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A safe serialization library for Python

Project description

SafeSerialize

SafeSerialize is a safe and extensible binary serialization library for Python.

Ever got an error like TypeError: Object of type set is not JSON serializable? - No more!

This library supports

  • Python's builtin data types (set, frozenset, dict, bytes, ...),
  • many types from Python's standard library (datetime, decimal, Counter, deque, ...),
  • NumPy arrays and scalar data types,
  • PyTorch tensors,
  • SciPy BSR, CSR, CSC and COO sparse matrices,
  • (experimental) Pandas support,
  • custom user-defined types.

Unlike pickle, this library is designed to be safe and does not execute arbitrary code when loading untrusted data.

Installation

You can install SafeSerialize from PyPI:

pip install safeserialize

Third party libraries (e.g. NumPy) are optional. Support will automatically be enabled once they are installed.

Usage

Here is a quick example of how to use SafeSerialize. It should mostly be a drop-in replacement for pickle.

from safeserialize import dumps, loads
from datetime import datetime
from decimal import Decimal
from collections import Counter

# Create a complex object
data = {
    "an_integer": 42,
    "a_string": "Hello, World!",
    "a_list": [1, 2.0, "three"],
    frozenset("a_set"): {"foo", "bar"},
    "a_datetime": datetime.now(),
    "a_counter": Counter("banana"),
    "a_decimal": Decimal("3.14159"),
}

# Serialize the data as a bytes
serialized_bytes = dumps(data)

# Deserialize the object
deserialized_data = loads(serialized_bytes)

assert data == deserialized_data
print("Serialization and deserialization successful!")

Serialization directly to files is also supported.

from safeserialize import dump, load

data = {1, 2.0, ..., "four!"}

filename = "data.safeserialize"

with open(filename, "wb") as f:
    dump(data, f)

with open(filename, "rb") as f:
    deserialized_data = load(f)

assert data == deserialized_data
print("Serialization and deserialization successful!")

For more usage examples, see the tests.

Running Tests

To run the tests, first clone the repository and install the development dependencies:

git clone https://github.com/your-username/safeserialize.git
cd safeserialize
pip install -e .[test]

Then, run pytest from the root directory:

pytest

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