119 lines
3.4 KiB
Python
119 lines
3.4 KiB
Python
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import re
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import os
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import json
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from pandas import read_excel, DataFrame
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def remove_signs():
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str = read_file()
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# lines =
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pattern = r"\(|\)"
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str = re.sub(pattern,'', str)
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# str = re.sub(')','', str)
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# str = re.sub('/','', str)
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return str
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def read_file():
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with open('./data/DATASET_2.txt', 'r', encoding='utf-8') as file:
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text = ''
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try:
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text = str(file.read())
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except:
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pass
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return text
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def read_file_by_address(file_address):
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with open(file_address, 'r', encoding='utf-8') as file:
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text = ''
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try:
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text = str(file.read())
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except:
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pass
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return text
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def save_to_file(result):
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with open('./data/DATASET_3.txt', 'a+', encoding='utf-8') as file:
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previous_result = ''
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try:
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previous_result = file.read()
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except:
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pass
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file.write(result)
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file.close()
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def save_to_file_by_address(file_address, text):
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with open(file_address, 'a+', encoding='utf-8') as file:
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previous_result = ''
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try:
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previous_result = file.read()
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except:
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pass
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file.write(text)
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file.close()
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def read_from_excel(file_address, column_name):
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# خواندن فایل اکسل
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data = read_excel(file_address)
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# استخراج محتوای ستون مورد نظر
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column_data = data[column_name]
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return column_data
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def add_columndata_to_excel(file_address, column_name, columndata):
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# خواندن فایل اکسل
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data = read_excel(file_address)
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# اضافه کردن ستون جدید به دادهها
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data[column_name] = columndata
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# ذخیره کردن دادهها در فایل اکسل
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data.to_excel(file_address, index=False)
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def write_to_excel(data_dict, file_name_and_address):
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df = DataFrame(data_dict)
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# ذخیره DataFrame به عنوان فایل اکسل
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df.to_excel(file_name_and_address, index=False)
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return True
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def write_to_json(dict, file_address):
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# تبدیل دیکشنری به فرمت JSON
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json_data = json.dumps(dict, indent=2, ensure_ascii=False)
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# ذخیره فایل
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with open(file_address, 'w+', encoding='utf-8') as file:
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file.write(json_data)
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return True
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def read_from_json(file_address):
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data_dict = []
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# خواندن اطلاعات از فایل JSON
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with open(file_address, 'r', encoding='utf-8') as file:
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loaded_data = json.load(file)
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# نمایش اطلاعات خوانده شده
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for item in loaded_data:
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data_dict.append(item)
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return data_dict
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def separated_date_format_finder(date_ner):
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result = False
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date_ner = date_ner.replace('.','/')
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date_ner = date_ner.replace('،','/')
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date_ner = date_ner.replace('ر','/')
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#date_pattern = r'\d{1,2} /\d{1,2} /\d{2,4}|\d{1,2}/\d{1,2}/\d{2,4}|\d{2,4} /\d{1,2} /\d{1,2}|\d{2,4}/\d{1,2}/\d{1,2}'
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date_pattern = r'\b(?:(?:1[0-2]|0?[1-9])/?(?:3[01]|[12][0-9]|0?[1-9])/?(?:14[0-7][0-9]|13[0-9][0-9]|128[0-9])|(?:1[0-2]|0?[1-9])/?(?:3[01]|[12][0-9]|0?[1-9])/?(?:14[0-7][0-9]|13[0-9][0-9]|128[0-9]|[0-9]{2}))\b'
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regex = re.compile(date_pattern)
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match_dates = regex.finditer(date_ner)
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for date_item in match_dates:
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result = True
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break
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return result
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if __name__ == "__main__":
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pass
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