Skip to main content

This code simplifies the conversion of Pydantic schemas into Aiogram handler groups, making it easy to create form-filling handlers.

Project description

Pydantic-handler-converter

This code simplifies the conversion of Pydantic schemas into Aiogram handler groups, making it easy to create form-filling handlers.

Installation

    pip install pydantic_handler_converter

Usage:

>>> from enum import Enum
>>> from typing import Union
>>> from pydantic import BaseModel
>>> from pydantic_handler_converter import BasePydanticFormHandlers

# ----------------------------------------Simple datatypes schema--------------------------------------

>>> class PersonPydanticFormSchema(BaseModel):
...     name: str
...     age: int
...     height: float 
... 

>>> class PersonFormHanlders(BasePydanticFormHandlers[PersonPydanticFormSchema]):
...     pass
...
...
>>> dirs = dir(PersonFormHanlders)
>>> assert len(tuple(filter(lambda x: not x in dirs, ['name_view', 'age_view', 'height_view']))) == 0
>>> assert PersonFormHanlders(finish_call=None)

# ----------------------------------------Enum datatype schema-----------------------------------------

>>> class Mood(Enum):
...     HAPPY = "😄 Happy"
...     SAD = "😢 Sad"
...     EXCITED = "🤩 Excited"
...     RELAXED = "😌 Relaxed"
...
>>>
>>>
>>> class PersonMoodPydanticFormSchema(BaseModel):
...     name: str
...     current_mood: Mood
...
>>> class PersonMoodFormHanlders(BasePydanticFormHandlers[PersonMoodPydanticFormSchema]): 
...     pass
...
...
>>> dirs = dir(PersonMoodFormHanlders)
>>> assert len(tuple(filter(lambda x: not x in dirs, ['name_view', 'current_mood_view']))) == 0
>>> assert PersonMoodFormHanlders(finish_call=None)

# ----------------------------------------Complex schema-----------------------------------------------

>>> class Address(BaseModel):
...     street: str
...     city: str
...     postal_code: str
...
>>> class Person(BaseModel):
...      name: str
...      age: int
...      address: Address
...
...
>>> class PersonFormHanlders(BasePydanticFormHandlers[Person]): 
...     pass
...
...
>>> dirs = dir(PersonFormHanlders)
>>> assert len(tuple(filter(lambda x: not x in dirs, 
...     ['name_view', 'address_street_view', 'address_city_view', 'address_postal_code_view']
... ))) == 0
...
>>> assert PersonFormHanlders(finish_call=None)

# ------------------------------------Combined Enum datatype schema------------------------------------

>>> class HappyMood(Enum):
...     HAPPY = "😄 Happy"
...
>>> class SadMood(Enum):
...     SAD = "😢 Sad"
...
>>> class ExcitedMood(Enum):
...     EXCITED = "🤩 Excited"
...
>>> class RelaxedMood(Enum):
...     RELAXED = "😌 Relaxed"
...
>>>
>>> class PersonMoodPydanticFormSchema(BaseModel):
...     name: str
...     current_mood: Union[HappyMood, SadMood, ExcitedMood, RelaxedMood]
...     future_mood: HappyMood | SadMood | ExcitedMood | RelaxedMood
...
...
>>> class PersonMoodFormHanlders(BasePydanticFormHandlers[PersonMoodPydanticFormSchema]): 
...     pass
...
...
>>> dirs = dir(PersonMoodFormHanlders)
>>> assert len(tuple(filter(lambda x: not x in dirs, ['name_view', 'current_mood_view']))) == 0
>>> assert PersonMoodFormHanlders(finish_call=None)

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pydantic_handler_converter-0.1.108.tar.gz (14.3 kB view details)

Uploaded Source

Built Distribution

File details

Details for the file pydantic_handler_converter-0.1.108.tar.gz.

File metadata

File hashes

Hashes for pydantic_handler_converter-0.1.108.tar.gz
Algorithm Hash digest
SHA256 cb635b9b396cdd0f8a4ac5569bf2546eaa1d186c58a85af08d3e998e73ca8dc5
MD5 e41fa582b44663eec3735378819c9b72
BLAKE2b-256 35ee2214e99107d0a7b4e058228ac123cb9dc2cf3e88e0ea473fc54b445ca878

See more details on using hashes here.

File details

Details for the file pydantic_handler_converter-0.1.108-py3-none-any.whl.

File metadata

File hashes

Hashes for pydantic_handler_converter-0.1.108-py3-none-any.whl
Algorithm Hash digest
SHA256 abc4b81d4db28f79f61ed9dd94cefa4a89c1ff37963c1343c921639b24e9c643
MD5 b65b49948a6a0d4f8f6203c4e6271c40
BLAKE2b-256 60b728a6f554792174b410971a977c97f15f795a1ca3b7f653db4ba3b0e08234

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page