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Benchmark utils
Utils for benchmark - wrapper over python timeit.
Tested on python 3.10 - 3.14
Install
Install from pypi:
pip install benchmark_utils
Or with uv:
uv pip install benchmark_utils
Or install from github repo:
pip install git+https://github.com/ayasyrev/benchmark_utils.git
For development, use uv:
uv pip install -e .
Basic use.
Lets benchmark some (dummy) functions.
output
```python from time import sleepdef func_to_test_1(sleep_time: float = 0.1, mult: int = 1) -> None: """simple 'sleep' func for test""" sleep(sleep_time * mult)
def func_to_test_2(sleep_time: float = 0.11, mult: int = 1) -> None: """simple 'sleep' func for test""" sleep(sleep_time * mult)
output
Let's create benchmark.
output
```python from benchmark_utils import Benchmark ```output
```python bench = Benchmark( [func_to_test_1, func_to_test_2], ) ```bench
output
Benchmark(func_to_test_1, func_to_test_2)</details>
Now we can benchmark that functions.
# we can run bench.run() or just:
bench()
output
Func name | Sec / run
func_to_test_1: 0.10 0.0%
func_to_test_2: 0.11 -9.1%
We can run it again, all functions, some of it, exclude some and change number of repeats.
bench.run(num_repeats=10)
output
Func name | Sec / run
func_to_test_1: 0.10 0.0%
func_to_test_2: 0.11 -9.1%
After run, we can print results - sorted or not, reversed, compare results with best or not.
bench.print_results(reverse=True)
output
Func name | Sec / run
func_to_test_2: 0.11 0.0%
func_to_test_1: 0.10 10.0%
We can add functions to benchmark as list of functions (or partial) or as dictionary: {"name": function}.
output
```python bench = Benchmark( [ func_to_test_1, partial(func_to_test_1, 0.12), partial(func_to_test_1, sleep_time=0.11), ] ) ```bench
output
Benchmark(func_to_test_1, func_to_test_1(0.12), func_to_test_1(sleep_time=0.11))</details>
bench.run()
output
Func name | Sec / run
func_to_test_1: 0.10 0.0%
func_to_test_1(sleep_time=0.11): 0.11 -9.1%
func_to_test_1(0.12): 0.12 -16.7%
output
```python bench = Benchmark( { "func_1": func_to_test_1, "func_2": func_to_test_2, } ) ```bench
output
Benchmark(func_1, func_2)</details>
When we run benchmark script in terminal, we got pretty progress thanks to rich. Lets run example_1.py from example folder:
BenchmarkIter
With BenchmarkIter we can benchmark functions over iterables, for example read list of files or run functions with different arguments.
output
```python def func_to_test_1(x: int) -> None: """simple 'sleep' func for test""" sleep(0.01)def func_to_test_2(x: int) -> None: """simple 'sleep' func for test""" sleep(0.015)
dummy_params = list(range(10))
<!-- cell -->
<details open> <summary>output</summary>
```python
from benchmark_utils import BenchmarkIter
bench = BenchmarkIter(
func=[func_to_test_1, func_to_test_2],
item_list=dummy_params,
)
```</details>
<!-- cell -->
```python
bench()
output
Func name | Items/sec
func_to_test_1: 97.93
func_to_test_2: 65.25
We can run it again, all functions, some of it, exclude some and change number of repeats.
And we can limit number of items with num_samples argument:
bench.run(num_samples=5)
Multiprocessing
By default we tun functions in one thread.
But we can use multiprocessing with multiprocessing=True argument:
bench.run(multiprocessing=True)
It will use all available cpu cores.
And we can use num_workers argument to limit used cpu cores:
bench.run(multiprocessing=True, num_workers=2)
bench.run(multiprocessing=True, num_workers=2)
output
Func name | Items/sec
func_to_test_1: 173.20
func_to_test_2: 120.80
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