MultiThreadedSearchEngine/search_engine.go at main · Amurr1/MultiThreadedSearchEngine · GitHub

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package main

import (
	"fmt"
	"math"
	"net/http"
	"net/url"
	"regexp"
	"sort"
	"time"
)

type Ranking struct {
	title string
	url   string
	score float64
}

type SearchEngine struct {
	data_handler DataHandler
	stop_words   map[string]struct{}
	doc_num      uint
}

// Constructs a search engine for a local corpus and starts a server with a search page containing the corpus
func NewLocalSearchEngine(
	data_handler DataHandler,
	stop_words map[string]struct{},
	default_delay float32,
	crawl_workers struct {
		clean_href int
		download   int
		extract    int
	},
	server_dir string,
	port string,
	relative_start_url string,
	verbose bool,
) (*SearchEngine, error) {
	// Create search engine
	this := &SearchEngine{
		data_handler: data_handler,
		stop_words:   stop_words,
		doc_num:      0,
	}

	// Start file server, get url, and wait to start before crawling
	main_url := this.StartServer(server_dir, port)
	start_url, err := url.JoinPath(main_url, relative_start_url)
	if err != nil {
		return nil, err
	}
	time.Sleep(500 * time.Millisecond)

	// Crawl corpus
	if verbose {
		fmt.Printf("Starting crawl of %s.\n", start_url)
	}
	crawler := NewCrawler(this.data_handler, this.stop_words, default_delay)
	download_errors, err := crawler.Crawl(start_url, crawl_workers)
	if err != nil {
		return nil, err
	}

	// Set document count
	this.doc_num, err = this.data_handler.Size()
	if err != nil {
		return nil, err
	}
	if verbose {
		fmt.Printf("Crawl of %d documents complete with %d download errors.\n", this.doc_num, download_errors)
	}
	return this, nil
}

// Constructs a search engine for a preexisting corpus. Does not start a server with a search page
func NewSearchEngine(
	data_handler DataHandler,
	stop_words map[string]struct{},
	default_delay float32,
	crawl_workers struct {
		clean_href int
		download   int
		extract    int
	},
	start_url string,
	verbose bool,
) (*SearchEngine, error) {
	// Create search engine
	this := &SearchEngine{
		data_handler: data_handler,
		stop_words:   stop_words,
		doc_num:      0,
	}

	// Crawl corpus
	if verbose {
		fmt.Printf("Starting crawl of %s.\n", start_url)
	}
	crawler := NewCrawler(data_handler, stop_words, default_delay)
	t_start := time.Now()
	download_errors, err := crawler.Crawl(start_url, crawl_workers)
	delta_t := time.Since(t_start)
	if err != nil {
		return nil, err
	}

	// Set document count
	this.doc_num, err = this.data_handler.Size()
	if err != nil {
		return nil, err
	}
	if verbose {
		fmt.Printf(
			"Crawl of %d documents complete with %d download errors. [%s]\n",
			this.doc_num,
			download_errors,
			delta_t.Round(time.Millisecond),
		)
	}
	return this, nil
}

// Starts a server with a search page for the contents of the search engine.
func (se *SearchEngine) StartServer(server_dir string, port string) string {
	// Create file server
	mux := http.NewServeMux()
	mux.Handle("/", http.FileServer(http.Dir(server_dir)))

	// Create search page
	mux.Handle("/search", http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
		// Get user inputted query, then find results. Abort if database fails
		query := r.URL.Query().Get("query")
		results, err := se.Rank(query)
		if err != nil {
			fmt.Println("Error: database query failed")
			return
		}
		// Create header
		w.Header().Set("Content-Type", "text/html; charset=utf-8")
		fmt.Fprintf(w, "<html><body>")
		fmt.Fprintf(w, "<h3>Search term: %s</h3>", query)

		// Create search box
		fmt.Fprintf(w, "<form action=\"/search\" method=\"GET\">")
		fmt.Fprintf(w, "<input type=\"text\" name=\"query\" placeholder=\"Search...\">")
		fmt.Fprintf(w, "<button type=\"submit\">Search</button>")
		fmt.Fprintf(w, "</form>")

		// List results
		fmt.Fprintf(w, "<ol>")
		for _, ranking := range results {
			fmt.Fprintf(w, "<li><a href=\"%s\">%s</a></li>\n", ranking.url, ranking.title)
		}
		fmt.Fprintf(w, "</ol>")
		fmt.Fprintf(w, "</body></html>")
	}))
	go http.ListenAndServe(":"+port, mux)
	return "http://localhost:" + port + "/"
}

// Returns a sorted slice of rankings based on TfIdf scores in relation to a multi-word query
func (se *SearchEngine) Rank(query string) ([]Ranking, error) {
	// Clean query
	word_re := regexp.MustCompile(`[a-zA-Z]+(['’][a-zA-Z]+)*`)
	q_words := NormalizeWords(word_re.FindAllString(query, -1))
	cleaned_query := []string{}
	for _, q_word := range q_words {
		if _, ok := se.stop_words[q_word]; !ok {
			cleaned_query = append(cleaned_query, q_word)
		}
	}

	// Create TfIdf score map
	unsorted_ranking_map := make(map[string]Ranking)
	for _, search_term := range cleaned_query {
		docs, err := se.Search(search_term)
		if err != nil {
			return nil, err
		}
		docs_with_word := uint(len(docs))
		for url, doc := range docs {
			score := se.TfIdf(search_term, url, doc.freq, doc.word_count, docs_with_word)
			ranking, ok := unsorted_ranking_map[url]
			if !ok {
				unsorted_ranking_map[url] = Ranking{doc.title, url, score}
			} else {
				unsorted_ranking_map[url] = Ranking{doc.title, url, ranking.score + score}
			}
		}
	}

	// Convert map to slice
	rankings := []Ranking{}
	for _, ranking := range unsorted_ranking_map {
		rankings = append(rankings, ranking)
	}

	// Sort slice by score
	sort.Slice(rankings, func(a, b int) bool {
		if rankings[a].score == rankings[b].score {
			return rankings[a].url > rankings[b].url
		}
		return rankings[a].score > rankings[b].score
	})
	return rankings, nil
}

// Returns a frequency map linking documents to frequency of the given search term
func (se *SearchEngine) Search(search_term string) (map[string]struct {
	title      string
	word_count uint
	freq       uint
}, error) {
	clean_search_term := NormalizeWords([]string{search_term})[0]
	doc_map, err := se.data_handler.GetDocsWithWord(clean_search_term)
	if err != nil {
		return nil, err
	}
	return doc_map, nil
}

// Returns a TfIdf score for a given url and search term
func (se *SearchEngine) TfIdf(search_term string, url string, freq uint, word_count uint, docs_with_word uint) float64 {
	tf := float64(freq) / float64(word_count+1)
	idf := math.Log(float64(se.doc_num) / (float64(docs_with_word + 1)))
	return tf * idf
}