117 lines
3.6 KiB
Python
117 lines
3.6 KiB
Python
import importlib
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import random
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from timeit import timeit
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import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib
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import string
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random.seed(18)
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plt.rc('font', size=13) # controls default text sizes
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plt.rc('axes', titlesize=18) # fontsize of the axes title
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plt.rc('axes', labelsize=15) # fontsize of the x and y labels
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plt.rc('xtick', labelsize=15) # fontsize of the tick labels
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plt.rc('ytick', labelsize=15) # fontsize of the tick labels
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plt.rc('legend', fontsize=15) # legend fontsize
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LIBRARIES = (
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"ratio",
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"partial_ratio",
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"token_sort_ratio",
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"token_set_ratio",
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"partial_token_sort_ratio",
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"partial_token_set_ratio",
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"QRatio",
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"WRatio"
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)
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def load_func(target):
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modname, funcname = target.rsplit('.', maxsplit=1)
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module = importlib.import_module(modname)
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return getattr(module, funcname)
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def get_platform():
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import platform
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uname = platform.uname()
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pyver = platform.python_version()
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return 'Python %s on %s (%s)' % (pyver, uname.system, uname.machine)
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def benchmark():
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words = [''.join(random.choice(string.ascii_letters + string.digits) for _ in range(10)) for _ in range(10000)]
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sample_rate = len(words) // 100
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sample = words[::sample_rate]
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total = len(words) * len(sample)
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print('System:', get_platform())
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print('Words :', len(words))
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print('Sample:', len(sample))
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print('Total : %s calls\n' % total)
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def wrap(f):
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def func():
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return len([f(x, y) for x in sample for y in words])
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return func
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fuzz = []
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rfuzz = []
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header_list = ['Function', 'RapidFuzz', 'FuzzyWuzzy', 'SpeedImprovement']
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row_format ="{:>25}" * len(header_list)
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print(row_format.format(*header_list))
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for target in LIBRARIES:
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func = load_func("fuzzywuzzy.fuzz." + target)
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sec = timeit('func()', globals={'func': wrap(func)}, number=1)
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calls = total / sec
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fuzz.append(calls)
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rfunc = load_func("rapidfuzz.fuzz." + target)
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rsec = timeit('func()', globals={'func': wrap(rfunc)}, number=1)
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rcalls = total / rsec
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rfuzz.append(rcalls)
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print(row_format.format(target, f"{rcalls//1000}k", f"{calls//1000}k", f"{int(100 * sec/rsec)}%"))
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labels = LIBRARIES
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x = np.arange(len(labels)) # the label locations
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width = 0.35 # the width of the bars
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fig, ax = plt.subplots(figsize=(17,10))
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rects1 = ax.bar(x - width/2, fuzz, width, label='FuzzyWuzzy', color="xkcd:coral")
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rects2 = ax.bar(x + width/2, rfuzz, width, label='RapidFuzz', color='#6495ED')
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# Add some text for labels, title and custom x-axis tick labels, etc.
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ax.set_ylabel('evaluated word pairs [inputs/s]')
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ax.set_xlabel('Scorer')
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ax.set_title('The number of word pairs evaluated per second\n(the larger the better)')
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ax.set_xticks(x)
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ax.set_xticklabels(labels, rotation=30 )
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ax.get_yaxis().set_major_formatter(
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matplotlib.ticker.FuncFormatter(lambda x, p: format(int(x), ',')))
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ax.legend()
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def autolabel(rects):
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"""Attach a text label above each bar in *rects*, displaying its height."""
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for rect in rects:
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height = rect.get_height()
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ax.annotate('{:,}'.format(int(height)),
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xy=(rect.get_x() + rect.get_width() / 2, height),
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xytext=(0, 3), # 3 points vertical offset
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textcoords="offset points",
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ha='center', va='bottom')
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autolabel(rects1)
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autolabel(rects2)
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fig.tight_layout()
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plt.show()
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if __name__ == '__main__':
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benchmark()
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