........... WARNING: the benchmark result may be unstable * Not enough samples to get a stable result (95% certainly of less than 1% variation) Try to rerun the benchmark with more runs, values and/or loops. Run 'python -m pyperf system tune' command to reduce the system jitter. Use pyperf stats, pyperf dump and pyperf hist to analyze results. Use --quiet option to hide these warnings. create_5_000_run_trees: Mean +- std dev: 659 ms +- 51 ms ........... WARNING: the benchmark result may be unstable * the standard deviation (137 ms) is 10% of the mean (1.33 sec) Try to rerun the benchmark with more runs, values and/or loops. Run 'python -m pyperf system tune' command to reduce the system jitter. Use pyperf stats, pyperf dump and pyperf hist to analyze results. Use --quiet option to hide these warnings. create_10_000_run_trees: Mean +- std dev: 1.33 sec +- 0.14 sec ........... WARNING: the benchmark result may be unstable * Not enough samples to get a stable result (95% certainly of less than 1% variation) Try to rerun the benchmark with more runs, values and/or loops. Run 'python -m pyperf system tune' command to reduce the system jitter. Use pyperf stats, pyperf dump and pyperf hist to analyze results. Use --quiet option to hide these warnings. create_20_000_run_trees: Mean +- std dev: 2.59 sec +- 0.19 sec ........... WARNING: the benchmark result may be unstable * Not enough samples to get a stable result (95% certainly of less than 1% variation) Try to rerun the benchmark with more runs, values and/or loops. Run 'python -m pyperf system tune' command to reduce the system jitter. Use pyperf stats, pyperf dump and pyperf hist to analyze results. Use --quiet option to hide these warnings. dumps_class_nested_py_branch_and_leaf_200x400: Mean +- std dev: 718 us +- 10 us ........... WARNING: the benchmark result may be unstable * Not enough samples to get a stable result (95% certainly of less than 1% variation) Try to rerun the benchmark with more runs, values and/or loops. Run 'python -m pyperf system tune' command to reduce the system jitter. Use pyperf stats, pyperf dump and pyperf hist to analyze results. Use --quiet option to hide these warnings. dumps_class_nested_py_leaf_50x100: Mean +- std dev: 25.1 ms +- 0.2 ms ........... WARNING: the benchmark result may be unstable * Not enough samples to get a stable result (95% certainly of less than 1% variation) Try to rerun the benchmark with more runs, values and/or loops. Run 'python -m pyperf system tune' command to reduce the system jitter. Use pyperf stats, pyperf dump and pyperf hist to analyze results. Use --quiet option to hide these warnings. dumps_class_nested_py_leaf_100x200: Mean +- std dev: 104 ms +- 4 ms ........... WARNING: the benchmark result may be unstable * Not enough samples to get a stable result (95% certainly of less than 1% variation) Try to rerun the benchmark with more runs, values and/or loops. Run 'python -m pyperf system tune' command to reduce the system jitter. Use pyperf stats, pyperf dump and pyperf hist to analyze results. Use --quiet option to hide these warnings. dumps_dataclass_nested_50x100: Mean +- std dev: 25.2 ms +- 0.2 ms ........... WARNING: the benchmark result may be unstable * the standard deviation (6.93 ms) is 13% of the mean (54.6 ms) Try to rerun the benchmark with more runs, values and/or loops. Run 'python -m pyperf system tune' command to reduce the system jitter. Use pyperf stats, pyperf dump and pyperf hist to analyze results. Use --quiet option to hide these warnings. dumps_pydantic_nested_50x100: Mean +- std dev: 54.6 ms +- 6.9 ms ........... WARNING: the benchmark result may be unstable * Not enough samples to get a stable result (95% certainly of less than 1% variation) Try to rerun the benchmark with more runs, values and/or loops. Run 'python -m pyperf system tune' command to reduce the system jitter. Use pyperf stats, pyperf dump and pyperf hist to analyze results. Use --quiet option to hide these warnings. dumps_pydanticv1_nested_50x100: Mean +- std dev: 194 ms +- 4 ms