A microbenchmark for Python
Project description
Tinybench 
Tinybench is a lightweight package to time, compare, and visualize various functions. This package was inspired by the R package microbenchmark
Installation
pip install tinybench
Usage
from tinybench import benchmark, benchmark_env # create two functions example functions to test def foo(a): test = [] for i in range(a): test.append(i) return test def bar(a, b): return a + b # example input variable c = 10000 iterations = 100 warmup = 10 # env should be globals(), or use benchmark_env(functions_list) # functions_list should at least contain all the functions to benchmark env = benchmark_env([foo, bar]) # instead, using globals() is recommended env = globals() b = benchmark(['Foo_Label:foo(c)', 'bar(10, 15)'], iterations, warmup, env) print(b) b.plot() # alternatively, we can benchmark using the process time instead of real time: b_process = benchmark(['Foo_Label:foo(c)', 'bar(10, 15)'], iterations, warmup, env, process_time = True)
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