I'm working through a book on clojure and ran into a stumbling block with "->>". The author provides an example of a comp that converts camelCased keywords into a clojure map with a more idiomatic camel-cased approach. Here's the code using comp:
(require '[clojure.string :as str])
(def camel->keyword (comp keyword
str/join
(partial interpose \-)
(partial map str/lower-case)
#(str/split % #"(?<=[a-z])(?=[A-Z])")))
This makes a lot of sense, but I don't really like using partial all over the place to handle a variable number of arguments. Instead, an alternative is provided here:
(defn camel->keyword
[s]
(->> (str/split s #"(?<=[a-z])(?=[A-Z])")
(map str/lower-case)
(interpose \-)
str/join
keyword))
This syntax is much more readable, and mimics the way I would think about solving a problem (front to back, instead of back to front). Extending the comp to complete the aforementioned goal...
(def camel-pairs->map (comp (partial apply hash-map)
(partial map-indexed (fn [i x]
(if (odd? i)
x
(camel->keyword x))))))
What would be the equivalent using ->>? I'm not exactly sure how to thread map-indexed (or any iterative function) using ->>. This is wrong:
(defn camel-pairs->map
[s]
(->> (map-indexed (fn [i x]
(if (odd? i)
x
(camel-keyword x)))
(apply hash-map)))
Three problems: missing a parenthesis, missing the > in the name of camel->keyword, and not "seeding" your ->> macro with the initial expression s.
(defn camel-pairs->map [s]
(->> s
(map-indexed
(fn [i x]
(if (odd? i)
x
(camel->keyword x))))
(apply hash-map)))
Is this really more clear than say?
(defn camel-pairs->map [s]
(into {}
(for [[k v] (partition 2 s)]
[(camel->keyword k) v])))
Related
How would I create a transducer from the following ordinary code, where combo is the alias for clojure.math.combinatorics:
(defn row->evenly-divided [xs]
(->> (combo/combinations (sort-by - xs) 2)
(some (fn [[big small]]
(assert (>= big small))
(let [res (/ big small)]
(when (int? res)
res))))))
As noted in a comment transducers are only applicable for processing each item. With this is mind I've made the code a little more transducer friendly by shifting the sorting so that it is now being done for each item. I don't think there's anything that can be done about the combinations part however!
(defn row->evenly-divided [xs]
(->> (combo/combinations xs 2)
(some (fn [xy]
(let [res (apply / (sort-by - xy))]
(when (int? res)
res))))))
This is the same function but with an introduced transducer:
(def x-row->evenly-divided (comp
(map (partial sort-by -))
(map (partial apply /))
(filter int?)))
(defn row->evenly-divided-2 [xs]
(->> (combo/combinations xs 2)
(sequence x-row->evenly-divided)
first))
Given the following data structure, I want to ask for "services-list" (a component) and receive back "entity-list" (a style).
(def style->components {"entity-list" ["services-list" "employee-list" "clients-list"]})
My solution is not so elegant:
(defn get-style-name [comp-name]
(-> (filter (fn [map-entry]
(let [v (val map-entry)
found-comp (some #(= % comp-name) v)]
found-comp
)) style->components)
first
first))
Is there a better way? Perhaps my problem started with the way I structured the data.
you can make it shorter and more clojurish this way:
(defn get-style-name [comp-name]
(ffirst (filter (fn [[_ v]]
(some #{comp-name} v))
component->style)))
there is a function ffirst, that works exactly like (first (first %))
using a destructuring in the filter function signature, you can retrieve the value of the map entry, avoiding unneeded let
instead of this function in some: #(= % comp-name) it is quite common to use the set: #{comp-name}
then you can use some instead of filter, as it returns the first logical true value returned by function, so you can remove ffirst:
(defn get-style-name [comp-name]
(some (fn [[k v]]
(when (some #{comp-name} v) k))
component->style))
also, if you change your data structure to use set instead of vector, you can make it even shorter:
(def component->style {"entity-list" #{"services-list"
"employee-list"
"clients-list"}})
(defn get-style-name [comp-name]
(some (fn [[k v]] (when (v comp-name) k))
component->style))
Just to add another alternative, nested sequence operations usually lend themselves to replacement with for:
(defn get-style-name
[comp-name]
(first
(for [[style-name comp-names] style->components
comp-name' comp-names
:when (= comp-name comp-name')]
style-name)))
Still, I'd prefer a solution where the mapping of component name to style name is pre-computed, e.g.
(def get-style-name
(->> (for [[style-name comp-names] style->components
comp-name comp-names]
[comp-name style-name])
(into {})))
This way, you avoid traversing the style->components map on every lookup.
I want to read file entries in a zip file into a sequence of strings if possible. Currently I'm doing something like this to print out directory names for example:
(defn entries [zipfile]
(lazy-seq
(if-let [entry (.getNextEntry zipfile)]
(cons entry (entries zipfile)))))
(defn with-each-entry [fileName f]
(with-open [z (ZipInputStream. (FileInputStream. fileName))]
(doseq [e (entries z)]
; (println (.getName e))
(f e)
(.closeEntry z))))
(with-each-entry "tmp/my.zip"
(fn [e] (if (.isDirectory e)
(println (.getName e)))))
However this will iterate through the entire zip file. How could I change this so I could take the first few entries say something like:
(take 10 (zip-entries "tmp/my.zip"
(fn [e] (if (.isDirectory e)
(println (.getName e)))))
This seems like a pretty natural fit for the new transducers in CLJ 1.7.
You just build up the transformations you want as a transducer using comp and the usual seq-transforming fns with no seq/collection argument. In your example cases,
(comp (map #(.getName %)) (take 10)) and
(comp (filter #(.isDirectory %)) (map #(-> % .getName println))).
This returns a function of multiple arities which you can use in a lot of ways. In this case you want to eagerly reduce it over the entries sequence (to ensure realization of the entries happens inside with-open), so you use transduce (example zip data made by zipping one of my clojure project folders):
(with-open [z (-> "training-day.zip" FileInputStream. ZipInputStream.)]
(let[transform (comp (map #(.getName %)) (take 10))]
(transduce transform conj (entries z))))
;;return value: [".gitignore" ".lein-failures" ".midje-grading-config.clj" ".nrepl-port" ".travis.yml" "project.clj" "README.md" "target/" "target/classes/" "target/repl-port"]
Here I'm transducing with base function conj which makes a vector of the names. If you instead want your transducer to perform side-effects and not return a value, you can do that with a base function like (constantly nil):
(with-open [z (-> "training-day.zip" FileInputStream. ZipInputStream.)]
(let[transform (comp (filter #(.isDirectory %)) (map #(-> % .getName println)))]
(transduce transform (constantly nil) (entries z))))
which gives output:
target/
target/classes/
target/stale/
test/
A potential downside with this is that you'll probably have to manually incorporate .closeEntry calls into each transducer you use here to prevent holding those resources, because you can't in the general case know when each transducer is done reading the entry.
I'm trying to figure out the best way to troll a namespace for functions that contain a specific bit of metadata. I've come up with a solution, but it feels a little awkward and I'm not at all sure I'm going about it the right way. There's a second component to this as well: I don't just want the names of the functions, I want to find them and then execute them. Here's a snippet of what I'm doing presently:
(defn wrap-routes
[req from-ns]
(let [publics (ns-publics from-ns)
routes (->>
(keys publics)
(map #(meta (% publics)))
(filter #(= (:route-handler %) true))
(map #(:name %)))
resp (first
(->>
(map #((% publics) req) routes)
(filter #(:status %))))]
(or resp not-found)))
As you can see, I'm doing all sorts of gymnastics to see if my metadata is attached to any functions in a given namespace and then am doing extra work after that to get the actual function back. I'm sure there must be a better way. So my question is, how would you do this?
(defn wrap-routes [req from-ns]
(or (first (filter :status
(for [[name f] (ns-publics from-ns)
:when (:route-handler (meta f))]
(f req))))
not-found))
You can do something like this:
(defn wrap-routes
[req from-ns]
(->> (ns-publics from-ns)
(filter #(:route-handler (meta (%1 1))))
(map #((%1 1) req))
(filter #(:status %))
first
(#(or % not-found))))
I had an idea for a higher-order function today that I'm not sure how to write. I have several sparse, lazy infinite sequences, and I want to create an abstraction that lets me check to see if a given number is in any of these lazy sequences. To improve performance, I wanted to push the values of the sparse sequence into a hashmap (or set), dynamically increasing the number of values in the hashmap whenever it is necessary. Automatic memoization is not the answer here due to sparsity of the lazy seqs.
Probably code is easiest to understand, so here's what I have so far. How do I change the following code so that the predicate uses a closed-over hashmap, but if needed increases the size of the hashmap and redefines itself to use the new hashmap?
(defn make-lazy-predicate [coll]
"Returns a predicate that returns true or false if a number is in
coll. Coll must be an ordered, increasing lazy seq of numbers."
(let [in-lazy-list? (fn [n coll top cache]
(if (> top n)
(not (nil? (cache n)))
(recur n (next coll) (first coll)
(conj cache (first coll)))]
(fn [n] (in-lazy-list? n coll (first coll) (sorted-set)))))
(def my-lazy-list (iterate #(+ % 100) 1))
(let [in-my-list? (make-lazy-predicate my-lazy-list)]
(doall (filter in-my-list? (range 10000))))
How do I solve this problem without reverting to an imperative style?
This is a thread-safe variant of Adam's solution.
(defn make-lazy-predicate
[coll]
(let [state (atom {:mem #{} :unknown coll})
update-state (fn [{:keys [mem unknown] :as state} item]
(let [[just-checked remainder]
(split-with #(<= % item) unknown)]
(if (seq just-checked)
(-> state
(assoc :mem (apply conj mem just-checked))
(assoc :unknown remainder))
state)))]
(fn [item]
(get-in (if (< item (first (:unknown #state)))
#state
(swap! state update-state item))
[:mem item]))))
One could also consider using refs, but than your predicate search might get rolled back by an enclosing transaction. This might or might not be what you want.
This function is based on the idea how the core memoize function works. Only numbers already consumed from the lazy list are cached in a set. It uses the built-in take-while instead of doing the search manually.
(defn make-lazy-predicate [coll]
(let [mem (atom #{})
unknown (atom coll)]
(fn [item]
(if (< item (first #unknown))
(#mem item)
(let [just-checked (take-while #(>= item %) #unknown)]
(swap! mem #(apply conj % just-checked))
(swap! unknown #(drop (count just-checked) %))
(= item (last just-checked)))))))