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import os | |
import random | |
import polars as pl | |
import timeit | |
import tqdm | |
results = [] | |
for shuffle_rhs in [False]: | |
for lhs_size in tqdm.tqdm([11, 100, 1_000, 10_000, 100_000, 1_000_000, 10_000_000]): | |
for rhs_size in [1, 10, 100, 1_000, 10_000, 100_000, 1_000_000, 10_000_000]: | |
lhs = pl.Series(range(lhs_size)) | |
rhs = pl.Series(range(rhs_size)) | |
if shuffle_rhs: | |
rhs = rhs.shuffle() | |
nrepeat = 5 | |
bench = lambda number: min(timeit.repeat('lhs.is_in(rhs)', number=number, globals=globals(), repeat=nrepeat))/number | |
time1 = bench(1) | |
number= min(100, max(3, int(1e-2/time1))) | |
time = bench(number) | |
results.append({ | |
"shuffled": shuffle_rhs, | |
"lhs_size": lhs_size, | |
"rhs_size": rhs_size, | |
f"{os.getenv('bench_name')}_time": time, | |
}) | |
pl.DataFrame(results).write_csv(f"/tmp/{os.getenv('bench_name')}.csv") |
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