pyngo 1.1.0

Utils to help integrate pydantic into Django projects

Pyngo

Utils to help integrate pydantic into Django projects

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Install the project: pip install pyngo

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Features 🎉

• Using Pydantic to Build your Models in Django Project.
• Using OpenAPI utilities to build params from a basic model.
• using QueryDictModel to build Pydantic models from a QueryDict object.
• propagate any errors from Pydantic in Django Rest Framework.
• Tested in Python 3.6 and up.

Examples 📚

OpenAPI

• pyngo.openapi_params() can build params from a basic model

from pydantic import BaseModel
from pyngo import openapi_params

class Model(BaseModel):
   bingo: int

print(openapi_params(Model))

• pyngo.ParameterDict.required is set according to the type of the variable

from typing import Optional
from pydantic import BaseModel
from pyngo import openapi_params

class Model(BaseModel):
   required_param: int
   optional_param: Optional[int]

print(openapi_params(Model))

Other fields can be set through the field’s info:

from pydantic import BaseModel, Field
from pyngo import openapi_params

class WithDescription(BaseModel):
   described_param: str = Field(
      description="Hello World Use Me!"
   )

class InPath(BaseModel):
   path_param: str = Field(location="path")

class WithDeprecated(BaseModel):
   deprecated_field: bool = Field(deprecated=True)

class WithNoAllowEmpty(BaseModel):
   can_be_empty: bool = Field(allowEmptyValue=False)

print(openapi_params(WithDescription)[0]["description"])
print(openapi_params(InPath)[0]["in"])
print(openapi_params(WithDeprecated)[0]["deprecated"])
print(openapi_params(WithNoAllowEmpty)[0]["allowEmptyValue"])

Django

• pyngo.querydict_to_dict() and pyngo.QueryDictModel are conveniences for building a pydantic.BaseModel from a django.QueryDict.

from typing import List
from django.http import QueryDict
from pydantic import BaseModel
from pyngo import QueryDictModel, querydict_to_dict

class Model(BaseModel):
   single_param: int
   list_param: List[str]

class QueryModel(QueryDictModel):
   single_param: int
   list_param: List[str]

query_dict = QueryDict("single_param=20&list_param=Life")

print(Model.parse_obj(querydict_to_dict(query_dict, Model)))
print(QueryModel.parse_obj(query_dict))

Note: Don't forget to Setup the Django Project.

Django Rest Framework

• pyngo.drf_error_details() will propagate any errors from Pydantic.

from pydantic import BaseModel, ValidationError
from pyngo import drf_error_details

class Model(BaseModel):
   foo: int
   bar: str

data = {"foo": "Cat"}

try:
   Model.parse_obj(data)
except ValidationError as e:
   print(drf_error_details(e))

Errors descend into nested fields:

from typing import List
from pydantic import BaseModel, ValidationError
from pyngo import drf_error_details

class Framework(BaseModel):
   frm_id: int

class Language(BaseModel):
   framework: List[Framework]

data = {"Framework": [{"frm_id": "not_a_number"}, {}]}
expected_details = {
   "framework": {
      "0": {"frm_id": ["value is not a valid integer"]},
      "1": {"frm_id": ["field required"]},
   }
}

try:
   Framework.parse_obj(data)
except ValidationError as e:
   print(drf_error_details(e))

Development 🚧

You should create a virtual environment and activate it:

python -m venv venv/

source venv/bin/activate

And then install the development dependencies:

pip install -r requirements.dev.txt

Test the code 📚

For Building the tests i use pytest, you can run it using a pre-configured command:

make test

Format the code 💅

Execute the following command to apply pre-commit formatting:

make lint

License 🍻

This project is licensed under the terms of the MIT license.