filterify 0.0.1

filterify is a pydantic-based library to handle filters from the query params.

filterify is a pydantic-based library to handle filters from the query params.

---

Documentation: https://filterify.boardpack.org

Source Code: https://github.com/boardpack/filterify

---

Requirements

Python 3.8+

filterify has the next dependencies:

• Pydantic

Installation

$ pip install filterify

---> 100%

First steps

To start to work with filterify, you just need to have some Pydantic model you want to have as filters.

Let's define simple Address and Shipment models. Then just pass the Shipment model to the Filterify constructor and you will get a callable object to parse query params. By default, the parser returns a dictionary structure with the parsing results.

from pydantic import BaseModel
from filterify import Filterify


class Address(BaseModel):
    street: str
    city: str
    country: str


class Shipment(BaseModel):
    name: str
    sender: Address
    recipient: Address
    weight: float


model_filter = Filterify(Shipment)

print(model_filter('name=shoes&sender__country=US&recipient__country__ne=CA'))
# [
#     {
#         'field': [
#             'name'
#         ],
#         'value': 'shoes',
#         'operation': 'eq'
#     },
#     {
#         'field': [
#             'sender',
#             'country'
#         ],
#         'value': 'US',
#         'operation': 'eq'
#     },
#     {
#         'field': [
#             'recipient',
#             'country'
#         ],
#         'value': 'CA',
#         'operation': 'ne'
#     }
# ]

(This script is complete, it should run "as is")

Filterify supports nested models and uses __ as a delimiter for the nested models and operations. If you want to change it, pass the needed delimiter to the constructor as it's shown in the next example.

from pydantic import BaseModel
from filterify import Filterify


class Address(BaseModel):
    country: str


class Shipment(BaseModel):
    sender: Address


model_filter = Filterify(Shipment, delimiter='$')

print(model_filter('sender$country$ne=US'))
# [
#     {
#         'field': [
#             'sender',
#             'country'
#         ],
#         'value': 'US',
#         'operation': 'ne'
#     }
# ]

(This script is complete, it should run "as is")

Also, by default unknown fields are ignored, but you can change this behavior by passing False to the constructor parameter ignore_unknown_name.

from pydantic import BaseModel
from filterify import Filterify


class User(BaseModel):
    name: str


model_filter = Filterify(User, ignore_unknown_name=False)

print(model_filter('sender=US'))
# filterify.exceptions.UnknownFieldError: Filter name is not presented in the model: sender

(This script is complete, it should run "as is")

Ordering option

You can add an ordering field that accepts all model field names. Currently, it's used a django-like style when desc is passed as -field_name.

from pydantic import BaseModel
from filterify import Filterify


class Address(BaseModel):
    country: str


class Shipment(BaseModel):
    name: str
    sender: Address


model_filter = Filterify(Shipment, ordering=True)

print(model_filter('ordering=unknown_field'))
# raises standard pydantic ValidationError with the next message:
# unexpected value; permitted: 'name', '-name', 'sender__country', '-sender__country'

(This script is complete, it should run "as is")

If you want to change the accepted field name list, you can pass a list instead of the True value.

from pydantic import BaseModel
from filterify import Filterify


class Address(BaseModel):
    country: str


class Shipment(BaseModel):
    name: str
    sender: Address


model_filter = Filterify(Shipment, ordering=['name'])

print(model_filter('ordering=unknown_field'))
# raises standard pydantic ValidationError with the next message:
# unexpected value; permitted: 'name', '-name'

(This script is complete, it should run "as is")

Usage with FastAPI

Most validation work is done by pydantic, so filterify can be easily used with FastAPI. The internal validation model is wrapped by fastapi.Depends and exposed by the as_dependency method.

import uvicorn
from fastapi import FastAPI
from pydantic import BaseModel

from filterify import Filterify


class Address(BaseModel):
    street: str
    city: str
    country: str


class Shipment(BaseModel):
    name: str
    sender: Address
    recipient: Address
    weight: float
    length: float
    height: float


shipment_filter = Filterify(Shipment)


app = FastAPI()


@app.get('/shipments', dependencies=[shipment_filter.as_dependency()])
def shipments():
    return []


@app.get('/another_shipments')
def another_shipments(filters=shipment_filter.as_dependency()):
    print(filters)
    return []


if __name__ == '__main__':
    uvicorn.run(app)

(This script is complete, it should run "as is")

Acknowledgments

Special thanks to Sebastián Ramírez and his FastAPI project, some scripts and documentation structure and parts were used from there.

License

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