Best Practices

Best Practices

Data Design

Type Selection

• Use appropriate types for data
• Prefer integers over floats when possible
• Use native DateTime instead of string dates
• Use UUID for unique identifiers
• Use binary type for binary data

Structure Organization

• Keep property names concise
• Group related properties
• Use consistent naming conventions
• Consider query patterns
• Optimize for common operations

Schema Design

• Define clear schemas
• Include property descriptions
• Set appropriate constraints
• Version schemas properly
• Plan for evolution

Performance

File Size

• Enable compression for storage
• Use appropriate types
• Minimize string usage
• Batch small objects
• Remove unnecessary fields

Processing Speed

• Use streaming for large files
• Implement batch processing
• Cache compiled schemas
• Reuse parser instances
• Profile performance bottlenecks

Memory Usage

• Process data in chunks
• Set appropriate buffer sizes
• Implement proper disposal
• Monitor memory usage
• Clean up resources

Implementation

Error Handling

• Validate input data
• Implement proper error handling
• Log validation errors
• Provide meaningful messages
• Handle edge cases

Security

• Validate all input
• Set size limits
• Control access permissions
• Sanitize output
• Implement proper logging

Testing

• Unit test serialization
• Test with various data sizes
• Validate error handling
• Performance test
• Integration test

Production Use

Deployment

• Version control schemas
• Document changes
• Plan migrations
• Monitor performance
• Set up logging

Monitoring

• Track file sizes
• Monitor processing times
• Watch memory usage
• Log error rates
• Set up alerts

Maintenance

• Regular backups
• Schema updates
• Performance optimization
• Security updates
• Documentation updates

Integration

APIs

• Use content negotiation
• Set appropriate timeouts
• Handle partial failures
• Implement retry logic
• Document endpoints

Storage

• Choose appropriate storage
• Implement caching
• Plan for scaling
• Monitor usage
• Backup strategy

Migration

• Plan data migration
• Test thoroughly
• Document process
• Provide rollback
• Monitor progress

Development

Code Organization

• Follow conventions
• Document code
• Write tests
• Use version control
• Review changes

Tools

• Use appropriate IDE
• Implement linting
• Set up CI/CD
• Use debugging tools
• Performance profiling

Documentation

• Keep docs updated
• Include examples
• Document changes
• Version documentation
• Review regularly

Examples

Good Practices

{
  "id": "550e8400-e29b-41d4-a716-446655440000",
  "created": "2025-01-19T08:39:44Z",
  "type": "user",
  "data": {
    "name": "John Doe",
    "email": "john@example.com",
    "settings": {
      "theme": "dark",
      "notifications": true
    }
  }
}

Schema Example

{
  "type": "object",
  "required": ["id", "created", "type", "data"],
  "properties": {
    "id": {
      "type": "string",
      "format": "uuid"
    },
    "created": {
      "type": "string",
      "format": "date-time"
    },
    "type": {
      "type": "string",
      "enum": ["user", "admin", "guest"]
    },
    "data": {
      "type": "object",
      "required": ["name", "email"],
      "properties": {
        "name": {
          "type": "string",
          "minLength": 1,
          "maxLength": 100
        },
        "email": {
          "type": "string",
          "format": "email"
        },
        "settings": {
          "type": "object",
          "properties": {
            "theme": {
              "type": "string",
              "enum": ["light", "dark"]
            },
            "notifications": {
              "type": "boolean"
            }
          }
        }
      }
    }
  }
}

Common Pitfalls

Anti-Patterns

• Storing large binary data inline
• Using strings for dates
• Deeply nested structures
• Inconsistent naming
• Missing validation

Performance Issues

• Loading entire files into memory
• Not using streaming
• Excessive validation
• Inefficient queries
• Memory leaks

Security Risks

• Unvalidated input
• Exposed sensitive data
• Insufficient logging
• Missing access control
• Unsanitized output

Checklist

Implementation

• Proper type usage
• Schema validation
• Error handling
• Performance optimization
• Security measures

Testing

• Unit tests
• Integration tests
• Performance tests
• Security tests
• Migration tests

Documentation

• API documentation
• Schema documentation
• Example code
• Error handling
• Best practices

Deployment

• Version control
• Backup strategy
• Monitoring
• Logging
• Security review