10 Best Practices for Working with JSON Data

JSON (JavaScript Object Notation) has become the standard format for data exchange in web applications and APIs. Its simplicity and flexibility make it ideal for transmitting structured data between servers and clients. However, with this flexibility comes the responsibility to use JSON effectively.

In this article, we'll explore 10 best practices for working with JSON data that will help you create more maintainable, readable, and efficient applications.

1. Use Consistent Naming Conventions

Consistent naming conventions make your JSON data more readable and easier to work with. Choose a naming style and stick with it throughout your application:

• camelCase: firstName, lastName (common in JavaScript)
• snake_case: first_name, last_name (common in Python, Ruby)
• kebab-case: first-name, last-name (less common in JSON)

Avoid mixing different naming conventions in the same JSON structure:

// Bad practice - mixed naming conventions
{
  "firstName": "John",
  "last_name": "Doe",
  "Email-Address": "john.doe@example.com"
}

// Good practice - consistent naming (camelCase)
{
  "firstName": "John",
  "lastName": "Doe",
  "emailAddress": "john.doe@example.com"
}

2. Keep Your JSON Structure Flat When Possible

While JSON supports nested structures, deeply nested objects can be difficult to navigate and process. When appropriate, keep your JSON structure relatively flat:

// Deeply nested structure
{
  "user": {
    "personal": {
      "name": {
        "first": "John",
        "last": "Doe"
      }
    },
    "contact": {
      "details": {
        "email": "john.doe@example.com"
      }
    }
  }
}

// Flatter structure
{
  "user": {
    "firstName": "John",
    "lastName": "Doe",
    "email": "john.doe@example.com"
  }
}

Flatter structures are easier to read, require less traversal code, and often perform better when parsing.

3. Use Arrays for Ordered Collections

When dealing with collections of items where order matters, use arrays instead of objects with numeric keys:

// Bad practice - using objects with numeric keys
{
  "items": {
    "0": { "name": "Item 1" },
    "1": { "name": "Item 2" },
    "2": { "name": "Item 3" }
  }
}

// Good practice - using arrays
{
  "items": [
    { "name": "Item 1" },
    { "name": "Item 2" },
    { "name": "Item 3" }
  ]
}

Arrays in JSON maintain order and are more natural for representing sequences of items. They also map directly to arrays/lists in most programming languages.

4. Validate JSON Data

Always validate JSON data, especially when receiving it from external sources:

• Verify that the JSON is well-formed (valid syntax)
• Check that required fields are present
• Validate data types for each field
• Consider using JSON Schema for formal validation

JSON Schema allows you to define the structure, types, and constraints for your JSON data, making validation more robust and consistent.

5. Use Appropriate Data Types

JSON supports several data types: strings, numbers, booleans, objects, arrays, and null. Use the appropriate type for each value:

// Bad practice - incorrect data types
{
  "id": "42",          // ID as string
  "active": "true",    // Boolean as string
  "score": "98.6",     // Number as string
  "tags": "one,two,three"  // Array as string
}

// Good practice - appropriate data types
{
  "id": 42,            // Number
  "active": true,      // Boolean
  "score": 98.6,       // Number
  "tags": ["one", "two", "three"]  // Array
}

Using appropriate data types reduces the need for type conversion in your code and makes your JSON more semantically correct.

6. Handle Dates Consistently

JSON doesn't have a native date type, so you need to establish a convention for date representation:

// Option 1: ISO 8601 string (recommended)
{
  "createdAt": "2023-04-15T14:30:00Z"
}

// Option 2: Unix timestamp (seconds since epoch)
{
  "createdAt": 1681567800
}

// Option 3: Separate date components
{
  "createdAt": {
    "year": 2023,
    "month": 4,
    "day": 15,
    "hour": 14,
    "minute": 30
  }
}

The ISO 8601 format (YYYY-MM-DDTHH:MM:SSZ) is widely recommended as it's standardized, human-readable, and supported by most programming languages.

7. Include Error Information in Responses

When returning JSON responses from APIs, include detailed error information when something goes wrong:

// Good error response
{
  "success": false,
  "error": {
    "code": "VALIDATION_ERROR",
    "message": "Invalid input data",
    "details": [
      {
        "field": "email",
        "message": "Must be a valid email address"
      },
      {
        "field": "age",
        "message": "Must be a positive number"
      }
    ]
  }
}

Detailed error information helps developers understand what went wrong and how to fix it, improving the developer experience of your API.

8. Use Pagination for Large Data Sets

When returning large collections of data, implement pagination to improve performance and usability:

{
  "data": [
    { "id": 1, "name": "Item 1" },
    { "id": 2, "name": "Item 2" },
    // ...more items
  ],
  "pagination": {
    "totalItems": 1253,
    "totalPages": 63,
    "currentPage": 1,
    "pageSize": 20,
    "nextPage": 2,
    "prevPage": null
  }
}

Including pagination metadata helps clients navigate through large data sets efficiently and provides context about the total available data.

9. Minimize JSON Size

For performance-critical applications, minimize the size of your JSON data:

• Remove unnecessary fields
• Use shorter property names (when appropriate)
• Consider compression (gzip) for transmission
• Remove whitespace in production (minify)

However, balance size optimization with readability and maintainability. In many cases, descriptive property names and well-structured JSON are worth the slight increase in size.

10. Document Your JSON Structure

Document your JSON structure, especially for APIs and data exchange formats:

• Use JSON Schema to formally define your structure
• Provide examples in your documentation
• Document the purpose of each field
• Specify required vs. optional fields
• Document any constraints or validation rules

Good documentation makes it easier for others (and your future self) to understand and work with your JSON data structures.

Conclusion

Following these best practices will help you create JSON data that is more maintainable, readable, and efficient. While not every practice applies to every situation, they provide a solid foundation for working with JSON in modern applications.

Remember that JSON is not just a data format—it's a communication medium between systems and developers. Clear, consistent, and well-structured JSON makes that communication more effective.

When you need to visualize and analyze your JSON data, our JSON to Table converter can help transform complex JSON structures into readable tables, making it easier to understand and work with your data.