https://github.com/kaliv0/pypermissive

Validation library in Python, modeled after Pydantic
https://github.com/kaliv0/pypermissive

pydantic-v2 python-validator validation-library

Last synced: about 2 months ago
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Validation library in Python, modeled after Pydantic

• Host: GitHub
• URL: https://github.com/kaliv0/pypermissive
• Owner: kaliv0
• License: mit
• Created: 2024-08-01T21:38:22.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-11-06T21:50:35.000Z (about 2 months ago)
• Last Synced: 2024-11-06T22:34:21.121Z (about 2 months ago)
• Topics: pydantic-v2, python-validator, validation-library
• Language: Python
• Homepage: https://pypi.org/project/pypermissive/
• Size: 101 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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---

# PyPermissive

[![tests](https://img.shields.io/github/actions/workflow/status/kaliv0/pypermissive/ci.yml)](https://github.com/kaliv0/pypermissive/actions/workflows/ci.yml)

![Python 3.x](https://img.shields.io/badge/python-3.12-blue?style=flat-square&logo=Python&logoColor=white)

[![PyPI](https://img.shields.io/pypi/v/pypermissive.svg)](https://pypi.org/project/pypermissive/)

[![Downloads](https://static.pepy.tech/badge/pypermissive)](https://pepy.tech/projects/pypermissive)

[![License](https://img.shields.io/badge/License-MIT-yellow?style=flat-square)](https://github.com/kaliv0/pypermissive/blob/main/LICENSE)

Validation library in Python, modeled after Pydantic

## Example

Inherit from BaseModel and describe required types.


PyPermissive supports validation for primitive types:

```python

class Employee(BaseModel):

    employee_id: int

    name: str

    salary: float

    elected_benefits: bool = False

    

employee = Employee(

    employee_id=1,

    name="Foo Bar",

    salary=123_000.00,

    elected_benefits=True,

)

```

collections:

```python

class Book(BaseModel):

    characters: dict[str, str]

    chapters: list[str]

    

book = Book(

    characters={"Pelleas": "he", "Melisande": "she"},

    chapters=["Beginning", "Middle", "End"]

)

```

unions, classes and fields.



Fields are similar to pydantic with one caveat: you need to give value type explicitly:

```python

class User(BaseModel):

    name: Field(type=str, default="Jimmie", frozen=True)

    age: Field(type=int, gt=18, lt=35)

    id: Field(type=UUID, default_factory=uuid4)

    email: Field(type=str, pattern=r"^[a-zA-Z0-9_.+-]+@[a-zA-Z0-9-]+[.][a-zA-Z0-9-.]+$")

    nickname: Field(type=str, min_length=6, max_length=12)

    PIN: Field(type=str, field_validator=lambda x: x.isdigit())

```

You can also use decorators:


@ComputedField (invoke only from instances) and @ComputedClassField (invoke both on class and instance level)

```python

class Thesis:

    BAZZ = ["1", "2", "3"]

    def __init__(self):

        self.fizz = [1, 2, 3, 4, 5]

        self.buzz = [6, 7, 8, 9]

    @ComputedField

    def foo(self):

        return [val for val in itertools.product(self.fizz, self.buzz)]

    @ComputedClassField

    def bar(self):

        return list(itertools.permutations(self.BAZZ))

    

```

The library supports @validate_call that checks both argument and return types:

```python

@validate_call

def some_func(delimiter: str, count: int, numbers: list[int]) -> str:

    return (delimiter * count).join([str(d) for d in numbers])

```