# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. import argparse import array from dataclasses import dataclass import datetime import os import random import sys from typing import Any, Dict, List import pyfury import pyperf # The benchmark case is rewritten from pyperformance bm_pickle # https://github.com/python/pyperformance/blob/main/pyperformance/data-files/benchmarks/bm_pickle/run_benchmark.py DICT = { "ads_flags": 0, "age": 18, "birthday": datetime.date(1980, 5, 7), "bulletin_count": 0, "comment_count": 0, "country": "BR", "encrypted_id": "G9urXXAJwjE", "favorite_count": 9, "first_name": "", "flags": 412317970704, "friend_count": 0, "gender": "m", "gender_for_display": "Male", "id": 302935349, "is_custom_profile_icon": 0, "last_name": "", "locale_preference": "pt_BR", "member": 0, "tags": ["a", "b", "c", "d", "e", "f", "g"], "profile_foo_id": 827119638, "secure_encrypted_id": "Z_xxx2dYx3t4YAdnmfgyKw", "session_number": 2, "signup_id": "201-19225-223", "status": "A", "theme": 1, "time_created": 1225237014, "time_updated": 1233134493, "unread_message_count": 0, "user_group": "0", "username": "collinwinter", "play_count": 9, "view_count": 7, "zip": "", } LARGE_DICT = {str(i): i for i in range(2**10 + 1)} TUPLE = ( [ 265867233, 265868503, 265252341, 265243910, 265879514, 266219766, 266021701, 265843726, 265592821, 265246784, 265853180, 45526486, 265463699, 265848143, 265863062, 265392591, 265877490, 265823665, 265828884, 265753032, ], 60, ) LARGE_TUPLE = tuple(range(2**20 + 1)) LARGE_FLOAT_TUPLE = tuple([random.random() * 10000 for _ in range(2**20 + 1)]) LARGE_BOOLEAN_TUPLE = tuple([bool(random.random() > 0.5) for _ in range(2**20 + 1)]) LIST = [[list(range(10)), list(range(10))] for _ in range(10)] LARGE_LIST = [i for i in range(2**20 + 1)] def mutate_dict(orig_dict, random_source): new_dict = dict(orig_dict) for key, value in new_dict.items(): rand_val = random_source.random() * sys.maxsize if isinstance(key, (int, bytes, str)): new_dict[key] = type(key)(rand_val) return new_dict random_source = random.Random(5) DICT_GROUP = [mutate_dict(DICT, random_source) for _ in range(3)] @dataclass class ComplexObject1: f1: Any = None f2: str = None f3: List[str] = None f4: Dict[pyfury.Int8Type, pyfury.Int32Type] = None f5: pyfury.Int8Type = None f6: pyfury.Int16Type = None f7: pyfury.Int32Type = None f8: pyfury.Int64Type = None f9: pyfury.Float32Type = None f10: pyfury.Float64Type = None f11: pyfury.Int16ArrayType = None f12: List[pyfury.Int16Type] = None @dataclass class ComplexObject2: f1: Any f2: Dict[pyfury.Int8Type, pyfury.Int32Type] COMPLEX_OBJECT = ComplexObject1( f1=ComplexObject2(f1=True, f2={-1: 2}), f2="abc", f3=["abc", "abc"], f4={1: 2}, f5=2**7 - 1, f6=2**15 - 1, f7=2**31 - 1, f8=2**63 - 1, f9=1.0 / 2, f10=1 / 3.0, f11=array.array("h", [1, 2]), f12=[-1, 4], ) def fury_object(language, ref_tracking, obj): fury = pyfury.Fury(language=language, ref_tracking=ref_tracking) binary = fury.serialize(obj) fury.deserialize(binary) def benchmark_args(): parser = argparse.ArgumentParser(description="Fury Benchmark") parser.add_argument("--xlang", action="store_true", default=False) parser.add_argument("--no-ref", action="store_true", default=False) parser.add_argument("--disable-cython", action="store_true", default=False) if "--help" in sys.argv: parser.print_help() return None args, unknown_args = parser.parse_known_args() sys.argv = sys.argv[:1] + unknown_args return args def micro_benchmark(): args = benchmark_args() runner = pyperf.Runner() if args and args.disable_cython: os.environ["ENABLE_FURY_CYTHON_SERIALIZATION"] = "0" sys.argv += ["--inherit-environ", "ENABLE_FURY_CYTHON_SERIALIZATION"] runner.parse_args() language = pyfury.Language.XLANG if args.xlang else pyfury.Language.PYTHON runner.bench_func("fury_dict", fury_object, language, not args.no_ref, DICT) runner.bench_func( "fury_large_dict", fury_object, language, not args.no_ref, LARGE_DICT ) runner.bench_func( "fury_dict_group", fury_object, language, not args.no_ref, DICT_GROUP ) runner.bench_func("fury_tuple", fury_object, language, not args.no_ref, TUPLE) runner.bench_func( "fury_large_tuple", fury_object, language, not args.no_ref, LARGE_TUPLE ) runner.bench_func("fury_list", fury_object, language, not args.no_ref, LIST) runner.bench_func( "fury_large_float_tuple", fury_object, language, not args.no_ref, LARGE_FLOAT_TUPLE, ) runner.bench_func( "fury_large_boolean_tuple", fury_object, language, not args.no_ref, LARGE_BOOLEAN_TUPLE, ) runner.bench_func("fury_list", fury_object, language, not args.no_ref, LIST) runner.bench_func( "fury_large_list", fury_object, language, not args.no_ref, LARGE_LIST ) runner.bench_func( "fury_complex", fury_object, language, not args.no_ref, COMPLEX_OBJECT ) if __name__ == "__main__": micro_benchmark()