Java tutorial
package org.commcare.android.util; import android.annotation.SuppressLint; import android.content.Context; import android.os.Build; import android.support.v4.util.LruCache; import android.text.Spannable; import android.util.Pair; import org.javarosa.core.services.locale.Localization; import org.javarosa.core.util.NoLocalizedTextException; import java.text.Normalizer; import java.util.regex.Pattern; /** * @author ctsims */ public class StringUtils { //TODO: Bro you can't just cache every fucking string ever. static LruCache<String, String> normalizationCache; static Pattern diacritics; //TODO: Really not sure about this size. Also, the LRU probably isn't really the best model here //since we'd _like_ for these caches to get cleaned up at _some_ point. static final private int cacheSize = 100 * 1024; /** * @param input A non-null string * @return a canonical version of the passed in string that is lower cased and has removed diacritical marks * like accents. */ @SuppressLint("NewApi") public synchronized static String normalize(String input) { if (normalizationCache == null) { normalizationCache = new LruCache<String, String>(cacheSize); diacritics = Pattern.compile("\\p{InCombiningDiacriticalMarks}+"); } String cachedString = normalizationCache.get(input); if (cachedString != null) { return cachedString; } //Initialized the normalized string (If we can, we'll use the Normalizer API on it) String normalized = input; //If we're above gingerbread we'll normalize this in NFD form //which helps a lot. Otherwise we won't be able to clear up some of those //issues, but we can at least still eliminate diacritics. if (Build.VERSION.SDK_INT >= Build.VERSION_CODES.GINGERBREAD) { normalized = Normalizer.normalize(input, Normalizer.Form.NFD); } else { //TODO: I doubt it's worth it, but in theory we could run //some other normalization for the minority of pre-API9 //devices. } String output = diacritics.matcher(normalized).replaceAll("").toLowerCase(); normalizationCache.put(input, output); return output; } /** * Computes the Levenshtein Distance between two strings. * <p/> * This code is sourced and unmodified from wikibooks under * the Creative Commons attribution share-alike 3.0 license and * by be re-used under the terms of that license. * <p/> * http://creativecommons.org/licenses/by-sa/3.0/ * <p/> * TODO: re-implement for efficiency/licensing possibly. */ public static int LevenshteinDistance(String s0, String s1) { int len0 = s0.length() + 1; int len1 = s1.length() + 1; // the array of distances int[] cost = new int[len0]; int[] newcost = new int[len0]; // initial cost of skipping prefix in String s0 for (int i = 0; i < len0; i++) cost[i] = i; // dynamicaly computing the array of distances // transformation cost for each letter in s1 for (int j = 1; j < len1; j++) { // initial cost of skipping prefix in String s1 newcost[0] = j - 1; // transformation cost for each letter in s0 for (int i = 1; i < len0; i++) { // matching current letters in both strings int match = (s0.charAt(i - 1) == s1.charAt(j - 1)) ? 0 : 1; // computing cost for each transformation int cost_replace = cost[i - 1] + match; int cost_insert = cost[i] + 1; int cost_delete = newcost[i - 1] + 1; // keep minimum cost newcost[i] = Math.min(Math.min(cost_insert, cost_delete), cost_replace); } // swap cost/newcost arrays int[] swap = cost; cost = newcost; newcost = swap; } // the distance is the cost for transforming all letters in both strings return cost[len0 - 1]; } /** * Identifies whether two strings are close enough that they are likely to be * intended to be the same string. Fuzzy matching is only performed on strings that are * longer than a certain size. * * @return A pair with two values. First value represents a match: true if the two strings * meet CommCare's fuzzy match definition, false otherwise. Second value is the actual string * distance that was matched, in order to be able to rank or otherwise interpret results. */ public static Pair<Boolean, Integer> fuzzyMatch(String source, String target) { //tweakable parameter: Minimum length before edit distance //starts being used (this is probably not necessary, and //basically only makes sure that "at" doesn't match "or" or similar if (source.length() > 3) { int distance = StringUtils.LevenshteinDistance(source, target); //tweakable parameter: edit distance past string length disparity if (distance <= 2) { return Pair.create(true, distance); } } return Pair.create(false, -1); } public static String getStringRobust(Context c, int resId) { return getStringRobust(c, resId, ""); } public static String getStringRobust(Context c, int resId, String args) { String resourceName = c.getResources().getResourceEntryName(resId); try { return Localization.get("odk_" + resourceName, new String[] { args }); } catch (NoLocalizedTextException e) { return c.getString(resId, args); } } public static String getStringRobust(Context c, int resId, String[] args) { String resourceName = c.getResources().getResourceEntryName(resId); try { return Localization.get("odk_" + resourceName, args); } catch (NoLocalizedTextException e) { return c.getString(resId, args); } } public static Spannable getStringSpannableRobust(Context c, int resId) { return getStringSpannableRobust(c, resId, ""); } public static Spannable getStringSpannableRobust(Context c, int resId, String args) { String resourceName = c.getResources().getResourceEntryName(resId); String ret = ""; try { ret = Localization.get("odk_" + resourceName, new String[] { args }); } catch (NoLocalizedTextException e) { ret = c.getString(resId, args); } return MarkupUtil.styleSpannable(c, ret); } }