Metadata-Version: 1.1
Name: pyjo
Version: 2.0.0
Summary: Python JSON Objects
Home-page: https://github.com/marcopaz/pyjo
Author: Marco Pazzaglia
Author-email: marco@pazzaglia.me
License: UNKNOWN
Download-URL: https://github.com/marcopaz/pyjo/archive/2.0.0.tar.gz
Description-Content-Type: UNKNOWN
Description: [![Build Status](https://travis-ci.org/marcopaz/pyjo.svg?branch=master)](https://travis-ci.org/marcopaz/pyjo)
        
        # pyjo
        
        > Python JSON Objects
        
        Easily specify and (de)serialize data models in Python.
        
        ## Install
        
        ```
        pip install pyjo
        ```
        
        ## How to use
        
        First you need to create a specification of your models and attributes by using the `Model` and the `Field` classes:
        
        ```python
        from pyjo import Model, Field, RangeField, EnumField
        
        class Gender(Enum):
            female = 0
            male = 1
        
        class Address(Model):
            city = Field(type=str)
            postal_code = Field(type=int)
            address = Field()
        
        class User(Model):
            name = Field(type=str, repr=True, required=True)
            age = RangeField(min=18, max=120)
            #  equivalent to: Field(type=int, validator=lambda x: 18 <= x <= 120)
            gender = EnumField(enum=Gender)
            address = Field(type=Address)
        ```
        
        By default any field is considered optional unless specified with `required` attribute. Every  and its presence will be checked during initialization.
        
        ```python
        u = User()
        # ...
        # pyjo.exceptions.RequiredField: Field 'name' is required
        ```
        
        ```python
        User(name='john', age=18, address=Address(city='NYC'))
        # <User(name=john)>
        ```
        
        When the `type` argument is provided, the type of the value of assigned to a field will be checked during initialization and assignment:
        
        ```python
        User(name=123)
        # ...
        # pyjo.exceptions.InvalidType: The value of the field 'name' is not of type str, given 123
        ```
        
        ```python
        u.address.city = 1
        # ...
        # pyjo.exceptions.InvalidType: The value of the field 'city' is not of type str, given 1
        ```
        
        In order to serialize a model you need to call `to_dict`:
        
        ```python
        u = User(name='john', age=18, address=Address(city='NYC'))
        
        print(u.to_dict())
        # {
        #     "name": "john",
        #     "age": 18,
        #     "address": {
        #         "city": "NYC"
        #     }
        # }
        ```
        
        To create a model starting from its python dictionary representation, use `from_dict`:
        
        ```python
        u = User.from_dict({
                "name": "john",
                "gender": "male",
                "age": 18,
                "address": {
                    "city": "NYC"
                }
            })
        
        print(u)
        # <User(name=john)>
        
        print(u.gender)
        # Gender.male
        
        print(u.address.city)
        # NYC
        ```
        Note that `from_dict` will also recreate all the nested pyjo objects.
        
        
        # API Documentation
        
        ## Field
        The `Field` object has several _optional_ arguments:
        
        * `type` specifies the type of the field. If specified, the type will be checked during initialization and assignment
        * `default` specifies the default value for the field. The value of a default can be a function and it will be computed and assigned during the initialization of the object
        * `required` boolean flag to indicate if the field must be specified and can't be `None` (`False` by default)
        * `repr` boolean flag to indicate if the field/value should be shown in the Python representation of the object, when printed (`False` by default)
        * `to_dict`, `from_dict` (functions) to add ad-hoc serialization/deserialization for the field
        
        ## Model
        
        * `to_dict()`, `from_dict()` serialize/deserialize to/from python dictionaries
        * `to_json()`, `from_json()` shortcuts for `json.dumps(model.to_dict())` and `Model.from_dict(json.loads(<dict>))`
        
        ## Field subclasses
        
        You can easily create subclasses of `Field` to handle specific types of objects. Several of them are already integrated in pyjo and more are coming (feel free to create a PR to add more):
        
        * `ListField` for fields containing a list of elements
        * `RegexField` for fields containing a string that matches a given regex
        * `RangeField` for fields containing a int with optional minimum/maximum value
        * `DatetimeField` for fields containing a UTC datetime
        
        # Extensions
        
        * [pyjo_mongo](https://github.com/marcopaz/pyjo_mongo) easily interact with MongoDB documents, a lightweight replacement of the `mongoengine` library
        
Platform: UNKNOWN
