It's become an obsession of mine to reduce the lines of code that I write in Lisp/Clojure. I am trying to make the following code (essentially a depth first search) shorter.
(defn find-node [nodeid in-node]
(if (= nodeid (:id in-node))
in-node
(loop [node nil activities (:activities in-node)]
(if (or (empty? activities) (not (nil? node)))
node
(recur (find-node nodeid (first activities)) (rest activities))))))
(defn find-node-in-graph [nodeid node activities]
(if (empty? activities)
node
(recur nodeid (find-node nodeid (first activities)) (rest activities))))
(defrecord Graph [id name activities])
(defrecord Node [id name activities])
"activities" is a list
This might be cheating, though it's only one line ;)
(def tree {:id 1 :children [{:id 2 :children [{:id 3}]} {:id 4}]})
core> (filter #(= 3 (:id %)) (tree-seq :children :children tree))
({:id 3})
core> (filter #(= 2 (:id %)) (tree-seq :children :children tree))
({:children [{:id 3}], :id 2})
Some points on the original intent of the question:
loop/recer is often not the most compact form, it wan usually be written with map or doseq
if/recur can often be replaced with a call to filter
If you seem to really need to write something like this because of some specific requirement, often zippers will solve the problem more elegantly.
Related
I have (for instance) a mix of data structures such as {:name "Peter" :children "Mark"} and {:name "Mark" :children ["Julia" "John"] i.e. :children value is either a single string or a collection of strings. Other functions in my code expect that the value of :children is always a collection of strings, so I need to adapt the data for them.
Of course I can use something like:
(defn data-adapter [m]
(let [children (:children m)]
(assoc m :children
(if (coll? children)
children
[children]))))
But is there a more idiomatic/laconic way?
I think you will have to take no for an answer.
(if (coll? x) x [x]) is about as terse and expressive as it gets. It’s what people usually use for this problem (sometimes with sequential? instead of coll?).
cond-> enthusiasts like me sometimes try to use it in place of a simple conditional, but here it is no improvement:
(cond-> x (not (coll? x)) vector)
In the context of your code, however, you can do a little better. A lookup and association is best expressed with update:
(defn data-adapter [m]
(update m :children #(if (coll? %) % [%])))
the only advice would be to abstract that logic to some function, to keep your actual business logic clean.
(defn data-adapter [m]
(let [children (:children m)]
(assoc m :children (ensure-coll children))))
or, more concise, with update:
(defn data-adapter [m]
(update m :children ensure-coll))
where ensure-coll could be something like this:
(defn iffun [check & {:keys [t f] :or {t identity f identity}}]
#((if (check %) t f) %))
(def ensure-coll (iffun coll? :f list))
(or whatever another implementation you like)
user> (data-adapter {:children 1})
;;=> {:children (1)}
user> (data-adapter {:children [1]})
;;=> {:children [1]}
Perhaps not idiomatic, but laconic:
(flatten [x])
https://clojuredocs.org/clojure.core/flatten
Let's say I have several vectors
(def coll-a [{:name "foo"} ...])
(def coll-b [{:name "foo"} ...])
(def coll-c [{:name "foo"} ...])
and that I would like to see if the names of the first elements are equal.
I could
(= (:name (first coll-a)) (:name (first coll-b)) (:name (first coll-c)))
but this quickly gets tiring and overly verbose as more functions are composed. (Maybe I want to compare the last letter of the first element's name?)
To directly express the essence of the computation it seems intuitive to
(apply = (map (comp :name first) [coll-a coll-b coll-c]))
but it leaves me wondering if there's a higher level abstraction for this sort of thing.
I often find myself comparing / otherwise operating on things which are to be computed via a single composition applied to multiple elements, but the map syntax looks a little off to me.
If I were to home brew some sort of operator, I would want syntax like
(-op- (= :name first) coll-a coll-b coll-c)
because the majority of the computation is expressed in (= :name first).
I'd like an abstraction to apply to both the operator & the functions applied to each argument. That is, it should be just as easy to sum as compare.
(def coll-a [{:name "foo" :age 43}])
(def coll-b [{:name "foo" :age 35}])
(def coll-c [{:name "foo" :age 28}])
(-op- (+ :age first) coll-a coll-b coll-c)
; => 106
(-op- (= :name first) coll-a coll-b coll-c)
; => true
Something like
(defmacro -op-
[[op & to-comp] & args]
(let [args' (map (fn [a] `((comp ~#to-comp) ~a)) args)]
`(~op ~#args')))
Is there an idiomatic way to do this in clojure, some standard library function I could be using?
Is there a name for this type of expression?
For your addition example, I often use transduce:
(transduce
(map (comp :age first))
+
[coll-a coll-b coll-c])
Your equality use case is trickier, but you could create a custom reducing function to maintain a similar pattern. Here's one such function:
(defn all? [f]
(let [prev (volatile! ::no-value)]
(fn
([] true)
([result] result)
([result item]
(if (or (= ::no-value #prev)
(f #prev item))
(do
(vreset! prev item)
true)
(reduced false))))))
Then use it as
(transduce
(map (comp :name first))
(all? =)
[coll-a coll-b coll-c])
The semantics are fairly similar to your -op- macro, while being both more idiomatic Clojure and more extensible. Other Clojure developers will immediately understand your usage of transduce. They may have to investigate the custom reducing function, but such functions are common enough in Clojure that readers can see how it fits an existing pattern. Also, it should be fairly transparent how to create new reducing functions for use cases where a simple map-and-apply wouldn't work. The transducing function can also be composed with other transformations such as filter and mapcat, for cases when you have a more complex initial data structure.
You may be looking for the every? function, but I would enhance clarity by breaking it down and naming the sub-elements:
(let [colls [coll-a coll-b coll-c]
first-name (fn [coll] (:name (first coll)))
names (map first-name colls)
tgt-name (first-name coll-a)
all-names-equal (every? #(= tgt-name %) names)]
all-names-equal => true
I would avoid the DSL, as there is no need and it makes it much harder for others to read (since they don't know the DSL). Keep it simple:
(let [colls [coll-a coll-b coll-c]
vals (map #(:age (first %)) colls)
result (apply + vals)]
result => 106
I don't think you need a macro, you just need to parameterize your op function and compare functions. To me, you are pretty close with your (apply = (map (comp :name first) [coll-a coll-b coll-c])) version.
Here is one way you could make it more generic:
(defn compare-in [op to-compare & args]
(apply op (map #(get-in % to-compare) args)))
(compare-in + [0 :age] coll-a coll-b coll-c)
(compare-in = [0 :name] coll-a coll-b coll-c)
;; compares last element of "foo"
(compare-in = [0 :name 2] coll-a coll-b coll-c)
I actually did not know you can use get on strings, but in the third case you can see we compare the last element of each foo.
This approach doesn't allow the to-compare arguments to be arbitrary functions, but it seems like your use case mainly deals with digging out what elements you want to compare, and then applying an arbitrary function to those values.
I'm not sure this approach is better than the transducer version supplied above (certainly not as efficient), but I think it provides a simpler alternative when that efficiency is not needed.
I would split this process into three stages:
transform items in collections into the data in collections you want to operate
on - (map :name coll);
Operate on transformed items in collections, returning collection of results - (map = transf-coll-a transf-coll-b transf-coll-c)
Finally, selecting which result in resulting collection to return - (first calculated-coll)
When playing with collections, I try to put more than one item into collection:
(def coll-a [{:name "foo" :age 43} {:name "bar" :age 45}])
(def coll-b [{:name "foo" :age 35} {:name "bar" :age 37}])
(def coll-c [{:name "foo" :age 28} {:name "bra" :age 30}])
For example, matching items by second char in :name and returning result for items in second place:
(let
[colls [coll-a coll-b coll-c]
transf-fn (comp #(nth % 1) :name)
op =
fetch second]
(fetch (apply map op (map #(map transf-fn %) colls))))
;; => false
In transducers world you can use sequence function which also works on multiple collections:
(let
[colls [coll-a coll-b coll-c]
transf-fn (comp (map :name) (map #(nth % 1)))
op =
fetch second]
(fetch (apply sequence (map op) (map #(sequence transf-fn %) colls))))
Calculate sum of ages (for all items at the same level):
(let
[colls [coll-a coll-b coll-c]
transf-fn (comp (map :age))
op +
fetch identity]
(fetch (apply sequence (map op) (map #(sequence transf-fn %) colls))))
;; => (106 112)
Given I have this action to perform
(def structure (atom [{:id "an-id"} {:id "another-id"}]))
(def job {:type "some-job"})
(reset! structure (map #(if (= "an-id" (:id %)) (update-in % [:performed-jobs] (fnil conj []) job) %) #structure))
next structure:
[{:id "an-id" :performed-jobs [{:type "some-job"}]} {:id "another-id"}]
How can I use swap! to change a single occurrence in my structure instead of resetting it all?
Replace reset! by swap! by giving it a function that takes the old value of the atom and returns a new value to store in the atom.
Replace dereferencing of the atom with the function's argument, the old value.
(swap! structure
(fn [old]
(map #(if (= "an-id" (:id %))
(update-in % [:performed-jobs]
(fnil conj []) job) %)
old)))
I have an atom called app-state that holds a map. It looks like this:
{:skills [{:id 1 :text "hi"} {:id 2 :text "yeah"}]}
What is the idiomatic way to remove the element inside the vector with :id = 2 ? The result would look like:
{:skills [{:id 1 :text "hi"}]}
...
So far, I have this:
(defn new-list [id]
(remove #(= id (:id %)) (get #app-state :skills)))
swap! app-state assoc :skills (new-list 2)
It works, but I feel like this isn't quite right. I think it could be something like:
swap! app-state update-in [:skills] remove #(= id (:id %))
But this doesn't seem to work.
Any help is much appreciated!
Try this:
(defn new-list [app-state-map id]
(assoc app-state-map :skills (into [] (remove #(= id (:id %)) (:skills app-state-map)))))
(swap! app-state new-list 2)
swap! will pass the current value of the atom to the function you supply it. There's no need to dereference it yourself in the function.
See the docs on swap! for more details.
(swap! state update :skills (partial remove (comp #{2} :id)))
(def skills {:skills [{:id 1 :text "hi"} {:id 2 :text "yeah"}]})
(defn remove-skill [id]
(update skills :skills (fn [sks] (vec (remove #(= id (:id %)) sks)))))
You would then be able to call say (remove-skill 1) and see that only the other one (skill with :id of 2) is left.
I like your way better. And this would need to be adapted for use against an atom.
You can use filter to do this. Here is a function that takes an id and the map and let's you filter out anything that doesn't match your criteria. Of course, you can make the #() reader macro check for equality rather than inequality depending on your needs.
user=> (def foo {:skills [{:id 1 :text "hi"} {:id 2 :text "yeah"}]})
#'user/foo
user=> (defn bar [id sklz] (filter #(not= (:id %) id) (:skills sklz)))
#'user/bar
user=> (bar 1 foo)
({:id 2, :text "yeah"})
user=> (bar 2 foo)
({:id 1, :text "hi"})
I'm trying to pull the values out of a complicated list structure.
Given something like this:
[{:a "whatever" :b [:c "foo"]} :e {:f "boo"} :g {:h [:i 62281]}]
I'd like to get:
["whatever" "foo" "boo" 62281]
So far I've only gotten to this point:
((62281) nil (boo) nil whatever foo)
Here's the code:
(defn get-values [params]
(apply conj
(map (fn [part]
(if (not (keyword? part))
(map (fn [v]
(if (vector? v)
(last v)
v))
(vals part))))
params)))
I can't seem to get rid of the nil's
I can't figure out why the values after a certain point are in lists.
I figure there's got to be a better way to do this.
Fix the data structure and everything will fall in place. As of now your data structure isn't consistent at all and that will make any function that touch this data way more complicated and error prone. You can model this data as a map:
(def data {:a "whatever"
:b nil
:c "foo"
:e nil
:f "boo"
:g nil
:h nil
:i 62281})
And then to get the desired result:
(->> (vals data)
(filter (comp not nil?))
(into []))
But for some strange reason you still want to parse the data structure you provided then:
(defn get-values [data]
(->> (map #(if (map? %) (into [] %) %) data)
flatten
(filter #(or (string? %) (number? %)))
(into [])))