├── stopwords.txt ├── .gitignore ├── clojure ├── doc │ └── intro.md ├── test │ └── tinysearch │ │ └── core_test.clj ├── project.clj ├── README.md ├── src │ └── tinysearch │ │ └── core.clj ├── tinysearch.iml └── LICENSE ├── README.md └── scala ├── freakinTinySearch.scala └── tinySearch.scala /stopwords.txt: -------------------------------------------------------------------------------- 1 | de 2 | o 3 | a 4 | an 5 | com 6 | the 7 | this 8 | that 9 | with 10 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | *.class 2 | scala/bin/ 3 | bin/ 4 | .idea 5 | .lein-repl-history 6 | .nrepl-port 7 | clojure/target 8 | -------------------------------------------------------------------------------- /clojure/doc/intro.md: -------------------------------------------------------------------------------- 1 | # Introduction to tinysearch 2 | 3 | TODO: write [great documentation](http://jacobian.org/writing/what-to-write/) 4 | -------------------------------------------------------------------------------- /clojure/test/tinysearch/core_test.clj: -------------------------------------------------------------------------------- 1 | (ns tinysearch.core-test 2 | (:require [clojure.test :refer :all] 3 | [tinysearch.core :refer :all])) 4 | 5 | (deftest a-test 6 | (testing "FIXME, I fail." 7 | (is (= 0 1)))) 8 | -------------------------------------------------------------------------------- /clojure/project.clj: -------------------------------------------------------------------------------- 1 | (defproject tinysearch "0.1.0-SNAPSHOT" 2 | :description "FIXME: write description" 3 | :url "http://example.com/FIXME" 4 | :license {:name "Eclipse Public License" 5 | :url "http://www.eclipse.org/legal/epl-v10.html"} 6 | :dependencies [[org.clojure/clojure "1.6.0"] [org.clojure/math.numeric-tower "0.0.2"]] 7 | :main ^:skip-aot tinysearch.core 8 | :target-path "target/%s" 9 | :profiles {:uberjar {:aot :all}}) 10 | -------------------------------------------------------------------------------- /clojure/README.md: -------------------------------------------------------------------------------- 1 | # tinysearch 2 | 3 | FIXME: description 4 | 5 | ## Installation 6 | 7 | Download from http://example.com/FIXME. 8 | 9 | ## Usage 10 | 11 | FIXME: explanation 12 | 13 | $ java -jar tinysearch-0.1.0-standalone.jar [args] 14 | 15 | ## Options 16 | 17 | FIXME: listing of options this app accepts. 18 | 19 | ## Examples 20 | 21 | ... 22 | 23 | ### Bugs 24 | 25 | ... 26 | 27 | ### Any Other Sections 28 | ### That You Think 29 | ### Might be Useful 30 | 31 | ## License 32 | 33 | Copyright © 2016 FIXME 34 | 35 | Distributed under the Eclipse Public License either version 1.0 or (at 36 | your option) any later version. 37 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | Tiny Search 2 | ----------- 3 | 4 | How many lines of code it takes to write a reasonable, understandable, full-text search engine? 5 | The code in this repository can give an easy and fast overview on the Vector Space Model (tf-idf). 6 | Feel free to contribute with improvements and other language implementations. 7 | 8 | Other languages 9 | ---------- 10 | 11 | Feel free to submit pull requests with implementations in any other languages. 12 | You can follow the same requirements of the Scala version: 13 | 14 | - in-memory index; 15 | - norms and IDF calculated online; 16 | - default OR operator between query terms; 17 | - index a document per line from a single file. 18 | - read stopwords from a file 19 | 20 | 21 | Scala 22 | --------- 23 | There are two Scala versions of the Vector Space Model. They are similar, except that "freakinTinySearch.scala" squeezes some more lines by getting rid of classes. 24 | 25 | Warnings: 26 | 27 | - I only tested the Scala code with 2.9. 28 | - This is not intented for real world production code. It is just for fun and educational purposes. 29 | - The Scala code calculates document norm and term IDF on-the-fly while processing the query. This is far from optimal, but it makes things shorter. 30 | 31 | 32 | 33 | -------------------------------------------------------------------------------- /scala/freakinTinySearch.scala: -------------------------------------------------------------------------------- 1 | object Search extends App { 2 | val stopwords = io.Source.fromFile("../stopwords.txt").getLines.toSet 3 | val invertedIndex = new collection.mutable.HashMap[String, List[(Int,Int)]] //Posting = (docId, TF) 4 | val dataset = new collection.mutable.ArrayBuffer[String] //Hold the documents contents 5 | def tokenize(s:String) = s.toLowerCase.split("[^a-z0-9äöüáéíóúãâêîôûàèìòùçñ]+").filter(!stopwords.contains(_)) 6 | def index(doc:String) { //dataset.size = current doc Id 7 | for(term <- tokenize(doc)) { 8 | val list = invertedIndex.getOrElse(term, Nil) 9 | if (list != Nil && list.head._1 == dataset.size) //not the first time this term appears in the document 10 | invertedIndex.put(term, (list.head._1, list.head._2 + 1) :: list.tail) 11 | else //first time of this term in the document 12 | invertedIndex.put(term, (dataset.size, 1) :: list) 13 | } 14 | dataset += doc 15 | } 16 | def docNorm(docId:Int) = math.sqrt(tokenize(dataset(docId)).foldLeft(0D)( (accum, t) => accum + (math.pow(idf(t), 2)))) 17 | def idf(term:String):Double = (scala.math.log(dataset.size.toDouble / invertedIndex.getOrElse(term, Nil).size.toDouble)) 18 | def searchOR(q:String, topk:Int) = { 19 | val accums = new collection.mutable.HashMap[Int, Double] //Map(docId -> Score) 20 | for(term <- tokenize(q); posting <- invertedIndex.getOrElse(term, Nil)) 21 | accums.put(posting._1, accums.getOrElse(posting._1, 0D) + posting._2 * math.pow(idf(term), 2)) 22 | accums.map(d => (d._1, dataset(d._1), d._2 / docNorm(d._1))).toSeq.sortWith(_._3 > _._3).take(topk) 23 | } 24 | io.Source.fromFile(args(0)).getLines.foreach(line => index(line)) 25 | while(true) { 26 | println("Input your query:") 27 | searchOR(readLine(), 10).foreach(println) 28 | } 29 | } 30 | -------------------------------------------------------------------------------- /clojure/src/tinysearch/core.clj: -------------------------------------------------------------------------------- 1 | (ns tinysearch.core 2 | (:gen-class) 3 | (:require [clojure.string :as str] 4 | [clojure.math.numeric-tower :as math])) 5 | 6 | (def inverted-index (atom {})) 7 | (def docs (atom [])) 8 | 9 | (defn add-posting [term tf doc-id] 10 | (swap! inverted-index update-in [term] conj {:doc-id doc-id :tf tf})) 11 | 12 | (defn tokenize [doc] 13 | (str/split doc #"[^a-z0-9äöüáéíóúãâêîôûàèìòùçñ]+")) 14 | 15 | (defn index-doc [doc] 16 | (swap! docs conj doc) 17 | (let [doc-id (dec (count @docs))] 18 | (->> 19 | (tokenize doc) 20 | (frequencies) 21 | (map (fn [[term tf]] (add-posting term tf doc-id))) 22 | (doall)))) 23 | 24 | (defn index-file [file] 25 | (->> 26 | (slurp file) 27 | (str/split-lines) 28 | (map index-doc) 29 | (doall))) 30 | 31 | (defn posting-list [term] 32 | (get @inverted-index term)) 33 | 34 | (defn doc-content [doc-id] 35 | (nth @docs doc-id)) 36 | 37 | (defn idf [term] 38 | (Math/log 39 | (double 40 | (/ (count @docs) (count (posting-list term)))))) 41 | 42 | (defn doc-norm [doc-id] 43 | (->> 44 | (doc-content doc-id) 45 | (tokenize) 46 | (map (fn [term] (Math/pow (idf term) 2))) 47 | (reduce +) 48 | (Math/sqrt))) 49 | 50 | (defn term-scores [{term :term postings :postings}] 51 | (->> 52 | postings 53 | (map (fn [p] (assoc p :score (* (:tf p) (math/expt (idf term) 2))))))) 54 | 55 | (defn search-or [query] 56 | (let [splitted-query (tokenize query)] 57 | (->> 58 | splitted-query 59 | (map (fn [t] {:term t :postings (posting-list t)})) ; postings 60 | (mapcat term-scores) 61 | (group-by :doc-id) 62 | (map 63 | (fn [[doc-id postings]] 64 | {:doc-id doc-id 65 | :score (double (/ (reduce + (map :score postings)) (doc-norm doc-id)))})) 66 | (sort-by :score) 67 | (reverse)))) 68 | 69 | (defn search-loop [] 70 | (while true 71 | (println "Type your search:") 72 | (->> 73 | (read-line) 74 | (search-or) 75 | (map (fn [result] (assoc result :doc (doc-content (:doc-id result))))) 76 | (map println) 77 | (doall)))) 78 | 79 | (defn index-and-search-loop [file] 80 | (index-file file) 81 | (search-loop)) 82 | 83 | (defn -main 84 | [& args] 85 | (index-and-search-loop (first args))) -------------------------------------------------------------------------------- /scala/tinySearch.scala: -------------------------------------------------------------------------------- 1 | case class Posting(docId: Int, tf: Int) 2 | 3 | case class Result(docId: Int, doc: String, score: Double) 4 | 5 | type Tokenizer = (String => Array[String]) 6 | type InvertedIndex = Map[String, List[Posting]] 7 | 8 | case class SimpleTokenizer(regex: String = "[^a-z0-9äöüáéíóúãâêîôûàèìòùçñ]+") extends Tokenizer { 9 | val stopwords = io.Source.fromFile("../stopwords.txt").getLines.toSet 10 | def apply(s: String) = s.toLowerCase.split(regex).filter( !stopwords.contains(_)) 11 | } 12 | 13 | class Index(val tokenizer: Tokenizer, 14 | private val invertedIndex: InvertedIndex = Map.empty, 15 | private val dataset: IndexedSeq[String] = Vector.empty) { 16 | def index(doc: String): Index = { 17 | val wordCounts = tokenizer(doc).groupBy(identity).mapValues(_.size) 18 | var newInverted = invertedIndex 19 | for((term, tf) <- wordCounts) { 20 | val newPostingList = Posting(dataset.size, tf) :: invertedIndex.getOrElse(term, Nil) 21 | newInverted += (term -> newPostingList) 22 | } 23 | new Index(tokenizer, newInverted, dataset :+ doc) 24 | } 25 | 26 | def size = invertedIndex.size 27 | def doc(id: Int) = dataset(id) 28 | def postings(term: String): List[Posting] = 29 | invertedIndex.getOrElse(term, Nil) 30 | def docCount(term: String) = postings(term).size 31 | } 32 | 33 | class Searcher(index: Index) { 34 | def docNorm(docId: Int) = { 35 | val docTerms = index.tokenizer(index.doc(docId)) 36 | math.sqrt( docTerms.map( term => math.pow(idf(term), 2) ).sum ) 37 | } 38 | 39 | def idf(term: String) = 40 | math.log(index.size.toDouble / index.docCount(term).toDouble) 41 | 42 | def searchOR(q: String, topK: Int = 10) = { 43 | val accums = new collection.mutable.HashMap[Int, Double].withDefaultValue(0D) //Map[docId -> Score] 44 | for (term <- index.tokenizer(q)) { 45 | for (posting <- index.postings(term)) { 46 | accums.put(posting.docId, accums(posting.docId) + posting.tf * math.pow(idf(term),2)) 47 | } 48 | } 49 | accums.map(accumToResult).toSeq.sortWith(_.score > _.score).take(topK) 50 | } 51 | 52 | private def accumToResult(docIdAndScore: (Int, Double)): Result = { 53 | val (docId, score) = docIdAndScore 54 | Result(docId, index.doc(docId), score / docNorm(docId)) 55 | } 56 | } 57 | 58 | object IndexAndSearch extends App { 59 | def indexFromFile(filePath: String): Index = { 60 | val emptyIndex = new Index(SimpleTokenizer()) 61 | val source = io.Source.fromFile(filePath) 62 | val index = source.getLines.foldLeft(emptyIndex) { (accIndex, line) => accIndex.index(line) } 63 | source.close() 64 | index 65 | } 66 | val searcher = new Searcher(indexFromFile(args(0))) 67 | while(true) { 68 | println("Ready for searching:") 69 | searcher.searchOR(scala.io.StdIn.readLine()).foreach(println) 70 | } 71 | } -------------------------------------------------------------------------------- /clojure/tinysearch.iml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 | 60 | 61 | 62 | 63 | 64 | 65 | 66 | 67 | 68 | 69 | 70 | 71 | 72 | 73 | 74 | 75 | 76 | 77 | 78 | 79 | 80 | 81 | 82 | 83 | 84 | 85 | 86 | 87 | 88 | 89 | -------------------------------------------------------------------------------- /clojure/LICENSE: -------------------------------------------------------------------------------- 1 | THE ACCOMPANYING PROGRAM IS PROVIDED UNDER THE TERMS OF THIS ECLIPSE PUBLIC 2 | LICENSE ("AGREEMENT"). 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