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Python Native Mode

pyfory provides a Python-native serialization mode that offers the same functionality as pickle/cloudpickle, but with significantly better performance, smaller data size, and enhanced security features.

Overview​

The binary protocol and API are similar to Fory's xlang mode, but Python-native mode can serialize any Python object—including global functions, local functions, lambdas, local classes and types with customized serialization using __getstate__/__reduce__/__reduce_ex__, which are not allowed in xlang mode.

To use Python-native mode, create Fory with xlang=False:

import pyfory
fory = pyfory.Fory(xlang=False, ref=False, strict=True)

Drop-in Replacement for Pickle/Cloudpickle​

pyfory can serialize any Python object with the following configuration:

  • For circular references: Set ref=True to enable reference tracking
  • For functions/classes: Set strict=False to allow deserialization of dynamic types

⚠️ Security Warning: When strict=False, Fory will deserialize arbitrary types, which can pose security risks if data comes from untrusted sources. Only use strict=False in controlled environments where you trust the data source completely.

Common Usage​

import pyfory

# Create Fory instance
fory = pyfory.Fory(xlang=False, ref=True, strict=False)

# serialize common Python objects
data = fory.dumps({"name": "Alice", "age": 30, "scores": [95, 87, 92]})
print(fory.loads(data))

# serialize custom objects
from dataclasses import dataclass

@dataclass
class Person:
    name: str
    age: int

person = Person("Bob", 25)
data = fory.dumps(person)
print(fory.loads(data))  # Person(name='Bob', age=25)

Serialize Global Functions​

Capture and serialize functions defined at module level. Fory deserialize and return same function object:

import pyfory

fory = pyfory.Fory(xlang=False, ref=True, strict=False)

def my_global_function(x):
    return 10 * x

data = fory.dumps(my_global_function)
print(fory.loads(data)(10))  # 100

Serialize Local Functions/Lambdas​

Serialize functions with closures and lambda expressions. Fory captures the closure variables automatically:

import pyfory

fory = pyfory.Fory(xlang=False, ref=True, strict=False)

# Local functions with closures
def my_function():
    local_var = 10
    def local_func(x):
        return x * local_var
    return local_func

data = fory.dumps(my_function())
print(fory.loads(data)(10))  # 100

# Lambdas
data = fory.dumps(lambda x: 10 * x)
print(fory.loads(data)(10))  # 100

Serialize Global Classes/Methods​

Serialize class objects, instance methods, class methods, and static methods:

from dataclasses import dataclass
import pyfory
fory = pyfory.Fory(xlang=False, ref=True, strict=False)

@dataclass
class Person:
    name: str
    age: int

    def f(self, x):
        return self.age * x

    @classmethod
    def g(cls, x):
        return 10 * x

    @staticmethod
    def h(x):
        return 10 * x

# Serialize global class
print(fory.loads(fory.dumps(Person))("Bob", 25))  # Person(name='Bob', age=25)

# Serialize instance method
print(fory.loads(fory.dumps(Person("Bob", 20).f))(10))  # 200

# Serialize class method
print(fory.loads(fory.dumps(Person.g))(10))  # 100

# Serialize static method
print(fory.loads(fory.dumps(Person.h))(10))  # 100

Serialize Local Classes/Methods​

Serialize classes defined inside functions along with their methods:

from dataclasses import dataclass
import pyfory
fory = pyfory.Fory(xlang=False, ref=True, strict=False)

def create_local_class():
    class LocalClass:
        def f(self, x):
            return 10 * x

        @classmethod
        def g(cls, x):
            return 10 * x

        @staticmethod
        def h(x):
            return 10 * x
    return LocalClass

# Serialize local class
data = fory.dumps(create_local_class())
print(fory.loads(data)().f(10))  # 100

# Serialize local class instance method
data = fory.dumps(create_local_class()().f)
print(fory.loads(data)(10))  # 100

# Serialize local class method
data = fory.dumps(create_local_class().g)
print(fory.loads(data)(10))  # 100

# Serialize local class static method
data = fory.dumps(create_local_class().h)
print(fory.loads(data)(10))  # 100

Performance Comparison​

import pyfory
import pickle
import timeit

fory = pyfory.Fory(xlang=False, ref=True, strict=False)

obj = {f"key{i}": f"value{i}" for i in range(10000)}
print(f"Fory: {timeit.timeit(lambda: fory.dumps(obj), number=1000):.3f}s")
print(f"Pickle: {timeit.timeit(lambda: pickle.dumps(obj), number=1000):.3f}s")