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from __future__ import annotations
import argparse
from glob import glob
from math import ceil
from os.path import isdir
from statistics import mean, stdev
from sys import argv
from time import perf_counter_ns
from chardet import detect as chardet_detect
from charset_normalizer import detect
def calc_percentile(data, percentile):
n = len(data)
p = n * percentile / 100
sorted_data = sorted(data)
return sorted_data[int(p)] if p.is_integer() else sorted_data[int(ceil(p)) - 1]
def performance_compare(arguments):
parser = argparse.ArgumentParser(
description="Performance CI/CD check for Charset-Normalizer"
)
parser.add_argument(
"-s",
"--size-increase",
action="store",
default=1,
type=int,
dest="size_coeff",
help="Apply artificial size increase to challenge the detection mechanism further",
)
args = parser.parse_args(arguments)
if not isdir("./char-dataset"):
print(
"This script require https://github.com/Ousret/char-dataset to be cloned on package root directory"
)
exit(1)
chardet_results = []
charset_normalizer_results = []
file_list = sorted(glob("./char-dataset/**/*.*"))
total_files = len(file_list)
for idx, tbt_path in enumerate(file_list):
with open(tbt_path, "rb") as fp:
content = fp.read() * args.size_coeff
before = perf_counter_ns()
chardet_detect(content)
chardet_time = round((perf_counter_ns() - before) / 1000000000, 5)
chardet_results.append(chardet_time)
before = perf_counter_ns()
detect(content)
charset_normalizer_time = round((perf_counter_ns() - before) / 1000000000, 5)
charset_normalizer_results.append(charset_normalizer_time)
charset_normalizer_time = charset_normalizer_time or 0.000005
cn_faster = (chardet_time / charset_normalizer_time) * 100 - 100
print(
f"{idx + 1:>3}/{total_files} {tbt_path:<82} C:{chardet_time:.5f} "
f"CN:{charset_normalizer_time:.5f} {cn_faster:.1f} %"
)
# Print the top 10 rows with the slowest execution time
print(
f"\n{'-' * 102}\nTop 10 rows with the slowest execution time of charset_normalizer:\n"
)
sorted_results = sorted(
enumerate(charset_normalizer_results), key=lambda x: x[1], reverse=True
)
for idx, time in sorted_results[:10]:
tbt_path = file_list[idx]
print(f"{idx + 1:>3}/{total_files} {tbt_path:<82} CN:{time:.5f}")
# Print charset normalizer statistics
min_time = min(charset_normalizer_results)
max_time = max(charset_normalizer_results)
stdev_time = stdev(charset_normalizer_results)
mean_time = mean(charset_normalizer_results)
cv = (stdev_time / mean_time) * 100 # Coefficient of variation
print(f"\n{'-' * 102}\nCharset Normalizer statistics:\n")
print(f"Minimum Execution Time: {min_time:.5f} seconds")
print(f"Maximum Execution Time: {max_time:.5f} seconds")
print(f"Mean Execution Time: {mean_time:.5f} seconds")
print(f"Standard Deviation: {stdev_time:.5f} seconds")
print(f"Coefficient of Variation (CV): {cv:.1f} %")
# Print comparison statistics for chardet and charset normalizer
chardet_avg_delay = round(mean(chardet_results) * 1000)
chardet_99p = round(calc_percentile(chardet_results, 99) * 1000)
chardet_95p = round(calc_percentile(chardet_results, 95) * 1000)
chardet_50p = round(calc_percentile(chardet_results, 50) * 1000)
charset_normalizer_avg_delay = round(mean(charset_normalizer_results) * 1000)
charset_normalizer_99p = round(
calc_percentile(charset_normalizer_results, 99) * 1000
)
charset_normalizer_95p = round(
calc_percentile(charset_normalizer_results, 95) * 1000
)
charset_normalizer_50p = round(
calc_percentile(charset_normalizer_results, 50) * 1000
)
# mypyc can offer performance ~1ms in the 50p. When eq to 0 assume 1 due to imprecise nature of this test.
if charset_normalizer_50p == 0:
charset_normalizer_50p = 1
print(f"\n{'-' * 102}\nCharset Normalizer vs Chardet statistics:\n")
print("------------------------------")
print("--> Chardet Conclusions")
print(" --> Avg: " + str(chardet_avg_delay) + "ms")
print(" --> 99th: " + str(chardet_99p) + "ms")
print(" --> 95th: " + str(chardet_95p) + "ms")
print(" --> 50th: " + str(chardet_50p) + "ms")
print("------------------------------")
print("--> Charset-Normalizer Conclusions")
print(" --> Avg: " + str(charset_normalizer_avg_delay) + "ms")
print(" --> 99th: " + str(charset_normalizer_99p) + "ms")
print(" --> 95th: " + str(charset_normalizer_95p) + "ms")
print(" --> 50th: " + str(charset_normalizer_50p) + "ms")
print("------------------------------")
print("--> Charset-Normalizer / Chardet: Performance Сomparison")
print(
" --> Avg: x"
+ str(round(chardet_avg_delay / charset_normalizer_avg_delay, 2))
)
print(" --> 99th: x" + str(round(chardet_99p / charset_normalizer_99p, 2)))
print(" --> 95th: x" + str(round(chardet_95p / charset_normalizer_95p, 2)))
print(" --> 50th: x" + str(round(chardet_50p / charset_normalizer_50p, 2)))
return (
0
if chardet_avg_delay > charset_normalizer_avg_delay
and chardet_99p > charset_normalizer_99p
else 1
)
if __name__ == "__main__":
exit(performance_compare(argv[1:]))
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