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Data validation and transformation library for Python. Successor to CleanCat.

Project description

CleanChausie

Data validation and transformation library for Python. Successor to CleanCat.

Key features:

  • Operate on/with type-checked objects that have good IDE/autocomplete support
  • Annotation-based declarations for simple fields
  • Composable/reusable fields and field validation logic
  • Support (but not require) passing around a context (to avoid global state)
    • Context pattern is compatible with explicit sqlalchemy-based session management. i.e. pass in a session when validating
  • Cleanly support intra-schema field dependencies (i.e. one field can depend on the validated value of another)
  • Explicit nullability/omission parameters
  • Errors returned for multiple fields at a time, with field attribution

CleanChausie By Example

Basic example in Flask

This is a direct port of the example from the OG cleancat README.

This shows:

  • Annotation-based declarations for simple fields.
  • Type-checked objects (successful validation results in initialized instances of the schema)
from typing import List
from cleancat.chausie.fields import (
  field, EmailField, listfield, URLField, ValidationError,
)
from cleancat.chausie.schema import Schema
from flask import app, request, jsonify

class JobApplication(Schema):
    first_name: str
    last_name: str
    email: str = field(EmailField())
    urls: List[str] = field(listfield(URLField(default_scheme='http://')))

@app.route('/job_application', methods=['POST'])
def test_view():
    result = JobApplication.clean(request.json)
    if isinstance(result, ValidationError):
        return jsonify({'errors': [{'msg': e.msg, 'field': e.field} for e in result.errors] }), 400

    # Now "result" has the validated data, in the form of a `JobApplication` instance.
    assert isinstance(result, JobApplication)
    name = f'{result.first_name} {result.last_name}'

Explicit Nullability

TODO revisit omission defaults so that they match the annotation

from typing import Optional, Union
from cleancat.chausie.consts import OMITTED
from cleancat.chausie.fields import field, StrField, Omittable, Required
from cleancat.chausie.schema import Schema

class NullabilityExample(Schema):
  # auto defined based on annotations
  nonnull_required: str
  nullable_omittable: Optional[str]
  
  # manually specified
  nonnull_omittable: Union[str, OMITTED] = field(StrField, nullability=Omittable(allow_none=False))
  nullable_required: Optional[str] = field(StrField, nullability=Required(allow_none=True))

Composable/Reusable Fields

from typing import Union
from cleancat.chausie.fields import field, Field, StrField, IntField, Error
from cleancat.chausie.schema import Schema

@field(parents=(StrField,))
def trimmed_string(value: str) -> str:
    return value.strip()

def max_val(max_value: int) -> Field:
    @field()
    def _max_val(value: int) -> Union[int, Error]:
        if value > max_value:
            return Error(msg=f'value is above allowed max of {max_value}')
        return value
    return _max_val

def min_val(min_value: int) -> Field:
    @field()
    def _min_val(value: int) -> Union[int, Error]:
        if value < min_value:
            return Error(msg=f'value is below allowed min of {min_value}')
        return value
    return _min_val

def constrained_int(min: int, max: int) -> Field:
    return field(parents=(IntField, min_val(min), max_val(max)))()

class ReusableFieldsExampleSchema(Schema):
    first_name: str = trimmed_string
    age: int = field(parents=(IntField, min_val(0)))()
    score: int = constrained_int(min=0, max=100)

Context Support

import attrs
from cleancat.chausie.fields import field, StrField
from cleancat.chausie.schema import Schema

class MyModel:  # some ORM model
    id: str
    created_by: 'User'

@attrs.frozen
class Context:
    authenticated_user: 'User'  # the User making a request
    session: 'Session'  # active ORM Session

class ContextExampleSchema(Schema):
    @field(parents=(StrField,), accepts=('id',))
    def obj(self, value: str, context: Context) -> MyModel:
        return (
            context.session
            .query(MyModel)
            .filter(MyModel.created_by == context.authenticated_user.id)
            .filter(MyModel.id == value)
        )

with atomic() as session:
    result = ContextExampleSchema.clean(
        data={'id': 'mymodel_primarykey'},
        context=Context(authenticated_user=EXAMPLE_USER, session=session)
    )
assert isinstance(result, ContextExampleSchema)
assert isinstance(result.obj, MyModel)

Intra-schema Field dependencies

from cleancat.chausie.fields import field
from cleancat.chausie.schema import Schema

class DependencyExampleSchema(Schema):
    a: str
    b: str
    
    @field()
    def a_and_b(self, a: str, b: str) -> str:
        return f'{a}::{b}'


result = DependencyExampleSchema.clean(
  data={'a': 'a', 'b': 'b'},
)
assert isinstance(result, DependencyExampleSchema)
assert result.a_and_b == 'a::b'

Per-Field Errors

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