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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
29 lines
546 B
Python
29 lines
546 B
Python
# Adapted from python/pyperformance 1.14.0 (json_dumps).
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import json
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empty = ({}, 2000)
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simple_data = {
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"key1": 0,
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"key2": True,
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"key3": "value",
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"key4": "foo",
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"key5": "string",
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}
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simple = (simple_data, 1000)
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nested_data = {
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"key1": 0,
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"key2": simple_data,
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"key3": "value",
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"key4": simple_data,
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"key5": simple_data,
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"key": "ąćż",
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}
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nested = (nested_data, 1000)
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huge = ([nested_data] * 1000, 1)
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for obj, count in (empty, simple, nested, huge):
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for _ in range(count):
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json.dumps(obj)
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