JSON to Java POJO Generator

JSON to Java POJO Generator

The JSON to Java POJO Generator converts JSON into Java classes so you can integrate APIs faster and avoid manual boilerplate. Paste JSON or a schema, click generate, and get Java classes with fields that match your payload. This is ideal for backend services, Spring applications, and data transfer objects (DTOs). The tool runs locally in your browser for privacy and speed.

Using POJOs gives you strong typing, clear models, and easier validation. It also improves readability and IDE support in Java projects. By generating POJOs from real API responses or schemas, you create models that reflect actual data instead of assumptions.

What the generator produces

• Java classes with public fields based on JSON keys.
• Nested classes for nested objects.
• Lists for arrays (e.g., List<String>).
• Basic Java types: String, double, boolean, Object.

Supported inputs and sources

• Raw JSON samples.
• JSON Schema definitions.
• YAML samples.
• YAML Schema definitions.

You can switch between source types without leaving the page. This makes it easy to compare a sample payload against a schema, or to convert YAML content from documentation into Java models in a single workflow.

How to use the Java POJO generator (step-by-step tutorial)

1. Paste JSON, JSON Schema, YAML, or YAML Schema on the left editor.
2. Set Package and Root class to match your Java project.
3. Choose the Source type that matches your input (JSON vs Schema, YAML vs YAML Schema).
4. Pick your Annotation style (Jackson, Gson, or none) based on your serializer.
5. Enable Validation annotations if you want size/email/required hints.
6. Toggle Serializable or Parcelable for JVM or Android needs.
7. Click Generate Models.
8. Use Preview to review output, then Copy or Download ZIP for multi-file output.

If you are unsure which settings to use, start with defaults and generate once. You can iterate quickly by adjusting options and regenerating until the output matches your project style.

Example: JSON to Java

Input JSON:

{
  "id": 1,
  "name": "Avi",
  "active": true,
  "roles": ["admin", "editor"],
  "profile": {
    "email": "avi@example.com",
    "score": 9.5
  }
}

Generated Java (simplified):

public class Root {
  public double id;
  public String name;
  public boolean active;
  public List<String> roles;
  public Profile profile;
}

public class Profile {
  public String email;
  public double score;
}

Handling arrays and nested objects

Arrays become List<T>. Nested JSON objects become nested classes. If arrays contain objects, a new class is generated for those items and used as the list element type.

When arrays are empty or mixed, the generator falls back to Object to avoid incorrect typing. For the cleanest models, provide a representative sample where each array contains consistent objects.

Generator options and output controls

• Package & root class: Define package name and entry class.
• Word delimiters: Customize how keys are split into Java names.
• Annotation style: Pick JSON annotation conventions for your stack.
• Validation annotations: Add constraints like required or format hints.
• Serializable/Parcelable: Generate interfaces for JVM or Android usage.
• Preview & download: Preview output, copy to clipboard, or download a ZIP.

Word delimiters are useful when your JSON uses snake_case or kebab-case. The generator can normalize those keys into Java-style camelCase fields.

Tutorial: Package and root class naming

1. Use your project's base package, such as com.company.project.models.
2. Set a root class that matches the API response name, like UserResponse or OrderPayload.
3. Regenerate to update nested classes automatically under the chosen package.

Tutorial: Generate from JSON Schema

1. Switch Source type to JSON Schema.
2. Paste your schema or load a sample.
3. Set package and root class.
4. Click Generate Models to create schema-accurate POJOs.

Schema-driven generation is best when you need strict typing, consistent enums, and validation rules. It also prevents missing optional fields because the schema defines the full contract.

Tutorial: Generate from YAML or YAML Schema

1. Switch Source type to YAML or YAML Schema.
2. Paste the YAML payload or schema.
3. Pick annotation and validation options.
4. Generate, then preview or download the output.

This is useful when your API documentation is in YAML (OpenAPI snippets or config files). You can generate POJOs directly without converting YAML manually.

Tutorial: Annotations for Jackson and Gson

If your Java stack uses Jackson, pick the Jackson option to generate @JsonProperty annotations. For Gson, choose Gson to generate @SerializedName annotations. This ensures JSON keys map to Java fields even when naming conventions differ.

Tutorial: Validation annotations

When validation is enabled, the generator adds Bean Validation annotations such as @NotNull or @Size based on the sample or schema. This helps you validate payloads early and return meaningful API errors.

Tutorial: Preview, copy, and ZIP download

1. Click Preview to open the generated Java in a readable window.
2. Use Copy to copy a single output to the clipboard.
3. Use Download ZIP when multiple classes are generated.

The ZIP output is ideal for large payloads with nested classes, so you can drop all files into your project at once.

Common errors and fixes

• Invalid JSON: Fix syntax with JSON Validator.
• Wrong source type: If you paste schema, switch to JSON Schema or YAML Schema input.
• Mixed array types: Arrays with inconsistent types can lead to Object or incorrect types. Normalize arrays for accuracy.
• Null values: Nulls are inferred as Object. Provide non-null samples for better typing.
• Unexpected class names: Names are inferred from keys. Rename classes after generation if needed.
• Fields missing: Optional fields must appear in the sample to be generated.

Best practices for Java models

• Use representative JSON samples that include all fields.
• Add getters/setters or Lombok annotations after generation.
• Consider using Jackson annotations for custom JSON field names.
• Use JSON Schema Validator to enforce strict contracts.
• Keep generated models in a dedicated package.

Advanced tips for clean models

• Convert numeric IDs to String if they exceed 32-bit range or contain leading zeros.
• For timestamps, map String to Instant or LocalDateTime after generation.
• Use Lombok @Builder when you want fluent creation of models in tests.
• Prefer schema input to enforce enums and required fields consistently.
• Keep one root class per response to avoid bloated models.

Java annotations and serialization

Generated POJOs can be annotated for serialization frameworks. For Jackson, use @JsonProperty when JSON keys differ from Java naming conventions. For Gson, use @SerializedName. Adding these annotations ensures reliable mapping between JSON and your Java models.

If you want immutability, consider converting the classes into Java records (Java 16+) or use Lombok @Value for immutable classes. This helps keep your models thread-safe and easier to reason about.

Nullability and optional fields

JSON often omits optional fields. In Java, you can represent optional fields with nullable types, wrappers like Optional<T>, or default values. Choose a strategy that matches your project's style. For validation, combine POJOs with Bean Validation annotations such as @NotNull, @Size, and @Email.

Example: adding annotations

public class User {
  @JsonProperty("user_name")
  public String userName;

  @Email
  public String email;
}

Use cases

REST APIs: Generate DTOs for request/response bodies.

Microservices: Keep shared models consistent across services.

Data ingestion: Parse JSON feeds into typed Java objects.

SDK generation: Provide typed models for client libraries.

Android apps: Use Parcelable for fast inter-process transfer.

Batch jobs: Validate and parse large payloads with strict schemas.

Common pitfalls

• IDs as numbers vs strings: Verify types against real data.
• Dates as strings: Map to String or convert to LocalDate manually.
• Lists of mixed types: Normalize arrays to a single type before generating.
• Deep nesting: Consider flattening or splitting models if classes become too large.

Performance and maintainability

Large JSON payloads can produce many nested classes. Use the preview to scan for oversized objects and simplify them if needed. Keeping models small improves serialization speed and makes API contracts easier to maintain.

Privacy and security

Your input stays in the browser. The generator does not upload JSON, YAML, or schemas to any server. This is safe for sensitive payloads and internal API data.

Java integration tips

In Spring or Jackson-based projects, annotate fields with @JsonProperty if key names differ from Java naming conventions. If you want immutability, convert the output into records or add constructors. For validation, combine POJOs with bean validation annotations like @NotNull or @Size.

Package and naming conventions

Keep generated POJOs in a dedicated package (e.g., com.example.models). This avoids naming collisions and keeps your project organized. Rename classes to match domain terminology, especially if the generator uses generic names like Root.

For collections, prefer meaningful class names like User, Order, and Item rather than generic names such as Item1. This improves readability and long-term maintenance.

Equality and hashing

If you plan to use generated models in collections or caches, implement equals() and hashCode(). Lombok annotations like @Data can generate these automatically. This is especially important when using models as keys in maps or sets.

Workflow checklist

1. Validate JSON input.
2. Generate Java POJOs.
3. Refine class names and packages.
4. Add annotations (Jackson, Lombok, validation).
5. Update models when API changes.

Testing and validation

After generation, write a quick unit test to deserialize a sample payload into the POJO. This confirms the model matches the API. If you rely on schema validation, validate the JSON before deserialization to catch errors early.

FAQs

Does this generate getters and setters?
The output uses public fields by default. Add getters/setters or Lombok as needed.

Can I generate records?
The tool generates classic classes. You can convert to records manually.

Can I use JSON Schema or YAML Schema?
Yes. Select the proper source type before generating.

Is my JSON uploaded?
No. Everything runs locally in your browser.

How do I handle enums?
Define enums manually after generation based on your domain rules.

Does it support nested arrays?
Yes. Arrays of objects create nested classes and list types.

Can I download all classes at once?
Yes. Use the ZIP download option for multi-file outputs.

Can I use this for database entities?
Yes, but add ORM annotations manually if needed.

What about optional fields?
Optionality is inferred from the sample. Mark fields optional manually if required.

How do I keep models updated?
Regenerate models when the API changes and compare diffs.

Does it support Android?
Yes. Enable Parcelable and use the generated classes in Android apps.

Can I keep custom edits?
Yes. Generate into a dedicated folder and apply custom changes afterward, then regenerate when the API changes and re-apply diffs.

Can I use these POJOs with Hibernate?
Yes, but add JPA annotations manually.

Does it support Lombok?
You can add Lombok annotations after generation for less boilerplate.

Can I generate nested packages?
The generator creates classes; package structure is up to you.

Can I add constructors?
Yes. Add constructors manually or use Lombok @AllArgsConstructor.

Does it support builder patterns?
You can add builders manually or use Lombok @Builder.