cleanchausie 1.16.0

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

CleanChausie

CleanChausie is a data validation and transformation library for Python. It is a successor to CleanCat.

Check out the docs!

Interested in working on projects like this? Close is looking for great engineers to join our team.

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

This is a short example of how a schema might be used to support a flask endpoint. More detailed examples can be found in the docs.

from typing import List
from cleanchausie import (
  clean, ListField, URLField, EmailField, field, ValidationError, 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 = clean(JobApplication, request.json)
  if isinstance(result, ValidationError):
    return jsonify(result.serialize()), 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}'

Release process

• Make sure to thoroughly review and test the code changes.
• Prepare for a new release
  • Update the package version within cleanchausie/__init__.py.
  • Add a changelog entry for the new version.
  • Merge to master
• Dispatch a new "build and release" workflow action within the github actions tab.

The resulting workflow will build and publish the new version to PyPi.