pyjo 1.1.0

Python JSON Objects

[](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, default=0)
address = Field(default=None)

class User(Model):
name = Field(type=str, repr=True)
age = RangeField(min=18, max=120)
# equivalent to: Field(type=int, validator=lambda x: 18 <= x <= 120)
gender = EnumField(enum=Gender, default=None)
address = Field(type=Address)
```

By default any field is considered required and its presence will be checked during initialization. To modify this behavior, pass a `default` argument to the `Field` constructor.

```python
u = User(name='john', age=18)
# ...
# pyjo.exceptions.RequiredField: Field 'address' is required
```

```python
User(name='john', age=18, address=Address(city='NYC'))
# <User(name=john)>
```

When specified by means of the `type` argument, also the argument types are checked during initialization and assignment:

```python
User(name=123, age=18, address=Address(city='NYC'))
# ...
# 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_json` (to obtain a JSON string) or `to_dict` (to obtain a JSON-serializable python object), depending on the format you want.

```python
u = User(name='john', age=18, address=Address(city='NYC'))

print(u.to_json(indent=4))
# {
# "name": "john",
# "gender": null,
# "age": 18,
# "address": {
# "address": null,
# "postal_code": 0,
# "city": "NYC"
# }
# }
```

To create a model starting from its JSON representation or python dictionary, use `from_json` and `from_dict`:

```python
uu = User.from_json("""
{
"name": "john",
"gender": "male",
"age": 18,
"address": {
"address": null,
"postal_code": 0,
"city": "NYC"
}
}
""")

print(uu)
# <User(name=john)>

print(uu.gender)
# Gender.male

print(uu.address.city)
# NYC
```
Note that the methods will also recreate all the nested objects, Python enums, etc.


## Documentation

### Field
The `Field` constructor 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. When specified (even if specified with value `None`) the field is considered optional and won't raise an exception if not present during initialization
* `repr` boolean flag to indicate if the field/value should be shown in the Python representation of the object, when printed
* `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(s))`


## Field subclasses

You can 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