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incoming: JSON validation framework for Python

incoming is a JSON validation framework.

Overview

Validating anything can get really messy. JSON being one of the most used formats for data exchange, incoming aims at solving the problem of validating JSON with structure and ease.

incoming is a small framework for validating JSON. Its up to you where and how to use it. A common use-case (and the primary reason why I wrote this framework) was using it for writing HTTP servers to validate incoming JSON payload.

Features

  • Classes that can be sub-classed for writing structured validators.
  • Basic validators (or datatypes) for performing common validations, like string, numbers, booleans, lists, nested JSON, etc.
  • Allows extending validators (datatypes) to write your own.
  • Allows writing callables for validating values.
  • Captures errors during validation and returns a complete report of errors.
  • Allows reporting different errors for different validation test failures for the same value.

Installation

Installation is simple.

python setup.py install

Basic Usage

import json

from datetime import date
from incoming import datatypes, PayloadValidator


class MovieValidator(PayloadValidator):

    name = datatypes.String()
    rating = datatypes.Function('validate_rating',
                                error='Rating must be in between 1 and 10.')
    actors = datatypes.Array()
    is_3d = datatypes.Boolean()
    release_year = datatypes.Function('validate_release_year',
                                      error=('Release year must be in between '
                                             '1800 and current year.'))

    # validation method can be a regular method
    def validate_rating(self, val, *args, **kwargs):
        if not isinstance(val, int):
            return False

        if val < 1 or val > 10:
            return False

        return True

    # validation method can be a staticmethod as well
    @staticmethod
    def validate_release_year(val, *args, **kwargs):
        if not isinstance(val, int):
            return False

        if val < 1800 or val > date.today().year:
            return False

        return True

payload = {
    'name': 'Avengers',
    'rating': 5,
    'actors': [
        'Robert Downey Jr.',
        'Samual L. Jackson',
        'Scarlett Johansson',
        'Mark Ruffalo'
    ],
    'is_3d': True,
    'release_year': 2012
}
result, errors = MovieValidator().validate(payload)
assert result and errors is None, 'Validation failed.\n%s' % json.dumps(errors, indent=2)

payload = {
    'name': 'Avengers',
    'rating': 11,
    'actors': [
        'Robert Downey Jr.',
        'Samual L. Jackson',
        'Scarlett Johansson',
        'Mark Ruffalo'
    ],
    'is_3d': 'True',
    'release_year': 2014
}
result, errors = MovieValidator().validate(payload)
assert result and errors is None, 'Validation failed.\n%s' % json.dumps(errors, indent=2)

Run the above script, you shall get a response like so:

Traceback (most recent call last):
  File "code.py", line 67, in <module>
    assert result and errors is None, 'Validation failed.\n%s' % json.dumps(errors, indent=2)
AssertionError: Validation failed.
{
  "rating": [
    "Rating must be in between 1 and 10."
  ],
  "is_3d": [
    "Invalid data. Expected a boolean value."
  ],
  "release_year": [
    "Release year must be in between 1800 and current year."
  ]
}

Tests

Run tests like so:

python setup.py test

or:

py.test incoming

User Guide

.. toctree::
   :maxdepth: 2

   payloadvalidators
   datatypes



Indices and tables