Crate fory 

Apache Fory™ Rust

Apache Fory™ is a blazingly fast multi-language serialization framework powered by JIT compilation and zero-copy techniques, providing up to ultra-fast performance while maintaining ease of use and safety.

The Rust implementation provides versatile and high-performance serialization with automatic memory management and compile-time type safety.

GitHub: https://github.com/apache/fory

Why Apache Fory™ Rust?

Apache Fory™ Rust solves the fundamental serialization dilemma: you shouldn’t have to choose between performance and developer experience. Traditional frameworks force you to pick between fast but fragile binary formats, flexible but slow text-based protocols, or complex solutions that don’t support your language’s advanced features.

Key differentiators:

• 🔥 Blazingly Fast: Zero-copy deserialization and optimized binary protocols
• 🌍 Cross-Language: Seamlessly serialize/deserialize data across Java, Python, C++, Go, JavaScript, and Rust
• 🎯 Type-Safe: Compile-time type checking with derive macros
• 🔄 Circular References: Automatic tracking of shared and circular references with Rc/Arc and weak pointers
• 🧬 Polymorphic: Serialize trait objects with Box<dyn Trait>, Rc<dyn Trait>, and Arc<dyn Trait>
• 📦 Schema Evolution: Compatible mode for independent schema changes
• ⚡ Two Modes: Object graph serialization and zero-copy row-based format

Quick Start

Add Apache Fory™ to your Cargo.toml:

[dependencies]
fory = "0.13"
fory-derive = "0.13"

Basic Example

use fory::{Fory, Error, Reader};
use fory::ForyObject;

#[derive(ForyObject, Debug, PartialEq)]
struct User {
    name: String,
    age: i32,
    email: String,
}

let mut fory = Fory::default();
fory.register::<User>(1)?;

let user = User {
    name: "Alice".to_string(),
    age: 30,
    email: "alice@example.com".to_string(),
};

// Serialize and deserialize
let bytes = fory.serialize(&user)?;
let decoded: User = fory.deserialize(&bytes)?;
assert_eq!(user, decoded);

// Serialize to specified buffer and deserialize from it
let mut buf: Vec<u8> = vec![];
fory.serialize_to(&user, &mut buf)?;
let mut reader = Reader::new(&buf);
let decoded: User = fory.deserialize_from(&mut reader)?;
assert_eq!(user, decoded);

Core Features

Apache Fory™ Rust provides seven major feature categories, each designed to solve specific serialization challenges in modern applications.

1. Object Graph Serialization

What it does: Automatically serializes complex nested data structures while preserving relationships and hierarchies.

Why it matters: Most real-world applications deal with complex domain models, not just flat data structures. Apache Fory™ handles arbitrary nesting depth, collections, and optional fields without manual mapping code.

Technical approach: The #[derive(ForyObject)] macro generates efficient serialization code at compile time using procedural macros. This eliminates runtime reflection overhead while maintaining type safety.

Key capabilities:

• Nested struct serialization with arbitrary depth
• Collection types (Vec, HashMap, HashSet, BTreeMap)
• Optional fields with Option<T>
• Automatic handling of primitive types and strings
• Efficient binary encoding with variable-length integers

use fory::{Fory, Error};
use fory::ForyObject;
use std::collections::HashMap;

#[derive(ForyObject, Debug, PartialEq)]
struct Person {
    name: String,
    age: i32,
    address: Address,
    hobbies: Vec<String>,
    metadata: HashMap<String, String>,
}

#[derive(ForyObject, Debug, PartialEq)]
struct Address {
    street: String,
    city: String,
    country: String,
}

let mut fory = Fory::default();
fory.register::<Address>(100);
fory.register::<Person>(200);

let person = Person {
    name: "John Doe".to_string(),
    age: 30,
    address: Address {
        street: "123 Main St".to_string(),
        city: "New York".to_string(),
        country: "USA".to_string(),
    },
    hobbies: vec!["reading".to_string(), "coding".to_string()],
    metadata: HashMap::from([
        ("role".to_string(), "developer".to_string()),
    ]),
};

let bytes = fory.serialize(&person)?;
let decoded: Person = fory.deserialize(&bytes)?;
assert_eq!(person, decoded);

2. Shared and Circular References

What it does: Automatically tracks and preserves reference identity for shared objects using Rc<T> and Arc<T>, and handles circular references using weak pointers.

Why it matters: Graph-like data structures (trees, linked lists, object-relational models) are common in real applications but notoriously difficult to serialize. Most frameworks either panic on circular references or require extensive manual handling.

Technical approach: Apache Fory™ maintains a reference tracking map during serialization. When the same object is encountered multiple times, it’s serialized only once and subsequent references use IDs. Weak pointers (RcWeak<T>, ArcWeak<T>) break cycles by serializing as references without strong ownership.

Benefits:

• Space efficiency: No data duplication in serialized output
• Reference identity preservation: Deserialized objects maintain the same sharing relationships
• Circular reference support: Use RcWeak<T> and ArcWeak<T> to break cycles
• Forward reference resolution: Callbacks handle weak pointers appearing before targets

Shared References with Rc/Arc

use fory::Fory;
use fory::Error;
use std::rc::Rc;

let fory = Fory::default();

let shared = Rc::new(String::from("shared_value"));
let data = vec![shared.clone(), shared.clone(), shared.clone()];

let bytes = fory.serialize(&data)?;
let decoded: Vec<Rc<String>> = fory.deserialize(&bytes)?;

assert_eq!(decoded.len(), 3);
assert!(Rc::ptr_eq(&decoded[0], &decoded[1]));
assert!(Rc::ptr_eq(&decoded[1], &decoded[2]));

For thread-safe shared references, use Arc<T>:

use fory::Fory;
use fory::Error;
use std::sync::Arc;

let fory = Fory::default();
let shared = Arc::new(String::from("shared_value"));
let data = vec![shared.clone(), shared.clone()];

let bytes = fory.serialize(&data)?;
let decoded: Vec<Arc<String>> = fory.deserialize(&bytes)?;

assert!(Arc::ptr_eq(&decoded[0], &decoded[1]));

Circular References with Weak Pointers

How it works:

• Weak pointers serialize as references to their target objects
• If the strong pointer has been dropped, weak serializes as Null
• Forward references (weak appearing before target) are resolved via callbacks
• All clones of a weak pointer share the same internal cell for automatic updates

use fory::{Fory, Error, RcWeak};
use fory::ForyObject;
use std::rc::Rc;
use std::cell::RefCell;

#[derive(ForyObject, Debug)]
struct Node {
    value: i32,
    parent: RcWeak<RefCell<Node>>,
    children: Vec<Rc<RefCell<Node>>>,
}

let mut fory = Fory::default();
fory.register::<Node>(2000);

let parent = Rc::new(RefCell::new(Node {
    value: 1,
    parent: RcWeak::new(),
    children: vec![],
}));

let child1 = Rc::new(RefCell::new(Node {
    value: 2,
    parent: RcWeak::from(&parent),
    children: vec![],
}));

parent.borrow_mut().children.push(child1.clone());

let bytes = fory.serialize(&parent)?;
let decoded: Rc<RefCell<Node>> = fory.deserialize(&bytes)?;

assert_eq!(decoded.borrow().children.len(), 1);
let upgraded_parent = decoded.borrow().children[0].borrow().parent.upgrade().unwrap();
assert!(Rc::ptr_eq(&decoded, &upgraded_parent));

Thread-Safe Circular Graphs with Arc:

use fory::{Fory, Error, ArcWeak};
use fory::ForyObject;
use std::sync::{Arc, Mutex};

#[derive(ForyObject)]
struct Node {
    val: i32,
    parent: ArcWeak<Mutex<Node>>,
    children: Vec<Arc<Mutex<Node>>>,
}

let mut fory = Fory::default();
fory.register::<Node>(6000);

let parent = Arc::new(Mutex::new(Node {
    val: 10,
    parent: ArcWeak::new(),
    children: vec![],
}));

let child = Arc::new(Mutex::new(Node {
    val: 20,
    parent: ArcWeak::from(&parent),
    children: vec![],
}));

parent.lock().unwrap().children.push(child.clone());

let bytes = fory.serialize(&parent)?;
let decoded: Arc<Mutex<Node>> = fory.deserialize(&bytes)?;

assert_eq!(decoded.lock().unwrap().children.len(), 1);

3. Trait Object Serialization

What it does: Enables polymorphic serialization through trait objects, supporting dynamic dispatch and type flexibility.

Why it matters: Rust’s trait system is powerful for abstraction, but serializing Box<dyn Trait> is notoriously difficult. This feature is essential for plugin systems, heterogeneous collections, and extensible architectures.

Technical approach: The register_trait_type! macro generates type registration and dispatch code for trait implementations. During serialization, type IDs are written alongside data, enabling correct deserialization to the concrete type.

Supported trait object types:

• Box<dyn Trait> - Owned trait objects
• Rc<dyn Trait> - Reference-counted trait objects
• Arc<dyn Trait> - Thread-safe reference-counted trait objects
• Rc<dyn Any> / Arc<dyn Any> - Runtime type dispatch without custom traits
• Collections: Vec<Box<dyn Trait>>, HashMap<K, Box<dyn Trait>>

Basic Trait Object Serialization

use fory::{Fory, register_trait_type, Serializer, Error};
use fory::ForyObject;

trait Animal: Serializer {
    fn speak(&self) -> String;
    fn name(&self) -> &str;
}

#[derive(ForyObject, Debug)]
struct Dog { name: String, breed: String }

impl Animal for Dog {
    fn speak(&self) -> String { "Woof!".to_string() }
    fn name(&self) -> &str { &self.name }
}

#[derive(ForyObject, Debug)]
struct Cat { name: String, color: String }

impl Animal for Cat {
    fn speak(&self) -> String { "Meow!".to_string() }
    fn name(&self) -> &str { &self.name }
}

register_trait_type!(Animal, Dog, Cat);

#[derive(ForyObject)]
struct Zoo {
    star_animal: Box<dyn Animal>,
}

let mut fory = Fory::default().compatible(true);
fory.register::<Dog>(100);
fory.register::<Cat>(101);
fory.register::<Zoo>(102);

let zoo = Zoo {
    star_animal: Box::new(Dog {
        name: "Buddy".to_string(),
        breed: "Labrador".to_string(),
    }),
};

let bytes = fory.serialize(&zoo)?;
let decoded: Zoo = fory.deserialize(&bytes)?;

assert_eq!(decoded.star_animal.name(), "Buddy");
assert_eq!(decoded.star_animal.speak(), "Woof!");

Serializing dyn Any Trait Objects

What it does: Supports serializing Rc<dyn Any> and Arc<dyn Any> for maximum runtime type flexibility without defining custom traits.

When to use: Plugin systems, dynamic type handling, or when you need runtime type dispatch without compile-time trait definitions.

Key points:

• Works with any type that implements Serializer
• Requires downcasting after deserialization to access the concrete type
• Type information is preserved during serialization

use fory::Fory;
use fory::Error;
use std::rc::Rc;
use std::any::Any;
use fory::ForyObject;

#[derive(ForyObject)]
struct Dog { name: String }

let mut fory = Fory::default();
fory.register::<Dog>(100);

let dog: Rc<dyn Any> = Rc::new(Dog {
    name: "Rex".to_string()
});

let bytes = fory.serialize(&dog)?;
let decoded: Rc<dyn Any> = fory.deserialize(&bytes)?;

let unwrapped = decoded.downcast_ref::<Dog>().unwrap();
assert_eq!(unwrapped.name, "Rex");

For thread-safe scenarios, use Arc<dyn Any>:

use fory::Fory;
use fory::Error;
use std::sync::Arc;
use std::any::Any;
use fory::ForyObject;

#[derive(ForyObject)]
struct Cat { name: String }

let mut fory = Fory::default();
fory.register::<Cat>(101);

let cat: Arc<dyn Any> = Arc::new(Cat {
    name: "Whiskers".to_string()
});

let bytes = fory.serialize(&cat)?;
let decoded: Arc<dyn Any> = fory.deserialize(&bytes)?;

let unwrapped = decoded.downcast_ref::<Cat>().unwrap();
assert_eq!(unwrapped.name, "Whiskers");

Rc/Arc-Based Trait Objects in Structs

For struct fields containing Rc<dyn Trait> or Arc<dyn Trait>, Apache Fory™ automatically handles the conversion without needing wrappers:

use fory::{Fory, register_trait_type, Serializer, Error};
use fory::ForyObject;
use std::sync::Arc;
use std::rc::Rc;

trait Animal: Serializer {
    fn name(&self) -> &str;
}

#[derive(ForyObject, Debug)]
struct Dog { name: String }
impl Animal for Dog {
    fn name(&self) -> &str { &self.name }
}

#[derive(ForyObject, Debug)]
struct Cat { name: String }
impl Animal for Cat {
    fn name(&self) -> &str { &self.name }
}

register_trait_type!(Animal, Dog, Cat);

#[derive(ForyObject)]
struct AnimalShelter {
    animals_rc: Vec<Rc<dyn Animal>>,
    animals_arc: Vec<Arc<dyn Animal>>,
}

let mut fory = Fory::default().compatible(true);
fory.register::<Dog>(100);
fory.register::<Cat>(101);
fory.register::<AnimalShelter>(102);

let shelter = AnimalShelter {
    animals_rc: vec![
        Rc::new(Dog { name: "Rex".to_string() }),
        Rc::new(Cat { name: "Mittens".to_string() }),
    ],
    animals_arc: vec![
        Arc::new(Dog { name: "Buddy".to_string() }),
    ],
};

let bytes = fory.serialize(&shelter)?;
let decoded: AnimalShelter = fory.deserialize(&bytes)?;

assert_eq!(decoded.animals_rc[0].name(), "Rex");
assert_eq!(decoded.animals_arc[0].name(), "Buddy");

Standalone Trait Object Serialization with Wrappers

Due to Rust’s orphan rule, Rc<dyn Trait> and Arc<dyn Trait> cannot implement Serializer directly. For standalone serialization (not inside struct fields), the register_trait_type! macro generates wrapper types.

Note: If you don’t want to use wrapper types, you can serialize as Rc<dyn Any> or Arc<dyn Any> instead (see the dyn Any section above).

The register_trait_type! macro generates AnimalRc and AnimalArc wrapper types:

use fory::{Fory, Error, register_trait_type, Serializer};
use fory::ForyObject;
use std::sync::Arc;
use std::rc::Rc;

trait Animal: Serializer {
    fn name(&self) -> &str;
}

#[derive(ForyObject, Debug)]
struct Dog { name: String }
impl Animal for Dog {
    fn name(&self) -> &str { &self.name }
}

register_trait_type!(Animal, Dog);

let mut fory = Fory::default().compatible(true);
fory.register::<Dog>(100);

// For Rc<dyn Trait>
let dog_rc: Rc<dyn Animal> = Rc::new(Dog { name: "Rex".to_string() });
let wrapper = AnimalRc::from(dog_rc);

let bytes = fory.serialize(&wrapper)?;
let decoded: AnimalRc = fory.deserialize(&bytes)?;

// Unwrap back to Rc<dyn Animal>
let unwrapped: Rc<dyn Animal> = decoded.unwrap();
assert_eq!(unwrapped.name(), "Rex");

// For Arc<dyn Trait>
let dog_arc: Arc<dyn Animal> = Arc::new(Dog { name: "Buddy".to_string() });
let wrapper = AnimalArc::from(dog_arc);

let bytes = fory.serialize(&wrapper)?;
let decoded: AnimalArc = fory.deserialize(&bytes)?;

let unwrapped: Arc<dyn Animal> = decoded.unwrap();
assert_eq!(unwrapped.name(), "Buddy");

4. Schema Evolution

What it does: Supports schema evolution in Compatible mode, allowing serialization and deserialization peers to have different type definitions.

Why it matters: In distributed systems and microservices, different services evolve independently. Schema evolution enables zero-downtime deployments where services can be updated gradually without breaking communication.

Technical approach: In Compatible mode, Apache Fory™ includes field names and type metadata in the serialized data. During deserialization, fields are matched by name, allowing for additions, deletions, and reordering.

Features:

• Add new fields with default values
• Remove obsolete fields (skipped during deserialization)
• Change field nullability (T ↔ Option<T>)
• Reorder fields (matched by name, not position)
• Type-safe fallback to default values for missing fields

Compatibility rules:

• Field names must match (case-sensitive)
• Type changes are not supported (except nullable/non-nullable)
• Nested struct types must be registered on both sides

use fory::{Fory, Error};
use fory::ForyObject;
use std::collections::HashMap;

#[derive(ForyObject, Debug)]
struct PersonV1 {
    name: String,
    age: i32,
    address: String,
}

#[derive(ForyObject, Debug)]
struct PersonV2 {
    name: String,
    age: i32,
    phone: Option<String>,
    metadata: HashMap<String, String>,
}

let mut fory1 = Fory::default().compatible(true);
fory1.register::<PersonV1>(1);

let mut fory2 = Fory::default().compatible(true);
fory2.register::<PersonV2>(1);

let person_v1 = PersonV1 {
    name: "Alice".to_string(),
    age: 30,
    address: "123 Main St".to_string(),
};

let bytes = fory1.serialize(&person_v1)?;
let person_v2: PersonV2 = fory2.deserialize(&bytes)?;

assert_eq!(person_v2.name, "Alice");
assert_eq!(person_v2.age, 30);
assert_eq!(person_v2.phone, None);

5. Enum Support

What it does: Supports C-style enums (enums without data payloads) with efficient varint encoding.

Why it matters: Enums are common for state machines, status codes, and type discriminators. Efficient encoding and schema evolution support are essential.

Technical approach: Each variant is assigned an ordinal value (0, 1, 2, …) during serialization. Ordinals are encoded using variable-length integers for space efficiency.

Features:

• Efficient varint encoding for ordinals
• Schema evolution support in Compatible mode
• Type-safe variant matching
• Default variant support with #[default]

use fory::Fory;
use fory::Error;
use fory::ForyObject;

#[derive(ForyObject, Debug, PartialEq, Default)]
enum Status {
    #[default]
    Pending,
    Active,
    Inactive,
    Deleted,
}

let mut fory = Fory::default();
fory.register::<Status>(1);

let status = Status::Active;
let bytes = fory.serialize(&status)?;
let decoded: Status = fory.deserialize(&bytes)?;
assert_eq!(status, decoded);

6. Custom Serializers

What it does: Allows manual implementation of the Serializer trait for types that don’t support #[derive(ForyObject)].

When to use:

• External types from other crates that you can’t modify
• Types with special serialization requirements
• Legacy data format compatibility
• Performance-critical custom encoding
• Complex types that require special handling

Technical approach: Implement the Serializer trait’s fory_write_data() and fory_read_data() methods to control exactly how data is written to and read from the binary buffer.

use fory::{Fory, TypeResolver, ReadContext, WriteContext, Serializer, ForyDefault, Error};
use std::any::Any;

#[derive(Debug, PartialEq, Default)]
struct CustomType {
    value: i32,
    name: String,
}

impl Serializer for CustomType {
    fn fory_write_data(&self, context: &mut WriteContext) -> Result<(), Error> {
        context.writer.write_i32(self.value);
        context.writer.write_varuint32(self.name.len() as u32);
        context.writer.write_utf8_string(&self.name);
        Ok(())
    }

    fn fory_read_data(context: &mut ReadContext) -> Result<Self, Error> {
        let value = context.reader.read_i32()?;
        let len = context.reader.read_varuint32()? as usize;
        let name = context.reader.read_utf8_string(len)?;
        Ok(Self { value, name })
    }

    fn fory_type_id_dyn(&self, type_resolver: &TypeResolver) -> Result<u32, Error> {
        Self::fory_get_type_id(type_resolver)
    }

    fn as_any(&self) -> &dyn Any {
        self
    }
}

impl ForyDefault for CustomType {
    fn fory_default() -> Self {
        Self::default()
    }
}

let mut fory = Fory::default();
fory.register_serializer::<CustomType>(100);

let custom = CustomType {
    value: 42,
    name: "test".to_string(),
};
let bytes = fory.serialize(&custom)?;
let decoded: CustomType = fory.deserialize(&bytes)?;
assert_eq!(custom, decoded);

7. Row-Based Serialization

What it does: Provides a high-performance row format for zero-copy deserialization, enabling random access to fields directly from binary data without full object reconstruction.

Why it matters: Traditional serialization reconstructs entire objects in memory. For analytics workloads or when you only need a few fields from large objects, this is wasteful. Row format provides O(1) field access without deserialization.

Technical approach: Fields are encoded in a binary row with fixed offsets for primitives. Variable-length data (strings, collections) are stored with offset pointers. A null bitmap tracks which fields are present. The generated code provides accessor methods that read directly from the binary buffer.

Key benefits:

• Zero-copy access: Read fields without allocating or copying data
• Partial deserialization: Access only the fields you need
• Memory-mapped files: Work with data larger than RAM
• Cache-friendly: Sequential memory layout for better CPU cache utilization
• Lazy evaluation: Defer expensive operations until field access

When to use row format:

• Analytics workloads with selective field access
• Large datasets where only a subset of fields is needed
• Memory-constrained environments
• High-throughput data pipelines
• Reading from memory-mapped files or shared memory

Performance characteristics:

Operation	Object Format	Row Format
Full deserialization	Allocates all objects	Zero allocation
Single field access	Full deserialization required	Direct offset read (O(1))
Memory usage	Full object graph in memory	Only accessed fields in memory
Suitable for	Small objects, full access	Large objects, selective access

use fory::{to_row, from_row};
use fory_derive::ForyRow;
use std::collections::BTreeMap;

#[derive(ForyRow)]
struct UserProfile {
    id: i64,
    username: String,
    email: String,
    scores: Vec<i32>,
    preferences: BTreeMap<String, String>,
    is_active: bool,
}

let profile = UserProfile {
    id: 12345,
    username: "alice".to_string(),
    email: "alice@example.com".to_string(),
    scores: vec![95, 87, 92, 88],
    preferences: BTreeMap::from([
        ("theme".to_string(), "dark".to_string()),
        ("language".to_string(), "en".to_string()),
    ]),
    is_active: true,
};

let row_data = to_row(&profile).unwrap();
let row = from_row::<UserProfile>(&row_data);

assert_eq!(row.id(), 12345);
assert_eq!(row.username(), "alice");
assert_eq!(row.is_active(), true);

let scores = row.scores();
assert_eq!(scores.size(), 4);
assert_eq!(scores.get(0), 95);

Supported Types

Apache Fory™ supports a comprehensive type system for maximum flexibility.

Primitive Types

• bool - Boolean values
• i8, i16, i32, i64 - Signed integers
• f32, f64 - Floating point numbers
• String - UTF-8 encoded strings

Collections

• Vec<T> - Dynamic arrays
• HashMap<K, V> - Hash-based maps
• BTreeMap<K, V> - Ordered maps
• HashSet<T> - Hash-based sets
• Option<T> - Optional values

Smart Pointers

• Box<T> - Heap allocation
• Rc<T> - Reference counting (shared references tracked automatically)
• Arc<T> - Thread-safe reference counting (shared references tracked)
• RcWeak<T> - Weak reference to Rc<T> (breaks circular references)
• ArcWeak<T> - Weak reference to Arc<T> (breaks circular references)
• RefCell<T> - Interior mutability with runtime borrow checking
• Mutex<T> - Thread-safe interior mutability

Date and Time (requires chrono feature)

• chrono::NaiveDate - Date without timezone
• chrono::NaiveDateTime - Timestamp without timezone

Custom Types

• Structs with #[derive(ForyObject)] - Object graph serialization
• Structs with #[derive(ForyRow)] - Row-based serialization
• C-style enums with #[derive(ForyObject)] - Enum support
• Manual Serializer implementation - Custom serialization logic

Trait Objects

• Box<dyn Trait> - Owned trait objects
• Rc<dyn Trait> - Reference-counted trait objects
• Arc<dyn Trait> - Thread-safe reference-counted trait objects
• Rc<dyn Any> - Runtime type dispatch without custom traits
• Arc<dyn Any> - Thread-safe runtime type dispatch

Serialization Modes

Apache Fory™ supports two serialization modes to balance between performance and flexibility:

SchemaConsistent Mode (Default)

When to use: Maximum performance when schemas are guaranteed to match.

Characteristics:

• Type declarations must match exactly between serialization and deserialization
• Smaller payload size (no field names or metadata)
• Faster serialization and deserialization
• Suitable for monolithic applications or tightly coupled services

use fory::Fory;

let fory = Fory::default();

Compatible Mode

When to use: Schema evolution in distributed systems or microservices.

Characteristics:

• Type declarations can differ between peers
• Allows field additions, deletions, and reordering
• Larger payload size (includes field names and metadata)
• Slightly slower due to metadata processing
• Essential for zero-downtime deployments

use fory::Fory;

let fory = Fory::default().compatible(true);

Cross-Language Serialization

What it enables: Seamless data exchange across Java, Python, C++, Go, JavaScript, and Rust implementations.

Why it matters: Microservices architectures often use multiple languages. Apache Fory™ provides a common binary protocol without IDL files or code generation.

How to enable:

use fory::Fory;
use fory::ForyObject;

let mut fory = Fory::default()
    .compatible(true)
    .xlang(true);

#[derive(ForyObject)]
struct MyStruct {
    field1: i32,
    field2: String,
}

fory.register_by_namespace::<MyStruct>("com.example", "MyStruct");

Type registration strategies:

• ID-based registration: fory.register::<T>(id) - Fastest, requires coordination
• Namespace-based registration: fory.register_by_namespace::<T>(namespace, name) - Automatic cross-language mapping

Performance Characteristics

Apache Fory™ Rust is designed for maximum performance through multiple techniques:

Compile-time code generation:

• Procedural macros generate specialized serialization code
• Zero runtime overhead, no reflection
• Monomorphization for type-specific optimizations

Zero-copy techniques:

• Row format enables direct memory access
• No intermediate object allocation
• Memory-mapped file support

Space efficiency:

• Variable-length integer encoding
• Reference deduplication (shared objects serialized once)
• Compact binary format

Buffer management:

• Pre-allocation based on fory_reserved_space() hints
• Minimized reallocations
• Little-endian layout for modern CPUs

Error Handling

Apache Fory™ uses Result<T, Error> for all fallible operations, providing comprehensive error handling:

use fory::{Fory, Error};
use fory::ForyObject;

#[derive(ForyObject)]
struct Data {
    value: i32,
}

fn process_data(bytes: &[u8]) -> Result<Data, Error> {
    let mut fory = Fory::default();
    fory.register::<Data>(100);

    let data: Data = fory.deserialize(bytes)?;
    Ok(data)
}

Thread Safety

Fory implements Send and Sync, so a single instance can be shared across threads (for example via Arc<Fory>) for concurrent serialization and deserialization. The internal context pools grow lazily and rely on thread-safe primitives, allowing multiple workers to reuse buffers without additional coordination.

use std::sync::Arc;
use std::thread;
use fory::Fory;
use fory::ForyObject;

#[derive(ForyObject, Clone, Copy, Debug)]
struct Item {
    value: i32,
}

let mut fory = Fory::default();
fory.register::<Item>(1000).unwrap();
let fory = Arc::new(fory);
let handles: Vec<_> = (0..8)
    .map(|i| {
        let shared = Arc::clone(&fory);
        thread::spawn(move || {
            let item = Item { value: i };
            shared.serialize(&item).unwrap()
        })
    })
    .collect();

for handle in handles {
    let bytes = handle.join().unwrap();
    let item: Item = fory.deserialize(&bytes).unwrap();
    assert!(item.value >= 0);
}

Best practice: Perform type registration (e.g., fory.register::<T>(id)) before spawning worker threads so metadata is ready, then share the configured instance.

Examples

See the tests/ directory for comprehensive examples:

• tests/tests/test_complex_struct.rs - Complex nested structures
• tests/tests/test_rc_arc_trait_object.rs - Trait object serialization
• tests/tests/test_weak.rs - Circular reference handling
• tests/tests/test_cross_language.rs - Cross-language compatibility

Troubleshooting

• Type registry errors: Errors such as TypeId ... not found in type_info registry mean the type was never registered with the active Fory instance. Ensure every serializable struct, enum, or trait implementation calls register::<T>(type_id) before use, and reuse the same IDs when deserializing.
• Quick error lookup: Always prefer the static constructors on fory_core::error::Error—for example Error::type_mismatch, Error::invalid_data, or Error::unknown. They keep diagnostics consistent and allow optional panic-on-error debugging.
• Panic on error for backtraces: Set FORY_PANIC_ON_ERROR=1 (or true) together with RUST_BACKTRACE=1 while running tests or binaries to panic exactly where an error is constructed. Unset the variable afterwards so production paths keep returning Result.
• Struct field tracing: Add the #[fory_debug] attribute next to #[derive(ForyObject)] when you need per-field instrumentation. Once compiled with debug hooks, call set_before_write_field_func, set_after_write_field_func, set_before_read_field_func, or set_after_read_field_func from fory_core::serializer::struct_ to install custom callbacks, and use reset_struct_debug_hooks() to restore defaults.
• Lightweight logging: If custom callbacks are unnecessary, enable ENABLE_FORY_DEBUG_OUTPUT=1 to have the default hook handlers print field-level read/write events. This is useful for spotting cursor misalignment or unexpected buffer growth.
• Test-time hygiene: Some integration tests expect FORY_PANIC_ON_ERROR to stay unset. Export it only during focused debugging, and rely on targeted commands such as cargo test --features tests -p tests --test <case> when isolating failures.

Documentation

• Protocol Specification - Binary protocol details
• Row Format Specification - Row format internals
• Type Mapping - Cross-language type mappings
• API Documentation - Complete API reference
• GitHub Repository - Source code and issue tracking

Macros

register_trait_type

Macro to register trait object conversions for custom traits.

Structs

ArcWeak

A serializable wrapper around std::sync::Weak<T> (thread-safe).

Fory

The main Fory serialization framework instance.

RcWeak

A serializable wrapper around std::rc::Weak<T>.

ReadContext

Deserialization state container used on a single thread at a time. Sharing the same instance across threads simultaneously causes undefined behavior.

Reader

TypeResolver

TypeResolver is a resolver for fast type/serializer dispatch.

WriteContext

Serialization state container used on a single thread at a time. Sharing the same instance across threads simultaneously causes undefined behavior.

Writer

Enums

Error

Error type for Fory serialization and deserialization operations.

TypeId

Traits

ForyDefault

Trait for creating default values during Fory deserialization.

Serializer

Core trait for Fory serialization and deserialization.

Functions

from_row

to_row

Derive Macros

ForyObject

Derive macro for object serialization.

ForyRow

Derive macro for row-based serialization.