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pysafe-pickle

Safe, fast, schema-evolvable Python object graph serialization powered by Rust.

Documentation PyPI License

📖 Documentation: https://abdullah-masood-05.github.io/pygraph/

What's New in v1.3.0

Performance

  • Faster than pickle — dumps is now faster than stdlib pickle on every benchmark shape; loads is on par or faster for most workloads
  • Dataclass serialization is 6x faster (dumps) and 22x faster (loads) for bulk dataclass payloads
  • String-heavy payloads serialize 2x faster

New Type Support

  • Arbitrary-precision integers (2**100, 10**1000, etc.)
  • bytearray (with identity/cycle preservation)
  • complex numbers
  • Strings with lone surrogates ("\ud800")

Bug Fixes

  • Dataclass self-referential cycles now load correctly
  • ClassVar and InitVar fields are no longer incorrectly serialized
  • Two dataclasses sharing a class name no longer corrupt each other's fields
  • Fields named self no longer break deserialization
  • loads() now accepts bytes, bytearray, and memoryview inputs

Features

  • Drop-in pickle API — dumps/loads/dump/load with the same signatures
  • Zero arbitrary code execution — no __reduce__ or __setstate__ calls during deserialization
  • Schema versioning — migration hooks for evolving your data models
  • Zero-copy tensor support — NumPy and PyTorch integration
  • Faster than pickle — Rust-powered serialization that beats stdlib pickle on most workloads
  • Extended type support — bytearray, complex, arbitrary-precision int, and surrogate strings
  • Pickle-compatible streaming — Pickler/Unpickler classes, PickleBuffer (PEP 574)
  • HMAC integrity — optional tamper detection on serialized data

Installation

pip install pysafe-pickle

For tensor support:

pip install pysafe-pickle[numpy]
pip install pysafe-pickle[torch]
pip install pysafe-pickle[all]

Quick Start

import pysafe_pickle as psp

# Serialize
data = {"key": "value", "numbers": [1, 2, 3]}
encoded = psp.dumps(data)

# Deserialize
decoded = psp.loads(encoded)
assert decoded == data

Schema Evolution

Define versioned dataclasses and register migrations:

from dataclasses import dataclass
import pysafe_pickle as psp

@dataclass
class User:
    name: str
    age: int
    email: str = ""
    __pysafe_pickle_version__ = 2

@psp.migrate(from_version=1, to_version=2, type_name="User")
def migrate_v1_to_v2(state: dict) -> dict:
    """V1 had 'name' + 'age', V2 adds 'email'."""
    state["email"] = ""
    state["__pysafe_pickle_version__"] = 2
    return state

How it works

  • Set __pysafe_pickle_version__ as a class attribute on your dataclass (legacy __pygraph_version__ is also fully supported)
  • Register migration functions with @psp.migrate(from_version=N, to_version=M, type_name="ClassName")
  • Migration functions receive a dict of the old state and return a dict with the new state
  • Chains of migrations are resolved automatically (e.g., v1 → v2 → v3)

Pickler / Unpickler

Use pickle-compatible streaming classes:

import pysafe_pickle as psp
import io

# Streaming dump
buf = io.BytesIO()
pickler = psp.Pickler(buf, protocol=5)
pickler.dump({"data": [1, 2, 3]})

# Streaming load
buf.seek(0)
unpickler = psp.Unpickler(buf)
result = unpickler.load()

Security

pysafe-pickle never calls __reduce__, __setstate__, or any arbitrary code during deserialization. Only allowlisted types can be loaded.

# Restrict deserialization to specific types
psp.loads(data, allowlist={"builtins.dict", "builtins.list"})

Allowlisted types

By default, pysafe-pickle supports:

Type Notes
None, bool, int, float Primitives
str, bytes Strings and binary
list, tuple Sequences
dict Mappings
set, frozenset Sets
dataclasses Any @dataclass instance

Any type not in this list raises UnsafeTypeError unless added to the allowlist.

Integrity verification

key = b"my-secret-key"
encoded = psp.dumps(data, hmac_key=key)
decoded = psp.loads(encoded, hmac_key=key)  # raises HMACError if tampered

Migration from v1.0.x (pygraph)

In v1.0.x, the package was imported as import pygraph. In v1.1.0:

  • The canonical import is now import pysafe_pickle as psp.
  • Zero code breaks: Existing code using import pygraph or from pygraph.migrations import migrate continues working identically via a backward-compatible shim, emitting a FutureWarning.
  • Binary compatibility: Files serialized with v1.0.x (magic PYGR) continue to deserialize seamlessly with zero warnings. New files are encoded with the PSPK magic header.
  • The pygraph shim will remain supported through v1.x and will be removed in v2.0.0.
# Legacy (deprecated in v1.1.0, emits warning, still works)
import pygraph
pygraph.dumps(data)

# Recommended
import pysafe_pickle as psp
psp.dumps(data)

Benchmarks

Run the benchmark suite to compare pysafe-pickle vs pickle:

uv run pytest benchmarks/ -v --benchmark-only

Development

# Install and build with uv / maturin
uv run maturin develop

# Run tests
cargo nextest run
uv run pytest tests/ -v

License

AGPL-3.0-only

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