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Custom Templates for JSON Output Formatting

JSON is a versatile data format, but sometimes the standard output isn't exactly what you need. Whether you're consuming an API, processing logs, or preparing data for a specific application, you might need to select specific fields, rename keys, flatten nested structures, or apply other transformations. This is where custom templates or programmatic formatting come into play, allowing you to tailor the JSON output precisely to your requirements.

Why Customize JSON Output?

Default JSON output from systems, databases, or APIs often includes more information than necessary or uses naming conventions that aren't ideal for your use case. Custom formatting helps you:

Reduce Data Size: Exclude unnecessary fields to minimize payload size, improving performance.
Simplify Data Structure: Flatten nested objects or arrays to make data easier to consume.
Harmonize Naming Conventions: Rename keys to match your application's standards (e.g., convert camelCase to snake_case).
Select Specific Data: Only output the fields you actually need.
Enhance Readability: Reorder fields or format specific values for clarity.

Approaches to Custom JSON Formatting

There are several ways to implement custom JSON output formatting, depending on your context:

1. Programmatic Transformation (Code)

Writing custom code (e.g., in JavaScript, Python, Java) to parse the original JSON and build a new JSON structure based on your logic. This offers maximum flexibility.

2. Templating Engines

Using templating languages designed for data transformation (e.g., JOLT for JSON transformation, Handlebars, Jinja for more general text templating that can output JSON). These often involve defining a template or specification for the output structure.

3. Query Languages (e.g., JMESPath, JSONata)

Specialized query languages for JSON that allow you to select and transform elements using expressions.

4. No-Code/Low-Code Tools

Visual tools or platforms that provide drag-and-drop interfaces or configuration options to define JSON transformations without writing code.

Example: Programmatic Transformation in JavaScript

One of the most common and flexible ways is to write a simple script or function that takes the input JSON and returns the desired output structure. Below is a JavaScript example demonstrating how to select fields, rename keys, and slightly restructure an array of objects.

Input JSON:

[
  {
    "userId": 101,
    "userName": "Alice",
    "userEmail": "alice@example.com",
    "userProfile": {
      "isActive": true,
      "lastLogin": "2023-10-26T10:00:00Z"
    },
    "tags": ["admin", "editor"]
  },
  {
    "userId": 102,
    "userName": "Bob",
    "userEmail": "bob@example.com",
    "userProfile": {
      "isActive": false,
      "lastLogin": "2023-10-25T15:30:00Z"
    },
    "tags": ["viewer"]
  }
]

JavaScript Transformation Function:

function transformUserData(inputJson) {
  // Ensure input is an array
  if (!Array.isArray(inputJson)) {
    console.error("Input must be an array");
    return [];
  }

  return inputJson.map(user => {
    // Select and rename fields
    const transformedUser = {
      id: user.userId, // Rename 'userId' to 'id'
      name: user.userName, // Rename 'userName' to 'name'
      email: user.userEmail, // Rename 'userEmail' to 'email'
      status: user.userProfile ? (user.userProfile.isActive ? 'Active' : 'Inactive') : 'Unknown', // Transform boolean to string
      roles: user.tags // Keep 'tags' as 'roles'
    };

    return transformedUser;
  });
}

// Example Usage (assuming inputJson is the array above)
// const transformedData = transformUserData(inputJson);
// console.log(JSON.stringify(transformedData, null, 2));

Output JSON (using the function):

[
  {
    "id": 101,
    "name": "Alice",
    "email": "alice@example.com",
    "status": "Active",
    "roles": ["admin", "editor"]
  },
  {
    "id": 102,
    "name": "Bob",
    "email": "bob@example.com",
    "status": "Inactive",
    "roles": ["viewer"]
  }
]

This example demonstrates selecting a subset of fields, renaming keys (`userId` to `id`, `userName` to `name`, `userEmail` to `email`), and transforming a boolean value (`isActive`) into a string (`status`).

Considerations When Using Custom Templates/Transformations

While custom formatting offers great power, keep these points in mind:

Complexity: Highly complex transformations can make the template or code difficult to read and maintain.
Performance: For very large JSON files, inefficient transformations can impact performance.
Error Handling: Robust handling is needed for missing fields or unexpected data types in the input.
Tooling: Choose an approach (programmatic, templating language, query language) that best fits your team's skills and the complexity of the task.

Conclusion

Custom templates or programmatic transformations are essential techniques for anyone working extensively with JSON data. They empower you to shape the output JSON to precisely match the requirements of your consuming application or process. By understanding the available approaches and practicing with examples, you can efficiently manage and prepare your JSON data, improving performance, readability, and usability.

Need help with your JSON?

Try our JSON Formatter tool to automatically identify and fix syntax errors in your JSON. JSON Formatter tool