An anthology of a variety of tools for the Persian language in Python
pip install persian-tools
Let's take a look at what an example test case would look like using persian-tools.
This module will help you to normalize digits from Persian, Arabic and English to only one of them.
from persian_tools import digits
digits.convert_to_fa(123) # '۱۲۳'
digits.convert_to_fa('123') # '۱۲۳'
digits.convert_to_fa('123٤٥٦') # '۱۲۳۴۵۶'
digits.convert_to_fa('sth 123٤٥٦') # 'sth ۱۲۳۴۵۶'
digits.convert_to_en('۱۲۳') # '123'
digits.convert_to_en('۱۲۳٤٥٦') # '123456'
digits.convert_to_en('sth ۱۲۳٤٥٦') # 'sth 123456'
digits.convert_to_ar(123) # '۱۲۳'
digits.convert_to_ar('123') # '۱۲۳'
digits.convert_to_ar('sth 123۴۵۶') # 'sth ۱۲۳٤٥٦'persian-tools also, has another function to convert numbers to words; you can convert result to ordinal mode with ordinal=True in inputs.
from persian_tools import digits
digits.convert_to_word(500443) # پانصد هزار و چهارصد و چهل و سه
digits.convert_to_word(-500443) # منفی پانصد هزار و چهارصد و چهل و سه
digits.convert_to_word(500443, ordinal=True) # پانصد هزار و چهارصد و چهل و سوم
digits.convert_to_word(30000000000) # سی میلیاردto convert words to number, you can use this function with different args:
from persian_tools import digits
digits.convert_from_word('منفی سه هزارمین') # -3000
digits.convert_from_word('منفی سه هزارم', digits='fa') # -۳۰۰۰
digits.convert_from_word('منفی سه هزار') # -3000
digits.convert_from_word('سه هزار دویست و دوازده') # 3212
digits.convert_from_word('دوازده هزار بیست دو', separator=True) # '12,022'
digits.convert_from_word('حقوق شیش صد و ۲۷ میلیون تومان سالانه') # 627000000Note: as you can see in examples, this function will remove ordinal suffix by default.
Adding or removing thousands separators will handle; default separator is ',' but can change with second input.
from persian_tools import separator
separator.add(300) # '300'
separator.add(3000000) # '3,000,000'
separator.add(3000000.0003) # '3,000,000.0003'
separator.add(3000000, '/') # '3/000/000'
separator.add('۳۰۰۰۰') # '۳۰,۰۰۰'
separator.remove('300') # '300'
separator.remove('3,000,000') # '3000000'
separator.remove('3/000/000', '/') # '3000000'
separator.remove('۳۰,۰۰۰') # '۳۰۰۰۰'Adding or removing ordinal suffix for persian numbers in word will handle.
from persian_tools import ordinal_suffix
ordinal_suffix.add('بیست') # 'بیستم'
ordinal_suffix.add('سی و سه') # 'سی و سوم'
ordinal_suffix.add('سی') # 'سی اُم'
ordinal_suffix.remove('دومین') # 'دو'
ordinal_suffix.remove('سی و سوم') # 'سی و سه'
ordinal_suffix.remove('بیستم') # 'بیست'
ordinal_suffix.remove('سی اُم') # 'سی'This module has useful functions related to bank cards number, like:
- validating them
- find bank data of a card number
- extract card numbers from a text
from persian_tools.bank import card_number
card_number.validate('6037701689095443') # True
card_number.validate('6219861034529007') # True
card_number.validate('6219861034529008') # False
card_number.bank_data('6219861034529007')
# {'nickname': 'saman', 'name': 'Saman Bank', 'persian_name': 'بانک سامان', 'card_prefix': ['621986'], 'sheba_code': ['056']}
card_number.bank_data('6037701689095443')
# {'nickname': 'keshavarzi', 'name': 'Keshavarzi', 'persian_name': 'بانک کشاورزی', 'card_prefix': ['603770', '639217'], 'sheba_code': ['016']}
card_number.extract_card_numbers('''شماره کارتم رو برات نوشتم:
6219-8610-3452-9007
اینم یه شماره کارت دیگه ای که دارم
۵۰۲۲-۲۹۱۰-۷۰۸۷-۳۴۶۶
5022291070873466''', # first argument is a text
check_validation=True, # a boolean that define you need only valid card numbers in result, default: True
detect_bank_name=True, # this will add bank name in result, default: False
filter_valid_card_numbers=True) # just valid card numbers will be in result; be careful to `check_validation` be also True, default: True
# result
# [
# {'pure': '6219861034529007', 'base': '6219-8610-3452-9007', 'index': 1, 'is_valid': True,
# 'bank_data': {
# 'nickname': 'saman',
# 'name': 'Saman Bank',
# 'persian_name': 'بانک سامان',
# 'card_prefix': ['621986'],
# 'sheba_code': ['056'],
# }},
# {'pure': '5022291070873466', 'base': '5022291070873466', 'index': 3, 'is_valid': True,
# 'bank_data': {
# 'nickname': 'pasargad',
# 'name': 'Pasargad Bank',
# 'persian_name': 'بانک پاسارگاد',
# 'card_prefix': ['502229', '639347'],
# 'sheba_code': ['057'],
# }},
# ]sheba module contain 2 functions:
- validating them
- find bank data of a sheba number
from persian_tools.bank import sheba
sheba.validate('IR820540102680020817909002') # True
sheba.validate('IR01234567890123456789') # False
sheba.bank_data('IR820540102680020817909002')
# {
# 'nickname': 'parsian',
# 'name': 'Parsian Bank',
# 'persian_name': 'بانک پارسیان',
# 'card_prefix': ['622106', '627884'],
# 'sheba_code': ['054'],
# 'account_number': '020817909002',
# 'formatted_account_number': '002-00817909-002'
# }This module has useful functions related to iranian national id (code-e melli), like:
- validating them
- generate a random one
- find place of national id by the prefix of id
from persian_tools import national_id
national_id.validate('0499370899') # True
national_id.validate('0684159415') # False
national_id.generate_random() # '0458096784'
national_id.generate_random() # '1156537101'
national_id.find_place('0906582709') # {'code': ['089', '090'], 'city': 'کاشمر', 'province': 'خراسان رضوی'}
national_id.find_place('0643005846') # {'code': ['064', '065'], 'city': 'بیرجند', 'province': 'خراسان جنوبی'}This module contains two functions to generate random iranian legal id (shenas-e melli) and validate any given id.
from persian_tools import legal_id
legal_id.validate('10380284790') # True
legal_id.validate('11053639140') # False
legal_id.generate_random() # '10100387143'
legal_id.generate_random() # '77111986110'This module can validate, normalize and give you some data from a phone number.
from persian_tools import phone_number
phone_number.validate('09123456789') # True
phone_number.validate('+989123456789') # True
phone_number.validate('989123456789') # True
phone_number.validate('98912345678') # False
phone_number.normalize('00989022002580') # 09022002580
phone_number.normalize('+989022002580') # 09022002580
phone_number.normalize('9022002580') # 09022002580
phone_number.normalize('9022002580', '0') # 09022002580
phone_number.normalize('9022002580', '+98') # +989022002580
phone_number.operator_data('09123456789')
# {'province': ['البرز', 'زنجان', 'سمنان', 'قزوین', 'قم', 'برخی از شهرستان های استان مرکزی'], 'base': 'تهران', 'type': ['permanent'], 'operator': 'همراه اول'}
phone_number.operator_data('09303456789')
# {'province': [], 'base': 'کشوری', 'type': ['permanent', 'credit'], 'operator': 'ایرانسل'}With bill_id and payment_id (or just barcode), you can get detail of a bill.
from persian_tools import bill
bill.get_detail(bill_id=7748317800142, payment_id=1770160)
# result
# {'amount': 1700,
# 'barcode': '77483178001420001770160',
# 'bill_id': 7748317800142,
# 'is_valid': True,
# 'is_valid_bill_id': True,
# 'is_valid_payment_id': True,
# 'payment_id': 1770160,
# 'type': 'تلفن ثابت'}
bill.get_detail(barcode='77483178001420001770160')
# same result
# default currency is set to Toman, but can change like as below
bill.get_detail(barcode='77483178001420001770160', currency=bill.CURRENCY_RIAL)
# result
# {'amount': 17000,
# ...Get information(province, category, type) about vehicles plate.
from persian_tools import plate
plate.get_info('12D45147')
# result
# {'category': 'دیپلمات',
# 'province': 'مرکزی',
# 'template': '12D451ایران47',
# 'type': 'Car'}
plate.get_info('12345678')
# result
# {'category': None,
# 'province': 'مرکز تهران',
# 'template': '123-45678',
# 'type': 'Motorcycle'}
plate.is_valid('12D45147') # True
plate.is_valid('12345678') # True
plate.is_valid('1234567') # False
plate.is_valid('1204567') # FalseNote: Plates that have farsi digits in them(like: الف، ب، ص) will be returned in this template:
{first_two_digits}{plate_character}{next_three_digits}ایران{province_code}