP library, and not simply a ReactJS wrapper. To put that another way, we think that Reagent at its best is closer in nature to Hoplon or Elm than it is OM. This wasn't obvious to us initially - we knew we liked reagent, but it took a while for the penny to drop as to why.
Finally, we believe in one way data flow. We don't like read/write cursors
which
allow for the two way flow of data. re-frame does implement two data way flow, but it
uses two, one-way flows to do it.
If you aren't familiar with FRP, or even if you think you are, I'd recomend reading [this FRP backgrounder](https://gist.github.com/staltz/868e7e9bc2a7b8c1f754 before you go any further.
The Parts
To explain re-frame, we'll now incrementally develop a diagram. We'll explain each part as it is added.
Well-formed Data at rest is as close to perfection in programming as it gets. All the crap that had to happen to put it there however...
— Fogus (@fogus) April 11, 2014
The Big Ratom
Our re-frame diagram starts with the "well formed data at rest" bit:
app-db
So, re-frame recomends that you put your data into one place (probably one dirty great
big atom) which we'll call app-db
. Structure the data in that place, of course.
Now, this advice is not the slightest bit controversial for 'real' databases, right? You'd happily put all your well formed data into Postgres or mysql. But within a running application (in memory), it is different. If you have background in OO, this data-in-one-place is a hard one to swallow. You've spent your life breaking systems into pieces, organised around behaviour and trying to hide the data. I still wake up in a sweat some nights thinking about all that clojure data lying around exposed and passive.
But, as @Fogus said above, data is the easy bit.
From here on, we'll assume app-db
is one of these:
(def app-db (reagent/atom {})) ;; a reagent atom, containing a map
Although it is a reagent atom (ratom), I'd encourage you to actively think about it as an (in-memory) database. It will contain structured data (perhaps with a formal Prismatic Schema spec). You will need to query that data. You will perform CRUD and other transformations on it. You'll often want to transact on this database atomically, etc. So "in-memory database" seems a more useful paradigm than plain old atom.
Finally, a clarification: app-db
doesn't actually have to be a reagent/atom containing
a map. In theory, re-frame
imposes no requirement here. It could be a datascript database. But, as you'll see, it
would have to be a "reactive datastore" of some description (an
"observable" datastore -- one that can tell you when it has changed).
The Magic Bit
Reagent provides a ratom
(reagent atom) and a reaction
. These are the two key building blocks.
ratoms
are like normal ClojureScript atoms. You can swap!
and reset!
them, watch
them, etc.
reactions
act a bit like functions. Its a macro which wraps some computation
(some forms?) and returns a ratom
containing the result of that computation
.
The magic bit is that reaction
will automatically rerun the computation
whenever the computation's "inputs" change, and it will reset!
the originally returned ratom
to the newly conputed value.
Go on, re-read that paragraph again, then look at this ...
(ns example1
(:require-macros [reagent.ratom :refer [reaction]])
(:require [reagent.core :as r]))
(def db-app (r/atom {:a 1})) ;; our base ratom
(def ratom2 (reaction {:b (:a @db-app)})) ;; reaction wraps a computation
(def ratom3 (reaction (cond = (:a @db-app) ;; reaction wraps another computation
0 "World"
1 "Hello")))
;; notice that both the computations above involve dereferencing db-app
;; notice also that both reactions above return a ratom.
(println @ratom2) ;; ==> {:b 1} ;; a computed result, involving @db-app
(println @ratom3) ;; ==> "Hello" ;; a computed result, involving @db-app
(reset! db-app {:a 0}) ;; this change to db-app, triggers recomputation
;; both ratom2 and ratom3 will get new values.
(println @ratom2) ;; ==> {:b 0} ;; ratom2 is result of {:b (:a @db-app)}
(println @ratom3) ;; ==> "World" ;; ratom3 is automatically updated too.
;; cleanup
(dispose ratom2)
(dispose ratom3)
So, reaction
wraps a computation, and returns a ratom
. Whenever the "inputs" to the computation change, the computation is rerun and the returned ratom is reset!
to the new value. The "inputs" to the computation are any ratoms which are dereferenced duration execution of the computation.
While the mechanics are different, this is similar in intent to lift' in [Elm] and
defc=` in hoplon.
So, in FRP terms, a reaction
will produce a "stream" of values, accessible via the ratom it returns.
The way that reagent harnesses these two building blocks is a delight.
Okay, that was all important background information. Let's get back with the diagram.
The Components
Extending the diagram a bit, we introduce components
:
db-app --> components --> hiccup
When using reagent, you write one or more components
. Think about
components
as pure functions
- data in, hiccup out. hiccup
is
ClojureScript data structures which represent DOM.
Here's a trivial component:
(defn greet
[]
[:div "Hello ratoms and recactions"])
(greet n)
;; ==> [:div "Hello ratoms and recactions"]
You'll notice that our component is a regular clojure function, nothing special. In this case, it takes no paramters and it returns a vector (hiccup).
Here is a slightly more interesting component:
(defn greet
[name] ;; 'name' is a ratom, contains a string
[:div "Hello " @name]) ;; dereference name here to get out the value it contains
;; create a ratom, containing a string
(def n (reagent/atom "re-frame"))
;; call our `component` function
(greet n)
;; ==> [:div "Hello " "re-frame"]
Okay, so have we got it that components are: data in, hiccup out ?
Good, let's introduce a reaction
:
(defn greet
[name] ;; name is a ratom
[:div "Hello " @name]) ;; dereference name here, to get out the value it contains
(def n (reagent/atom "re-frame"))
;; The computation '(greet n)' produces hiccup which is stored into 'hiccup-ratom'
(def hiccup-ratom (reaction (greet n))) ;; notice the used of reaction
;; what is the result of the initial computation ?
(println @hiccup-ratom)
;; ==> [:div "Hello " "re-frame"]
;; now change the ratom which is dereferenced in the computation
(reset! n "blah") ;; change n to a new value
;; the computaton '(greet n)' has been rerun, and 'hiccup-ratom' has an updated value
(println @hiccup-ratom)
;; ==> [:div "Hello " "blah"]
So, as n
changes value, hiccup-ratom
changes value. In fact, we could view a series of changes to n
as producing a "stream" of changes to hiccup-ratom
(over time).
If you understand the concept of re-computation, then we're there.
Truth injection time. I haven't been completely straight with you, so we could just focus on the concepts. Here's the reality -- reagent runs reactions
(re-computations) via requestAnnimationFrame, which is, say, 16ms in the future, or after the current thread of processing finishes, which ever is the greater. So if you were to actually run the lines of code above one after the other, you might not see the re-computation done after n
gets reset!, unless the animation frame has run. Not that this bit of annoying truth really matters much. All you need is the concept.
On with my lies and distortions ...
A component
like greet
is a bit like the templates you'd find in frameworks
like Django or Rails or Mustache -- it maps data to HTML -- except for two massive differences:
- you have available the full power of ClojureScript (you are just generating a clojure datastructure). The downside tradeoff is that these are not "designer friendly" HTML templates.
- these components are reactive. When their "inputs" change, they
are automatically rerun, producing new hiccup. reagent adroitly shields you from
the details, but
components
are wrapped by areaction
.
Summary: when the stream of data flowing into a component
changes, the component
is re-computed, producing a "stream" of output hiccup, which, as we'll see below, is turned into DOM and stitched into the GUI. Reagent largely looks after this part of the "flow" for us.
ReactJS
The complete data flow from data to DOM is:
ratom --> components --> Hiccup --> Reagent --> VDOM --> ReactJS --> DOM
Best to imagine this process as a pipeline of 3 functions. Each function takes data from the previous step, and produces data for the next step. In the next diagram, the three functions are marked. The unmarked nodes are data, produced by one step, becoming the input to the next step. hiccup, VDOM and DOM are all various forms of HTML markup (in our world that's data).
ratom --> components --> hiccup --> Reagent --> VDOM --> ReactJS --> DOM
f1 f2 f3
The combined three-function pipeline should be seen as a pure
function P
which takes a ratom as input, and produces DOM.
One way data flow:
ratom --> P --> DOM
This arrangement is:
- Easy to test. We put data into the ratom, allow the DOM to be rendered, and check that the right divs are in place. This would typically be done via phantomjs.
- Easily understood. Generally, components can be understood in isolation. In almost all cases, a component is genuinely a pure fucntion, or is conceptually a pure function.
The whole thing might be a multistep process, but we only have to bother ourselves with the writing of the components. Reagent/ReactJS looks after the rest.
If the ratom changes, the DOM changes. The DOM is a function of the ratom (state of the app).
But wait ... we do have to do some work to kick off the flow correctly ...
Subscriptions
Bback to the first part of our diagram:
app-db --> components --> hiccup
How does the flow begin. How does data flow from the app-db
to the components?
We want our say that components subscribe
to changes in app-db
.
XXX Talk about subscribe XXX Talk about registration of subscription handlers.
(subscribe [:pods]
components tend to be organised into a heirarchy and often data is flowing from parent to child compoentns.
But at certain points, for example at the root compoentns, something has to 'subscribe' to app-db
Event Flow
The data flow from app-db
to the DOM is the first half of the story. We now need to consider the 2nd part of the story: the data flow in the opposite direction.
In response to user interaction, a DOM will generate events like "the user clicked the delete button on item 42" or "the user unticked the checkbox for 'send me spam'".
These events have to "handled". The code doing this handling might mutate the ratom, or requrest more data from thet server, or POST somewhere, etc.
An app will have many handlers, and collectively they represent the control layer of the application.
The backward data flow happens in one (conveyor belt) hop:
app-db --> components --> Hiccup --> Reagent --> VDOM --> ReactJS --> 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. It is the state. And the DOM presented to the user is a function of that state. So that's the cycle. GUI events cause app-db
change, which then causes a rerender, and the users sees something different.
So handlers which look after events, are the part of the system which does app-db
mutation. You
could almost imagine them as a "stored procedure" in a
database. Almost. Stretching it? We do like our in-memory
database analogies.
What are events?
Events are data. You choose the format.
Our implementation chooses to represent events as vectors. For example:
[:delete-item 42]
The first item in the vector identifies the event and the rest of the vector is the optional parameters -- in this cse, the id (42) of the item to delete.
Here are some other example events:
[:set-spam-wanted false]
[[:complicated :multi :part :key] "a parameter" "another one" 45.6]
Back To The DOM
Events start in the DOM. They are dispatched
.
For example, a button component might look like this:
(defn yes-button
[]
[:div {:class "button-class"
:on-click #(dispatch [:yes-button-clicked])}
"Yes"])
Notice the on-click
handler:
#(dispatch [:yes-button-clicked])
With re-frame, we try to keep the DOM as passive as possible. It is simply a rendering of the data. So that "on-click" is a simple as we can make it.
There is a signle dispatch
function in the entire app, and it takes only one paramter, the event.
Let's update our diagram:
app-db --> components --> Hiccup --> Reagent --> VDOM --> ReactJS --> DOM
^ |
| v
handlers <------------------------------------------------------ (dispatch [event-id other stuff])
a "conveyor belt" takes events
from the DOM to the handlers
Routing
Once they are dispatched, events have to be routed to a handler.
In re-frame, handlers have to be registered.
dispatch
can be implemtned in There's a bunch of ways to implement "dispatch events". You could push the events into a core.asyc channel. Or you could call a dispatch
multimethod, and find the right event handler by inspection of first
on the event vectory.
We use a technique in which the
Events are then routed to the right handler via a conveyor belt. Remember, an event is just data. And it is flowing in the opposite direction to the data which causes the DOm to be rendered in the first place.
and routed to the right handler.
So here's what a
When an event reaches the end of the conveyor belt, it has to be routed to the right handler -- the one which handles this kind of event.
So something has to look at first
in event vector cand know how to call the right handler.
The conveyor belt could easily be done via core.async, but we do it the simplest possible way.
Event Handlers
Collectively, event handlers provide the control logic in the applications.
The job of many event handlers is to change the ratom in some way. Add an item here. Delete this one. So often CRUD.
Even though they appear to be about mutation, event handlers are implemented as pure fucntions.
(ratom-state, event) -> ratom-state
It is re-frame which feeds the current state in ratom into the handler (along with the event), and the job of a handler to to return a modified version of the data in ratom (whcih re-frame will then put back into the ratom -- ensuring an undo/redo is available).
But I repeat, the handlers themselves are written as pure functions, and this makes it nice and easy to test and understand them.