json_get

JSON Get Example

This is a comprehensive example of JSON data retrieval functionality, demonstrating various uses of the Get() method and related functions in the json package.

Feature Demonstrations

1. Basic Retrieval

• Use json.Get() to retrieve values of any type
• Demonstrate retrieval of different data types: strings, numbers, booleans, null values
• Show access to nested objects and array elements

2. Type-Safe Retrieval

• Use type-safe functions like json.GetString(), json.GetInt(), json.GetFloat64()
• Use json.GetTyped[T]() for generic type-safe retrieval
• Demonstrate type-safe retrieval of arrays and objects

3. Array Access

• Access array elements using indices: users[0], users[1]
• Support negative indices: users[-1] to access the last element
• Nested array access: metadata.tags[0]

4. Array Slice Access

• Range access: users[0:3] to get the first 3 users
• Open-ended ranges: users[2:] from index 2 to the end
• Negative index ranges: users[-2:] to get the last 2 elements
• Exclusive ranges: users[1:-1] to get middle elements

5. Nested Object Access

• Use dot notation: company.name, company.config.debug
• Deep nested access: company.config.features.auth
• Object access within arrays: company.departments[0].employees[0].name

6. Path Expressions

• Use wildcard {} for bulk data extraction
• Flatten nested arrays: a{g}{name} extracts all name fields
• Complex nested extraction: company.departments{employees}{name} gets all employee names
• Automatic array flattening: company.departments{employees}{skills} gets all skills

7. Multiple Path Retrieval

• Use json.GetMultiple() to batch retrieve multiple values
• More efficient than individual Get() calls
• Support batch operations on complex paths

8. Advanced Processor Usage

• Custom processor configuration
• Enable caching for improved performance
• Processor statistics and health checks
• Custom processing options

9. Error Handling

• Invalid JSON handling
• Non-existent path handling
• Invalid array index handling
• Type conversion error handling
• Null value handling

10. Performance Optimization

• Performance comparison: batch operations vs individual operations
• Performance comparison: path expressions vs multiple individual gets
• Performance comparison: processor reuse vs creating new processors
• Performance optimization recommendations

Sample Data

The example uses three different JSON data structures:

1. Basic JSON (jsonStr): Complex structure with nested arrays and objects
2. User Array JSON (arrayJsonStr): User list and metadata
3. Complex Organizational JSON (complexJsonStr): Multi-level nested organizational structure

Key Features

• Path Syntax Support: Dot notation, array indices, slicing, JSON Pointer
• Type Safety: Automatic type conversion and type-safe getter functions
• Batch Operations: Efficient multi-path retrieval
• Wildcard Support: Use {} for bulk data extraction and automatic flattening
• Error Handling: Comprehensive error handling and edge case management
• Performance Optimization: Caching, processor reuse, and other performance optimization techniques

Performance Tips

1. Use GetMultiple() for batch operations
2. Use path expressions with {} for bulk data extraction
3. Reuse processors instead of creating new ones
4. Enable caching for repeated operations
5. Use type-safe getter functions when possible

🚀 Running the Example

To run this example:

cd examples/json_get
go run example.go

Expected Output

The example will demonstrate:

• ✅ Basic value retrieval with different data types
• ✅ Type-safe operations with automatic conversion
• ✅ Array access with positive and negative indices
• ✅ Complex path expressions and bulk extraction
• ✅ Performance comparisons and error handling

🔗 Related Examples

• basic - Start here for basic JSON operations
• json_set - Learn about setting and modifying JSON data
• flat_extraction - Advanced extraction techniques