Is there a better, more elegant (and/or possibly faster) way than
boolean isNumber = false;
try{
Double.valueOf(myNumber);
isNumber = true;
} catch (NumberFormatException e) {
}
...?
Edit: Since I can't pick two answers I'm going with the regex one because a) it's elegant and b) saying "Jon Skeet solved the problem" is a tautology because Jon Skeet himself is the solution to all problems.
I don't believe there's anything built into Java to do it faster and still reliably, assuming that later on you'll want to actually parse it with Double.valueOf (or similar).
I'd use Double.parseDouble instead of Double.valueOf to avoid creating a Double unnecessarily, and you can also get rid of blatantly silly numbers quicker than the exception will by checking for digits, e/E, - and . beforehand. So, something like:
public boolean isDouble(String value)
{
boolean seenDot = false;
boolean seenExp = false;
boolean justSeenExp = false;
boolean seenDigit = false;
for (int i=0; i < value.length(); i++)
{
char c = value.charAt(i);
if (c >= '0' && c <= '9')
{
seenDigit = true;
continue;
}
if ((c == '-' || c=='+') && (i == 0 || justSeenExp))
{
continue;
}
if (c == '.' && !seenDot)
{
seenDot = true;
continue;
}
justSeenExp = false;
if ((c == 'e' || c == 'E') && !seenExp)
{
seenExp = true;
justSeenExp = true;
continue;
}
return false;
}
if (!seenDigit)
{
return false;
}
try
{
Double.parseDouble(value);
return true;
}
catch (NumberFormatException e)
{
return false;
}
}
Note that despite taking a couple of tries, this still doesn't cover "NaN" or hex values. Whether you want those to pass or not depends on context.
In my experience regular expressions are slower than the hard-coded check above.
You could use a regex, i.e. something like String.matches("^[\\d\\-\\.]+$"); (if you're not testing for negative numbers or floating point numbers you could simplify a bit).
Not sure whether that would be faster than the method you outlined though.
Edit: in the light of all this controversy, I decided to make a test and get some data about how fast each of these methods were. Not so much the correctness, but just how quickly they ran.
You can read about my results on my blog. (Hint: Jon Skeet FTW).
See java.text.NumberFormat (javadoc).
NumberFormat nf = NumberFormat.getInstance(Locale.FRENCH);
Number myNumber = nf.parse(myString);
int myInt = myNumber.intValue();
double myDouble = myNumber.doubleValue();
The correct regex is actually given in the Double javadocs:
To avoid calling this method on an invalid string and having a NumberFormatException be thrown, the regular expression below can be used to screen the input string:
final String Digits = "(\\p{Digit}+)";
final String HexDigits = "(\\p{XDigit}+)";
// an exponent is 'e' or 'E' followed by an optionally
// signed decimal integer.
final String Exp = "[eE][+-]?"+Digits;
final String fpRegex =
("[\\x00-\\x20]*"+ // Optional leading "whitespace"
"[+-]?(" + // Optional sign character
"NaN|" + // "NaN" string
"Infinity|" + // "Infinity" string
// A decimal floating-point string representing a finite positive
// number without a leading sign has at most five basic pieces:
// Digits . Digits ExponentPart FloatTypeSuffix
//
// Since this method allows integer-only strings as input
// in addition to strings of floating-point literals, the
// two sub-patterns below are simplifications of the grammar
// productions from the Java Language Specification, 2nd
// edition, section 3.10.2.
// Digits ._opt Digits_opt ExponentPart_opt FloatTypeSuffix_opt
"((("+Digits+"(\\.)?("+Digits+"?)("+Exp+")?)|"+
// . Digits ExponentPart_opt FloatTypeSuffix_opt
"(\\.("+Digits+")("+Exp+")?)|"+
// Hexadecimal strings
"((" +
// 0[xX] HexDigits ._opt BinaryExponent FloatTypeSuffix_opt
"(0[xX]" + HexDigits + "(\\.)?)|" +
// 0[xX] HexDigits_opt . HexDigits BinaryExponent FloatTypeSuffix_opt
"(0[xX]" + HexDigits + "?(\\.)" + HexDigits + ")" +
")[pP][+-]?" + Digits + "))" +
"[fFdD]?))" +
"[\\x00-\\x20]*");// Optional trailing "whitespace"
if (Pattern.matches(fpRegex, myString))
Double.valueOf(myString); // Will not throw NumberFormatException
else {
// Perform suitable alternative action
}
This does not allow for localized representations, however:
To interpret localized string representations of a floating-point value, use subclasses of NumberFormat.
Use StringUtils.isDouble(String) in Apache Commons.
Leveraging off Mr. Skeet:
private boolean IsValidDoubleChar(char c)
{
return "0123456789.+-eE".indexOf(c) >= 0;
}
public boolean isDouble(String value)
{
for (int i=0; i < value.length(); i++)
{
char c = value.charAt(i);
if (IsValidDoubleChar(c))
continue;
return false;
}
try
{
Double.parseDouble(value);
return true;
}
catch (NumberFormatException e)
{
return false;
}
}
I would use the Jakarta commons-lang, as always ! But I have no idea if their implementation is fast or not. It doesnt rely on Exceptions, which might be a good thig performance wise ...
Most of these answers are somewhat acceptable solutions. All of the regex solutions have the issue of not being correct for all cases you may care about.
If you really want to ensure that the String is a valid number, then I would use your own solution. Don't forget that, I imagine, that most of the time the String will be a valid number and won't raise an exception. So most of the time the performance will be identical to that of Double.valueOf().
I guess this really isn't an answer, except that it validates your initial instinct.
Randy
Following Phill's answer can I suggest another regex?
String.matches("^-?\\d+(\\.\\d+)?$");
I prefer using a loop over the Strings's char[] representation and using the Character.isDigit() method. If elegance is desired, I think this is the most readable:
package tias;
public class Main {
private static final String NUMERIC = "123456789";
private static final String NOT_NUMERIC = "1L5C";
public static void main(String[] args) {
System.out.println(isStringNumeric(NUMERIC));
System.out.println(isStringNumeric(NOT_NUMERIC));
}
private static boolean isStringNumeric(String aString) {
if (aString == null || aString.length() == 0) {
return false;
}
for (char c : aString.toCharArray() ) {
if (!Character.isDigit(c)) {
return false;
}
}
return true;
}
}
If you want something that's blisteringly fast, and you have a very clear idea of what formats you want to accept, you can build a state machine DFA by hand. This is essentially how regexes work under the hood anyway, but you can avoid the regex compilation step this way, and it may well be faster than a generic regex compiler.
