# JSON Tools RS
A high-performance Rust library for advanced JSON manipulation with SIMD-accelerated parsing, providing unified flattening and unflattening operations through a clean builder pattern API.
[](https://crates.io/crates/json-tools-rs)
[](https://docs.rs/json-tools-rs)
[](LICENSE-MIT)
## Why JSON Tools RS?
JSON Tools RS is designed for developers who need to:
- **Transform nested JSON** into flat structures for databases, CSV exports, or analytics
- **Clean and normalize** JSON data from external APIs or user input
- **Process large batches** of JSON documents efficiently
- **Maintain type safety** with perfect roundtrip support (flatten → unflatten → original)
- **Work with both Rust and Python** using the same consistent API
Unlike simple JSON parsers, JSON Tools RS provides a complete toolkit for JSON transformation with production-ready performance and error handling.
## Features
- 🚀 **Unified API**: Single `JSONTools` entry point for flattening, unflattening, or pass-through transforms (`.normal()`)
- 🔧 **Builder Pattern**: Fluent, chainable API for easy configuration and method chaining
- ⚡ **High Performance**: SIMD-accelerated JSON parsing with FxHashMap and optimized memory allocations
- 🚄 **Parallel Processing**: Built-in Rayon-based parallelism for 3-5x speedup on batch operations (automatic, no configuration needed)
- 🎯 **Complete Roundtrip**: Flatten JSON and unflatten back to original structure with perfect fidelity
- 🧹 **Comprehensive Filtering**: Remove empty strings, nulls, empty objects, and empty arrays (works for both flatten and unflatten)
- 🔄 **Advanced Replacements**: Literal and regex-based key/value replacements using standard Rust regex syntax
- 🛡️ **Collision Handling**: Intelligent `.handle_key_collision(true)` to collect colliding values into arrays
- 🔀 **Automatic Type Conversion**: Convert strings to numbers and booleans with `.auto_convert_types(true)` - handles currency, thousands separators, scientific notation
- 📦 **Batch Processing**: Process single JSON or batches; Python also supports dicts and lists of dicts
- 🐍 **Python Bindings**: Full Python support with perfect type preservation (input type = output type)
- 🧰 **Robust Errors**: Comprehensive `JsonToolsError` enum with helpful suggestions for debugging
- 🔥 **Performance Optimizations**: FxHashMap (~15-30% faster), SIMD parsing, Cow-based string handling, and automatic parallel processing
## Table of Contents
- [Why JSON Tools RS?](#why-json-tools-rs)
- [Features](#features)
- [Quick Start](#quick-start)
- [Rust Examples](#rust---unified-jsontools-api)
- [Python Examples](#python---unified-jsontools-api)
- [Quick Reference](#quick-reference)
- [Installation](#installation)
- [Performance](#performance)
- [API Reference](#api-reference)
- [Core Methods](#core-methods)
- [Configuration Methods](#configuration-methods)
- [Input/Output Types](#inputoutput-types)
- [Error Handling](#error-handling)
- [Common Use Cases](#common-use-cases)
- [Examples and Testing](#examples-and-testing)
- [Limitations and Known Issues](#limitations-and-known-issues)
- [FAQ](#frequently-asked-questions-faq)
- [Contributing](#contributing)
- [License](#license)
- [Changelog](#changelog)
## Quick Start
### Rust - Unified JSONTools API
The `JSONTools` struct provides a unified builder pattern API for all JSON manipulation operations. Simply call `.flatten()` or `.unflatten()` to set the operation mode, then chain configuration methods and call `.execute()`.
#### Basic Flattening
```rust
use json_tools_rs::{JSONTools, JsonOutput};
let json = r#"{"user": {"name": "John", "profile": {"age": 30, "city": "NYC"}}}"#;
let result = JSONTools::new()
.flatten()
.execute(json)?;
if let JsonOutput::Single(flattened) = result {
println!("{}", flattened);
}
// Output: {"user.name": "John", "user.profile.age": 30, "user.profile.city": "NYC"}
```
#### Advanced Flattening with Filtering
```rust
use json_tools_rs::{JSONTools, JsonOutput};
let json = r#"{"user": {"name": "John", "details": {"age": null, "city": ""}}}"#;
let result = JSONTools::new()
.flatten()
.separator("::")
.lowercase_keys(true)
.key_replacement("(User|Admin)_", "")
.value_replacement("@example.com", "@company.org")
.remove_empty_strings(true)
.remove_nulls(true)
.remove_empty_objects(true)
.remove_empty_arrays(true)
.execute(json)?;
if let JsonOutput::Single(flattened) = result {
println!("{}", flattened);
}
// Output: {"user::name": "John"}
```
#### Basic Unflattening
```rust
use json_tools_rs::{JSONTools, JsonOutput};
let flattened = r#"{"user.name": "John", "user.profile.age": 30}"#;
let result = JSONTools::new()
.unflatten()
.execute(flattened)?;
match result {
JsonOutput::Single(unflattened) => println!("{}", unflattened),
JsonOutput::Multiple(_) => unreachable!(),
}
// Output: {"user": {"name": "John", "profile": {"age": 30}}}
```
#### Advanced Unflattening with Configuration
```rust
use json_tools_rs::{JSONTools, JsonOutput};
let flattened = r#"{"user::name": "John", "user::age": 30, "user::email": ""}"#;
let result = JSONTools::new()
.unflatten()
.separator("::")
.lowercase_keys(true)
.remove_empty_strings(true)
.remove_nulls(true)
.execute(flattened)?;
match result {
JsonOutput::Single(unflattened) => println!("{}", unflattened),
JsonOutput::Multiple(_) => unreachable!(),
}
// Output: {"user": {"name": "John", "age": 30}}
```
#### Key Collision Handling
When transformations make different keys end up identical, enable collision handling to collect values into arrays.
```rust
use json_tools_rs::{JSONTools, JsonOutput};
let json = r#"{"user_name": "John", "admin_name": "Jane"}"#;
let result = JSONTools::new()
.flatten()
.key_replacement("(user|admin)_", "") // both become "name"
.handle_key_collision(true) // collect colliding values
.execute(json)?;
if let JsonOutput::Single(flattened) = result {
println!("{}", flattened);
}
// Output: {"name": ["John", "Jane"]}
```
#### Automatic Type Conversion
Convert string values to numbers and booleans automatically for data cleaning and normalization.
```rust
use json_tools_rs::{JSONTools, JsonOutput};
let json = r#"{
"id": "123",
"price": "$1,234.56",
"quantity": "1,000",
"active": "true",
"verified": "FALSE",
"name": "Product"
}"#;
let result = JSONTools::new()
.flatten()
.auto_convert_types(true)
.execute(json)?;
if let JsonOutput::Single(flattened) = result {
println!("{}", flattened);
}
// Output: {
// "id": 123,
// "price": 1234.56,
// "quantity": 1000,
// "active": true,
// "verified": false,
// "name": "Product" // Keeps as string (not a valid number or boolean)
// }
```
#### Perfect Roundtrip Support
```rust
use json_tools_rs::{JSONTools, JsonOutput};
let original = r#"{"user": {"name": "John", "age": 30}, "items": [1, 2, {"nested": "value"}]}"#;
// Flatten
let flattened = JSONTools::new().flatten().execute(original)?;
let flattened_str = match flattened { JsonOutput::Single(s) => s, _ => unreachable!() };
// Unflatten back to original structure
let restored = JSONTools::new().unflatten().execute(&flattened_str)?;
let restored_str = match restored { JsonOutput::Single(s) => s, _ => unreachable!() };
// Verify perfect roundtrip
assert_eq!(
serde_json::from_str::<serde_json::Value>(original)?,
serde_json::from_str::<serde_json::Value>(&restored_str)?
);
```
### Python - Unified JSONTools API
The Python bindings provide the same unified `JSONTools` API with **perfect type matching**: input type equals output type. This makes the API predictable and easy to use.
#### Type Preservation Examples
```python
import json_tools_rs as jt
# Example 1: dict input → dict output
result = jt.JSONTools().flatten().execute({"user": {"name": "John", "age": 30}})
print(result) # {'user.name': 'John', 'user.age': 30}
print(type(result)) # <class 'dict'>
# Example 2: JSON string input → JSON string output
result = jt.JSONTools().flatten().execute('{"user": {"name": "John", "age": 30}}')
print(result) # '{"user.name": "John", "user.age": 30}'
print(type(result)) # <class 'str'>
# Example 3: List[dict] input → List[dict] output
batch = [{"a": {"b": 1}}, {"c": {"d": 2}}]
result = jt.JSONTools().flatten().execute(batch)
print(result) # [{'a.b': 1}, {'c.d': 2}]
print(type(result[0])) # <class 'dict'>
# Example 4: List[str] input → List[str] output
batch = ['{"a": {"b": 1}}', '{"c": {"d": 2}}']
result = jt.JSONTools().flatten().execute(batch)
print(result) # ['{"a.b": 1}', '{"c.d": 2}']
print(type(result[0])) # <class 'str'>
```
#### Basic Usage
```python
import json_tools_rs as jt
# Basic flattening - dict input → dict output
result = jt.JSONTools().flatten().execute({"user": {"name": "John", "age": 30}})
print(result) # {'user.name': 'John', 'user.age': 30}
# Basic unflattening - dict input → dict output
result = jt.JSONTools().unflatten().execute({"user.name": "John", "user.age": 30})
print(result) # {'user': {'name': 'John', 'age': 30}}
```
#### Advanced Configuration
```python
import json_tools_rs as jt
# Advanced flattening with filtering and transformations
tools = (jt.JSONTools()
.flatten()
.separator("::")
.lowercase_keys(True)
.remove_empty_strings(True)
.remove_nulls(True)
.remove_empty_objects(True)
.remove_empty_arrays(True)
.key_replacement("(User|Admin)_", "")
.value_replacement("@example.com", "@company.org"))
data = {"User_name": "John", "Admin_email": "john@example.com", "empty": "", "null_val": None}
result = tools.execute(data)
print(result) # {'name': 'John', 'email': 'john@company.org'}
# Advanced unflattening with same configuration options
result = (jt.JSONTools()
.unflatten()
.separator("::")
.lowercase_keys(True)
.remove_empty_strings(True)
.remove_nulls(True)
.key_replacement("prefix_", "user_")
.value_replacement("@company.org", "@example.com")
.execute({"PREFIX_NAME": "john", "PREFIX_EMAIL": "john@company.org", "empty": ""}))
print(result) # {'user': {'name': 'john', 'email': 'john@example.com'}}
```
#### Key Collision Handling
When transformations make different keys end up identical, enable collision handling to collect values into arrays.
```python
import json_tools_rs as jt
tools = (jt.JSONTools()
.flatten()
.key_replacement("(user|admin)_", "") # both become "name"
.handle_key_collision(True)) # collect colliding values
data = {"user_name": "John", "admin_name": "Jane"}
print(tools.execute(data)) # {'name': ['John', 'Jane']}
```
#### Automatic Type Conversion
Convert string values to numbers and booleans automatically for data cleaning and normalization.
```python
import json_tools_rs as jt
# Type conversion with dict input
data = {
"id": "123",
"price": "$1,234.56",
"quantity": "1,000",
"active": "true",
"verified": "FALSE",
"name": "Product"
}
result = (jt.JSONTools()
.flatten()
.auto_convert_types(True)
.execute(data))
print(result)
# Output: {
# 'id': 123,
# 'price': 1234.56,
# 'quantity': 1000,
# 'active': True,
# 'verified': False,
# 'name': 'Product' # Keeps as string (not a valid number or boolean)
# }
# Works with JSON strings too
json_str = '{"id": "456", "enabled": "true", "amount": "€99.99"}'
result = jt.JSONTools().flatten().auto_convert_types(True).execute(json_str)
print(result) # '{"id": 456, "enabled": true, "amount": 99.99}'
```
#### Batch Processing with Type Preservation
```python
import json_tools_rs as jt
tools = jt.JSONTools().flatten()
# List[str] input → List[str] output
str_batch = ['{"a": {"b": 1}}', '{"c": {"d": 2}}']
results = tools.execute(str_batch)
print(results) # ['{"a.b": 1}', '{"c.d": 2}']
# List[dict] input → List[dict] output
dict_batch = [{"a": {"b": 1}}, {"c": {"d": 2}}]
results = tools.execute(dict_batch)
print(results) # [{'a.b': 1}, {'c.d': 2}]
# Mixed types are handled automatically
mixed_batch = ['{"a": 1}', {"b": {"c": 2}}]
results = tools.execute(mixed_batch)
print(results) # ['{"a": 1}', {'b.c': 2}]
```
#### Perfect Roundtrip Support
```python
import json_tools_rs
# Perfect roundtrip with Python dicts
original = {"user": {"name": "John", "age": 30}, "items": [1, 2, {"nested": "value"}]}
# Flatten
flattened = json_tools_rs.JSONTools().flatten().execute(original)
print(f"Flattened: {flattened}")
# Unflatten back to original structure
restored = json_tools_rs.JSONTools().unflatten().execute(flattened)
print(f"Restored: {restored}")
# Verify perfect roundtrip
assert original == restored # Perfect roundtrip with dicts!
```
## Quick Reference
### Method Cheat Sheet
| Method | Description | Example |
|--------|-------------|---------|
| `.flatten()` | Set operation mode to flatten | `JSONTools::new().flatten()` |
| `.unflatten()` | Set operation mode to unflatten | `JSONTools::new().unflatten()` |
| `.separator(sep)` | Set key separator (default: `"."`) | `.separator("::")` |
| `.lowercase_keys(bool)` | Convert keys to lowercase | `.lowercase_keys(true)` |
| `.remove_empty_strings(bool)` | Remove empty string values | `.remove_empty_strings(true)` |
| `.remove_nulls(bool)` | Remove null values | `.remove_nulls(true)` |
| `.remove_empty_objects(bool)` | Remove empty objects `{}` | `.remove_empty_objects(true)` |
| `.remove_empty_arrays(bool)` | Remove empty arrays `[]` | `.remove_empty_arrays(true)` |
| `.key_replacement(find, replace)` | Replace key patterns (regex or literal) | `.key_replacement("user_", "")` |
| `.value_replacement(find, replace)` | Replace value patterns (regex or literal) | `.value_replacement("@old.com", "@new.com")` |
| `.handle_key_collision(bool)` | Collect colliding keys into arrays | `.handle_key_collision(true)` |
| `.execute(input)` | Execute the configured operation | `.execute(json_string)` |
### Common Patterns
**Flatten with filtering:**
```rust
JSONTools::new()
.flatten()
.remove_nulls(true)
.remove_empty_strings(true)
.execute(json)?
```
**Unflatten with custom separator:**
```rust
JSONTools::new()
.unflatten()
.separator("::")
.execute(flattened_json)?
```
**Transform keys and values:**
```rust
JSONTools::new()
.flatten()
.lowercase_keys(true)
.key_replacement("(user|admin)_", "")
.value_replacement("@example.com", "@company.org")
.execute(json)?
```
**Handle key collisions:**
```rust
JSONTools::new()
.flatten()
.key_replacement("prefix_", "")
.handle_key_collision(true) // Colliding values → arrays
.execute(json)?
```
## Installation
### Rust
Add to your `Cargo.toml`:
```toml
[dependencies]
json-tools-rs = "0.7.0"
```
Or install via cargo:
```bash
cargo add json-tools-rs
```
**Note**: Parallel processing is built-in and automatic - no feature flags needed!
### Python
#### From PyPI (Recommended)
```bash
pip install json-tools-rs
```
#### Build from Source with Maturin
If you want to build from source or contribute to development:
```bash
# Clone the repository
git clone https://github.com/amaye15/JSON-Tools-rs.git
cd JSON-Tools-rs
# Install maturin if you haven't already
pip install maturin
# Build and install the Python package
maturin develop --features python
# Or build a wheel for distribution
maturin build --features python --release
```
#### Development Setup
```bash
# For development with automatic rebuilds
maturin develop --features python
# Run Python examples
python python/examples/basic_usage.py
python python/examples/examples.py
```
## Performance
JSON Tools RS delivers exceptional performance through multiple carefully implemented optimizations:
### Performance Optimizations
1. **FxHashMap** - ~15-30% faster string key operations compared to standard HashMap
- Optimized hash function for string keys
- Reduced collision overhead
2. **SIMD JSON Parsing** - Hardware-accelerated parsing and serialization via simd-json
- Leverages CPU SIMD instructions for parallel processing
- Significantly faster than standard serde_json for large payloads
3. **Reduced Allocations** - Minimized memory allocations using Cow (Copy-on-Write) and scoped buffers
- ~50% reduction in string clones during key transformations
- Efficient memory reuse across operations
4. **Smart Capacity Management** - Pre-sized maps and string builders to minimize rehashing
- Reduces reallocation overhead
- Improves cache locality
5. **Parallel Batch Processing** (built-in, always enabled) - Rayon-based parallelism for batch operations
- **3-5x speedup** for batches of 10+ items on multi-core CPUs
- Adaptive threshold prevents overhead for small batches
- Zero per-item memory overhead
- Thread-safe regex cache with Arc<Regex> for O(1) cloning
### Parallel Processing
Parallel processing is **built-in and automatic** - no feature flags or special configuration needed!
JSON-Tools-rs provides **two levels of parallelism**:
#### 1. Batch-Level Parallelism (Across Multiple Documents)
Process multiple JSON documents in parallel automatically.
**Performance Gains:**
- Batch size 10: **2.5x faster**
- Batch size 50: **3.3x faster**
- Batch size 100: **3.3x faster**
- Batch size 500: **5.3x faster**
- Batch size 1000: **5.4x faster**
**Configuration (Optional):**
```rust
use json_tools_rs::JSONTools;
// Default threshold (10 items) - optimal for most use cases
// Parallelism activates automatically for batches ≥ 10 items
let result = JSONTools::new()
.flatten()
.execute(batch)?;
// Custom threshold for fine-tuning
let result = JSONTools::new()
.flatten()
.parallel_threshold(50) // Only parallelize batches ≥ 50 items
.execute(batch)?;
// Custom thread count
let result = JSONTools::new()
.flatten()
.num_threads(Some(4)) // Use exactly 4 threads
.execute(batch)?;
// Environment variables (runtime configuration)
// JSON_TOOLS_PARALLEL_THRESHOLD=20 cargo run
// JSON_TOOLS_NUM_THREADS=4 cargo run
```
**How it works:**
- Batches below threshold (default: 10): Sequential processing (no overhead)
- Batches 10-1000: Rayon work-stealing parallelism
- Batches > 1000: Chunked processing for optimal cache locality
- Each worker thread gets its own regex cache
- Zero per-item memory increase (only 8-16MB one-time thread pool)
- Thread count defaults to number of logical CPUs (configurable via `num_threads()` or `JSON_TOOLS_NUM_THREADS`)
#### 2. Nested Parallelism (Within Large Documents)
For large individual JSON documents, nested parallelism automatically parallelizes the processing of large objects and arrays **within** a single document.
**Performance Gains:**
- Large documents (20,000+ items): **7-12% faster**
- Very large documents (100,000+ items): **7-12% faster**
- Small/medium documents: No overhead (stays sequential)
**Configuration (Optional):**
```rust
use json_tools_rs::JSONTools;
// Default threshold (100 items) - optimal for most use cases
// Objects/arrays with 100+ keys/items are processed in parallel
let result = JSONTools::new()
.flatten()
.execute(large_json)?;
// Custom threshold for very large documents
let result = JSONTools::new()
.flatten()
.nested_parallel_threshold(50) // More aggressive parallelism
.execute(large_json)?;
// Disable nested parallelism (for small/medium documents)
let result = JSONTools::new()
.flatten()
.nested_parallel_threshold(usize::MAX) // Disable
.execute(json)?;
// Environment variable (runtime configuration)
// JSON_TOOLS_NESTED_PARALLEL_THRESHOLD=200 cargo run
```
**How it works:**
- Objects/arrays below threshold (default: 100): Sequential processing
- Objects/arrays above threshold: Parallel processing using Rayon
- Each parallel branch gets its own string builder
- Results are merged efficiently with minimal overhead
- Rayon's work-stealing automatically balances load across CPU cores
- Minimal memory overhead (< 1 MB for very large documents)
**When to use:**
- ✅ Large JSON documents (20,000+ items)
- ✅ Very large JSON documents (100,000+ items)
- ✅ Wide, flat structures (many keys at same level)
- ❌ Small documents (< 5,000 items) - no benefit
- ❌ Deeply nested but narrow structures - marginal benefit
### Benchmark Results
Performance varies by workload complexity, but typical results on modern hardware include:
- **Basic flattening**: 2,000+ operations/ms
- **Advanced configuration**: 1,300+ operations/ms (with filtering and transformations)
- **Regex replacements**: 1,800+ operations/ms (with pattern matching)
- **Batch processing**: 1,900+ operations/ms (for multiple JSON documents)
- **Roundtrip operations**: 1,000+ flatten→unflatten cycles/ms
*Note: Benchmarks run on typical development hardware. Your results may vary based on CPU, memory, and workload characteristics.*
### Running Benchmarks
```bash
# Run comprehensive benchmarks
cargo bench
# Run specific benchmark suites
cargo bench flatten
cargo bench unflatten
cargo bench roundtrip
# Generate HTML reports (available in target/criterion)
cargo bench --features html_reports
```
## API Reference
### JSONTools - Unified API
The `JSONTools` struct is the single entry point for all JSON manipulation operations. It provides a builder pattern API that works for both flattening and unflattening operations.
#### Core Methods
- **`JSONTools::new()`** - Create a new instance with default settings
- **`.flatten()`** - Configure for flattening operations (converts nested JSON to flat key-value pairs)
- **`.unflatten()`** - Configure for unflattening operations (converts flat key-value pairs back to nested JSON)
- **`.normal()`** - Configure for pass-through operations (apply transformations without flattening/unflattening)
- **`.execute(input)`** - Execute the configured operation on the provided input
#### Configuration Methods
All configuration methods are chainable and available for both flattening and unflattening operations:
##### Key/Value Transformation Methods
- **`.separator(sep: &str)`** - Set separator for nested keys (default: `"."`)
- Example: `separator("::")` makes keys like `user::name::first`
- **`.lowercase_keys(value: bool)`** - Convert all keys to lowercase
- Example: `UserName` becomes `username`
- **`.key_replacement(find: &str, replace: &str)`** - Add key replacement pattern
- Supports standard Rust regex syntax (automatically detected)
- Falls back to literal string replacement if regex compilation fails
- Example: `key_replacement("(user|admin)_", "")` removes prefixes
- **`.value_replacement(find: &str, replace: &str)`** - Add value replacement pattern
- Supports standard Rust regex syntax (automatically detected)
- Falls back to literal string replacement if regex compilation fails
- Example: `value_replacement("@example.com", "@company.org")` updates email domains
##### Filtering Methods
All filtering methods work for both flatten and unflatten operations:
- **`.remove_empty_strings(value: bool)`** - Remove keys with empty string values (`""`)
- **`.remove_nulls(value: bool)`** - Remove keys with null values
- **`.remove_empty_objects(value: bool)`** - Remove keys with empty object values (`{}`)
- **`.remove_empty_arrays(value: bool)`** - Remove keys with empty array values (`[]`)
##### Collision Handling Methods
- **`.handle_key_collision(value: bool)`** - When enabled, collects values with identical keys into arrays
- Useful when transformations cause different keys to become identical
- Example: After removing prefixes, `user_name` and `admin_name` both become `name`
- With collision handling: `{"name": ["John", "Jane"]}`
- Without collision handling: Last value wins
##### Type Conversion Methods
- **`.auto_convert_types(enable: bool)`** - Automatically convert string values to numbers and booleans
- **Number conversion**: Handles various formats including:
- Basic numbers: `"123"` → `123`, `"45.67"` → `45.67`, `"-10"` → `-10`
- Thousands separators: `"1,234.56"` → `1234.56` (US), `"1.234,56"` → `1234.56` (EU)
- Currency symbols: `"$123.45"` → `123.45`, `"€99.99"` → `99.99`
- Scientific notation: `"1e5"` → `100000`, `"1.23e-4"` → `0.000123`
- **Boolean conversion**: Only these exact variants:
- `"true"`, `"TRUE"`, `"True"` → `true`
- `"false"`, `"FALSE"`, `"False"` → `false`
- **Lenient behavior**: If conversion fails, keeps the original string value (no errors thrown)
- **Works for all modes**: `.flatten()`, `.unflatten()`, and `.normal()`
- **Example**:
```rust
let json = r#"{"id": "123", "price": "$1,234.56", "active": "true"}"#;
let result = JSONTools::new()
.flatten()
.auto_convert_types(true)
.execute(json)?;
// Result: {"id": 123, "price": 1234.56, "active": true}
```
#### Input/Output Types
**Rust:**
- `&str` (JSON string) → `JsonOutput::Single(String)`
- `Vec<&str>` or `Vec<String>` → `JsonOutput::Multiple(Vec<String>)`
**Python (Perfect Type Preservation):**
- `str` → `str` (JSON string input → JSON string output)
- `dict` → `dict` (Python dict input → Python dict output)
- `List[str]` → `List[str]` (list of JSON strings → list of JSON strings)
- `List[dict]` → `List[dict]` (list of Python dicts → list of Python dicts)
- Mixed lists preserve original element types
### Error Handling
The library uses a comprehensive `JsonToolsError` enum that provides detailed error information and actionable suggestions for debugging:
#### Error Variants
- **`JsonParseError`** - JSON parsing failures with syntax suggestions
- Triggered by: Invalid JSON syntax, malformed input
- Suggestion: Verify JSON syntax, check for missing quotes, trailing commas, unescaped characters
- **`RegexError`** - Regex pattern compilation errors with pattern suggestions
- Triggered by: Invalid regex patterns in `key_replacement()` or `value_replacement()`
- Suggestion: Verify regex syntax using standard Rust regex patterns
- **`InvalidJsonStructure`** - Structure validation errors with format guidance
- Triggered by: Incompatible JSON structure for the requested operation
- Suggestion: Ensure input matches expected format (nested for flatten, flat for unflatten)
- **`ConfigurationError`** - API usage errors with correct usage examples
- Triggered by: Calling `.execute()` without setting operation mode
- Suggestion: Call `.flatten()` or `.unflatten()` before `.execute()`
- **`BatchProcessingError`** - Batch operation errors with item-specific details
- Triggered by: Invalid item in batch processing
- Includes: Index of failing item for easy debugging
- Suggestion: Check the JSON at the specified index
- **`InputValidationError`** - Input validation errors with helpful guidance
- Triggered by: Invalid input type or empty input
- Suggestion: Ensure input is valid JSON string, dict, or list
- **`SerializationError`** - JSON serialization failures with debugging information
- Triggered by: Internal serialization errors (rare)
- Suggestion: Report as potential bug
#### Error Handling Examples
**Rust:**
```rust
use json_tools_rs::{JSONTools, JsonToolsError};
match JSONTools::new().flatten().execute(invalid_json) {
Ok(result) => println!("Success: {:?}", result),
Err(JsonToolsError::JsonParseError { message, suggestion, .. }) => {
eprintln!("Parse error: {}", message);
eprintln!("💡 {}", suggestion);
}
Err(e) => eprintln!("Error: {}", e),
}
```
**Python:**
```python
import json_tools_rs
try:
result = json_tools_rs.JSONTools().flatten().execute(invalid_json)
except json_tools_rs.JsonToolsError as e:
print(f"Error: {e}")
# Error messages include helpful suggestions
```
## Common Use Cases
### 1. Data Pipeline Transformations
Flatten nested API responses for easier processing in data pipelines:
```rust
use json_tools_rs::{JSONTools, JsonOutput};
let api_response = r#"{
"user": {
"id": 123,
"profile": {"name": "John", "email": "john@example.com"},
"settings": {"theme": "dark", "notifications": true}
}
}"#;
let flattened = JSONTools::new()
.flatten()
.execute(api_response)?;
// Result: {"user.id": 123, "user.profile.name": "John", ...}
// Perfect for CSV export, database insertion, or analytics
```
### 2. Data Cleaning and Normalization
Remove empty values and normalize keys for consistent data processing:
```python
import json_tools_rs as jt
# Clean messy data from external sources
messy_data = {
"UserName": "Alice",
"Email": "", # Empty string
"Age": None, # Null value
"Preferences": {}, # Empty object
"Tags": [] # Empty array
}
cleaned = (jt.JSONTools()
.flatten()
.lowercase_keys(True)
.remove_empty_strings(True)
.remove_nulls(True)
.remove_empty_objects(True)
.remove_empty_arrays(True)
.execute(messy_data))
# Result: {'username': 'Alice'}
# All empty/null values removed, keys normalized
```
### 3. Configuration File Processing
Transform between flat and nested configuration formats:
```rust
use json_tools_rs::{JSONTools, JsonOutput};
// Convert flat environment-style config to nested structure
let flat_config = r#"{
"database.host": "localhost",
"database.port": 5432,
"database.name": "myapp",
"cache.enabled": true,
"cache.ttl": 3600,
"cache.redis.host": "redis.local"
}"#;
let nested = JSONTools::new()
.unflatten()
.execute(flat_config)?;
// Result: {
// "database": {"host": "localhost", "port": 5432, "name": "myapp"},
// "cache": {"enabled": true, "ttl": 3600, "redis": {"host": "redis.local"}}
// }
```
### 4. Batch Data Processing
Process multiple JSON documents efficiently with type preservation:
```python
import json_tools_rs as jt
# Process batch of API responses
responses = [
{"user": {"id": 1, "name": "Alice", "email": "alice@example.com"}},
{"user": {"id": 2, "name": "Bob", "email": "bob@example.com"}},
{"user": {"id": 3, "name": "Charlie", "email": "charlie@example.com"}}
]
# Flatten all responses in one call
flattened_batch = jt.JSONTools().flatten().execute(responses)
# Result: [
# {'user.id': 1, 'user.name': 'Alice', 'user.email': 'alice@example.com'},
# {'user.id': 2, 'user.name': 'Bob', 'user.email': 'bob@example.com'},
# {'user.id': 3, 'user.name': 'Charlie', 'user.email': 'charlie@example.com'}
# ]
```
### 5. Multi-Source Data Aggregation
Aggregate data from multiple sources with key collision handling:
```python
import json_tools_rs as jt
# Data from different sources with overlapping keys
user_data = {"name": "John", "source": "database"}
admin_data = {"name": "Jane", "source": "ldap"}
guest_data = {"name": "Guest", "source": "default"}
# Combine with collision handling
combined = jt.JSONTools().flatten().handle_key_collision(True).execute([
user_data, admin_data, guest_data
])
# With collision handling, duplicate keys become arrays
# Result: [
# {'name': 'John', 'source': 'database'},
# {'name': 'Jane', 'source': 'ldap'},
# {'name': 'Guest', 'source': 'default'}
# ]
```
### 6. ETL Pipeline: Extract, Transform, Load
Complete ETL workflow with data transformation:
```rust
use json_tools_rs::{JSONTools, JsonOutput};
// Extract: Raw data from source
let raw_data = r#"{
"USER_ID": 12345,
"USER_PROFILE": {
"FIRST_NAME": "John",
"LAST_NAME": "Doe",
"EMAIL_ADDRESS": "john.doe@oldcompany.com",
"METADATA": {"created": "", "updated": null}
}
}"#;
// Transform: Clean and normalize
let transformed = JSONTools::new()
.flatten()
.lowercase_keys(true) // Normalize keys
.key_replacement("user_profile.", "") // Remove prefix
.value_replacement("@oldcompany.com", "@newcompany.com") // Update domain
.remove_empty_strings(true) // Clean empty values
.remove_nulls(true) // Remove nulls
.execute(raw_data)?;
// Load: Result ready for database insertion
// Result: {
// "user_id": 12345,
// "first_name": "John",
// "last_name": "Doe",
// "email_address": "john.doe@newcompany.com"
// }
```
## Examples and Testing
### Running Examples
**Rust Examples:**
```bash
# Basic usage examples
cargo run --example basic_usage
# View all available examples
ls examples/
```
**Python Examples:**
```bash
# Basic usage with type preservation
python python/examples/basic_usage.py
# Advanced features and collision handling
python python/examples/examples.py
```
### Running Tests
**Rust Tests:**
```bash
# Run all Rust tests
cargo test
# Run tests with verbose output
cargo test -- --nocapture
# Run tests with Python features enabled
cargo test --features python
# Run specific test module
cargo test test_module_name
```
**Python Tests:**
```bash
# Install test dependencies
pip install pytest
# Build the Python package first
maturin develop --features python
# Run all Python tests
python -m pytest python/tests/
# Run with verbose output
python -m pytest python/tests/ -v
# Run specific test file
python -m pytest python/tests/tests.py::TestClassName
```
## Limitations and Known Issues
### Current Limitations
1. **Array Index Notation**: Arrays are flattened using numeric indices (e.g., `array.0`, `array.1`). Custom array handling is not currently supported.
2. **Separator Constraints**: The separator cannot contain characters that are valid in JSON keys without escaping. Choose separators carefully to avoid conflicts.
3. **Regex Syntax**: Only standard Rust regex syntax is supported. Some advanced regex features may not be available.
4. **Memory Usage**: For very large JSON documents (>100MB), consider processing in smaller batches to optimize memory usage.
### Workarounds
**For custom array handling:**
```rust
// Pre-process arrays before flattening if custom handling is needed
// Or post-process the flattened result to transform array indices
```
**For separator conflicts:**
```rust
// Use a separator that won't appear in your keys
JSONTools::new().flatten().separator("::").execute(json)?
```
### Reporting Issues
If you encounter a bug or have a feature request, please [open an issue](https://github.com/amaye15/JSON-Tools-rs/issues) on GitHub with:
- A minimal reproducible example
- Expected vs. actual behavior
- Your environment (Rust version, OS, etc.)
## Frequently Asked Questions (FAQ)
### General Questions
**Q: What's the difference between `.flatten()` and `.unflatten()`?**
A: `.flatten()` converts nested JSON structures into flat key-value pairs with dot-separated keys. `.unflatten()` does the reverse, converting flat key-value pairs back into nested structures.
```rust
// Flatten: {"user": {"name": "John"}} → {"user.name": "John"}
// Unflatten: {"user.name": "John"} → {"user": {"name": "John"}}
```
**Q: Can I use the same configuration methods for both flatten and unflatten?**
A: Yes! All configuration methods (filtering, transformations, etc.) work for both operations. The library applies them intelligently based on the operation mode.
**Q: What happens if I don't call `.flatten()` or `.unflatten()` before `.execute()`?**
A: You'll get a `ConfigurationError` with a helpful message telling you to set the operation mode first.
### Python-Specific Questions
**Q: What input types does the Python API support?**
A: The Python API supports:
- `str` (JSON strings)
- `dict` (Python dictionaries)
- `List[str]` (lists of JSON strings)
- `List[dict]` (lists of Python dictionaries)
- Mixed lists (preserves original types)
**Q: Does the output type always match the input type?**
A: Yes! This is a key feature. `str` input → `str` output, `dict` input → `dict` output, etc. This makes the API predictable and easy to use.
### Performance Questions
**Q: How does performance compare to other JSON libraries?**
A: JSON Tools RS is optimized for high performance with SIMD-accelerated parsing, FxHashMap, and reduced allocations. Benchmarks show 2,000+ operations/ms for basic flattening. See the [Performance](#performance) section for details.
**Q: Is it safe to use in production?**
A: Yes! The library includes comprehensive error handling, extensive test coverage, and has been optimized for both correctness and performance.
### Feature Questions
**Q: How do I handle key collisions?**
A: Use `.handle_key_collision(true)` to collect colliding values into arrays. For example, if transformations cause `user_name` and `admin_name` to both become `name`, the result will be `{"name": ["John", "Jane"]}`.
**Q: Can I use regex patterns in replacements?**
A: Yes! Both `.key_replacement()` and `.value_replacement()` support standard Rust regex syntax. The library automatically detects regex patterns and falls back to literal replacement if the pattern is invalid.
**Q: What filtering options are available?**
A: You can remove:
- Empty strings: `.remove_empty_strings(true)`
- Null values: `.remove_nulls(true)`
- Empty objects: `.remove_empty_objects(true)`
- Empty arrays: `.remove_empty_arrays(true)`
All filtering methods work for both flatten and unflatten operations.
**Q: Can I process multiple JSON documents at once?**
A: Yes! Pass a `Vec<String>` in Rust or a `List[str]` or `List[dict]` in Python. The library will process them efficiently in batch mode.
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.
### Development Setup
1. **Clone the repository**
```bash
git clone https://github.com/amaye15/JSON-Tools-rs.git
cd JSON-Tools-rs
```
2. **Install Rust** (latest stable)
```bash
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
```
3. **Install Python 3.8+** and maturin for Python bindings
```bash
pip install maturin pytest
```
4. **Run tests** to ensure everything works
```bash
# Rust tests
cargo test
# Python tests
maturin develop --features python
python -m pytest python/tests/
```
5. **Run benchmarks** to verify performance
```bash
cargo bench
```
### Contribution Guidelines
- Write tests for new features
- Update documentation for API changes
- Run `cargo fmt` and `cargo clippy` before submitting
- Ensure all tests pass before creating a PR
- Add examples for significant new features
## License
This project is licensed under either of
- Apache License, Version 2.0 ([LICENSE-APACHE](LICENSE-APACHE) or http://www.apache.org/licenses/LICENSE-2.0)
- MIT License ([LICENSE-MIT](LICENSE-MIT) or http://opensource.org/licenses/MIT)
at your option.
## Changelog
### v0.4.0 (Current)
- Comprehensive README documentation update
- Enhanced API reference with detailed method descriptions
- Improved error handling documentation with examples
- Updated installation instructions
- Added contribution guidelines
- Performance optimization details and benchmarking guide
### v0.3.0
- Performance optimizations (FxHashMap, SIMD parsing, reduced allocations)
- Enhanced error messages with actionable suggestions
- Improved Python bindings stability
- Bug fixes and code quality improvements
### v0.2.0
- Updated README with comprehensive documentation
- Improved API documentation and examples
- Enhanced Python bindings documentation
- Performance optimization details
- Complete error handling documentation
### v0.1.0
- Initial release with unified JSONTools API
- Complete flattening and unflattening support
- Advanced filtering and transformation capabilities
- Key collision handling with `.handle_key_collision()`
- Python bindings with perfect type matching
- Comprehensive error handling with detailed suggestions
Raw data
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"keywords": "json, flatten, manipulation, parsing, rust, simd, performance",
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"description": "# JSON Tools RS\n\nA high-performance Rust library for advanced JSON manipulation with SIMD-accelerated parsing, providing unified flattening and unflattening operations through a clean builder pattern API.\n\n[](https://crates.io/crates/json-tools-rs)\n[](https://docs.rs/json-tools-rs)\n[](LICENSE-MIT)\n\n## Why JSON Tools RS?\n\nJSON Tools RS is designed for developers who need to:\n- **Transform nested JSON** into flat structures for databases, CSV exports, or analytics\n- **Clean and normalize** JSON data from external APIs or user input\n- **Process large batches** of JSON documents efficiently\n- **Maintain type safety** with perfect roundtrip support (flatten \u2192 unflatten \u2192 original)\n- **Work with both Rust and Python** using the same consistent API\n\nUnlike simple JSON parsers, JSON Tools RS provides a complete toolkit for JSON transformation with production-ready performance and error handling.\n\n## Features\n\n- \ud83d\ude80 **Unified API**: Single `JSONTools` entry point for flattening, unflattening, or pass-through transforms (`.normal()`)\n- \ud83d\udd27 **Builder Pattern**: Fluent, chainable API for easy configuration and method chaining\n- \u26a1 **High Performance**: SIMD-accelerated JSON parsing with FxHashMap and optimized memory allocations\n- \ud83d\ude84 **Parallel Processing**: Built-in Rayon-based parallelism for 3-5x speedup on batch operations (automatic, no configuration needed)\n- \ud83c\udfaf **Complete Roundtrip**: Flatten JSON and unflatten back to original structure with perfect fidelity\n- \ud83e\uddf9 **Comprehensive Filtering**: Remove empty strings, nulls, empty objects, and empty arrays (works for both flatten and unflatten)\n- \ud83d\udd04 **Advanced Replacements**: Literal and regex-based key/value replacements using standard Rust regex syntax\n- \ud83d\udee1\ufe0f **Collision Handling**: Intelligent `.handle_key_collision(true)` to collect colliding values into arrays\n- \ud83d\udd00 **Automatic Type Conversion**: Convert strings to numbers and booleans with `.auto_convert_types(true)` - handles currency, thousands separators, scientific notation\n- \ud83d\udce6 **Batch Processing**: Process single JSON or batches; Python also supports dicts and lists of dicts\n- \ud83d\udc0d **Python Bindings**: Full Python support with perfect type preservation (input type = output type)\n- \ud83e\uddf0 **Robust Errors**: Comprehensive `JsonToolsError` enum with helpful suggestions for debugging\n- \ud83d\udd25 **Performance Optimizations**: FxHashMap (~15-30% faster), SIMD parsing, Cow-based string handling, and automatic parallel processing\n\n## Table of Contents\n\n- [Why JSON Tools RS?](#why-json-tools-rs)\n- [Features](#features)\n- [Quick Start](#quick-start)\n - [Rust Examples](#rust---unified-jsontools-api)\n - [Python Examples](#python---unified-jsontools-api)\n- [Quick Reference](#quick-reference)\n- [Installation](#installation)\n- [Performance](#performance)\n- [API Reference](#api-reference)\n - [Core Methods](#core-methods)\n - [Configuration Methods](#configuration-methods)\n - [Input/Output Types](#inputoutput-types)\n- [Error Handling](#error-handling)\n- [Common Use Cases](#common-use-cases)\n- [Examples and Testing](#examples-and-testing)\n- [Limitations and Known Issues](#limitations-and-known-issues)\n- [FAQ](#frequently-asked-questions-faq)\n- [Contributing](#contributing)\n- [License](#license)\n- [Changelog](#changelog)\n\n## Quick Start\n\n### Rust - Unified JSONTools API\n\nThe `JSONTools` struct provides a unified builder pattern API for all JSON manipulation operations. Simply call `.flatten()` or `.unflatten()` to set the operation mode, then chain configuration methods and call `.execute()`.\n\n#### Basic Flattening\n\n```rust\nuse json_tools_rs::{JSONTools, JsonOutput};\n\nlet json = r#\"{\"user\": {\"name\": \"John\", \"profile\": {\"age\": 30, \"city\": \"NYC\"}}}\"#;\nlet result = JSONTools::new()\n .flatten()\n .execute(json)?;\n\nif let JsonOutput::Single(flattened) = result {\n println!(\"{}\", flattened);\n}\n// Output: {\"user.name\": \"John\", \"user.profile.age\": 30, \"user.profile.city\": \"NYC\"}\n```\n\n#### Advanced Flattening with Filtering\n\n```rust\nuse json_tools_rs::{JSONTools, JsonOutput};\n\nlet json = r#\"{\"user\": {\"name\": \"John\", \"details\": {\"age\": null, \"city\": \"\"}}}\"#;\nlet result = JSONTools::new()\n .flatten()\n .separator(\"::\")\n .lowercase_keys(true)\n .key_replacement(\"(User|Admin)_\", \"\")\n .value_replacement(\"@example.com\", \"@company.org\")\n .remove_empty_strings(true)\n .remove_nulls(true)\n .remove_empty_objects(true)\n .remove_empty_arrays(true)\n .execute(json)?;\n\nif let JsonOutput::Single(flattened) = result {\n println!(\"{}\", flattened);\n}\n// Output: {\"user::name\": \"John\"}\n```\n\n#### Basic Unflattening\n\n```rust\nuse json_tools_rs::{JSONTools, JsonOutput};\n\nlet flattened = r#\"{\"user.name\": \"John\", \"user.profile.age\": 30}\"#;\nlet result = JSONTools::new()\n .unflatten()\n .execute(flattened)?;\n\nmatch result {\n JsonOutput::Single(unflattened) => println!(\"{}\", unflattened),\n JsonOutput::Multiple(_) => unreachable!(),\n}\n// Output: {\"user\": {\"name\": \"John\", \"profile\": {\"age\": 30}}}\n```\n\n#### Advanced Unflattening with Configuration\n\n```rust\nuse json_tools_rs::{JSONTools, JsonOutput};\n\nlet flattened = r#\"{\"user::name\": \"John\", \"user::age\": 30, \"user::email\": \"\"}\"#;\nlet result = JSONTools::new()\n .unflatten()\n .separator(\"::\")\n .lowercase_keys(true)\n .remove_empty_strings(true)\n .remove_nulls(true)\n .execute(flattened)?;\n\nmatch result {\n JsonOutput::Single(unflattened) => println!(\"{}\", unflattened),\n JsonOutput::Multiple(_) => unreachable!(),\n}\n// Output: {\"user\": {\"name\": \"John\", \"age\": 30}}\n```\n\n#### Key Collision Handling\n\nWhen transformations make different keys end up identical, enable collision handling to collect values into arrays.\n\n```rust\nuse json_tools_rs::{JSONTools, JsonOutput};\n\nlet json = r#\"{\"user_name\": \"John\", \"admin_name\": \"Jane\"}\"#;\nlet result = JSONTools::new()\n .flatten()\n .key_replacement(\"(user|admin)_\", \"\") // both become \"name\"\n .handle_key_collision(true) // collect colliding values\n .execute(json)?;\n\nif let JsonOutput::Single(flattened) = result {\n println!(\"{}\", flattened);\n}\n// Output: {\"name\": [\"John\", \"Jane\"]}\n```\n\n#### Automatic Type Conversion\n\nConvert string values to numbers and booleans automatically for data cleaning and normalization.\n\n```rust\nuse json_tools_rs::{JSONTools, JsonOutput};\n\nlet json = r#\"{\n \"id\": \"123\",\n \"price\": \"$1,234.56\",\n \"quantity\": \"1,000\",\n \"active\": \"true\",\n \"verified\": \"FALSE\",\n \"name\": \"Product\"\n}\"#;\n\nlet result = JSONTools::new()\n .flatten()\n .auto_convert_types(true)\n .execute(json)?;\n\nif let JsonOutput::Single(flattened) = result {\n println!(\"{}\", flattened);\n}\n// Output: {\n// \"id\": 123,\n// \"price\": 1234.56,\n// \"quantity\": 1000,\n// \"active\": true,\n// \"verified\": false,\n// \"name\": \"Product\" // Keeps as string (not a valid number or boolean)\n// }\n```\n\n#### Perfect Roundtrip Support\n\n```rust\nuse json_tools_rs::{JSONTools, JsonOutput};\n\nlet original = r#\"{\"user\": {\"name\": \"John\", \"age\": 30}, \"items\": [1, 2, {\"nested\": \"value\"}]}\"#;\n\n// Flatten\nlet flattened = JSONTools::new().flatten().execute(original)?;\nlet flattened_str = match flattened { JsonOutput::Single(s) => s, _ => unreachable!() };\n\n// Unflatten back to original structure\nlet restored = JSONTools::new().unflatten().execute(&flattened_str)?;\nlet restored_str = match restored { JsonOutput::Single(s) => s, _ => unreachable!() };\n\n// Verify perfect roundtrip\nassert_eq!(\n serde_json::from_str::<serde_json::Value>(original)?,\n serde_json::from_str::<serde_json::Value>(&restored_str)?\n);\n```\n\n\n### Python - Unified JSONTools API\n\nThe Python bindings provide the same unified `JSONTools` API with **perfect type matching**: input type equals output type. This makes the API predictable and easy to use.\n\n#### Type Preservation Examples\n\n```python\nimport json_tools_rs as jt\n\n# Example 1: dict input \u2192 dict output\nresult = jt.JSONTools().flatten().execute({\"user\": {\"name\": \"John\", \"age\": 30}})\nprint(result) # {'user.name': 'John', 'user.age': 30}\nprint(type(result)) # <class 'dict'>\n\n# Example 2: JSON string input \u2192 JSON string output\nresult = jt.JSONTools().flatten().execute('{\"user\": {\"name\": \"John\", \"age\": 30}}')\nprint(result) # '{\"user.name\": \"John\", \"user.age\": 30}'\nprint(type(result)) # <class 'str'>\n\n# Example 3: List[dict] input \u2192 List[dict] output\nbatch = [{\"a\": {\"b\": 1}}, {\"c\": {\"d\": 2}}]\nresult = jt.JSONTools().flatten().execute(batch)\nprint(result) # [{'a.b': 1}, {'c.d': 2}]\nprint(type(result[0])) # <class 'dict'>\n\n# Example 4: List[str] input \u2192 List[str] output\nbatch = ['{\"a\": {\"b\": 1}}', '{\"c\": {\"d\": 2}}']\nresult = jt.JSONTools().flatten().execute(batch)\nprint(result) # ['{\"a.b\": 1}', '{\"c.d\": 2}']\nprint(type(result[0])) # <class 'str'>\n```\n\n#### Basic Usage\n\n```python\nimport json_tools_rs as jt\n\n# Basic flattening - dict input \u2192 dict output\nresult = jt.JSONTools().flatten().execute({\"user\": {\"name\": \"John\", \"age\": 30}})\nprint(result) # {'user.name': 'John', 'user.age': 30}\n\n# Basic unflattening - dict input \u2192 dict output\nresult = jt.JSONTools().unflatten().execute({\"user.name\": \"John\", \"user.age\": 30})\nprint(result) # {'user': {'name': 'John', 'age': 30}}\n```\n\n#### Advanced Configuration\n\n```python\nimport json_tools_rs as jt\n\n# Advanced flattening with filtering and transformations\ntools = (jt.JSONTools()\n .flatten()\n .separator(\"::\")\n .lowercase_keys(True)\n .remove_empty_strings(True)\n .remove_nulls(True)\n .remove_empty_objects(True)\n .remove_empty_arrays(True)\n .key_replacement(\"(User|Admin)_\", \"\")\n .value_replacement(\"@example.com\", \"@company.org\"))\n\ndata = {\"User_name\": \"John\", \"Admin_email\": \"john@example.com\", \"empty\": \"\", \"null_val\": None}\nresult = tools.execute(data)\nprint(result) # {'name': 'John', 'email': 'john@company.org'}\n\n# Advanced unflattening with same configuration options\nresult = (jt.JSONTools()\n .unflatten()\n .separator(\"::\")\n .lowercase_keys(True)\n .remove_empty_strings(True)\n .remove_nulls(True)\n .key_replacement(\"prefix_\", \"user_\")\n .value_replacement(\"@company.org\", \"@example.com\")\n .execute({\"PREFIX_NAME\": \"john\", \"PREFIX_EMAIL\": \"john@company.org\", \"empty\": \"\"}))\nprint(result) # {'user': {'name': 'john', 'email': 'john@example.com'}}\n```\n\n#### Key Collision Handling\n\nWhen transformations make different keys end up identical, enable collision handling to collect values into arrays.\n\n```python\nimport json_tools_rs as jt\n\ntools = (jt.JSONTools()\n .flatten()\n .key_replacement(\"(user|admin)_\", \"\") # both become \"name\"\n .handle_key_collision(True)) # collect colliding values\n\ndata = {\"user_name\": \"John\", \"admin_name\": \"Jane\"}\nprint(tools.execute(data)) # {'name': ['John', 'Jane']}\n```\n\n#### Automatic Type Conversion\n\nConvert string values to numbers and booleans automatically for data cleaning and normalization.\n\n```python\nimport json_tools_rs as jt\n\n# Type conversion with dict input\ndata = {\n \"id\": \"123\",\n \"price\": \"$1,234.56\",\n \"quantity\": \"1,000\",\n \"active\": \"true\",\n \"verified\": \"FALSE\",\n \"name\": \"Product\"\n}\n\nresult = (jt.JSONTools()\n .flatten()\n .auto_convert_types(True)\n .execute(data))\n\nprint(result)\n# Output: {\n# 'id': 123,\n# 'price': 1234.56,\n# 'quantity': 1000,\n# 'active': True,\n# 'verified': False,\n# 'name': 'Product' # Keeps as string (not a valid number or boolean)\n# }\n\n# Works with JSON strings too\njson_str = '{\"id\": \"456\", \"enabled\": \"true\", \"amount\": \"\u20ac99.99\"}'\nresult = jt.JSONTools().flatten().auto_convert_types(True).execute(json_str)\nprint(result) # '{\"id\": 456, \"enabled\": true, \"amount\": 99.99}'\n```\n\n#### Batch Processing with Type Preservation\n\n```python\nimport json_tools_rs as jt\n\ntools = jt.JSONTools().flatten()\n\n# List[str] input \u2192 List[str] output\nstr_batch = ['{\"a\": {\"b\": 1}}', '{\"c\": {\"d\": 2}}']\nresults = tools.execute(str_batch)\nprint(results) # ['{\"a.b\": 1}', '{\"c.d\": 2}']\n\n# List[dict] input \u2192 List[dict] output\ndict_batch = [{\"a\": {\"b\": 1}}, {\"c\": {\"d\": 2}}]\nresults = tools.execute(dict_batch)\nprint(results) # [{'a.b': 1}, {'c.d': 2}]\n\n# Mixed types are handled automatically\nmixed_batch = ['{\"a\": 1}', {\"b\": {\"c\": 2}}]\nresults = tools.execute(mixed_batch)\nprint(results) # ['{\"a\": 1}', {'b.c': 2}]\n```\n\n#### Perfect Roundtrip Support\n\n```python\nimport json_tools_rs\n\n# Perfect roundtrip with Python dicts\noriginal = {\"user\": {\"name\": \"John\", \"age\": 30}, \"items\": [1, 2, {\"nested\": \"value\"}]}\n\n# Flatten\nflattened = json_tools_rs.JSONTools().flatten().execute(original)\nprint(f\"Flattened: {flattened}\")\n\n# Unflatten back to original structure\nrestored = json_tools_rs.JSONTools().unflatten().execute(flattened)\nprint(f\"Restored: {restored}\")\n\n# Verify perfect roundtrip\nassert original == restored # Perfect roundtrip with dicts!\n```\n\n## Quick Reference\n\n### Method Cheat Sheet\n\n| Method | Description | Example |\n|--------|-------------|---------|\n| `.flatten()` | Set operation mode to flatten | `JSONTools::new().flatten()` |\n| `.unflatten()` | Set operation mode to unflatten | `JSONTools::new().unflatten()` |\n| `.separator(sep)` | Set key separator (default: `\".\"`) | `.separator(\"::\")` |\n| `.lowercase_keys(bool)` | Convert keys to lowercase | `.lowercase_keys(true)` |\n| `.remove_empty_strings(bool)` | Remove empty string values | `.remove_empty_strings(true)` |\n| `.remove_nulls(bool)` | Remove null values | `.remove_nulls(true)` |\n| `.remove_empty_objects(bool)` | Remove empty objects `{}` | `.remove_empty_objects(true)` |\n| `.remove_empty_arrays(bool)` | Remove empty arrays `[]` | `.remove_empty_arrays(true)` |\n| `.key_replacement(find, replace)` | Replace key patterns (regex or literal) | `.key_replacement(\"user_\", \"\")` |\n| `.value_replacement(find, replace)` | Replace value patterns (regex or literal) | `.value_replacement(\"@old.com\", \"@new.com\")` |\n| `.handle_key_collision(bool)` | Collect colliding keys into arrays | `.handle_key_collision(true)` |\n| `.execute(input)` | Execute the configured operation | `.execute(json_string)` |\n\n### Common Patterns\n\n**Flatten with filtering:**\n```rust\nJSONTools::new()\n .flatten()\n .remove_nulls(true)\n .remove_empty_strings(true)\n .execute(json)?\n```\n\n**Unflatten with custom separator:**\n```rust\nJSONTools::new()\n .unflatten()\n .separator(\"::\")\n .execute(flattened_json)?\n```\n\n**Transform keys and values:**\n```rust\nJSONTools::new()\n .flatten()\n .lowercase_keys(true)\n .key_replacement(\"(user|admin)_\", \"\")\n .value_replacement(\"@example.com\", \"@company.org\")\n .execute(json)?\n```\n\n**Handle key collisions:**\n```rust\nJSONTools::new()\n .flatten()\n .key_replacement(\"prefix_\", \"\")\n .handle_key_collision(true) // Colliding values \u2192 arrays\n .execute(json)?\n```\n\n## Installation\n\n### Rust\n\nAdd to your `Cargo.toml`:\n\n```toml\n[dependencies]\njson-tools-rs = \"0.7.0\"\n```\n\nOr install via cargo:\n\n```bash\ncargo add json-tools-rs\n```\n\n**Note**: Parallel processing is built-in and automatic - no feature flags needed!\n\n### Python\n\n#### From PyPI (Recommended)\n\n```bash\npip install json-tools-rs\n```\n\n#### Build from Source with Maturin\n\nIf you want to build from source or contribute to development:\n\n```bash\n# Clone the repository\ngit clone https://github.com/amaye15/JSON-Tools-rs.git\ncd JSON-Tools-rs\n\n# Install maturin if you haven't already\npip install maturin\n\n# Build and install the Python package\nmaturin develop --features python\n\n# Or build a wheel for distribution\nmaturin build --features python --release\n```\n\n#### Development Setup\n\n```bash\n# For development with automatic rebuilds\nmaturin develop --features python\n\n# Run Python examples\npython python/examples/basic_usage.py\npython python/examples/examples.py\n```\n\n## Performance\n\nJSON Tools RS delivers exceptional performance through multiple carefully implemented optimizations:\n\n### Performance Optimizations\n\n1. **FxHashMap** - ~15-30% faster string key operations compared to standard HashMap\n - Optimized hash function for string keys\n - Reduced collision overhead\n\n2. **SIMD JSON Parsing** - Hardware-accelerated parsing and serialization via simd-json\n - Leverages CPU SIMD instructions for parallel processing\n - Significantly faster than standard serde_json for large payloads\n\n3. **Reduced Allocations** - Minimized memory allocations using Cow (Copy-on-Write) and scoped buffers\n - ~50% reduction in string clones during key transformations\n - Efficient memory reuse across operations\n\n4. **Smart Capacity Management** - Pre-sized maps and string builders to minimize rehashing\n - Reduces reallocation overhead\n - Improves cache locality\n\n5. **Parallel Batch Processing** (built-in, always enabled) - Rayon-based parallelism for batch operations\n - **3-5x speedup** for batches of 10+ items on multi-core CPUs\n - Adaptive threshold prevents overhead for small batches\n - Zero per-item memory overhead\n - Thread-safe regex cache with Arc<Regex> for O(1) cloning\n\n### Parallel Processing\n\nParallel processing is **built-in and automatic** - no feature flags or special configuration needed!\n\nJSON-Tools-rs provides **two levels of parallelism**:\n\n#### 1. Batch-Level Parallelism (Across Multiple Documents)\n\nProcess multiple JSON documents in parallel automatically.\n\n**Performance Gains:**\n- Batch size 10: **2.5x faster**\n- Batch size 50: **3.3x faster**\n- Batch size 100: **3.3x faster**\n- Batch size 500: **5.3x faster**\n- Batch size 1000: **5.4x faster**\n\n**Configuration (Optional):**\n\n```rust\nuse json_tools_rs::JSONTools;\n\n// Default threshold (10 items) - optimal for most use cases\n// Parallelism activates automatically for batches \u2265 10 items\nlet result = JSONTools::new()\n .flatten()\n .execute(batch)?;\n\n// Custom threshold for fine-tuning\nlet result = JSONTools::new()\n .flatten()\n .parallel_threshold(50) // Only parallelize batches \u2265 50 items\n .execute(batch)?;\n\n// Custom thread count\nlet result = JSONTools::new()\n .flatten()\n .num_threads(Some(4)) // Use exactly 4 threads\n .execute(batch)?;\n\n// Environment variables (runtime configuration)\n// JSON_TOOLS_PARALLEL_THRESHOLD=20 cargo run\n// JSON_TOOLS_NUM_THREADS=4 cargo run\n```\n\n**How it works:**\n- Batches below threshold (default: 10): Sequential processing (no overhead)\n- Batches 10-1000: Rayon work-stealing parallelism\n- Batches > 1000: Chunked processing for optimal cache locality\n- Each worker thread gets its own regex cache\n- Zero per-item memory increase (only 8-16MB one-time thread pool)\n- Thread count defaults to number of logical CPUs (configurable via `num_threads()` or `JSON_TOOLS_NUM_THREADS`)\n\n#### 2. Nested Parallelism (Within Large Documents)\n\nFor large individual JSON documents, nested parallelism automatically parallelizes the processing of large objects and arrays **within** a single document.\n\n**Performance Gains:**\n- Large documents (20,000+ items): **7-12% faster**\n- Very large documents (100,000+ items): **7-12% faster**\n- Small/medium documents: No overhead (stays sequential)\n\n**Configuration (Optional):**\n\n```rust\nuse json_tools_rs::JSONTools;\n\n// Default threshold (100 items) - optimal for most use cases\n// Objects/arrays with 100+ keys/items are processed in parallel\nlet result = JSONTools::new()\n .flatten()\n .execute(large_json)?;\n\n// Custom threshold for very large documents\nlet result = JSONTools::new()\n .flatten()\n .nested_parallel_threshold(50) // More aggressive parallelism\n .execute(large_json)?;\n\n// Disable nested parallelism (for small/medium documents)\nlet result = JSONTools::new()\n .flatten()\n .nested_parallel_threshold(usize::MAX) // Disable\n .execute(json)?;\n\n// Environment variable (runtime configuration)\n// JSON_TOOLS_NESTED_PARALLEL_THRESHOLD=200 cargo run\n```\n\n**How it works:**\n- Objects/arrays below threshold (default: 100): Sequential processing\n- Objects/arrays above threshold: Parallel processing using Rayon\n- Each parallel branch gets its own string builder\n- Results are merged efficiently with minimal overhead\n- Rayon's work-stealing automatically balances load across CPU cores\n- Minimal memory overhead (< 1 MB for very large documents)\n\n**When to use:**\n- \u2705 Large JSON documents (20,000+ items)\n- \u2705 Very large JSON documents (100,000+ items)\n- \u2705 Wide, flat structures (many keys at same level)\n- \u274c Small documents (< 5,000 items) - no benefit\n- \u274c Deeply nested but narrow structures - marginal benefit\n\n### Benchmark Results\n\nPerformance varies by workload complexity, but typical results on modern hardware include:\n\n- **Basic flattening**: 2,000+ operations/ms\n- **Advanced configuration**: 1,300+ operations/ms (with filtering and transformations)\n- **Regex replacements**: 1,800+ operations/ms (with pattern matching)\n- **Batch processing**: 1,900+ operations/ms (for multiple JSON documents)\n- **Roundtrip operations**: 1,000+ flatten\u2192unflatten cycles/ms\n\n*Note: Benchmarks run on typical development hardware. Your results may vary based on CPU, memory, and workload characteristics.*\n\n### Running Benchmarks\n\n```bash\n# Run comprehensive benchmarks\ncargo bench\n\n# Run specific benchmark suites\ncargo bench flatten\ncargo bench unflatten\ncargo bench roundtrip\n\n# Generate HTML reports (available in target/criterion)\ncargo bench --features html_reports\n```\n\n## API Reference\n\n### JSONTools - Unified API\n\nThe `JSONTools` struct is the single entry point for all JSON manipulation operations. It provides a builder pattern API that works for both flattening and unflattening operations.\n\n#### Core Methods\n\n- **`JSONTools::new()`** - Create a new instance with default settings\n- **`.flatten()`** - Configure for flattening operations (converts nested JSON to flat key-value pairs)\n- **`.unflatten()`** - Configure for unflattening operations (converts flat key-value pairs back to nested JSON)\n- **`.normal()`** - Configure for pass-through operations (apply transformations without flattening/unflattening)\n- **`.execute(input)`** - Execute the configured operation on the provided input\n\n#### Configuration Methods\n\nAll configuration methods are chainable and available for both flattening and unflattening operations:\n\n##### Key/Value Transformation Methods\n\n- **`.separator(sep: &str)`** - Set separator for nested keys (default: `\".\"`)\n - Example: `separator(\"::\")` makes keys like `user::name::first`\n\n- **`.lowercase_keys(value: bool)`** - Convert all keys to lowercase\n - Example: `UserName` becomes `username`\n\n- **`.key_replacement(find: &str, replace: &str)`** - Add key replacement pattern\n - Supports standard Rust regex syntax (automatically detected)\n - Falls back to literal string replacement if regex compilation fails\n - Example: `key_replacement(\"(user|admin)_\", \"\")` removes prefixes\n\n- **`.value_replacement(find: &str, replace: &str)`** - Add value replacement pattern\n - Supports standard Rust regex syntax (automatically detected)\n - Falls back to literal string replacement if regex compilation fails\n - Example: `value_replacement(\"@example.com\", \"@company.org\")` updates email domains\n\n##### Filtering Methods\n\nAll filtering methods work for both flatten and unflatten operations:\n\n- **`.remove_empty_strings(value: bool)`** - Remove keys with empty string values (`\"\"`)\n- **`.remove_nulls(value: bool)`** - Remove keys with null values\n- **`.remove_empty_objects(value: bool)`** - Remove keys with empty object values (`{}`)\n- **`.remove_empty_arrays(value: bool)`** - Remove keys with empty array values (`[]`)\n\n##### Collision Handling Methods\n\n- **`.handle_key_collision(value: bool)`** - When enabled, collects values with identical keys into arrays\n - Useful when transformations cause different keys to become identical\n - Example: After removing prefixes, `user_name` and `admin_name` both become `name`\n - With collision handling: `{\"name\": [\"John\", \"Jane\"]}`\n - Without collision handling: Last value wins\n\n##### Type Conversion Methods\n\n- **`.auto_convert_types(enable: bool)`** - Automatically convert string values to numbers and booleans\n - **Number conversion**: Handles various formats including:\n - Basic numbers: `\"123\"` \u2192 `123`, `\"45.67\"` \u2192 `45.67`, `\"-10\"` \u2192 `-10`\n - Thousands separators: `\"1,234.56\"` \u2192 `1234.56` (US), `\"1.234,56\"` \u2192 `1234.56` (EU)\n - Currency symbols: `\"$123.45\"` \u2192 `123.45`, `\"\u20ac99.99\"` \u2192 `99.99`\n - Scientific notation: `\"1e5\"` \u2192 `100000`, `\"1.23e-4\"` \u2192 `0.000123`\n - **Boolean conversion**: Only these exact variants:\n - `\"true\"`, `\"TRUE\"`, `\"True\"` \u2192 `true`\n - `\"false\"`, `\"FALSE\"`, `\"False\"` \u2192 `false`\n - **Lenient behavior**: If conversion fails, keeps the original string value (no errors thrown)\n - **Works for all modes**: `.flatten()`, `.unflatten()`, and `.normal()`\n - **Example**:\n ```rust\n let json = r#\"{\"id\": \"123\", \"price\": \"$1,234.56\", \"active\": \"true\"}\"#;\n let result = JSONTools::new()\n .flatten()\n .auto_convert_types(true)\n .execute(json)?;\n // Result: {\"id\": 123, \"price\": 1234.56, \"active\": true}\n ```\n\n#### Input/Output Types\n\n**Rust:**\n- `&str` (JSON string) \u2192 `JsonOutput::Single(String)`\n- `Vec<&str>` or `Vec<String>` \u2192 `JsonOutput::Multiple(Vec<String>)`\n\n**Python (Perfect Type Preservation):**\n- `str` \u2192 `str` (JSON string input \u2192 JSON string output)\n- `dict` \u2192 `dict` (Python dict input \u2192 Python dict output)\n- `List[str]` \u2192 `List[str]` (list of JSON strings \u2192 list of JSON strings)\n- `List[dict]` \u2192 `List[dict]` (list of Python dicts \u2192 list of Python dicts)\n- Mixed lists preserve original element types\n\n### Error Handling\n\nThe library uses a comprehensive `JsonToolsError` enum that provides detailed error information and actionable suggestions for debugging:\n\n#### Error Variants\n\n- **`JsonParseError`** - JSON parsing failures with syntax suggestions\n - Triggered by: Invalid JSON syntax, malformed input\n - Suggestion: Verify JSON syntax, check for missing quotes, trailing commas, unescaped characters\n\n- **`RegexError`** - Regex pattern compilation errors with pattern suggestions\n - Triggered by: Invalid regex patterns in `key_replacement()` or `value_replacement()`\n - Suggestion: Verify regex syntax using standard Rust regex patterns\n\n- **`InvalidJsonStructure`** - Structure validation errors with format guidance\n - Triggered by: Incompatible JSON structure for the requested operation\n - Suggestion: Ensure input matches expected format (nested for flatten, flat for unflatten)\n\n- **`ConfigurationError`** - API usage errors with correct usage examples\n - Triggered by: Calling `.execute()` without setting operation mode\n - Suggestion: Call `.flatten()` or `.unflatten()` before `.execute()`\n\n- **`BatchProcessingError`** - Batch operation errors with item-specific details\n - Triggered by: Invalid item in batch processing\n - Includes: Index of failing item for easy debugging\n - Suggestion: Check the JSON at the specified index\n\n- **`InputValidationError`** - Input validation errors with helpful guidance\n - Triggered by: Invalid input type or empty input\n - Suggestion: Ensure input is valid JSON string, dict, or list\n\n- **`SerializationError`** - JSON serialization failures with debugging information\n - Triggered by: Internal serialization errors (rare)\n - Suggestion: Report as potential bug\n\n#### Error Handling Examples\n\n**Rust:**\n```rust\nuse json_tools_rs::{JSONTools, JsonToolsError};\n\nmatch JSONTools::new().flatten().execute(invalid_json) {\n Ok(result) => println!(\"Success: {:?}\", result),\n Err(JsonToolsError::JsonParseError { message, suggestion, .. }) => {\n eprintln!(\"Parse error: {}\", message);\n eprintln!(\"\ud83d\udca1 {}\", suggestion);\n }\n Err(e) => eprintln!(\"Error: {}\", e),\n}\n```\n\n**Python:**\n```python\nimport json_tools_rs\n\ntry:\n result = json_tools_rs.JSONTools().flatten().execute(invalid_json)\nexcept json_tools_rs.JsonToolsError as e:\n print(f\"Error: {e}\")\n # Error messages include helpful suggestions\n```\n\n## Common Use Cases\n\n### 1. Data Pipeline Transformations\n\nFlatten nested API responses for easier processing in data pipelines:\n\n```rust\nuse json_tools_rs::{JSONTools, JsonOutput};\n\nlet api_response = r#\"{\n \"user\": {\n \"id\": 123,\n \"profile\": {\"name\": \"John\", \"email\": \"john@example.com\"},\n \"settings\": {\"theme\": \"dark\", \"notifications\": true}\n }\n}\"#;\n\nlet flattened = JSONTools::new()\n .flatten()\n .execute(api_response)?;\n// Result: {\"user.id\": 123, \"user.profile.name\": \"John\", ...}\n// Perfect for CSV export, database insertion, or analytics\n```\n\n### 2. Data Cleaning and Normalization\n\nRemove empty values and normalize keys for consistent data processing:\n\n```python\nimport json_tools_rs as jt\n\n# Clean messy data from external sources\nmessy_data = {\n \"UserName\": \"Alice\",\n \"Email\": \"\", # Empty string\n \"Age\": None, # Null value\n \"Preferences\": {}, # Empty object\n \"Tags\": [] # Empty array\n}\n\ncleaned = (jt.JSONTools()\n .flatten()\n .lowercase_keys(True)\n .remove_empty_strings(True)\n .remove_nulls(True)\n .remove_empty_objects(True)\n .remove_empty_arrays(True)\n .execute(messy_data))\n\n# Result: {'username': 'Alice'}\n# All empty/null values removed, keys normalized\n```\n\n### 3. Configuration File Processing\n\nTransform between flat and nested configuration formats:\n\n```rust\nuse json_tools_rs::{JSONTools, JsonOutput};\n\n// Convert flat environment-style config to nested structure\nlet flat_config = r#\"{\n \"database.host\": \"localhost\",\n \"database.port\": 5432,\n \"database.name\": \"myapp\",\n \"cache.enabled\": true,\n \"cache.ttl\": 3600,\n \"cache.redis.host\": \"redis.local\"\n}\"#;\n\nlet nested = JSONTools::new()\n .unflatten()\n .execute(flat_config)?;\n// Result: {\n// \"database\": {\"host\": \"localhost\", \"port\": 5432, \"name\": \"myapp\"},\n// \"cache\": {\"enabled\": true, \"ttl\": 3600, \"redis\": {\"host\": \"redis.local\"}}\n// }\n```\n\n### 4. Batch Data Processing\n\nProcess multiple JSON documents efficiently with type preservation:\n\n```python\nimport json_tools_rs as jt\n\n# Process batch of API responses\nresponses = [\n {\"user\": {\"id\": 1, \"name\": \"Alice\", \"email\": \"alice@example.com\"}},\n {\"user\": {\"id\": 2, \"name\": \"Bob\", \"email\": \"bob@example.com\"}},\n {\"user\": {\"id\": 3, \"name\": \"Charlie\", \"email\": \"charlie@example.com\"}}\n]\n\n# Flatten all responses in one call\nflattened_batch = jt.JSONTools().flatten().execute(responses)\n# Result: [\n# {'user.id': 1, 'user.name': 'Alice', 'user.email': 'alice@example.com'},\n# {'user.id': 2, 'user.name': 'Bob', 'user.email': 'bob@example.com'},\n# {'user.id': 3, 'user.name': 'Charlie', 'user.email': 'charlie@example.com'}\n# ]\n```\n\n### 5. Multi-Source Data Aggregation\n\nAggregate data from multiple sources with key collision handling:\n\n```python\nimport json_tools_rs as jt\n\n# Data from different sources with overlapping keys\nuser_data = {\"name\": \"John\", \"source\": \"database\"}\nadmin_data = {\"name\": \"Jane\", \"source\": \"ldap\"}\nguest_data = {\"name\": \"Guest\", \"source\": \"default\"}\n\n# Combine with collision handling\ncombined = jt.JSONTools().flatten().handle_key_collision(True).execute([\n user_data, admin_data, guest_data\n])\n\n# With collision handling, duplicate keys become arrays\n# Result: [\n# {'name': 'John', 'source': 'database'},\n# {'name': 'Jane', 'source': 'ldap'},\n# {'name': 'Guest', 'source': 'default'}\n# ]\n```\n\n### 6. ETL Pipeline: Extract, Transform, Load\n\nComplete ETL workflow with data transformation:\n\n```rust\nuse json_tools_rs::{JSONTools, JsonOutput};\n\n// Extract: Raw data from source\nlet raw_data = r#\"{\n \"USER_ID\": 12345,\n \"USER_PROFILE\": {\n \"FIRST_NAME\": \"John\",\n \"LAST_NAME\": \"Doe\",\n \"EMAIL_ADDRESS\": \"john.doe@oldcompany.com\",\n \"METADATA\": {\"created\": \"\", \"updated\": null}\n }\n}\"#;\n\n// Transform: Clean and normalize\nlet transformed = JSONTools::new()\n .flatten()\n .lowercase_keys(true) // Normalize keys\n .key_replacement(\"user_profile.\", \"\") // Remove prefix\n .value_replacement(\"@oldcompany.com\", \"@newcompany.com\") // Update domain\n .remove_empty_strings(true) // Clean empty values\n .remove_nulls(true) // Remove nulls\n .execute(raw_data)?;\n\n// Load: Result ready for database insertion\n// Result: {\n// \"user_id\": 12345,\n// \"first_name\": \"John\",\n// \"last_name\": \"Doe\",\n// \"email_address\": \"john.doe@newcompany.com\"\n// }\n```\n\n## Examples and Testing\n\n### Running Examples\n\n**Rust Examples:**\n```bash\n# Basic usage examples\ncargo run --example basic_usage\n\n# View all available examples\nls examples/\n```\n\n**Python Examples:**\n```bash\n# Basic usage with type preservation\npython python/examples/basic_usage.py\n\n# Advanced features and collision handling\npython python/examples/examples.py\n```\n\n### Running Tests\n\n**Rust Tests:**\n```bash\n# Run all Rust tests\ncargo test\n\n# Run tests with verbose output\ncargo test -- --nocapture\n\n# Run tests with Python features enabled\ncargo test --features python\n\n# Run specific test module\ncargo test test_module_name\n```\n\n**Python Tests:**\n```bash\n# Install test dependencies\npip install pytest\n\n# Build the Python package first\nmaturin develop --features python\n\n# Run all Python tests\npython -m pytest python/tests/\n\n# Run with verbose output\npython -m pytest python/tests/ -v\n\n# Run specific test file\npython -m pytest python/tests/tests.py::TestClassName\n```\n\n## Limitations and Known Issues\n\n### Current Limitations\n\n1. **Array Index Notation**: Arrays are flattened using numeric indices (e.g., `array.0`, `array.1`). Custom array handling is not currently supported.\n\n2. **Separator Constraints**: The separator cannot contain characters that are valid in JSON keys without escaping. Choose separators carefully to avoid conflicts.\n\n3. **Regex Syntax**: Only standard Rust regex syntax is supported. Some advanced regex features may not be available.\n\n4. **Memory Usage**: For very large JSON documents (>100MB), consider processing in smaller batches to optimize memory usage.\n\n### Workarounds\n\n**For custom array handling:**\n```rust\n// Pre-process arrays before flattening if custom handling is needed\n// Or post-process the flattened result to transform array indices\n```\n\n**For separator conflicts:**\n```rust\n// Use a separator that won't appear in your keys\nJSONTools::new().flatten().separator(\"::\").execute(json)?\n```\n\n### Reporting Issues\n\nIf you encounter a bug or have a feature request, please [open an issue](https://github.com/amaye15/JSON-Tools-rs/issues) on GitHub with:\n- A minimal reproducible example\n- Expected vs. actual behavior\n- Your environment (Rust version, OS, etc.)\n\n## Frequently Asked Questions (FAQ)\n\n### General Questions\n\n**Q: What's the difference between `.flatten()` and `.unflatten()`?**\n\nA: `.flatten()` converts nested JSON structures into flat key-value pairs with dot-separated keys. `.unflatten()` does the reverse, converting flat key-value pairs back into nested structures.\n\n```rust\n// Flatten: {\"user\": {\"name\": \"John\"}} \u2192 {\"user.name\": \"John\"}\n// Unflatten: {\"user.name\": \"John\"} \u2192 {\"user\": {\"name\": \"John\"}}\n```\n\n**Q: Can I use the same configuration methods for both flatten and unflatten?**\n\nA: Yes! All configuration methods (filtering, transformations, etc.) work for both operations. The library applies them intelligently based on the operation mode.\n\n**Q: What happens if I don't call `.flatten()` or `.unflatten()` before `.execute()`?**\n\nA: You'll get a `ConfigurationError` with a helpful message telling you to set the operation mode first.\n\n### Python-Specific Questions\n\n**Q: What input types does the Python API support?**\n\nA: The Python API supports:\n- `str` (JSON strings)\n- `dict` (Python dictionaries)\n- `List[str]` (lists of JSON strings)\n- `List[dict]` (lists of Python dictionaries)\n- Mixed lists (preserves original types)\n\n**Q: Does the output type always match the input type?**\n\nA: Yes! This is a key feature. `str` input \u2192 `str` output, `dict` input \u2192 `dict` output, etc. This makes the API predictable and easy to use.\n\n### Performance Questions\n\n**Q: How does performance compare to other JSON libraries?**\n\nA: JSON Tools RS is optimized for high performance with SIMD-accelerated parsing, FxHashMap, and reduced allocations. Benchmarks show 2,000+ operations/ms for basic flattening. See the [Performance](#performance) section for details.\n\n**Q: Is it safe to use in production?**\n\nA: Yes! The library includes comprehensive error handling, extensive test coverage, and has been optimized for both correctness and performance.\n\n### Feature Questions\n\n**Q: How do I handle key collisions?**\n\nA: Use `.handle_key_collision(true)` to collect colliding values into arrays. For example, if transformations cause `user_name` and `admin_name` to both become `name`, the result will be `{\"name\": [\"John\", \"Jane\"]}`.\n\n**Q: Can I use regex patterns in replacements?**\n\nA: Yes! Both `.key_replacement()` and `.value_replacement()` support standard Rust regex syntax. The library automatically detects regex patterns and falls back to literal replacement if the pattern is invalid.\n\n**Q: What filtering options are available?**\n\nA: You can remove:\n- Empty strings: `.remove_empty_strings(true)`\n- Null values: `.remove_nulls(true)`\n- Empty objects: `.remove_empty_objects(true)`\n- Empty arrays: `.remove_empty_arrays(true)`\n\nAll filtering methods work for both flatten and unflatten operations.\n\n**Q: Can I process multiple JSON documents at once?**\n\nA: Yes! Pass a `Vec<String>` in Rust or a `List[str]` or `List[dict]` in Python. The library will process them efficiently in batch mode.\n\n## Contributing\n\nContributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.\n\n### Development Setup\n\n1. **Clone the repository**\n ```bash\n git clone https://github.com/amaye15/JSON-Tools-rs.git\n cd JSON-Tools-rs\n ```\n\n2. **Install Rust** (latest stable)\n ```bash\n curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh\n ```\n\n3. **Install Python 3.8+** and maturin for Python bindings\n ```bash\n pip install maturin pytest\n ```\n\n4. **Run tests** to ensure everything works\n ```bash\n # Rust tests\n cargo test\n\n # Python tests\n maturin develop --features python\n python -m pytest python/tests/\n ```\n\n5. **Run benchmarks** to verify performance\n ```bash\n cargo bench\n ```\n\n### Contribution Guidelines\n\n- Write tests for new features\n- Update documentation for API changes\n- Run `cargo fmt` and `cargo clippy` before submitting\n- Ensure all tests pass before creating a PR\n- Add examples for significant new features\n\n## License\n\nThis project is licensed under either of\n\n- Apache License, Version 2.0 ([LICENSE-APACHE](LICENSE-APACHE) or http://www.apache.org/licenses/LICENSE-2.0)\n- MIT License ([LICENSE-MIT](LICENSE-MIT) or http://opensource.org/licenses/MIT)\n\nat your option.\n\n## Changelog\n\n### v0.4.0 (Current)\n- Comprehensive README documentation update\n- Enhanced API reference with detailed method descriptions\n- Improved error handling documentation with examples\n- Updated installation instructions\n- Added contribution guidelines\n- Performance optimization details and benchmarking guide\n\n### v0.3.0\n- Performance optimizations (FxHashMap, SIMD parsing, reduced allocations)\n- Enhanced error messages with actionable suggestions\n- Improved Python bindings stability\n- Bug fixes and code quality improvements\n\n### v0.2.0\n- Updated README with comprehensive documentation\n- Improved API documentation and examples\n- Enhanced Python bindings documentation\n- Performance optimization details\n- Complete error handling documentation\n\n### v0.1.0\n- Initial release with unified JSONTools API\n- Complete flattening and unflattening support\n- Advanced filtering and transformation capabilities\n- Key collision handling with `.handle_key_collision()`\n- Python bindings with perfect type matching\n- Comprehensive error handling with detailed suggestions\n\n",
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