schemadict 0.0.4

Validate Python dictionaries like JSON schema

A schemadict is a regular Python dictionary which specifies the type and format of values for some given key. To check if a test dictionary is conform with the expected schema, schemadict provides the validate() method. If the test dictionary is ill-defined, an error will be thrown, otherwise None is returned.

Examples

Basic usage

>>> from schemadict import schemadict

>>> schema = schemadict({
...     'name': {
...         'type': str,
...         'min_len': 3,
...         'max_len': 12,
...     },
...     'age': {
...         'type': int,
...         '>=': 0,
...         '<': 150,
...     },
... })
>>>
>>> testdict = {'name': 'Neil', 'age': 55}
>>> schema.validate(testdict)
>>>

>>> testdict = {'name': 'Neil', 'age': -12}
>>> schema.validate(testdict)
Traceback (most recent call last):
    ...
ValueError: 'age' too small: expected >= 0, but was -12
>>>

>>> testdict = {'name': 'Neil', 'age': '55'}
>>> schema.validate(testdict)
Traceback (most recent call last):
    ...
TypeError: unexpected type for 'age': expected <class 'int'>, but was <class 'str'>
>>>

Nested schemadict

>>> schema_city = schemadict({
...     'name': {
...         'type': str
...     },
...     'population': {
...         'type': int,
...         '>=': 0,
...     },
... })
>>>
>>> schema_country = schemadict({
...     'name': {'type': str},
...     'cities': {
...         'type': list,
...         'item_type': dict,
...         'item_schema': schema_city,
...     },
... })
>>>
>>> test_country = {
...     'name': 'Neverland',
...     'cities': [
...         {'name': 'Faketown', 'population': 3},
...         {'name': 'Evergreen', 'population': True},
...     ],
... }
>>>
>>> schema_country.validate(test_country)
Traceback (most recent call last):
    ...
TypeError: unexpected type for 'population': expected <class 'int'>, but was <class 'bool'>
>>>

Custom validation functions

TODO

Full documentation: https://schemadict.readthedocs.io/

Features

Schemadicts supports

• Built-in support for Python’s primitive types

• Specification of required and optional keys

• Validation of nested schemas

Features currently in development

• Adding custom validator functions

• Metaschema validation

• Validation of subschemas in list or tuples

• Regex support for strings

• Lazy validation and summary of all errors

• Allow schema variations: schmea 1 OR schema 2

• Add support for validation of type number.Number

Installation

Schemadict is available on PyPI and may simply be installed with

pip install schemadict

Idea

Schemadict is loosely inspired by JSON schema and jsonschema, a JSON schema validator for Python.

License

License: Apache-2.0