docs/object-serialization/python/native.md

---
title: Python Native Serialization
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id: native
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Python native serialization is the Python-only wire mode selected with `xlang=False`. Use it when
every writer and reader is Python and the payload should follow Python's object model instead of
the portable xlang type system.

Use [Cross-Language Interoperability](basic-serialization.md#cross-language-interoperability), the default Python mode, when bytes must be read
by Java, C++, Go, Rust, JavaScript/TypeScript, C#, Swift, Dart, Scala, Kotlin,
or another non-Python Fory implementation.

## When To Use Native Serialization

Use native serialization when:

- A payload is produced and consumed only by Python applications.
- You are replacing `pickle` or `cloudpickle` for Python-only object graphs.
- The data model includes functions, lambdas, local classes, methods, or Python reduction hooks.
- The graph can contain shared objects or cycles that need Python reference tracking.
- You need pickle protocol 5-style out-of-band buffers for large Python data objects.

Native mode can serialize Python-specific values such as global functions, local functions, lambdas,
local classes, methods, and objects customized with `__getstate__`, `__setstate__`, `__reduce__`,
or `__reduce_ex__`. Those values are not valid xlang payloads.

## Create a Native-Mode Fory Instance

Create `Fory` with `xlang=False`:

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

Keep `strict=True` for registered, trusted type surfaces. Use `strict=False` only when native-mode
payloads need dynamic Python types such as functions, local classes, or objects reconstructed by
reduction hooks.

## Common Usage

```python
import pyfory

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

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

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)
```

Use `dumps`/`loads` for pickle-style APIs, or `serialize`/`deserialize` when matching the xlang
API shape in code that switches modes explicitly.

## Security And Dynamic Types

Native mode can reconstruct Python objects that execute import and construction logic during
deserialization. Treat untrusted native-mode bytes the same way you would treat untrusted pickle
bytes.

- Keep `strict=True` when deserializing data that should contain only registered or built-in types.
- Use `strict=False` only for trusted payloads that require dynamic Python classes or functions.
- Provide a `policy=` deserialization policy when dynamic types are required but the accepted type
  surface should still be restricted.
- Do not use xlang/native mode choice as a security control. Apply strict mode, policies,
  registration, and resource limits based on the payload source.

## Python-specific values and hooks

See [Functions, Classes, and Methods](functions-classes-methods.md) for callable and type values, then [Serialization Hooks](serialization-hooks.md) for reduction, state, construction, and pickle/cloudpickle migration.

## References And Cycles

Enable `ref=True` when object identity, shared references, or cycles must round-trip:

```python
import pyfory

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

node = {}
node["self"] = node
data = fory.dumps(node)
decoded = fory.loads(data)
assert decoded["self"] is decoded
```

Disable reference tracking for value-shaped payloads that do not need identity preservation. It
keeps the payload smaller and the hot path simpler.

## Out-of-Band Buffers

Python native mode can use pickle protocol 5-style out-of-band buffers for large binary payloads
and data structures backed by external memory:

```python
import pickle
import pyfory

data = b"Large binary data"
pickle_buffer = pickle.PickleBuffer(data)

buffer_objects = []
fory = pyfory.Fory(xlang=False, ref=True, strict=False)
serialized = fory.dumps(pickle_buffer, buffer_callback=buffer_objects.append)
buffers = [obj.getbuffer() for obj in buffer_objects]
decoded = fory.loads(serialized, buffers=buffers)
assert bytes(decoded.raw()) == data
```

Use this when the payload stays in Python and large buffers should avoid extra copies. See
[Out-of-Band Serialization](out-of-band.md).

## Native And Xlang Comparison

| Requirement                                | Use native serialization | Use xlang serialization |
| ------------------------------------------ | ------------------------ | ----------------------- |
| Python-only payloads                       | Yes                      | Optional                |
| Non-Python readers or writers              | No                       | Yes                     |
| Functions, lambdas, local classes          | Yes                      | No                      |
| `__reduce__` / `__getstate__` object hooks | Yes                      | No                      |
| Pickle/cloudpickle replacement             | Yes                      | No                      |
| Portable type mapping across languages     | No                       | Yes                     |

## Performance Comparison

```python
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")
```

## Troubleshooting

### Another language cannot read the payload

The writer is using native serialization. Rebuild it with `xlang=True`, register portable schemas
on every peer, and avoid Python-only values such as lambdas or local classes.

### A dynamic class or function fails to deserialize

Use `strict=False` for trusted payloads and provide a deserialization `policy=` when only selected
dynamic types should be accepted.

### A cycle does not round-trip

Create the `Fory` instance with `ref=True`.

### A value depends on pickle hooks

Keep the payload in native mode. Xlang mode does not execute Python `__reduce__`,
`__reduce_ex__`, `__getstate__`, or `__setstate__` object reconstruction hooks.

## Related Topics

- [Cross-Language Interoperability](basic-serialization.md#cross-language-interoperability) - Cross-language Python payloads
- [Configuration](configuration.md) - Python `Fory` options
- [Out-of-Band Serialization](out-of-band.md) - Zero-copy buffer support
- [Configuration](configuration.md#security) - Deserialization policies