........... 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: 663 ms +- 60 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. create_10_000_run_trees: Mean +- std dev: 1.37 sec +- 0.09 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: 2.62 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. dumps_class_nested_py_branch_and_leaf_200x400: Mean +- std dev: 701 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: 24.9 ms +- 0.3 ms ........... dumps_class_nested_py_leaf_100x200: Mean +- std dev: 104 ms +- 2 ms ........... dumps_dataclass_nested_50x100: Mean +- std dev: 25.3 ms +- 0.2 ms ........... WARNING: the benchmark result may be unstable * the standard deviation (7.70 ms) is 14% of the mean (56.0 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: 56.0 ms +- 7.7 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: 198 ms +- 5 ms