# ## Some functions to clean text import re import string import polars as pl # Add calendar months onto stop words import calendar #from tqdm import tqdm import gradio as gr from typing import List # Adding custom words to the stopwords custom_words = [] my_stop_words = custom_words cal_month = (list(calendar.month_name)) cal_month = [x.lower() for x in cal_month] # Remove blanks cal_month = [i for i in cal_month if i] #print(cal_month) custom_words.extend(cal_month) # #### Some of my cleaning functions replace_backslash = r'\\' email_start_pattern_regex = r'.*importance:|.*subject:' email_end_pattern_regex = r'kind regards.*|many thanks.*|sincerely.*' html_pattern_regex = r'<.*?>|&([a-z0-9]+|#[0-9]{1,6}|#x[0-9a-f]{1,6});|\xa0| ' email_pattern_regex = r'\S*@\S*\s?' num_pattern_regex = r'[0-9]+' postcode_pattern_regex = r'(\b(?:[A-Z][A-HJ-Y]?[0-9][0-9A-Z]? ?[0-9][A-Z]{2})|((GIR ?0A{2})\b$)|(?:[A-Z][A-HJ-Y]?[0-9][0-9A-Z]? ?[0-9]{1}?)$)|(\b(?:[A-Z][A-HJ-Y]?[0-9][0-9A-Z]?)\b$)' warning_pattern_regex = r'caution: this email originated from outside of the organization. do not click links or open attachments unless you recognize the sender and know the content is safe.' nbsp_pattern_regex = r' ' multiple_spaces_regex = r'\s{2,}' # Pre-compiling the regular expressions for efficiency # email_start_pattern = re.compile(email_start_pattern_regex) # email_end_pattern = re.compile(email_end_pattern_regex) # html_pattern = re.compile(html_pattern_regex) # email_pattern = re.compile(email_end_pattern_regex) # num_pattern = re.compile(num_pattern_regex) # postcode_pattern = re.compile(postcode_pattern_regex) # warning_pattern = re.compile(warning_pattern_regex) # nbsp_pattern = re.compile(nbsp_pattern_regex) def initial_clean(texts:List[str] , progress=gr.Progress()): texts = pl.Series(texts)#[] text = texts.str.replace_all(replace_backslash, '/') text = text.str.replace_all(html_pattern_regex, '') text = text.str.replace_all(email_start_pattern_regex, '') text = text.str.replace_all(email_end_pattern_regex, '') text = text.str.replace_all(email_pattern_regex, '') text = text.str.replace_all(multiple_spaces_regex, ' ') text = text.to_list() return text def remove_hyphens(text_text): return re.sub(r'(\w+)-(\w+)-?(\w)?', r'\1 \2 \3', text_text) def remove_characters_after_tokenization(tokens): pattern = re.compile('[{}]'.format(re.escape(string.punctuation))) filtered_tokens = filter(None, [pattern.sub('', token) for token in tokens]) return filtered_tokens def convert_to_lowercase(tokens): return [token.lower() for token in tokens if token.isalpha()] def remove_short_tokens(tokens): return [token for token in tokens if len(token) > 3] def remove_dups_text(data_samples_ready, data_samples_clean, data_samples): # Identify duplicates in the data: https://stackoverflow.com/questions/44191465/efficiently-identify-duplicates-in-large-list-500-000 # Only identifies the second duplicate seen = set() dups = [] for i, doi in enumerate(data_samples_ready): if doi not in seen: seen.add(doi) else: dups.append(i) #data_samples_ready[dupes[0:]] # To see a specific duplicated value you know the position of #matching = [s for s in data_samples_ready if data_samples_ready[83] in s] #matching # Remove duplicates only (keep first instance) #data_samples_ready = list( dict.fromkeys(data_samples_ready) ) # This way would keep one version of the duplicates ### Remove all duplicates including original instance # Identify ALL duplicates including initial values # https://stackoverflow.com/questions/11236006/identify-duplicate-values-in-a-list-in-python from collections import defaultdict D = defaultdict(list) for i,item in enumerate(data_samples_ready): D[item].append(i) D = {k:v for k,v in D.items() if len(v)>1} # https://stackoverflow.com/questions/952914/how-to-make-a-flat-list-out-of-a-list-of-lists L = list(D.values()) flat_list_dups = [item for sublist in L for item in sublist] # https://stackoverflow.com/questions/11303225/how-to-remove-multiple-indexes-from-a-list-at-the-same-time for index in sorted(flat_list_dups, reverse=True): del data_samples_ready[index] del data_samples_clean[index] del data_samples[index] # Remove blanks data_samples_ready = [i for i in data_samples_ready if i] data_samples_clean = [i for i in data_samples_clean if i] data_samples = [i for i in data_samples if i] return data_samples_ready, data_samples_clean, flat_list_dups, data_samples