1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267
|
<h1 style="text-align: center;">
Djantic
</h1>
<p style="text-align: center;">
<em><a href="https://pydantic-docs.helpmanual.io/">Pydantic</a> model support for <a href="https://www.djangoproject.com/"> Django</a></em>
</p>
---
**Documentation**: https://jordaneremieff.github.io/djantic/
---
Djantic is a library that provides a configurable utility class for automatically creating a Pydantic model instance for any Django model class. It is intended to support all of the underlying Pydantic model functionality such as JSON schema generation and introduces custom behaviour for exporting Django model instance data.
## Quickstart
Install using pip:
```shell
pip install djantic
```
Create a model schema:
```python
from users.models import User
from djantic import ModelSchema
class UserSchema(ModelSchema):
class Config:
model = User
print(UserSchema.schema())
```
**Output:**
```python
{
"title": "UserSchema",
"description": "A user of the application.",
"type": "object",
"properties": {
"profile": {"title": "Profile", "description": "None", "type": "integer"},
"id": {"title": "Id", "description": "id", "type": "integer"},
"first_name": {
"title": "First Name",
"description": "first_name",
"maxLength": 50,
"type": "string",
},
"last_name": {
"title": "Last Name",
"description": "last_name",
"maxLength": 50,
"type": "string",
},
"email": {
"title": "Email",
"description": "email",
"maxLength": 254,
"type": "string",
},
"created_at": {
"title": "Created At",
"description": "created_at",
"type": "string",
"format": "date-time",
},
"updated_at": {
"title": "Updated At",
"description": "updated_at",
"type": "string",
"format": "date-time",
},
},
"required": ["first_name", "email", "created_at", "updated_at"],
}
```
See https://pydantic-docs.helpmanual.io/usage/models/ for more.
### Loading and exporting model instances
Use the `from_orm` method on the model schema to load a Django model instance for <a href="https://pydantic-docs.helpmanual.io/usage/exporting_models/">export</a>:
```python
user = User.objects.create(
first_name="Jordan",
last_name="Eremieff",
email="jordan@eremieff.com"
)
user_schema = UserSchema.from_orm(user)
print(user_schema.json(indent=2))
```
**Output:**
```json
{
"profile": null,
"id": 1,
"first_name": "Jordan",
"last_name": "Eremieff",
"email": "jordan@eremieff.com",
"created_at": "2020-08-15T16:50:30.606345+00:00",
"updated_at": "2020-08-15T16:50:30.606452+00:00"
}
```
### Using multiple level relations
Djantic supports multiple level relations. This includes foreign keys, many-to-many, and one-to-one relationships.
Consider the following example Django model and Djantic model schema definitions for a number of related database records:
```python
# models.py
from django.db import models
class OrderUser(models.Model):
email = models.EmailField(unique=True)
class OrderUserProfile(models.Model):
address = models.CharField(max_length=255)
user = models.OneToOneField(OrderUser, on_delete=models.CASCADE, related_name='profile')
class Order(models.Model):
total_price = models.DecimalField(max_digits=8, decimal_places=5, default=0)
user = models.ForeignKey(
OrderUser, on_delete=models.CASCADE, related_name="orders"
)
class OrderItem(models.Model):
price = models.DecimalField(max_digits=8, decimal_places=5, default=0)
quantity = models.IntegerField(default=0)
order = models.ForeignKey(
Order, on_delete=models.CASCADE, related_name="items"
)
class OrderItemDetail(models.Model):
name = models.CharField(max_length=30)
order_item = models.ForeignKey(
OrderItem, on_delete=models.CASCADE, related_name="details"
)
```
```python
# schemas.py
from djantic import ModelSchema
from orders.models import OrderItemDetail, OrderItem, Order, OrderUserProfile
class OrderItemDetailSchema(ModelSchema):
class Config:
model = OrderItemDetail
class OrderItemSchema(ModelSchema):
details: List[OrderItemDetailSchema]
class Config:
model = OrderItem
class OrderSchema(ModelSchema):
items: List[OrderItemSchema]
class Config:
model = Order
class OrderUserProfileSchema(ModelSchema):
class Config:
model = OrderUserProfile
class OrderUserSchema(ModelSchema):
orders: List[OrderSchema]
profile: OrderUserProfileSchema
```
Now let's assume you're interested in exporting the order and profile information for a particular user into a JSON format that contains the details accross all of the related item objects:
```python
user = OrderUser.objects.first()
print(OrderUserSchema.from_orm(user).json(ident=4))
```
**Output:**
```json
{
"profile": {
"id": 1,
"address": "",
"user": 1
},
"orders": [
{
"items": [
{
"details": [
{
"id": 1,
"name": "",
"order_item": 1
}
],
"id": 1,
"price": 0.0,
"quantity": 0,
"order": 1
}
],
"id": 1,
"total_price": 0.0,
"user": 1
}
],
"id": 1,
"email": ""
}
```
The model schema definitions are composable and support customization of the output according to the auto-generated fields and any additional annotations.
### Including and excluding fields
The fields exposed in the model instance may be configured using two options: `include` and `exclude`. These represent iterables that should contain a list of field name strings. Only one of these options may be set at the same time, and if neither are set then the default behaviour is to include all of the fields from the Django model.
For example, to include all of the fields from a user model <i>except</i> a field named `email_address`, you would use the `exclude` option:
```python
class UserSchema(ModelSchema):
class Config:
exclude = ["email_address"]
```
In addition to this, you may also limit the fields to <i>only</i> include annotations from the model schema class by setting the `include` option to a special string value: `"__annotations__"`.
```python
class ProfileSchema(ModelSchema):
website: str
class Config:
model = Profile
include = "__annotations__"
assert ProfileSchema.schema() == {
"title": "ProfileSchema",
"description": "A user's profile.",
"type": "object",
"properties": {
"website": {
"title": "Website",
"type": "string"
}
},
"required": [
"website"
]
}
```
|