Which library to use?
As of this writing, they are three libraries that emerge:
I don't include Apache Any23 because it uses ICU4j 3.4 under the hood.
How to tell which one has detected the right charset (or as close as possible)?
It's impossible to certify the charset detected by each above libraries. However, it's possible to ask them in turn and score the returned response.
How to score the returned response?
Each response can be assigned one point. The more points a response have, the more confidence the detected charset has. This is a simple scoring method. You can elaborate others.
Is there any sample code?
Here is a full snippet implementing the strategy described in the previous lines.
public static String guessEncoding(InputStream input) throws IOException {
// Load input data
long count = 0;
int n = 0, EOF = -1;
byte[] buffer = new byte[4096];
ByteArrayOutputStream output = new ByteArrayOutputStream();
while ((EOF != (n = input.read(buffer))) && (count <= Integer.MAX_VALUE)) {
output.write(buffer, 0, n);
count += n;
}
if (count > Integer.MAX_VALUE) {
throw new RuntimeException("Inputstream too large.");
}
byte[] data = output.toByteArray();
// Detect encoding
Map<String, int[]> encodingsScores = new HashMap<>();
// * GuessEncoding
updateEncodingsScores(encodingsScores, new CharsetToolkit(data).guessEncoding().displayName());
// * ICU4j
CharsetDetector charsetDetector = new CharsetDetector();
charsetDetector.setText(data);
charsetDetector.enableInputFilter(true);
CharsetMatch cm = charsetDetector.detect();
if (cm != null) {
updateEncodingsScores(encodingsScores, cm.getName());
}
// * juniversalchardset
UniversalDetector universalDetector = new UniversalDetector(null);
universalDetector.handleData(data, 0, data.length);
universalDetector.dataEnd();
String encodingName = universalDetector.getDetectedCharset();
if (encodingName != null) {
updateEncodingsScores(encodingsScores, encodingName);
}
// Find winning encoding
Map.Entry<String, int[]> maxEntry = null;
for (Map.Entry<String, int[]> e : encodingsScores.entrySet()) {
if (maxEntry == null || (e.getValue()[0] > maxEntry.getValue()[0])) {
maxEntry = e;
}
}
String winningEncoding = maxEntry.getKey();
//dumpEncodingsScores(encodingsScores);
return winningEncoding;
}
private static void updateEncodingsScores(Map<String, int[]> encodingsScores, String encoding) {
String encodingName = encoding.toLowerCase();
int[] encodingScore = encodingsScores.get(encodingName);
if (encodingScore == null) {
encodingsScores.put(encodingName, new int[] { 1 });
} else {
encodingScore[0]++;
}
}
private static void dumpEncodingsScores(Map<String, int[]> encodingsScores) {
System.out.println(toString(encodingsScores));
}
private static String toString(Map<String, int[]> encodingsScores) {
String GLUE = ", ";
StringBuilder sb = new StringBuilder();
for (Map.Entry<String, int[]> e : encodingsScores.entrySet()) {
sb.append(e.getKey() + ":" + e.getValue()[0] + GLUE);
}
int len = sb.length();
sb.delete(len - GLUE.length(), len);
return "{ " + sb.toString() + " }";
}
Improvements:
The guessEncoding method reads the inputstream entirely. For large inputstreams this can be a concern. All these libraries would read the whole inputstream. This would imply a large time consumption for detecting the charset.
It's possible to limit the initial data loading to a few bytes and perform the charset detection on those few bytes only.
