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
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
cleanchausie-1.0.0.tar.gz
(20.2 kB
view details)
File details
Details for the file cleanchausie-1.0.0.tar.gz
.
File metadata
- Download URL: cleanchausie-1.0.0.tar.gz
- Upload date:
- Size: 20.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.10.8
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8dbf697170347f7db6019fbe4c9f2ee323d3070547ef0442cda7706c7fd9d1b5 |
|
MD5 | 8fc52544c86d785c6960b7459b487b6a |
|
BLAKE2b-256 | 51b2b2c4f170613b23d223805ef5a5cdeb377706191c5e357a7d82338c643be8 |