Maybe we need some sort of lazy map where:
(def m (assoc-computed {:first-name "Robert" :last-name "Plankton"}
:full-name #(str (:first-name %) " " (:last-name
%))))
;; will call the function to compute the value and will memoize it:
(:full-name m)
;; now the memoized value is returned without calling the function
(:full-name m)
;; equality / hashing will trigger computation+memoization of all m
;; computed keys if they aren't computed yet:
(= m other-map)
Computing functions must be pure, so m internally is a mutable object but
you can't really distinguish it from an immutable one :)
Saludos,
Nahuel Greco.
On Sat, Oct 18, 2014 at 5:02 PM, Mark Engelberg <[email protected]>
wrote:
> I think all of James' points about the proven value of structuring an
> application primarily around data rather than a complex API are right on
> point. It is one of the things I love about the Clojure philosophy.
>
> But there's nothing about the value of data-driven development that
> requires data lookups and data computations to be so different. There's
> plenty of room for Clojure to have continued evolution in this area and
> still preserve the essence of its approach.
>
> For example, consider that several years ago, Rich declared that Clojure
> would never have a simple mutable box. But lo and behold, now we have
> volatiles. Consider the rise of records, protocols, and components -- a
> lot of judiciously applied OOish concepts.
>
> I really enjoy introducing Java programmers to the Clojure way of thinking
> about data. But when I do, I like to explain the current thinking in the
> Clojure community, talk about some of the most triumphant success stories
> (e.g., Ring), acknowledge some of the pain points, talk about some of the
> ways that Clojure has grown to handle other data modeling pain points, and
> some of the ways that Clojure may continue to grow.
>
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