jcrist

import vaex
import numpy as np
import dask.dataframe as dd
import dask
import dask.distributed
import json
import os
import time
import argparse
import multiprocessing

jcrist

"""A quick benchmark comparing the performance of:

- msgspec: https://github.com/jcrist/msgspec
- pydantic V1: https://docs.pydantic.dev/1.10/
- pydantic V2: https://docs.pydantic.dev/dev-v2/

The benchmark is modified from the one in the msgspec repo here:
https://github.com/jcrist/msgspec/blob/main/benchmarks/bench_validation.py

I make no claims that it's illustrative of all use cases. I wrote this up

jcrist

import sys
import importlib.metadata
import timeit
from dataclasses import dataclass

import msgspec
import orjson
from mashumaro.codecs.json import JSONEncoder, JSONDecoder
from mashumaro.codecs.orjson import ORJSONEncoder, ORJSONDecoder

jcrist

jcrist

jcrist

# This is a modified version of `orig_benchmark.py`, using different data to
# highlight performance differences.
import json
import random
import string
import timeit
from statistics import mean, stdev

import orjson
import simdjson

jcrist

"""
A simple implementation of GeoJSON (RFC 7946) using msgspec
(https://jcristharif.com/msgspec/) for parsing and validation.

The `loads` and `dumps` methods work like normal `json.loads`/`json.dumps`,
but:

- Will result in high-level GeoJSON types
- Will error nicely if a field is missing or the wrong type
- Will fill in default values for optional fields

jcrist

from datetime import date
from enum import StrEnum, auto
from typing import Annotated

from msgspec import Struct, Meta


class OrderStatus(StrEnum):
    OPEN = auto()
    CLOSED = auto()

jcrist

"""A quick benchmark comparing how quickly `__init__` with default values runs
for various dataclass-like libraries.

We also compare against the time it takes to initialize a `dict` or `tuple`
with the same data, as a "low-bar" for pure-python implementations.
"""

import timeit

import attrs

jcrist

"""
This benchmark is a modified version of the benchmark available at
https://github.com/samuelcolvin/pydantic/tree/master/benchmarks to support
benchmarking msgspec.

The benchmark measures the time to JSON encode/decode `n` random objects
matching a specific schema. It compares the time required for both
serialization _and_ schema validation.
"""