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Lee Dogeon
99a63f92aa
Add dependency-free CPU-bound workloads adapted from pyperformance 1.14.0 to cover interpreter, standard-library serialization, regex, numeric, and garbage-collection paths under the existing Criterion and CodSpeed harnesses. Keep inputs deterministic and scale expensive cases for simulation while checking that benchmark execution does not leak interpreter state. Assisted-by: Codex:gpt-5.6-sol
34 lines
841 B
Python
34 lines
841 B
Python
# Adapted from python/pyperformance 1.14.0 (pickle_pure_python).
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import datetime
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import pickle
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profile = {
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"age": 18,
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"birthday": datetime.date(1980, 5, 7),
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"country": "BR",
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"encrypted_id": "G9urXXAJwjE",
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"flags": 412317970704,
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"friend_count": 0,
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"locale_preference": "pt_BR",
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"tags": ["a", "b", "c", "d", "e", "f", "g"],
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"username": "collinwinter",
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}
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record = ([*range(20)], 60)
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group = [dict(profile, id=index) for index in range(3)]
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list_data = [[list(range(10)), list(range(10))] for _ in range(10)]
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dict_data = {key: dict.fromkeys(range(10)) for key in range(100)}
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protocol = pickle.HIGHEST_PROTOCOL
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dumps = pickle._dumps
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for obj, count in (
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(profile, 20),
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(record, 20),
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(group, 20),
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(list_data, 10),
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(dict_data, 5),
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):
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for _ in range(count):
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dumps(obj, protocol)
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