383 lines
16 KiB
Python
383 lines
16 KiB
Python
import re
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from copy import deepcopy
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from traceback import print_exc
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def add_slash_to_text_as_regex(text: str):
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if text is None or len(text) == 0:
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return text
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special_char_iter = re.finditer("\W", text)
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for special_iter in special_char_iter:
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if len(special_iter.group().strip()) == 0:
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continue
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replace = r"\{0}".format(special_iter.group())
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if replace not in text:
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text = re.sub(replace, replace, text)
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text = re.sub(r"\s+", r"\\s+", text)
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return text
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def clean_text(text: str) -> str:
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# text = text.lower()
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# update the specical character which begin with \u, e.g \u2004 or \u00a0 to be space
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text = re.sub(r"\\u[A-Z0-9a-z]{4}", ' ', text)
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text = re.sub(r"( ){2,}", ' ', text.strip())
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return text
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def get_most_similar_name(text: str, name_list: list, pre_common_word_list: list = None) -> str:
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"""
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Get the most similar fund name from fund_name_list by jacard similarity
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"""
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try:
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copy_fund_name_list = deepcopy(name_list)
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if text is None or len(text.split()) == 0 or \
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copy_fund_name_list is None or len(copy_fund_name_list) == 0:
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return None, None
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copy_fund_name_list = [replace_abbrevation(copy_fund_name) for copy_fund_name
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in copy_fund_name_list]
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# get common words in fund_name_list
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common_word_list = []
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if len(name_list) > 1:
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_, common_word_list = remove_common_word(copy_fund_name_list)
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if pre_common_word_list is not None and len(pre_common_word_list) > 0:
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common_word_list.extend([word for word in pre_common_word_list
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if word not in common_word_list])
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text = text.strip()
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text = remove_special_characters(text)
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text = replace_abbrevation(text)
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text_splits = text.split()
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if len(text_splits) == 1:
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text = split_words_without_space(text)
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else:
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new_splits = []
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for split in text_splits:
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if len(split) > 1:
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new_splits.extend(split_words_without_space(split).split())
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else:
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new_splits.append(split)
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lower_new_splits = [split.lower() for split in new_splits]
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for word in common_word_list:
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if word not in lower_new_splits:
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# remove word in fund_name_list
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for i in range(len(copy_fund_name_list)):
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temp_splits = copy_fund_name_list[i].split()
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copy_fund_name_list[i] = ' '.join([split for split in temp_splits
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if remove_special_characters(split).lower() != word])
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for i in range(len(copy_fund_name_list)):
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temp_splits = copy_fund_name_list[i].split()
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copy_fund_name_list[i] = ' '.join([split for split in temp_splits
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if remove_special_characters(split).lower() not in ['fund', 'portfolio', 'class', 'share', 'shares']])
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final_splits = []
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for split in new_splits:
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if split.lower() not in ['fund', 'portfolio', 'class', 'share', 'shares']:
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final_splits.append(split)
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text = ' '.join(final_splits)
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max_similarity = 0
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max_similarity_fund_name = None
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text = remove_special_characters(text)
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text, copy_fund_name_list = update_for_currency(text, copy_fund_name_list)
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for fund_name, copy_fund_name in zip(name_list , copy_fund_name_list):
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copy_fund_name = remove_special_characters(copy_fund_name)
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copy_fund_name = split_words_without_space(copy_fund_name)
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similarity = get_jacard_similarity(text,
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copy_fund_name,
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need_remove_numeric_characters=False)
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if similarity > max_similarity:
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max_similarity = similarity
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max_similarity_fund_name = fund_name
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if max_similarity == 1:
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break
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if max_similarity < 0.35:
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return None, max_similarity
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return max_similarity_fund_name, max_similarity
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except Exception as e:
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print(e)
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print_exc()
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return None, 0.0
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def update_for_currency(text: str, compare_list: list):
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text_split = text.split()
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with_currency = False
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total_currency_list = ['USD', 'EUR', 'AUD', 'JPY', 'CHF', 'GBP', 'SEK', 'CNY',
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'NZD', 'CNH', 'NOK', 'SGD', 'HKD', 'ZAR', 'PLN', 'CAD',
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'CZK', 'HUF', 'DKK', 'BRL', 'SKK', 'RON', 'TRY', 'BGN',
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'CUP', 'MXN', 'TOP', 'ILS', 'CLF', 'XCD', 'ISK', 'IDR',
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'MNT', 'AED', 'AFN', 'INR', 'ESP', 'RUB', 'CLP', 'KRW',
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'ETB', 'DZD', 'XEU', 'XFO']
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for split in text_split:
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if split.upper() in total_currency_list:
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with_currency = True
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break
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with_currency_list = []
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without_currency_list = []
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for index, compare in enumerate(compare_list):
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compare_split = compare.split()
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with_currency_compare = False
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for split in compare_split:
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if split.upper() in total_currency_list:
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with_currency_compare = True
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break
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if with_currency_compare:
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with_currency_list.append(index)
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else:
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without_currency_list.append(index)
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if not with_currency and len(with_currency_list) == 0:
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return text, compare_list
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elif not with_currency and len(with_currency_list) > 0:
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last_split = text_split[-1]
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updated = False
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if len(last_split) < 4 and last_split.upper() == last_split:
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if len(without_currency_list) > 0:
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for index in without_currency_list:
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if last_split in compare_list[index].split():
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text = text + ' ' + 'USD'
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updated = True
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break
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if not updated:
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currency_list = []
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for index in with_currency_list:
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compare_split = compare_list[index].split()
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if last_split in compare_split:
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current_currency_list = [split for split in compare_split
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if split.upper() in total_currency_list]
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if len(current_currency_list) > 0:
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currency_list.append(current_currency_list[-1])
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if len(currency_list) == 1:
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text = text + ' ' + currency_list[0]
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updated = True
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for index in without_currency_list:
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compare_list[index] = compare_list[index] + ' ' + 'USD'
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if not updated:
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text = text + ' ' + 'USD'
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return text, compare_list
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elif with_currency and len(without_currency_list) == 0:
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for index in without_currency_list:
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compare_list[index] = compare_list[index] + ' ' + 'USD'
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return text, compare_list
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else:
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return text, compare_list
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def remove_common_word(text_list: list):
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if text_list is None or len(text_list) == 0:
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return text_list
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new_text_list = []
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for text in text_list:
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text = text.lower()
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text = remove_special_characters(text)
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text_splits = text.split()
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while 'fund' in text_splits:
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text_splits.remove('fund')
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while 'portfolio' in text_splits:
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text_splits.remove('portfolio')
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while 'share' in text_splits:
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text_splits.remove('share')
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while 'class' in text_splits:
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text_splits.remove('class')
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text = ' '.join(text_splits)
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new_text_list.append(text)
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# remove common word in new_text_list, such as 'Blackrock Global Fund' and 'Blackrock Growth Fund', then 'Blackrock', 'Fund' are common words
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# the result is ['Global', 'Growth']
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common_word_list = []
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new_text_splits_list = [text.split() for text in new_text_list]
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for i in range(len(new_text_splits_list)):
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for j in range(i+1, len(new_text_splits_list)):
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if common_word_list is None or len(common_word_list) == 0:
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common_word_list = list(
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set(new_text_splits_list[i]).intersection(set(new_text_splits_list[j])))
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else:
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common_word_list = list(
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set(common_word_list).intersection(set(new_text_splits_list[j])))
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common_word_list = list(set(common_word_list))
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for i in range(len(new_text_splits_list)):
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for common_word in common_word_list:
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if common_word in new_text_splits_list[i]:
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new_text_splits_list[i].remove(common_word)
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new_text_list = [' '.join(text_splits)
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for text_splits in new_text_splits_list]
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return new_text_list, common_word_list
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def split_words_without_space(text: str):
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"""
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Split words without space, such as 'BlackrockGlobalFund' will be split to 'Blackrock', 'Global', 'Fund'
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"""
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if text is None or len(text.strip()) == 0:
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return []
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text = text.strip()
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# splits = text.split()
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# if len(splits) > 1:
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# return text
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# find all words with capital letter + lower letter
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regex = r'[A-Z][a-z]+'
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word_list = re.findall(regex, text)
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if len(word_list) > 0:
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for word in word_list:
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text = text.replace(word, ' ' + word + ' ')
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text = re.sub(r'(\s)+', ' ', text)
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return text.strip()
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def remove_special_characters(text):
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text = re.sub(r'[^a-zA-Z0-9\s]', ' ', text)
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text = re.sub(r'\s+', ' ', text)
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text = text.strip()
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return text
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def get_unique_words_text(text):
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text = remove_special_characters(text)
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text = text.lower()
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text_split = text.split()
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text_split = list(set(text_split))
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# sort the list
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text_split.sort()
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return_text = ' '.join(text_split)
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return return_text
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def remove_numeric_characters(text):
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# remove numeric characters
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text = re.sub(r'\d+', ' ', text)
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text = re.sub(r'\s+', ' ', text)
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text = text.strip()
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return text
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def get_jacard_similarity(text_left,
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text_right,
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need_remove_special_characters=True,
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need_remove_numeric_characters=True):
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if need_remove_special_characters:
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text_left = remove_special_characters(text_left)
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text_right = remove_special_characters(text_right)
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if need_remove_numeric_characters:
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text_left = remove_numeric_characters(text_left)
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text_right = remove_numeric_characters(text_right)
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text_left = text_left.lower()
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text_right = text_right.lower()
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text_left = text_left.split()
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text_right = text_right.split()
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intersection = set(text_left).intersection(set(text_right))
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union = set(text_left).union(set(text_right))
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if len(union) > 0:
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return round(len(intersection) / len(union), 3)
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else:
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return 0
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def get_beginning_common_words(text_list: list):
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"""
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Get the beginning common words in text_list
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"""
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if text_list is None or len(text_list) < 2:
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return []
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common_words_list = []
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first_text_split = text_list[0].split()
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for w_i, word in enumerate(first_text_split):
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all_same = True
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for text in text_list[1:]:
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text_split = text.split()
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if w_i >= len(text_split):
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all_same = False
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break
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if text_split[w_i] != word:
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all_same = False
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break
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if all_same:
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common_words_list.append(word)
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else:
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break
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return ' '.join(common_words_list).strip()
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def replace_abbrevation(text: str):
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if text is None or len(text.strip()) == 0:
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return text
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text = text.strip()
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if 'swiss franc' in text.lower():
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text = re.sub(r'swiss\s+franc', 'CHF', text, flags=re.IGNORECASE)
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elif 'us dollar' in text.lower():
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text = re.sub(r'us\s+dollar', 'USD', text, flags=re.IGNORECASE)
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elif 'singapore dollar' in text.lower():
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text = re.sub(r'singapore\s+dollar', 'SGD', text, flags=re.IGNORECASE)
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elif 'hong kong dollar' in text.lower():
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text = re.sub(r'hong\s+kong\s+dollar', 'HKD', text, flags=re.IGNORECASE)
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elif 'hongkong dollar' in text.lower():
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text = re.sub(r'hongkong\s+dollar', 'HKD', text, flags=re.IGNORECASE)
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elif 'australian dollar' in text.lower():
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text = re.sub(r'australian\s+dollar', 'AUD', text, flags=re.IGNORECASE)
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elif 'japanese yen' in text.lower():
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text = re.sub(r'japanese\s+yen', 'JPY', text, flags=re.IGNORECASE)
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elif 'south african rand' in text.lower():
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text = re.sub(r'South\s+African\s+rand', 'ZAR', text, flags=re.IGNORECASE)
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elif 'canadian dollar' in text.lower():
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text = re.sub(r'canadian\s+dollar', 'CAD', text, flags=re.IGNORECASE)
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elif 'new zealand dollar' in text.lower():
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text = re.sub(r'new\s+zealand\s+dollar', 'NZD', text, flags=re.IGNORECASE)
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elif 'norwegian krone' in text.lower():
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text = re.sub(r'norwegian\s+krone', 'NOK', text, flags=re.IGNORECASE)
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elif 'danish krone' in text.lower():
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text = re.sub(r'danish\s+krone', 'DKK', text, flags=re.IGNORECASE)
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elif 'swedish krona' in text.lower():
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text = re.sub(r'swedish\s+krona', 'SEK', text, flags=re.IGNORECASE)
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elif 'swedish kronor' in text.lower():
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text = re.sub(r'swedish\s+kronor', 'SEK', text, flags=re.IGNORECASE)
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elif 'sterling' in text.lower().split():
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text = re.sub(r'sterling', 'GBP', text, flags=re.IGNORECASE)
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elif 'euro' in text.lower().split():
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text = re.sub(r'euro', 'EUR', text, flags=re.IGNORECASE)
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elif '€' in text.lower().split():
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text = re.sub(r'\€', 'EUR', text, flags=re.IGNORECASE)
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elif '$' in text.lower().split():
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text = re.sub(r'\$', 'USD', text, flags=re.IGNORECASE)
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elif '£' in text.lower().split():
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text = re.sub(r'\£', 'GBP', text, flags=re.IGNORECASE)
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elif 'RMB' in text.lower().split():
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text = re.sub(r'RMB', 'CNY', text, flags=re.IGNORECASE)
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else:
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pass
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text_splits = text.split()
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new_text_splits = []
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for split in text_splits:
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if split.lower() in ['acc', 'acc.']:
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new_text_splits.append('Accumulation')
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elif split.lower() in ['inc', 'inc.']:
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new_text_splits.append('Income')
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elif split.lower() in ['dist', 'dist.']:
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new_text_splits.append('Distribution')
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elif split.lower() in ['inv', 'inv.']:
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new_text_splits.append('Investor')
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elif split.lower() in ['inst', 'inst.', 'institution']:
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new_text_splits.append('Institutional')
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elif split.lower() in ['cap', 'cap.']:
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new_text_splits.append('Capitalisation')
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elif split.lower() in ['adm', 'adm.']:
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new_text_splits.append('Admin')
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elif split.lower() in ['adv', 'adv.']:
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new_text_splits.append('Advantage')
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elif split.lower() in ['hdg', 'hgd', 'hdg.', 'hgd.', '(h)']:
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new_text_splits.append('Hedged')
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elif split.lower() in ['cl', 'cl.']:
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new_text_splits.append('Class')
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elif split.lower() in ['ser', 'ser.']:
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new_text_splits.append('Series')
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elif split.lower() in ['u.s.']:
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new_text_splits.append('US')
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elif split.lower() in ['nc', 'nc.']:
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new_text_splits.append('no trail')
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else:
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new_text_splits.append(split)
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new_text = ' '.join(new_text_splits)
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return new_text |