Pydantic Types

Common used type definitions with Pydantic.

Advantage

• Out of the box

Out of the box

You don't need to define customized types for common use cases. This package provides a set of commonly used types that can be directly imported and used in your Pydantic models.

Quickstart

pip install pydantictypes

Supported Types

Constraint Functions

These functions create types with numeric or length constraints:

API

Integer Conversion Types

ConstrainedStringToOptionalInt

from pydantictypes import ConstrainedStringToOptionalInt
from pydantic import BaseModel, ValidationError

class MyModel(BaseModel):
    optional_int: ConstrainedStringToOptionalInt

# Successful conversions:
model1 = MyModel(optional_int="123")     # Result: model1.optional_int = 123
model2 = MyModel(optional_int="0")       # Result: model2.optional_int = 0
model3 = MyModel(optional_int="")        # Result: model3.optional_int = None
model4 = MyModel(optional_int=None)      # Result: model4.optional_int = None

# These inputs raise ValidationError:
try:
    MyModel(optional_int="1,000")        # Commas not supported
except ValidationError:
    pass

constringtooptionalint (with constraints)

from pydantictypes import constringtooptionalint
from pydantic import BaseModel, ValidationError

# Create a type with constraints
Optional10Digits = constringtooptionalint(ge=0, le=9999999999)

class MyModel(BaseModel):
    value: Optional10Digits

# Successful conversions:
model1 = MyModel(value="1234567890")     # Result: model1.value = 1234567890
model2 = MyModel(value="")               # Result: model2.value = None

# Constraint violations raise ValidationError:
try:
    MyModel(value="10000000000")         # Exceeds le=9999999999
except ValidationError:
    pass

try:
    MyModel(value="-1")                  # Less than ge=0
except ValidationError:
    pass

StrictStringWithCommaToInt

from pydantictypes import StrictStringWithCommaToInt
from pydantic import BaseModel, ValidationError

class MyModel(BaseModel):
    number: StrictStringWithCommaToInt

# Successful conversions:
model1 = MyModel(number="1")             # Result: model1.number = 1
model2 = MyModel(number="1,000")         # Result: model2.number = 1000
model3 = MyModel(number="1,000,000")     # Result: model3.number = 1000000

# These inputs raise ValidationError:
try:
    MyModel(number="1.0")                # Decimals not supported
except ValidationError:
    pass

StrictStringWithCommaToOptionalInt

from pydantictypes import StrictStringWithCommaToOptionalInt
from pydantic import BaseModel, ValidationError

class MyModel(BaseModel):
    optional_number: StrictStringWithCommaToOptionalInt

# Successful conversions:
model1 = MyModel(optional_number="1")           # Result: model1.optional_number = 1
model2 = MyModel(optional_number="1,000")       # Result: model2.optional_number = 1000
model3 = MyModel(optional_number="")            # Result: model3.optional_number = None
model4 = MyModel(optional_number=None)          # Result: model4.optional_number = None

# These inputs raise ValidationError:
try:
    MyModel(optional_number="1.0")              # Decimals not supported
except ValidationError:
    pass

constringwithcommatooptionalint (with constraints)

from pydantictypes import constringwithcommatooptionalint
from pydantic import BaseModel, ValidationError

# Create a type with constraints
BoundedNumber = constringwithcommatooptionalint(ge=0, le=1000000, multiple_of=100)

class MyModel(BaseModel):
    amount: BoundedNumber

# Successful conversions:
model1 = MyModel(amount="1,000")         # Result: model1.amount = 1000
model2 = MyModel(amount="500,000")       # Result: model2.amount = 500000
model3 = MyModel(amount="")              # Result: model3.amount = None

# Constraint violations raise ValidationError:
try:
    MyModel(amount="1,500")              # Not a multiple of 100
except ValidationError:
    pass

StrictKanjiYenStringToInt

from pydantictypes import StrictKanjiYenStringToInt
from pydantic import BaseModel, ValidationError

class MyModel(BaseModel):
    price: StrictKanjiYenStringToInt

# Successful conversions:
model1 = MyModel(price="1円")           # Result: model1.price = 1
model2 = MyModel(price="1,000円")       # Result: model2.price = 1000
model3 = MyModel(price="1,000,000円")   # Result: model3.price = 1000000

# These inputs raise ValidationError:
try:
    MyModel(price="1.0円")      # Decimals not supported
except ValidationError:
    pass

try:
    MyModel(price="1000")       # Missing 円 character
except ValidationError:
    pass

StrictSymbolYenStringToInt

from pydantictypes import StrictSymbolYenStringToInt
from pydantic import BaseModel, ValidationError

class MyModel(BaseModel):
    price: StrictSymbolYenStringToInt

# Successful conversions:
model1 = MyModel(price=r"\1")           # Result: model1.price = 1
model2 = MyModel(price=r"\1,000")       # Result: model2.price = 1000
model3 = MyModel(price=r"\1,000,000")   # Result: model3.price = 1000000

# These inputs raise ValidationError:
try:
    MyModel(price=r"\1.0")              # Decimals not supported
except ValidationError:
    pass

try:
    MyModel(price="$1")                 # Dollar symbol not supported
except ValidationError:
    pass

String Validation Types

HalfWidthString / OptionalHalfWidthString

from pydantictypes import HalfWidthString, OptionalHalfWidthString
from pydantic import BaseModel, ValidationError

class MyModel(BaseModel):
    code: HalfWidthString
    optional_code: OptionalHalfWidthString

# Successful conversions:
model1 = MyModel(code="ABC123", optional_code="XYZ")
model2 = MyModel(code="hello", optional_code="")      # optional_code = None
model3 = MyModel(code="test", optional_code=None)     # optional_code = None

# These inputs raise ValidationError:
try:
    MyModel(code="ABC", optional_code=None)         # Full-width characters not allowed
except ValidationError:
    pass

constrained_string / constrained_optional_string

from pydantictypes import constrained_string, constrained_optional_string
from pydantic import BaseModel, ValidationError

# Create types with length constraints
Code5Chars = constrained_string(equal_to=5)
Name = constrained_optional_string(min_length=1, max_length=50)

class MyModel(BaseModel):
    code: Code5Chars
    name: Name

# Successful conversions:
model1 = MyModel(code="ABCDE", name="John")
model2 = MyModel(code="12345", name="")           # name = None

# These inputs raise ValidationError:
try:
    MyModel(code="ABC", name="John")              # code length != 5
except ValidationError:
    pass

StringToOptionalStr / constringtooptionalstr

from pydantictypes import StringToOptionalStr, constringtooptionalstr
from pydantic import BaseModel, ValidationError

# Create type with transformations and constraints
TrimmedLowerName = constringtooptionalstr(
    strip_whitespace=True,
    to_lower=True,
    min_length=1,
    max_length=100,
    regex=r"^[a-z\s]+$"
)

class MyModel(BaseModel):
    name: TrimmedLowerName

# Successful conversions:
model1 = MyModel(name="  JOHN DOE  ")     # Result: model1.name = "john doe"
model2 = MyModel(name="")                  # Result: model2.name = None

# These inputs raise ValidationError:
try:
    MyModel(name="John123")               # Contains numbers (regex mismatch)
except ValidationError:
    pass

Boolean Conversion Types

StringToBoolean / StringToOptionalBool

from pydantictypes import StringToBoolean, StringToOptionalBool
from pydantic import BaseModel, ValidationError

class MyModel(BaseModel):
    is_active: StringToOptionalBool

# Successful conversions:
model1 = MyModel(is_active="1")      # Result: model1.is_active = StringToBoolean.TRUE
model2 = MyModel(is_active="0")      # Result: model2.is_active = StringToBoolean.FALSE
model3 = MyModel(is_active="")       # Result: model3.is_active = None

# String representation:
print(str(model1.is_active))         # Output: "1"
print(str(model2.is_active))         # Output: "0"

# These inputs raise ValidationError:
try:
    MyModel(is_active="true")        # Must be "1", "0", or ""
except ValidationError:
    pass

DateTime Conversion Types

StringSlashToDateTime

from pydantictypes import StringSlashToDateTime
from pydantic import BaseModel, ValidationError
import datetime

class MyModel(BaseModel):
    date: StringSlashToDateTime

# Successful conversions:
model1 = MyModel(date="2020/01/01")   # Result: model1.date = datetime.datetime(2020, 1, 1, 0, 0)
model2 = MyModel(date="2020/12/31")   # Result: model2.date = datetime.datetime(2020, 12, 31, 0, 0)
model3 = MyModel(date="2020/02/29")   # Result: model3.date = datetime.datetime(2020, 2, 29, 0, 0)

# These inputs raise ValidationError:
try:
    MyModel(date="2020/02/30")        # Invalid date
except ValidationError:
    pass

try:
    MyModel(date="2020-01-01")        # Wrong format (uses hyphens)
except ValidationError:
    pass

StringSlashMonthDayOnlyToDatetime

from pydantictypes import StringSlashMonthDayOnlyToDatetime
from pydantic import BaseModel, ValidationError
import datetime

class MyModel(BaseModel):
    date: StringSlashMonthDayOnlyToDatetime

# Successful conversions:
model1 = MyModel(date="01/01")    # Result: model1.date = datetime.datetime(1904, 1, 1, 0, 0)
model2 = MyModel(date="12/31")    # Result: model2.date = datetime.datetime(1904, 12, 31, 0, 0)
model3 = MyModel(date="02/29")    # Result: model3.date = datetime.datetime(1904, 2, 29, 0, 0)

# These inputs raise ValidationError:
try:
    MyModel(date="01/32")         # Invalid day
except ValidationError:
    pass

try:
    MyModel(date="2020/01/01")    # Wrong format (includes year)
except ValidationError:
    pass

Special Types

EmptyStringToNone

from pydantictypes import EmptyStringToNone
from pydantic import BaseModel, ValidationError

class MyModel(BaseModel):
    empty_field: EmptyStringToNone

# Successful conversion:
model1 = MyModel(empty_field="")      # Result: model1.empty_field = None

# These inputs raise ValidationError:
try:
    MyModel(empty_field="not empty")  # Only empty string allowed
except ValidationError:
    pass

try:
    MyModel(empty_field=None)         # Must be a string
except ValidationError:
    pass

Credits

This package was created with Cookiecutter and the yukihiko-shinoda/cookiecutter-pypackage project template.