Skip to main content

No project description provided

Project description

Numeral Converter

Coverage Status Coverage Status

Coverage Status Coverage Status

Numeral converter:

  • converts an integer value into a numerator in natural language, bringing it into the form given by the arguments
  • converts the numerator from natural language to integer value
  • handles spelling errors

Installation

pip install numeral-converter

Quickstart

Loading Language Data

from numeral_converter import (
    get_available_languages, 
    load_numeral_data,
    maximum_number_order_to_convert
)
get_available_languages()
# ['uk', 'ru', 'en']

load_numeral_data('en')
maximum_number_order_to_convert("en")
# 24

load_numeral_data('uk')
maximum_number_order_to_convert("uk")
# 33

load_numeral_data('ru')
maximum_number_order_to_convert("ru")
# 123

Converting from Numeral to Integer

from numeral_converter import numeral2int

numeral2int("two thousand and twenty-three", lang='en')
# 2023

numeral2int("дві тисячі двадцять третій", lang="uk")
# 2023

numeral2int("двох тисяч двадцяти трьох", lang="uk")
# 2023

numeral2int("двe тысячи двадцать третий", lang="ru")
# 2023

numeral2int("сто тисяч мільйонів", lang="uk")
# 100000000000

numeral2int("сто тисяч", lang="uk")
# 100000

numeral2int("три десятки", lang="uk")
# 30

numeral2int("три тисячі три сотні три десятки три", lang="uk")
# 3333

Converting from Numeral to Integer (with mistakes)

from numeral_converter import numeral2int

numeral2int("дви тисичи двадцить тре", lang="uk")
# 2023

numeral2int("дві тисячі двадцять три роки", lang="uk")
# ValueError('can\'t convert "роки" to integer')
        
numeral2int("три мільярди тисяча пятдесят пять мільонів", lang="uk")
# ValueError(
#     "position 1: order of 1000000000:9 is less/equal "
#     "of summary order in next group: 9")

numeral2int("три мільярди тисячний пятдесят пятий мільон", lang="uk")
# ValueError("the number in the middle of the numeral cannot be ordinal")

Converting from Integer to Numeral

from numeral_converter import int2numeral

int2numeral(2023, lang='uk', case="nominative", num_class="quantitative")
# {
#   'numeral': 'дві тисячі двадцять три', 
#   'numeral_forms': ['дві тисячі двадцять три', ]
# }

int2numeral(
    2021, 
    lang='uk',
    case="nominative",
    gender="neuter",
    num_class="quantitative")
# {
#   'numeral': 'дві тисячі двадцять одне (одно)', 
#   'numeral_forms': [
#       'дві тисячі двадцять одне',
#       'дві тисячі двадцять одно'
#    ]
# } 

int2numeral(
    89, 
    lang='uk',
    case="prepositional", 
    num_class="quantitative")
# {
#   'numeral': 'вісімдесяти (вісімдесятьох) дев’яти (дев’ятьох)', 
#   'numeral_forms': [
#       'вісімдесяти дев’яти',
#       'вісімдесяти дев’ятьох',
#       'вісімдесятьох дев’яти',
#       'вісімдесятьох дев’ятьох'
#    ]
# }    

int2numeral(10000000, lang="uk")
# {'numeral': 'десять мільйонів', 'numeral_forms': ['десять мільйонів']}

Converting Numeral to Integer in Text

from numeral_converter import convert_numerical_in_text
s = "After twenty, numbers such as twenty-five, fifty, seventy-five, " \
    "and one hundred follow. So long as one knows the core number, or the number " \
    "situated in the tens or hundreds position that determines the general " \
    "amount, understanding these more complicated numbers won't be difficult. " \
    "For example thirty-three is simply \"thirty\" plus three; sixty-seven " \
    "is \"sixty\" plus seven; and sixty-nine is simply \"sixty\" plus nine." \
convert_numerical_in_text(s, lang="en")
# "After 20, numbers such as 25, 50, 75, and 100 follow. So long as 1 "
# "knows the core number, or the number situated in the 10 or 100 "
# "position that determines the general amount, understanding these more "
# "complicated numbers won't be difficult. For example 33 is simply "
# "\"30\" plus 3; 67 is \"60\" plus 7; and 69 is simply \"60\" plus 9."

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

numeral_converter-0.0.2.tar.gz (11.8 kB view details)

Uploaded Source

Built Distribution

numeral_converter-0.0.2-py3-none-any.whl (12.0 kB view details)

Uploaded Python 3

File details

Details for the file numeral_converter-0.0.2.tar.gz.

File metadata

  • Download URL: numeral_converter-0.0.2.tar.gz
  • Upload date:
  • Size: 11.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.13

File hashes

Hashes for numeral_converter-0.0.2.tar.gz
Algorithm Hash digest
SHA256 116fecbc58d6cc9f1448297568ed5d9649e8da5c12b708d4af808b584a636da9
MD5 7a740d56a71a50a3f848d406e065da0b
BLAKE2b-256 783d3215c89de87a17e25bdbde9fb2524dd4fc6d75a8f2ac7c1a553209bfe894

See more details on using hashes here.

Provenance

File details

Details for the file numeral_converter-0.0.2-py3-none-any.whl.

File metadata

File hashes

Hashes for numeral_converter-0.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 ed018f599a78188d00b8a8ed3b8821c18da5693c46686795ab3c09f98616fa89
MD5 3af0eab415f5bdd4b1597f76c1bdb8bb
BLAKE2b-256 f46f2f7bf7ad8d6fce63db45ed6d632ef714fc2c1964505255159688d0af9a2e

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page