RapidFuzz/bench/benchmark_extractOne.py

130 lines
4.1 KiB
Python

import importlib
import random
from timeit import timeit
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
import string
random.seed(18)
plt.rc('font', size=13) # controls default text sizes
plt.rc('axes', titlesize=18) # fontsize of the axes title
plt.rc('axes', labelsize=15) # fontsize of the x and y labels
plt.rc('xtick', labelsize=15) # fontsize of the tick labels
plt.rc('ytick', labelsize=15) # fontsize of the tick labels
plt.rc('legend', fontsize=15) # legend fontsize
PROCESSOR = {
"ratio":False,
"partial_ratio":False,
"token_sort_ratio":True,
"token_set_ratio":True,
"partial_token_sort_ratio":True,
"partial_token_set_ratio":True,
"QRatio":True,
"WRatio":True
}
LIBRARIES = (
"ratio",
"partial_ratio",
"token_sort_ratio",
"token_set_ratio",
"partial_token_sort_ratio",
"partial_token_set_ratio",
"QRatio",
"WRatio",
)
def load_func(target):
modname, funcname = target.rsplit('.', maxsplit=1)
module = importlib.import_module(modname)
return getattr(module, funcname)
def get_platform():
import platform
uname = platform.uname()
pyver = platform.python_version()
return 'Python %s on %s (%s)' % (pyver, uname.system, uname.machine)
def benchmark():
words = [''.join(random.choice(string.ascii_letters + string.digits) for _ in range(10)) for _ in range(10000)]
sample_rate = len(words) // 100
sample = words[::sample_rate]
total = len(words) * len(sample)
print('System:', get_platform())
print('Words :', len(words))
print('Sample:', len(sample))
print('Total : %s calls\n' % total)
def wrap(f, scorer, processor):
def func():
if not processor:
return len([f(x, words, scorer=scorer, processor=None) for x in sample])
return len([f(x, words, scorer=scorer) for x in sample])
return func
fuzz = []
rfuzz = []
header_list = ['Function', 'RapidFuzz', 'FuzzyWuzzy', 'SpeedImprovement']
row_format ="{:>25}" * len(header_list)
print(row_format.format(*header_list))
for target in LIBRARIES:
func = load_func("fuzzywuzzy.process.extractOne")
scorer = load_func("fuzzywuzzy.fuzz." + target)
sec = timeit('func()', globals={'func': wrap(func, scorer, PROCESSOR[target])}, number=1)
calls = total / sec
fuzz.append(calls)
rfunc = load_func("rapidfuzz.process.extractOne")
rscorer = load_func("rapidfuzz.fuzz." + target)
rsec = timeit('func()', globals={'func': wrap(rfunc, rscorer, PROCESSOR[target])}, number=1)
rcalls = total / rsec
rfuzz.append(rcalls)
print(row_format.format(target, f"{rcalls//1000}k", f"{calls//1000}k", f"{int(100 * sec/rsec)}%"))
labels = LIBRARIES
x = np.arange(len(labels)) # the label locations
width = 0.35 # the width of the bars
fig, ax = plt.subplots(figsize=(17,10))
rects1 = ax.bar(x - width/2, fuzz, width, label='FuzzyWuzzy', color="xkcd:coral")
rects2 = ax.bar(x + width/2, rfuzz, width, label='RapidFuzz', color='#6495ED')
# Add some text for labels, title and custom x-axis tick labels, etc.
ax.set_ylabel('evaluated word pairs [inputs/s]')
ax.set_xlabel('Scorer')
ax.set_title('The number of word pairs evaluated per second\n(the larger the better)')
ax.set_xticks(x)
ax.set_xticklabels(labels, rotation=30 )
ax.get_yaxis().set_major_formatter(
matplotlib.ticker.FuncFormatter(lambda x, p: format(int(x), ',')))
ax.legend()
def autolabel(rects):
"""Attach a text label above each bar in *rects*, displaying its height."""
for rect in rects:
height = rect.get_height()
ax.annotate('{:,}'.format(int(height)),
xy=(rect.get_x() + rect.get_width() / 2, height),
xytext=(0, 3), # 3 points vertical offset
textcoords="offset points",
ha='center', va='bottom')
autolabel(rects1)
autolabel(rects2)
fig.tight_layout()
plt.show()
if __name__ == '__main__':
benchmark()