I would like to update values in hashes, but I'm not sure how this can be done efficiently
I tried using a loop approach, but keeping the previous record's value also in account seems like a big challenge.
This is what I am trying to do,
Considering the records are sorted based on created_at in descending order, For example,
[{:id 1, :created_at "2016-08-30 11:07:00"}{:id 2, :created_at "2016-08-30 11:05:00"}...]
]
; Basically in humanised form.
Could anyone share some ideas to achieve this? Thanks in advance.
Simplified example:
(def data [{:value 10} {:value 8} {:value 3}])
(conj
(mapv
(fn [[m1 m2]] (assoc m1 :difference (- (:value m1) (:value m2))))
(partition 2 1 data))
(last data))
;;=> [{:value 10, :difference 2} {:value 8, :difference 5} {:value 3}]
what you need, is to iterate over all the pairs of consecutive records, keeping the first of them, adding the difference to it.
first some utility functions for dates handling:
(defn parse-date [date-str]
(.parse (java.text.SimpleDateFormat. "yyyy-MM-dd HH:mm:ss") date-str))
(defn dates-diff [date-str1 date-str2]
(- (.getTime (parse-date date-str1))
(.getTime (parse-date date-str2))))
then the mapping part:
user> (def data [{:id 1, :created_at "2016-08-30 11:07:00"}
{:id 2, :created_at "2016-08-30 11:05:00"}
{:id 3, :created_at "2016-08-30 10:25:00"}])
user> (map (fn [[rec1 rec2]]
(assoc rec1 :difference
(dates-diff (:created_at rec1)
(:created_at rec2))))
(partition 2 1 data))
({:id 1, :created_at "2016-08-30 11:07:00", :difference 120000}
{:id2, :created_at "2016-08-30 11:05:00", :difference 2400000})
notice that it doesn't contain the last item, since it was never the first item of a pair. So you would have to add it manually:
user> (conj (mapv (fn [[rec1 rec2]]
(assoc rec1 :difference
(dates-diff (:created_at rec1)
(:created_at rec2))))
(partition 2 1 data))
(assoc (last data) :difference ""))
[{:id 1, :created_at "2016-08-30 11:07:00", :difference 120000}
{:id 2, :created_at "2016-08-30 11:05:00", :difference 2400000}
{:id 3, :created_at "2016-08-30 10:25:00", :difference ""}]
now it's ok. The only difference with your desired variant, is that the diff is in millis, rather than formatted string. To do that you can add the formatting to the dates-diff function.
Related
My problem is next, i have list of maps, for example:
({:id 1 :request-count 10 ..<another key-value pair>..}
{:id 2 :request-count 15 ..<another key-value pair>..}
...)
Need create map with records in which, key is value of 'id' and value is value of 'request-count', for each map from prev example, like:
{1 10
2 15
...}
I know how to do this. My question is - standard library have function for achieve this? Or maybe i can achiev this with combination few function, without 'reduce'?
Use the juxt function to generate a sequence of pairs, and then toss them into a map:
(into {} (map (juxt :id :request-count) data))
Example:
user=> (def data [{:id 1 :request-count 10 :abc 1}
#_=> {:id 2 :request-count 15 :def 2}
#_=> {:id 3 :request-count 20 :ghi 3}])
#'user/data
user=> (into {} (map (juxt :id :request-count) data))
{1 10, 2 15, 3 20}
Be aware that if there is more than one map in data with the same :id, then the last one encountered by map will be the one that survives in the output map.
I would do it like so:
(def data
[{:id 1 :request-count 10}
{:id 2 :request-count 15}] )
(defn make-id-req-map [map-seq]
(vec (for [curr-map map-seq]
(let [{:keys [id request-count]} curr-map]
{id request-count}))))
With result:
(make-id-req-map data) => [{1 10} {2 15}]
Note: while you could combine the map destructuring into the for statement, I usually like to label the intermediate values as described in Martin Fowler's refactoring "Introduce Explaining Variable".
I need some help with maps. After I get data with jdbc/query from a database, the result looks like this:
({:product_id 1, :name product1, :rating 3.000M}
{:product_id 2, :name product2, :rating 1.333M}
{:product_id 3, :name product3}, :rating nil)
I want to display everything with Selmer, but I just want only 1 number after the comma. Something like this:
({:product_id 1, :name product1, :rating 3.0}
{:product_id 2, :name product2, :rating 1.3}
{:product_id 3, :name product3}, :rating nil)
I found out, how to iterate over a map, but i dont know how to change the specific value. The query data is saved in data
(doseq [keyval data]
(doseq [keyval2 keyval]
(doseq [keyval3 keyval2]
(prn keyval3))))
Can you help me create a new data variable. Thanks!
clojure data is immutable, so you can't update it in a common way. Rather you make the copy of your data adding the needed changes using clojure's data manipulation functions. Nice introduction can be found here: http://www.braveclojure.com/functional-programming/
so what you do is something like this
user> (defn round-to [^Double num places] (when num (Math/round num)))
#'user/round-to ;; not-a-real-round-to (simplified for brevity)
user> (def data '({:product_id 1, :name product1, :rating 3.000M}
{:product_id 2, :name product2, :rating 1.333M}
{:product_id 3, :name product3, :rating nil}))
#'user/data
user> (map #(update % :rating round-to 2) data)
;;=> ({:product_id 1, :name product1, :rating 3}
;; {:product_id 2, :name product2, :rating 1}
;; {:product_id 3, :name product3, :rating nil})
(defn round2
"Round a double to the given precision (number of significant digits)"
[precision d]
(let [factor (Math/pow 10 precision)]
(/ (Math/round (* d factor)) factor)))
(map #(assoc % :rating (when-some [r (:rating %)] (round2 1 r)))
'({:product_id 1, :name 'product1, :rating 3.000M}
{:product_id 2, :name 'product2, :rating 1.333M}
{:product_id 3, :name 'product3, :rating nil}))
Given a vector:
(def vec [{:key 1, :value 10, :other "bla"}, {:key 2, :value 13, :other "bla"}, {:key 1, :value 7, :other "bla"}])
I'd like to iterate over each element and update :value with the sum of all :values to that point, so I would have:
[{:key 1, :value 10, :other "bla"}, {:key 2, :value 23, :other "bla"}, {:key 1, :value 30, :other "bla"}])
I've found this for printing the result, but I've tried to change the prn command to update-in, assoc-in in the code below (extracted from the link above) but I didn't work quite well.
(reduce (fn [total {:keys [key value]}]
(let [total (+ total value)]
(prn key total)
total))
0 vec)
I'm new to Clojure, how can I make it work?
If you want to get the running totals then the simplest way is to use reductions:
(reductions (fn [acc ele] (+ acc (:value ele)))
0
[{:key 1, :value 10, :other "bla"}, {:key 2, :value 13, :other "bla"}, {:key 1, :value 7, :other "bla"}])
;; => (0 10 23 30)
As you can see the function you pass to reductions has the same signature as the function you pass to a reduce. It is like you are asking for a reduce to be done every time a new element is reached. Another way of thinking about it is that every time a new accumulator is calculated it is kept, unlike with reduce where the caller only gets to see the result of the last calculation.
And so this is the code that would directly answer your question:
(->> [{:key 1, :value 10, :other "bla"}, {:key 2, :value 13, :other "bla"}, {:key 1, :value 7, :other "bla"}]
(reductions #(update %2 :value + (:value %1))
{:value 0})
next
vec)
;; => [{:key 1, :value 10, :other "bla"} {:key 2, :value 23, :other "bla"} {:key 1, :value 30, :other "bla"}]
You can accumulate the :values thus:
(reductions + (map :value v))
=> (10 23 30)
(I renamed the vector v to avoid tripping over clojure.core/vec.)
Then you can use mapv over assoc:
(let [value-sums (reductions + (map :value v))]
(mapv #(assoc %1 :value %2) v value-sums))
=> [{:key 1, :value 10, :other "bla"} {:key 2, :value 23, :other "bla"} {:key 1, :value 30, :other "bla"}]
I have a collection of maps
(def a '({:id 9345 :value 3 :type "orange"}
{:id 2945 :value 2 :type "orange"}
{:id 145 :value 3 :type "orange"}
{:id 2745 :value 6 :type "apple"}
{:id 2345 :value 6 :type "apple"}))
I want to group this first by value, followed by type.
My output should look like:
{
:orange [{
:value 3,
:id [9345, 145]
}, {
:value 2,
:id [2935]
}],
:apple [{
:value 6,
:id [2745, 2345]
}]
}
How would I do this in Clojure? Appreciate your answers.
Thanks!
Edit:
Here is what I had so far:
(defn by-type-key [data]
(group-by #(get % "type") data))
(reduce-kv
(fn [m k v] (assoc m k (reduce-kv
(fn [sm sk sv] (assoc sm sk (into [] (map #(:id %) sv))))
{}
(group-by :value (map #(dissoc % :type) v)))))
{}
(by-type-key a))
Output:
=> {"orange" {3 [9345 145], 2 [2945]}, "apple" {6 [2745 2345], 3 [125]}}
I just couldnt figure out how to proceed next...
Your requirements are a bit inconsistent (or rather irregular) - you use :type values as keywords in the result, but the rest of the keywords are carried through. Maybe that's what you must do to satisfy some external formats - otherwise you need to either use the same approach as with :type through, or add a new keyword to the result, like :group or :rows and keep the original keywords intact. I will assume the former approach for the moment (but see below, I will get to the shape as you want it,) so the final shape of data is like
{:orange
{:3 [9345 145],
:2 [2945]},
:apple
{:6 [2745 2345]}
}
There is more than one way of getting there, here's the gist of one:
(group-by (juxt :type :value) a)
The result:
{["orange" 3] [{:id 9345, :value 3, :type "orange"} {:id 145, :value 3, :type "orange"}],
["orange" 2] [{:id 2945, :value 2, :type "orange"}],
["apple" 6] [{:id 2745, :value 6, :type "apple"} {:id 2345, :value 6, :type "apple"}]}
Now all rows in your collection are grouped by the keys you need. From this, you can go and get the shape you want, say to get to the shape above you can do
(reduce
(fn [m [k v]]
(let [ks (map (comp keyword str) k)]
(assoc-in m ks
(map :id v))))
{}
(group-by (juxt :type :value) a))
The basic idea is to get the rows grouped by the key sequence (and that's what group-by and juxt do,) and then combine reduce and assoc-in or update-in to beat the result into place.
To get exactly the shape you described:
(reduce
(fn [m [k v]]
(let [type (keyword (first k))
value (second k)
ids (map :id v)]
(update-in m [type]
#(conj % {:value value :id ids}))))
{}
(group-by (juxt :type :value) a))
It's a bit noisy, and it might be harder to see the forest for the trees - that's why I simplified the shape, to highlight the main idea. The more regular your shapes are, the shorter and more regular your functions become - so if you have control over it, try to make it simpler for you.
I would do the transform in two stages (using reduce):
the first to collect the values
the second for formating
The following code solves your problem:
(def a '({:id 9345 :value 3 :type "orange"}
{:id 2945 :value 2 :type "orange"}
{:id 145 :value 3 :type "orange"}
{:id 2745 :value 6 :type "apple"}
{:id 2345 :value 6 :type "apple"}))
(defn standardise [m]
(->> m
;; first stage
(reduce (fn [out {:keys [type value id]}]
(update-in out [type value] (fnil #(conj % id) [])))
{})
;; second stage
(reduce-kv (fn [out k v]
(assoc out (keyword k)
(reduce-kv (fn [out value id]
(conj out {:value value
:id id}))
[]
v)))
{})))
(standardise a)
;; => {:orange [{:value 3, :id [9345 145]}
;; {:value 2, :id [2945]}],
;; :apple [{:value 6, :id [2745 2345]}]}
the output of the first stage is:
(reduce (fn [out {:keys [type value id]}]
(update-in out [type value] (fnil #(conj % id) [])))
{}
a)
;;=> {"orange" {3 [9345 145], 2 [2945]}, "apple" {6 [2745 2345]}}
You may wish to use the built-in function group-by. See http://clojuredocs.org/clojure.core/group-by
I am writing a piece of code that needs to read in a text file that has data. The text file is in the format:
name 1 4
name 2 4 5
name 3 1 9
I am trying to create a vector of a map in the form [:name Sarah :weight 1 cost :4].
When I try reading the file in with the line-seq reader, it reads each line as an item so the partition is not correct. See repl below:
(let [file-text (line-seq (reader "C://Drugs/myproject/src/myproject/data.txt"))
new-test-items (vec (map #(apply struct item %) (partition 3 file-text)))]
(println file-text)
(println new-test-items))
(sarah 1 1 jason 4 5 nila 3 2 jonas 5 6 judy 8 15 denny 9 14 lis 2 2 )
[{:name sarah 1 1, :weight jason 4 5, :value nila 3 2 } {:name jonas 5 6, :weight judy 8 15, :value denny 9 14}]
I then tried to just take 1 partition, but still the structure is not right.
=> (let [file-text (line-seq (reader "C://Drugs/myproject/src/myproject/data.txt"))
new-test-items (vec (map #(apply struct item %) (partition 1 file-text)))]
(println file-text)
(println new-test-items))
(sarah 1 1 jason 4 5 nila 3 2 jonas 5 6 judy 8 15 denny 9 14 lis 2 2 )
[{:name sarah 1 1, :weight nil, :value nil} {:name jason 4 5, :weight nil, :value nil} {:name nila 3 2 , :weight nil, :value nil} {:name jonas 5 6, :weight nil, :value nil} {:name judy 8 15, :weight nil, :value nil} {:name denny 9 14, :weight nil, :value nil} {:name lis 2 2, :weight nil, :value nil} {:name , :weight nil, :value nil}]
nil
Next I tried to slurp the file, but that is worse:
=> (let [slurp-input (slurp "C://Drugs/myproject/src/myproject/data.txt")
part-items (partition 3 slurp-input)
mapping (vec (map #(apply struct item %) part-items))]
(println slurp-input)
(println part-items)
(println mapping))
sarah 1 1
jason 4 5
nila 3 2
jonas 5 6
judy 8 15
denny 9 14
lis 2 2
((s a r) (a h ) (1 1) (
Please help! This seems like such an easy thing to do in Java, but is killing me in Clojure.
split it into a sequence of lines:
(line-seq (reader "/tmp/data"))
split each of them into a sequence of words
(map #(split % #" ") data)
make a function that takes a vector of one data and turns it into a map with the correct keys
(fn [[name weight cost]]
(hash-map :name name
:weight (Integer/parseInt weight)
:cost (Integer/parseInt cost)))
then nest them back together
(map (fn [[name weight cost]]
(hash-map :name name
:weight (Integer/parseInt weight)
:cost (Integer/parseInt cost)))
(map #(split % #" ") (line-seq (reader "/tmp/data"))))
({:weight 1, :name "name", :cost 4}
{:weight 2, :name "name", :cost 4}
{:weight 3, :name "name", :cost 1})
you can also make this more compact by using zip-map
You are trying to do everything in one place without testing intermediate results. Instead Clojure recommends to decompose task into a number of subtasks - this makes code much more flexible and testable. Here's the code for your task (I assume records in file describe people):
(defn read-lines [filename]
(with-open [rdr (clojure.java.io/reader filename)]
(doall (line-seq rdr))))
(defn make-person [s]
(reduce conj (map hash-map [:name :weight :value] (.split s " "))))
(map make-person (read-lines "/path/to/file"))