datalogic-rs 3.0.1

A fast, type-safe Rust implementation of JSONLogic for evaluating logical rules as JSON. Perfect for business rules engines and dynamic filtering in Rust applications.
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datalogic-rs

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A lightweight, high-performance Rust implementation of JSONLogic, optimized for rule-based decision-making and dynamic expressions.

Why datalogic-rs?

  • 🏆 Fully JSONLogic-compliant (100% test coverage)
  • 🚀 Fast & lightweight: Zero-copy JSON parsing, minimal allocations
  • 🔒 Thread-safe: Designed for parallel execution
  • Optimized for production: Static dispatch and rule optimization
  • 🔌 Extensible: Support for custom operators

Overview

datalogic-rs provides a robust implementation of JSONLogic rules with arena-based memory management for optimal performance. The library provides both a parser for JSON-based rules and a fluent builder API for constructing rules in a type-safe manner.

Features

  • Arena-based memory management for optimal performance
  • Comprehensive JSONLogic operator support
  • Fluent builder API for type-safe rule construction
  • Factory methods for common rule patterns
  • Optimizations for static rule components
  • Zero copy rule creation and evaluation
  • High test coverage and compatibility with standard JSONLogic

Using the Builder API

The builder API provides a fluent interface for creating JSONLogic rules in a type-safe manner. All memory allocations happen directly in the arena for maximum performance.

use datalogic_rs::DataLogic;
use serde_json::json;

// Create a new DataLogic instance with its own arena
let logic = DataLogic::new();

// Get a builder that uses the arena
let builder = logic.builder();

// Build a rule using the fluent API
let rule = builder
    .compare()
    .greater_than()
    .var("score")
    .value(50)
    .build();

// Evaluate the rule with data
let data = json!({"score": 75});
let result = logic.evaluate(&rule, &logic.parse_data(&data.to_string()).unwrap()).unwrap();
assert!(result.to_json().as_bool().unwrap());

Building More Complex Rules

You can build complex rules by composing simpler ones:

// Create a rule that checks if a person is an adult of working age
let rule = builder
    .control()
    .and()
    .add(
        builder
            .compare()
            .greater_than_or_equal()
            .var("age")
            .value(18)
            .build()
    )
    .add(
        builder
            .compare()
            .less_than()
            .var("age")
            .value(65)
            .build()
    )
    .build();

Working with Arrays

The library provides builders for array operations like map, filter, and reduce:

// Filter users by age and get their names
let adult_names = builder
    .array()
    .map()
    .array(
        builder
            .array()
            .filter()
            .array(builder.var("users"))
            .condition(
                builder
                    .compare()
                    .greater_than_or_equal()
                    .var("age")
                    .value(18)
                    .build()
            )
            .build()
    )
    .mapper(builder.var("name"))
    .build();

Performance Benefits

The builder API leverages arena allocation for all rule components, providing several performance benefits:

  1. Zero-copy rule construction
  2. Reduced memory allocations
  3. Improved cache locality
  4. Optimization opportunities during construction

License

Licensed under Apache License, Version 2.0


📦 Installation

Add datalogic-rs to your Cargo.toml:

[dependencies]
datalogic-rs = "3.0.0"

🚀 Quick Start: Evaluating JSONLogic Rules

use datalogic_rs::DataLogic;
use serde_json::json;

fn main() {
    // Create a DataLogic instance
    let dl = DataLogic::new();
    
    // Parse and evaluate a rule in one step
    let result = dl.evaluate_str(
        r#"{
            "if": [
                {">": [{"var": "cart.total"}, 100]},
                "Eligible for discount",
                "No discount"
            ]
        }"#,
        r#"{"cart": {"total": 120}}"#,
        None
    ).unwrap();
    
    assert_eq!(result.as_str().unwrap(), "Eligible for discount");
}

🛠️ Features

✅ Supported Operations

Category Operators
Comparison ==, ===, !=, !==, >, >=, <, <=
Logic and, or, !, !!
Arithmetic +, -, *, /, %, min, max
Control Flow if, ?:, ??
Arrays map, filter, reduce, merge, all, none, some
Strings substr, cat, in
Data Access var, val, exists, missing, missing_some
Special preserve, throw, try
Custom Support for user-defined operators

💡 Advanced Features

  • Static Optimization: Rules are optimized at compile-time
  • Error Handling: Built-in error handling with try operator
  • Memory Efficiency: Zero-copy JSON deserialization
  • Type Coercion: JSONLogic-compliant type conversions
  • Thread Safety: All operations are thread-safe
  • Custom Operators: Extend with your own operators

🔌 Custom Operators

use datalogic_rs::{DataLogic, CustomOperator, LogicError};
use serde_json::{json, Value};
use std::borrow::Cow;

// Define a custom power operator
struct PowerOperator;

impl CustomOperator for PowerOperator {
    fn name(&self) -> &str {
        "pow"
    }
    
    fn apply<'a>(&self, args: &[Value], _data: &'a Value) -> Result<Cow<'a, Value>, LogicError> {
        if args.len() != 2 {
            return Err(LogicError::InvalidArguments {
                reason: "pow requires 2 arguments".into()
            });
        }
        let base = args[0].as_f64().unwrap_or(0.0);
        let exp = args[1].as_f64().unwrap_or(0.0);
        Ok(Cow::Owned(json!(base.powf(exp))))
    }
}

// Create a DataLogic instance
let mut dl = DataLogic::new();

// Register the operator
dl.register_custom_operator(Box::new(PowerOperator));

// Use in rules
let result = dl.evaluate_str(
    r#"{"pow": [2, 3]}"#,
    r#"{}"#,
    None
).unwrap();

assert_eq!(result.as_f64().unwrap(), 8.0);

🎯 Use Cases

datalogic-rs is ideal for rule-based decision engines in:

  • Feature flagging (Enable features dynamically based on user attributes)
  • Dynamic pricing (Apply discounts or surge pricing based on conditions)
  • Fraud detection (Evaluate transaction risk using JSON-based rules)
  • Form validation (Check field dependencies dynamically)
  • Authorization rules (Implement complex access control policies)
  • Business rule engines (Enforce business policies with configurable rules)

📊 Performance

Benchmark results show datalogic-rs is 30% faster than the next fastest JSONLogic implementations, thanks to:

  • Arena-based memory management
  • Static operator dispatch
  • Zero-copy deserialization
  • Optimized rule compilation

🛠️ Contributing

We welcome contributions! See the CONTRIBUTING.md for details.

📜 License: Apache-2.0


🚀 Next Steps

✅ Try out datalogic-rs today!
📖 Check out the API documentation for detailed usage instructions
📚 See the docs.rs documentation for comprehensive reference
⭐ Star the GitHub repository if you find it useful!