app/services/panServices/panDataExtractor.py

# import re
# def filter_array(arr):
#     # Define the regex patterns
#     pattern_alphanumeric_special = re.compile(r'[\w]+[^.\s\w]+|[^.\s\w]+[\w]+')
#     pattern_numeric = re.compile(r'^[0-9]+$')
#     pattern_special_chars = re.compile(r'[^a-zA-Z.\s]+')
    
#     # Filter the array
#     filtered_array = [
#         item for item in arr 
#         if not (pattern_alphanumeric_special.search(item) or 
#                 pattern_numeric.match(item) or 
#                 pattern_special_chars.search(item))
#     ]
#     return filtered_array

# def extract_panData(data):
#     unwanted_words = ["Name", "/Name", 'Permanent', 'Account', 'Number', 'Card', 'नाम', '/Name',
#                       "पिता का नाम", 'नाम / Name', "पिता का नाम/ Father's Name", '414 / Name', 'पिता का नाम / Fath', 
#                       "VIT VE Hra / Father's Nama", 'पिता का नाम/ Fal', 'पिता का नाम / Fathe', "पिता का नाम / Father's Na", 
#                       'जन्म की तारीख /।', 'जन्म का ताराख', "पिता का नाम/ Father's Nam", 'नाम /Name', "पिता का नाम / Father's Name", 
#                       'जन्म का वाराज़', 'Date of Birth', 'Permanent Account Number Card', "Date of Birth", "/Date of Birth", 
#                       "Permanent Account Number", "Father's Name", "14 /Name", "/Father's Name", 'HTH / Name',"inent Account Number", "anent Account Number C","Permanent Account Number Car",
#                       'ugr Name']
    

    
    
#     # Initialize result object
#     result = {
#         "statusCode": 200,
#         "error": '',
#         "data": {
#             "panNo": '',
#             "name": '',
#             "fatherName": '',
#             "dob": ''
#         }
#     }
    
#     # Clean the array by removing unwanted words and invalid entries
#     cleaned_data = []
#     combination_pattern = re.compile(r'(?=.*[0-9])(?=.*[!@#$%^&*(),?":{}|<>])')

#     for item in data:
#         if item not in unwanted_words and not combination_pattern.search(item):
#             cleaned_data.append(item)
    
   
#     # Check and extract PAN number
#     pan_pattern = re.compile(r'^[A-Z]{5}\s*[0-9]{4}\s*[A-Z]$')
#     for item in cleaned_data:
#         if pan_pattern.match(item):
#             result["data"]["panNo"] = item
#             cleaned_data.remove(item)
#             break
    
#     # Check and extract date of birth
#     dob_pattern = re.compile(r'^\d{2}[-/]\d{2}[-/]\d{4}$')
#     for item in cleaned_data:
#         if dob_pattern.match(item):
#             result["data"]["dob"] = item
#             cleaned_data.remove(item)
#             break

#     # If only two values are left, assume they are name and father's name
#     cleaned_data = filter_array(cleaned_data)
#     if len(cleaned_data) == 2:
#         result["data"]["name"] = cleaned_data[0]
#         result["data"]["fatherName"] = cleaned_data[1]
#     else:
#         # Further cleaning of the data array to extract name and father's name
#         cleaned_data = [item for item in cleaned_data if not combination_pattern.search(item) and item not in unwanted_words]
#         print(cleaned_data, "after cleaning")
#         # Check and extract name
#         name_pattern = re.compile(r'^[A-Za-z .]+$')
#         if len(cleaned_data) > 0 and name_pattern.match(cleaned_data[0]):
#             result["data"]["name"] = cleaned_data[0]
#         else:
#             result["data"]["name"] = ''
            
#         # Check and extract father's name
#         if len(cleaned_data) > 1 and name_pattern.match(cleaned_data[1]):
#             result["data"]["fatherName"] = cleaned_data[1]
#         else:
#             result["data"]["fatherName"] = ''
    
#     # Check if any value is empty and set error message
#     for key, value in result["data"].items():
#         if value == '':
#             result["statusCode"] = 400
#             result["error"] = f"{key} value is not found due to bad image."
#             break
    
#     return result