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Benchmarking timing performance Keyword Extraction between regex and flashtext
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| #!/bin/python | |
| from flashtext.keyword import KeywordProcessor | |
| import random | |
| import string | |
| import re | |
| import time | |
| def get_word_of_length(str_length): | |
| """ | |
| generate a radom word of given length | |
| """ | |
| return ''.join(random.choice(string.ascii_lowercase) for _ in range(str_length)) | |
| # generate a list of 100K words of randomly chosen size | |
| all_words = [get_word_of_length(random.choice([3, 4, 5, 6, 7, 8])) for i in range(100000)] | |
| string_length_to_time_map = [] | |
| for keywords_length in range(0, 20000, 1000): | |
| """ | |
| Run the benchmark from 0 to 20K at 1K interval. | |
| """ | |
| # chose 1000 terms and create a string to search in. | |
| all_words_chosen = random.sample(all_words, 1000) | |
| story = ' '.join(all_words_chosen) | |
| # get unique keywords from the list of words generated. | |
| unique_keywords_sublist = list(set(random.sample(all_words, keywords_length))) | |
| # compile regex | |
| compiled_re = re.compile('|'.join([r'\b' + keyword + r'\b' for keyword in unique_keywords_sublist])) | |
| # add keywords to flashtext | |
| keyword_processor = KeywordProcessor() | |
| keyword_processor.add_keywords_from_list(unique_keywords_sublist) | |
| # time the modules | |
| start = time.time() | |
| _ = keyword_processor.extract_keywords(story) | |
| mid = time.time() | |
| _ = compiled_re.findall(story) | |
| end = time.time() | |
| # add results to dictionary as Count, FlashText time, Regex time | |
| string_length_to_time_map.append((len(unique_keywords_sublist), mid - start, end - mid)) | |
| print('Count | FlashText | Regex ') | |
| print('------------------------------') | |
| for value in string_length_to_time_map: | |
| print(str(value[0]).ljust(6), '|', | |
| "{0:.5f}".format(value[1]).ljust(9), '|', | |
| "{0:.5f}".format(value[2]).ljust(9), '|',) | |
| # output: Count, Timinging in Seconds. | |
| # Count | FlashText | Regex | |
| # ------------------------------ | |
| # 0 | 0.00118 | 0.00079 | | |
| # 1000 | 0.00149 | 0.00944 | | |
| # 2000 | 0.00186 | 0.02233 | | |
| # 3000 | 0.00160 | 0.02909 | | |
| # 4000 | 0.00171 | 0.03714 | | |
| # 5000 | 0.00166 | 0.05882 | | |
| # 6000 | 0.00212 | 0.06964 | | |
| # 7000 | 0.00174 | 0.09775 | | |
| # 8000 | 0.00169 | 0.08188 | | |
| # 9000 | 0.00206 | 0.09672 | | |
| # 10000 | 0.00214 | 0.11071 | | |
| # 11000 | 0.00242 | 0.10869 | | |
| # 12000 | 0.00221 | 0.12309 | | |
| # 13000 | 0.00246 | 0.14295 | | |
| # 14000 | 0.00188 | 0.15157 | | |
| # 15000 | 0.00198 | 0.15419 | | |
| # 16000 | 0.00207 | 0.17049 | | |
| # 17000 | 0.00236 | 0.17179 | | |
| # 18000 | 0.00253 | 0.20256 | | |
| # 19000 | 0.00223 | 0.19117 | |
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