schemadict 0.0.3

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)
    ...
ValueError: 'age' too small: expected >= 0, but was -12
>>>

>>> testdict = {'name': 'Neil', 'age': '55'}
>>> schema.validate(testdict)
    ...
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)
    ...
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

• Adding custom validator functions

Features currently in progress

• Metaschema validation

• Validation of subschemas in list or tuples

• Regex support for strings

• Lazy validation and summary of all errors

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