philiprehberger-timerfunc 0.2.0

Measure execution time of any function

philiprehberger-timerfunc

Measure execution time of any function.

Installation

pip install philiprehberger-timerfunc

Usage

Context Manager

from philiprehberger_timerfunc import timer

with timer() as t:
    do_work()
print(f"Took {t.elapsed_ms:.1f}ms")

Decorator

from philiprehberger_timerfunc import timed

@timed
def process_data():
    ...  # logs: "process_data took 42.3ms"

@timed(threshold_ms=100)
def api_call():
    ...  # only logs if slower than 100ms

Benchmark

from philiprehberger_timerfunc import benchmark

result = benchmark(my_function, args=(data,), iterations=1000)
print(f"Mean: {result.mean_ms:.2f}ms, P95: {result.p95_ms:.2f}ms")
print(f"Fastest: {result.fastest:.2f}ms, Slowest: {result.slowest:.2f}ms")
print(result)  # full stats summary

Comparing benchmarks

from philiprehberger_timerfunc import benchmark, compare_benchmarks

old = benchmark(old_impl, iterations=1000)
new = benchmark(new_impl, iterations=1000)

ratio = compare_benchmarks(new, old)
# ratio > 1 means `new` is faster than `old` (old took proportionally longer)
print(f"new is {ratio:.2f}x faster than old")

API

Function / Class	Description
timer()	Context manager returning TimerResult
@timed / @timed(threshold_ms=0)	Decorator logging execution time
benchmark(fn, args, kwargs, iterations, warmup)	Returns BenchmarkResult
BenchmarkResult.fastest	Duration of the fastest run (ms); alias of min_ms
BenchmarkResult.slowest	Duration of the slowest run (ms); alias of max_ms
compare_benchmarks(a, b)	Returns b.mean / a.mean; values > 1 mean a is faster

Development

pip install -e .
python -m pytest tests/ -v

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License

MIT