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A schema loading and validation library

Project description

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Schemable is a schema parsing and validation library that let’s you define schemas simply using dictionaries, lists, types, and callables.

Features

  • Simple schema definitions using dict, list, and type objects

  • Complex schema definitions using Any, All, As, and predicates

  • Detailed validation error messages

  • Partial data loading on validation failure

  • Strict and non-strict parsing modes

  • Python 3.4+

Quickstart

Install using pip:

pip install schemable

Define a schema using dict and list objects:

from schemable import Schema, All, Any, As, Optional, SchemaError

user_schema = Schema({
    'name': str,
    'email': All(str, lambda email: len(email) > 3 and '@' in email),
    'active': bool,
    'settings': {
        Optional('theme'): str,
        Optional('language', default='en'): str,
        Optional('volume'): int,
        str: str
    },
    'aliases': [str],
    'phone': All(str,
                 As(lambda phone: ''.join(filter(str.isdigit, phone))),
                 lambda phone: 10 <= len(phone) <= 15),
    'addresses': [{
        'street_addr1': str,
        Optional('street_addr2', default=None): Any(str, None),
        'city': str,
        'state': str,
        'country': str,
        'zip_code': str
    }]
})

Then validate and load by passing data to user_schema():

# Fail!
result = user_schema({
    'name': 'Bob Smith',
    'email': 'bob.example.com',
    'active': 1,
    'settings': {
        'theme': False,
        'extra_setting1': 'val1',
        'extra_setting2': True
    },
    'phone': 1234567890,
    'addresses': [
        {'street_addr1': '123 Lane',
         'city': 'City',
         'state': 'ST',
         'country': 'US',
         'zip_code': 11000}
    ]
})

print(result)
# SchemaResult(
#     data={'name': 'Bob Smith',
#           'settings': {'extra_setting1': 'val1',
#                        'language': 'en'}
#           'addresses': [{'street_addr1': '123 Lane',
#                          'city': 'City',
#                          'state': 'ST',
#                          'country': 'US',
#                          'street_addr2': None}]},
#     errors={'email': "bad value: <lambda>('bob.example.com') should evaluate to True",
#             'active': 'bad value: type error, expected bool but found int',
#             'settings': {'theme': 'bad value: type error, expected str but found bool',
#                          'extra_setting2': 'bad value: type error, expected str but found bool'},
#             'phone': 'bad value: type error, expected str but found int',
#             'addresses': {0: {'zip_code': 'bad value: type error, expected str but found int'}},
#             'aliases': 'missing required key'})

# Fail!
result = user_schema({
    'name': 'Bob Smith',
    'email': 'bob@example.com',
    'active': True,
    'settings': {
        'theme': False,
        'extra_setting1': 'val1',
        'extra_setting2': 'val2'
    },
    'phone': '123-456-789',
    'addresses': [
        {'street_addr1': '123 Lane',
         'city': 'City',
         'state': 'ST',
         'country': 'US',
         'zip_code': '11000'}
    ]
})

print(result)
# SchemaResult(
#     data={'name': 'Bob Smith',
#           'email': 'bob@example.com',
#           'active': True,
#           'settings': {'extra_setting1': 'val1',
#                        'extra_setting2': 'val2',
#                        'language': 'en'},
#           'addresses': [{'street_addr1': '123 Lane',
#                          'city': 'City',
#                          'state': 'ST',
#                          'country': 'US',
#                          'zip_code': '11000',
#                          'street_addr2': None}]},
#     errors={'settings': {'theme': 'bad value: type error, expected str but found bool'},
#             'phone': "bad value: <lambda>('123456789') should evaluate to True",
#             'aliases': 'missing required key'})

Or can raise an exception on validation failure instead of returning results:

# Fail strictly!
try:
    user_schema({
        'name': 'Bob Smith',
        'email': 'bob@example.com',
        'active': True,
        'settings': {
            'theme': False,
            'extra_setting1': 'val1',
            'extra_setting2': 'val2'
        },
        'phone': '123-456-789',
        'addresses': [
            {'street_addr1': '123 Lane',
             'city': 'City',
             'state': 'ST',
             'country': 'US',
             'zip_code': '11000'}
        ]
    }, strict=True)
except SchemaError as exc:
    print(exc)
    # Schema validation failed: \
    # {'settings': {'theme': 'bad value: type error, expected str but found bool'}, \
    # 'phone': "bad value: <lambda>('123456789') should evaluate to True", \
    # 'aliases': 'missing required key'}

Access the parsed data after successful validation:

# Pass!
result = user_schema({
    'name': 'Bob Smith',
    'email': 'bob@example.com',
    'active': True,
    'settings': {
        'theme': 'dark',
        'extra_setting1': 'val1',
        'extra_setting2': 'val2'
    },
    'phone': '123-456-7890',
    'aliases': [],
    'addresses': [
        {'street_addr1': '123 Lane',
         'city': 'City',
         'state': 'ST',
         'country': 'US',
         'zip_code': '11000'}
    ]
})

print(result)
# SchemaResult(
#     data={'name': 'Bob Smith',
#           'email': 'bob@example.com',
#           'active': True,
#           'settings': {'theme': 'dark',
#                        'extra_setting1': 'val1',
#                        'extra_setting2': 'val2',
#                        'language': 'en'},
#           'phone': '1234567890',
#           'aliases': [],
#           'addresses': [{'street_addr1': '123 Lane',
#                          'city': 'City',
#                          'state': 'ST',
#                          'country': 'US',
#                          'zip_code': '11000',
#                          'street_addr2': None}]},
#     errors={})

For more details, please see the full documentation at https://schemable.readthedocs.io.

Changelog

v0.5.0 (2018-08-17)

  • Don’t load partial data from a nested schema if it was created with strict=True (e.g. Schema({'key': Schema({...}, strict=True)})).

v0.4.1 (2018-08-14)

  • Fix previous fix for case where schema results could have data or errors with schema classes as keys.

  • Ensure that Select('key', <iteratee>) doesn’t call <iteratee> if 'key' was not found in the source data.

v0.4.0 (2018-08-14)

  • Fix case where schema object with an Optional(key) would result in SchemaResult.errors[Optional(key)]. Ensure that SchemaResult.errors[key] is set instead.

  • Ignore KeyError when using Schema({'key': Select('other_key')}) when 'other_key' isn’t present in the source object. Return a missing key error instead.

v0.3.1 (2018-07-31)

  • If a validate callable raises an exception, use its string representation as the schema error message. Previously, a custom error message stating that the callable should evaluate to true was used when validator returned falsey and when it raised an exception. That message is now only returned when the validator doesn’t raise but returns falsey.

v0.3.0 (2018-07-27)

  • Add schema helpers:

    • Select

    • Use

  • Include execption class name in error message returned by As.

  • Always return a dict when parsing from dictionary schemas instead of trying to use the source data’s type as an initializer. (breaking change)

v0.2.0 (2018-07-25)

  • Rename Collection to List. (breaking change)

  • Rename Object to Dict. (breaking change)

  • Allow collections.abc.Mapping objects to be valid Dict objects.

  • Modify Type validation so that objects are only compared with isinstance.

  • Improve docs.

v0.1.0 (2018-07-24)

  • First release.

License

The MIT License (MIT)

Copyright (c) 2018, Derrick Gilland

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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