srsly: Modern high-performance serialization utilities for Python

This package bundles some of the best Python serialization libraries into one standalone package, with a high-level API that makes it easy to write code that’s correct across platforms and Pythons. This allows us to provide all the serialization utilities we need in a single binary wheel. Currently supports JSON, JSONL, MessagePack, Pickle and YAML.

Motivation

Serialization is hard, especially across Python versions and multiple platforms. After dealing with many subtle bugs over the years (encodings, locales, large files) our libraries like spaCy and Prodigy have steadily grown a number of utility functions to wrap the multiple serialization formats we need to support (especially json, msgpack and pickle). These wrapping functions ended up duplicated across our codebases, so we wanted to put them in one place.

At the same time, we noticed that having a lot of small dependencies was making maintenance harder, and making installation slower. To solve this, we’ve made srsly standalone, by including the component packages directly within it. This way we can provide all the serialization utilities we need in a single binary wheel.

srsly currently includes forks of the following packages:

• ujson
• msgpack
• msgpack-numpy
• cloudpickle
• ruamel.yaml (without unsafe implementations!)

Installation

⚠️
Note that v2.x is only compatible with Python 3.6+. For 2.7+ compatibility, use v1.x.

srsly can be installed from pip. Before installing, make sure that your pip, setuptools and wheel are up to date.

pip install -U pip setuptools wheel
pip install srsly

Or from conda via conda-forge:

conda install -c conda-forge srsly

Alternatively, you can also compile the library from source. You’ll need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler (XCode command-line tools on macOS / OS X or Visual C++ build tools on Windows), pip, virtualenv and git installed.

pip install -r requirements.txt  # install development dependencies
python setup.py build_ext --inplace  # compile the library

API

JSON

?
The underlying module is exposed via srsly.ujson. However, we normally interact with it via the utility functions only.

function srsly.json_dumps

Serialize an object to a JSON string. Falls back to json if sort_keys=True is used (until it’s fixed in ujson).

data = {"foo": "bar", "baz": 123}
json_string = srsly.json_dumps(data)

function srsly.json_loads

Deserialize unicode or bytes to a Python object.

data = '{"foo": "bar", "baz": 123}'
obj = srsly.json_loads(data)

function srsly.write_json

Create a JSON file and dump contents or write to standard output.

data = {"foo": "bar", "baz": 123}
srsly.write_json("/path/to/file.json", data)

function srsly.read_json

Load JSON from a file or standard input.

data = srsly.read_json("/path/to/file.json")

function srsly.write_gzip_json

Create a gzipped JSON file and dump contents.

data = {"foo": "bar", "baz": 123}
srsly.write_gzip_json("/path/to/file.json.gz", data)

function srsly.read_gzip_json

Load gzipped JSON from a file.

data = srsly.read_gzip_json("/path/to/file.json.gz")

function srsly.write_jsonl

Create a JSONL file (newline-delimited JSON) and dump contents line by line, or write to standard output.

data = [{"foo": "bar"}, {"baz": 123}]
srsly.write_jsonl("/path/to/file.jsonl", data)

function srsly.read_jsonl

Read a JSONL file (newline-delimited JSON) or from JSONL data from standard input and yield contents line by line. Blank lines will always be skipped.

data = srsly.read_jsonl("/path/to/file.jsonl")

function srsly.is_json_serializable

Check if a Python object is JSON-serializable.

assert srsly.is_json_serializable({"hello": "world"}) is True
assert srsly.is_json_serializable(lambda x: x) is False

msgpack

?
The underlying module is exposed via srsly.msgpack. However, we normally interact with it via the utility functions only.

function srsly.msgpack_dumps

Serialize an object to a msgpack byte string.

data = {"foo": "bar", "baz": 123}
msg = srsly.msgpack_dumps(data)

function srsly.msgpack_loads

Deserialize msgpack bytes to a Python object.

msg = b"\x82\xa3foo\xa3bar\xa3baz{"
data = srsly.msgpack_loads(msg)

function srsly.write_msgpack

Create a msgpack file and dump contents.

data = {"foo": "bar", "baz": 123}
srsly.write_msgpack("/path/to/file.msg", data)

function srsly.read_msgpack

Load a msgpack file.

data = srsly.read_msgpack("/path/to/file.msg")

pickle

?
The underlying module is exposed via srsly.cloudpickle. However, we normally interact with it via the utility functions only.

function srsly.pickle_dumps

Serialize a Python object with pickle.

data = {"foo": "bar", "baz": 123}
pickled_data = srsly.pickle_dumps(data)

function srsly.pickle_loads

Deserialize bytes with pickle.

pickled_data = b"\x80\x04\x95\x19\x00\x00\x00\x00\x00\x00\x00}\x94(\x8c\x03foo\x94\x8c\x03bar\x94\x8c\x03baz\x94K{u."
data = srsly.pickle_loads(pickled_data)

YAML

?
The underlying module is exposed via srsly.ruamel_yaml. However, we normally interact with it via the utility functions only.

function srsly.yaml_dumps

Serialize an object to a YAML string. See the ruamel.yaml docs for details on the indentation format.

data = {"foo": "bar", "baz": 123}
yaml_string = srsly.yaml_dumps(data)

function srsly.yaml_loads

Deserialize unicode or a file object to a Python object.

data = 'foo: bar\nbaz: 123'
obj = srsly.yaml_loads(data)

function srsly.write_yaml

Create a YAML file and dump contents or write to standard output.

data = {"foo": "bar", "baz": 123}
srsly.write_yaml("/path/to/file.yml", data)

function srsly.read_yaml

Load YAML from a file or standard input.

data = srsly.read_yaml("/path/to/file.yml")

function srsly.is_yaml_serializable

Check if a Python object is YAML-serializable.

assert srsly.is_yaml_serializable({"hello": "world"}) is True
assert srsly.is_yaml_serializable(lambda x: x) is False

GitHub

https://github.com/explosion/srsly