extended-type

Boost Python's type hinting with extended-types: regex and range validations seamlessly.

This is an experimental collection of code snippets that work as intended, but it's not packaged for distribution yet.

from dataclasses import dataclass
from typing import Literal

from extended_type import RangeInt, RegexStr
from extended_type.type_extended import type_extended


@type_extended
@dataclass
class School:
    school_code: RegexStr[Literal["^school.*$"]]
    school_name: str
    age: RangeInt[Literal[10], Literal[20]]

school = School(school_code="school_1", school_name="School 1", age=15) # okay
school = School(school_code="sch", school_name="School 1", age=10) # ValueError: 'sch' does not match regex pattern '^school.*$'
school = School(school_code="school_1", school_name="School 1", age=21) # ValueError: 21 is not in range [10, 20]
school.school_code = "sch" # ValueError: 'sch' does not match regex pattern '^school.*$'

Types Extended

str

• RegexStr: Easily validate string attributes with regex patterns.

from typing import Literal
from extended_type import RegexStr, TypeExtended
from dataclasses import dataclass

@dataclass
class School(TypeExtended):
    school_code: RegexStr[Literal["^school.*$"]]
    school_name: str

school = School(school_code="school_1", school_name="School 1")
school = School(school_code="scho", school_name="School 1") # ValueError: 'scho' does not match regex pattern '^school.*$'

• PrefixStr: Validate string attributes with a prefix.

• SuffixStr: Validate string attributes with a suffix.

• ContainsStr: Validate string attributes with a substring.

• EmailStr: Validate string attributes with an email pattern.

TBD

• NotContainsStr: Validate string attributes with a not contains pattern.

• LengthStr: Validate string attributes with a length pattern.

• NumericStr: Validate string attributes with a numeric pattern.

• AlphabeticalStr: Validate string attributes with an alphabetical pattern.

• AlphanumericStr: Validate string attributes with an alphanumeric pattern.

• UrlStr: Validate string attributes with a url pattern.

• PhoneStr: Validate string attributes with a phone pattern.

• CreditCardStr: Validate string attributes with a credit card pattern.

• LowercaseStr: Validate string attributes with a lowercase pattern.

• UppercaseStr: Validate string attributes with an uppercase pattern.

Numeric

• RangeInt: Set boundaries for integer attributes.

from typing import Literal
from extended_type.range_int import RangeInt, TypeExtended
from dataclasses import dataclass

@dataclass
class Student(TypeExtended):
    age: RangeInt[Literal[10], Literal[20]]

student = Student(age=15)
student = Student(age=9) # ValueError: 9 is not in range [10, 20]
student = Student(age=21) # ValueError: 21 is not in range [10, 20]

• RangeFloat: Set boundaries for float attributes.

from typing import Literal
from extended_type.range_float import RangeFloat, TypeExtended
from dataclasses import dataclass

@dataclass
class Product(TypeExtended):
    weight: RangeFloat[Literal['0.5'], Literal['5.0']]
    height: RangeFloat[Literal[1], Literal[5]]

product = Product(weight=2.5, height=2.5)
product = Product(weight=0.4, height=3) # ValueError: 0.4 is not in range [0.5, 5.0]
product = Product(weight=2.5, height=7) # ValueError: 7 is not in range [1.0, 5.0]

• RangeDecimal: Set boundaries for decimal attributes.

from typing import Literal
from extended_type.range_decimal import RangeDecimal, TypeExtended
from dataclasses import dataclass

@dataclass
class Transaction(TypeExtended):
    amount: RangeDecimal[Literal["0.01"], Literal["1000.00"]]
    amount2: RangeDecimal[Literal[1], Literal[10]]

transaction = Transaction(amount=Decimal("150.75"), amount2=Decimal("5.0"))
transaction = Transaction(amount=Decimal("0.005"), amount2=Decimal("5.0")) # ValueError: 0.005 is not in range [0.01, 1000.00]
transaction = Transaction(amount=Decimal("150.75"), amount2=Decimal("15")) # ValueError: 15 is not in range [1, 10]

TBD

• Positive*: Validate integer | float | Decimal attributes with a positive pattern.

• Negative*: Validate integer | float | Decimal attributes with a negative pattern.

• Odd*: Validate integer | float | Decimal attributes with an odd pattern.

• Even*: Validate integer | float | Decimal attributes with an even pattern.

• Divisible*: Validate integer | float | Decimal attributes with a divisible pattern.

ETC

... More types will be added soon. Your suggestions are welcome! 🎉

To Do

• Add Tests
• Add CI/CD
• Add PyPi package
• Add more types (Suggestions are welcome! 🎉)