1. Peter Fačka
  2. dict2colander

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dict2colander

Convert python dict (YAML, JSON) to colander schema.

Colander is library, which enables you to validate and convert YAML, JSON and HTML form data. Colander schema as it is could be defined only in Python declaratively for example like this:

import colander

class Person(colander.MappingSchema):
    name = colander.SchemaNode(colander.String())
    age = colander.SchemaNode(colander.Int(),
                              validator=colander.Range(0, 200))

    @colander.instantiate()
    class phones(colander.SequenceSchema):

        @colander.instantiate()
        class phone(colander.MappingSchema):
            location = colander.SchemaNode(colander.String(),
                                 validator=colander.OneOf(['home', 'work']))
            number = colander.SchemaNode(colander.String())

With dict2colander you can define the same colander schema in dictionary and convert it to colader.MappingSchema object.

Instalation

You can install dict2colander from Python Package Index like this:

pip install dict2colander

Usage

from dict2colander import dict2colander

schema_dict = {
    'type': 'Mapping',
    'name': 'person',
    'subnodes': [
        {'type': 'String', 'name': 'name'},

        {'type': 'Integer', 'name': 'age',
         'validators':
            {'Range': {'args': ('0', '200')}}},

        {'type': 'Sequence',
         'name': 'phones',
         'subnodes': [

             {'type': 'Mapping', 'name': 'phone',
              'subnodes': [

                  {'type': 'String', 'name': 'location',
                   'validators':
                     {'OneOf': {'args': (['home', 'work'],)}}},

                  {'type': 'String', 'name': 'number'}

              ]}]},
    ]
}

schema = dict2colander(schema_dict)
data = {
         'name': 'keith',
         'age': '20',
         'friends':[('1', 'jim'),('2', 'bob'), ('3', 'joe'), ('4', 'fred')],
         'phones':[{'location':'home', 'number':'555-1212'},
                   {'location':'work', 'number':'555-8989'},],
         }

serialized_data = schema.deserialize(data)
print serialized_data

Dict2colander is intended to make possible to read colander schemas from YAML or JSON format. So here is schema from previous example written in YAML:

---
name: person
type: Mapping

subnodes:
    - name: name
      type: String

    - name: age
      type: Integer
      validators:
        Range:
            args: ['0', '200']

    - name: phones
      type: Sequence
      subnodes: 
        - name: phone
          type: Mapping
          subnodes:
            - name: location
              type: String
              validators:
                OneOf:
                    args: [[home, work]]

            - name: number
              type: String

Note that Range validator has arguments defined as Strings not Integers although that field age is of type Integer.

Here are data to deserialize in YAML format from first example:

---
name: keith
age: 20
friends:
    - [1, jim]
    - [2, bob]
    - [3, joe]
    - [4, fred]

phones:
    - location: home
      number: 555-1212

    - location: work
      number: 555-8989

Here is example how YAML data are deserialized with schema defined in YAML document.

import yaml
import dict2colander

def deserialize(yaml_doc, yaml_schema):
    mapping_schema = dict2colander.dict2colander(yaml_schema)
    return mapping_schema.deserialize(yaml_doc)

f = open('doc.yaml')
doc = yaml.load(f)
f.close()

f = open('schema.yaml')
schema = yaml.load(f)
f.close()

dict_doc = deserialize(doc, schema)
print dict_doc

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