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-0.1.48.tar.gz (11.1 kB view details)

Uploaded Source

Built Distribution

File details

Details for the file pydantic_handler_converter-0.1.48.tar.gz.

File metadata

  • Download URL: pydantic_handler_converter-0.1.48.tar.gz
  • Upload date:
  • Size: 11.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.6.1 CPython/3.10.6 Linux/5.15.0-1047-azure

File hashes

Hashes for pydantic_handler_converter-0.1.48.tar.gz
Algorithm Hash digest
SHA256 b5448aa5f246805c482fa4c8ba02cab55c41e156488e93fa40e0e02f2346ddf2
MD5 70ced46e4272890f3b310426de2937f8
BLAKE2b-256 0cdbebea412914255b21ee0a0edc33c6b2bc6be00dc5c532a0039aae15060a3d

See more details on using hashes here.

File details

Details for the file pydantic_handler_converter-0.1.48-py3-none-any.whl.

File metadata

File hashes

Hashes for pydantic_handler_converter-0.1.48-py3-none-any.whl
Algorithm Hash digest
SHA256 0b3675ff6f975d61a3e845ded332717d986254f0c289efbe1c1693a86d2990ef
MD5 545a35a7abe913c77133256b2d19faa6
BLAKE2b-256 3fc6ec07fb83b27ac959c72d56c21657e1d31443f9b03345d07df993f7f94ab9

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