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1. Overview

In this quick article, we’ll explore a fundamental class in Java – the StringTokenizer.

2. StringTokenizer

The StringTokenizer class helps us split Strings into multiple tokens.

StreamTokenizer provides similar functionality but the tokenization method of StringTokenizer is much simpler than the one used by the StreamTokenizer class. Methods of StringTokenizer do not distinguish among identifiers, numbers, and quoted strings, nor recognize and skip comments.

The set of delimiters (the characters that separate tokens) may be specified either at the creation time or on a per-token basis.

3. Using the StringTokenizer

The simplest example of using StringTokenizer will be to split a String based on specified delimiters.

In this quick example, we’re going to split the argument String and add the tokens into a list:

public List<String> getTokens(String str) {
    List<String> tokens = new ArrayList<>();
    StringTokenizer tokenizer = new StringTokenizer(str, ",");
    while (tokenizer.hasMoreElements()) {
        tokens.add(tokenizer.nextToken());
    }
    return tokens;
}

Notice how we’re breaking the String into the list of tokens based on delimiter ‘,‘. Then in the loop, using tokens.add() method; we are adding each token into the ArrayList.

For example, if a user gives input as “Welcome,to,baeldung.com“, this method should return a list containing a three-word fragment as “Welcome“, “to” and “baeldung.com“.

3.1. Java 8 Approach

Since StringTokenizer implements Enumeration<Object> interface, we can use it with Java‘s Collections interface.

If we consider the earlier example, we can retrieve the same set of tokens using Collections.list() method and Stream API:

public List<String> getTokensWithCollection(String str) {
    return Collections.list(new StringTokenizer(str, ",")).stream()
      .map(token -> (String) token)
      .collect(Collectors.toList());
}

Here, we are passing the StringTokenizer itself as a parameter in the Collections.list() method.

Point to note here is that, since the Enumeration is an Object type, we need to type-cast the tokens to String type (i.e. depends on the implementation; if we use List of Integer/Float then we’ll need to type-cast with Integer/Float).

3.2. Variants of StringTokenizer

StringTokenizer comes with two overloaded constructors beside the default constructor: StringTokenizer(String str) and StringTokenizer(String str, String delim, boolean returnDelims):

StringTokenizer(String str, String delim, boolean returnDelims) takes an extra boolean input. If the boolean value is true, then StringTokenizer considers the delimiter itself as a token and add it to its internal pool of tokens.

StringTokenizer(String str) is a shortcut for the previous example; it internally calls the other constructor with hard-coded delimiter as ” \t\n\r\f” and the boolean value as false.

3.3. Token Customization

StringTokenizer also comes with an overloaded nextToken() method which takes a string fragment as input. This String fragment acts as an extra set of delimiters; based on which tokens are re-organized again.

For example, if we can pass ‘e‘ in the nextToken() method to further break the string based on the delimiter ‘e‘:

tokens.add(tokenizer.nextToken("e"));

Hence, for a given string of ‘Hello,baeldung.com‘ we will produce following tokens:

H
llo
ba
ldung.com

3.4. Token Length

To count the available numbers of tokens, we can use StringTokenizer‘s countTokens method:

int tokenLength = tokens.countTokens();

3.5. Reading From CSV File

Now, let’s try using StringTokenizer in a real use case.

There are scenarios where we try to read data from CSV files and parse the data based on the user-given delimiter.

Using StringTokenizer, we can easily get there:

public List<String> getTokensFromFile( String path , String delim ) {
    List<String> tokens = new ArrayList<>();
    String currLine = "";
    StringTokenizer tokenizer;
    try (BufferedReader br = new BufferedReader(
        new InputStreamReader(Application.class.getResourceAsStream( 
          "/" + path )))) {
        while (( currLine = br.readLine()) != null ) {
            tokenizer = new StringTokenizer( currLine , delim );
            while (tokenizer.hasMoreElements()) {
                tokens.add(tokenizer.nextToken());
            }
        }
    } catch (IOException e) {
        e.printStackTrace();
    }
    return tokens;
}

Here, the function takes two arguments; one as CSV file name (i.e. read from the resources [src -> main -> resources] folder) and the other one as a delimiter.

Based on this two arguments, the CSV data is read line by line, and each line gets tokenized using StringTokenizer.

For example, we’ve put following content in the CSV:

1|IND|India
2|MY|Malaysia
3|AU|Australia

Hence, following tokens should be generated:

1
IND
India
2
MY
Malaysia
3
AU
Australia

3.6. Testing

Now, let’s create a quick test case:

public class TokenizerTest {

    private MyTokenizer myTokenizer = new MyTokenizer();
    private List<String> expectedTokensForString = Arrays.asList(
      "Welcome" , "to" , "baeldung.com" );
    private List<String> expectedTokensForFile = Arrays.asList(
      "1" , "IND" , "India" , 
      "2" , "MY" , "Malaysia" , 
      "3", "AU" , "Australia" );

    @Test
    public void givenString_thenGetListOfString() {
        String str = "Welcome,to,baeldung.com";
        List<String> actualTokens = myTokenizer.getTokens( str );
 
        assertEquals( expectedTokensForString, actualTokens );
    }

    @Test
    public void givenFile_thenGetListOfString() {
        List<String> actualTokens = myTokenizer.getTokensFromFile( 
          "data.csv", "|" );
 
        assertEquals( expectedTokensForFile , actualTokens );
    }
}

4. Conclusion

In this quick tutorial, we had a look at some practical examples of using the core Java StringTokenizer.

The code backing this article is available on GitHub. Once you're logged in as a Baeldung Pro Member, start learning and coding on the project.
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Once the early-adopter seats are all used, the price will go up and stay at $33/year.

Partner – Microsoft – NPI EA (cat = Spring Boot)
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Azure Container Apps is a fully managed serverless container service that enables you to build and deploy modern, cloud-native Java applications and microservices at scale. It offers a simplified developer experience while providing the flexibility and portability of containers.

Of course, Azure Container Apps has really solid support for our ecosystem, from a number of build options, managed Java components, native metrics, dynamic logger, and quite a bit more.

To learn more about Java features on Azure Container Apps, visit the documentation page.

You can also ask questions and leave feedback on the Azure Container Apps GitHub page.

Partner – Orkes – NPI EA (cat = Spring)
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Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.

Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.

With Orkes Conductor managed through Orkes Cloud, developers can focus on building mission critical applications without worrying about infrastructure maintenance to meet goals and, simply put, taking new products live faster and reducing total cost of ownership.

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Partner – Orkes – NPI EA (tag = Microservices)
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Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.

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