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tank-34on [dead]

No schema files. No resolvers. No boilerplate.

Just decorators and Python. Your SQLModel classes become GraphQL APIs instantly.

Plus: expose your GraphQL via MCP to AI assistants (Claude, GPT, etc.) with zero extra code.

tank-34on FastAPI Voyager's new feature: application levle ER Diagram

repo: https://github.com/allmonday/fastapi-voyager

tank-34on FastAPI Voyager's new feature: application levle ER Diagram

declare the relationship:

class Story(BaseModel, BaseEntity):

    __pydantic_resolve_relationships__ = [
        Relationship( field='id', target_kls=list[task_schema.Task], loader=task_loader.story_to_task_loader),
        Relationship( field='owner_id', target_kls=user_schema.User, loader=user_loader.user_batch_loader)
    ]

    id: int
    name: str
    owner_id: int
    sprint_id: int

    model_config = ConfigDict(from_attributes=True)

and consume it

class Story1(DefineSubset):

    __subset__ = (BaseStory, ('id', 'name', 'owner_id'))

    tasks: Annotated[list[Task1], LoadBy('id')] = []
    assignee: Annotated[Optional[BaseUser], LoadBy('owner_id')] = None

    related_users: list[BaseUser] = []
    def post_related_users(self, collector=Collector(alias='related_users')):
        return collector.values()

tank-34on [dead]

In the new version, an ER model at the application layer was designed to better describe the business model and manage the DataLoader. Developers can focus more on describing the relationships between data without worrying prematurely about databases or other query details.

tank-34on [dead]

Clean Architecture Practice with Pydantic-Resolve and FastAPI-Voyager

tank-34on Pydantic-resolve: A solid tool for building graph-like data

A solid tool for building fixed graph-like data.

Easily construct complex business data by defining ER diagrams, combining data, and applying various data adjustment methods

Minimal cognitive load

Extremely developer-friendly for those with GraphQL experience, helping improve the code quality and maintainability of API integrations

When combined with fastapi-voyager, it allows visualizing the constructed code graphically

tank-34on FastAPI-Voyager: visualization tool now support ER diagram

toggle the 'ER diagram' and show the full picture in graph

application level ER diagram can provide much more information for business entities and hide unnecesary middle tables.

definition: https://github.com/allmonday/composition-oriented-developmen...

fastapi-voyager itself is also improved a lot for better experiences.

tank-34on Some new features updated in FastAPI-Voyager

https://github.com/allmonday/fastapi-voyager

Visualize your FastAPI endpoints, and explore them interactively.

- better search experience - better graph interaction - persistent page in query string

tank-34on Visualize FastAPI endpoints with FastAPI-Voyager

to better describe the relationship, it borrows the concept 'subset' from pydantic-resolve, which act like pick several fields from original class but you can still reference to it.

@subset(User) class PickedUser: ....

tank-34on Visualize FastAPI endpoints with FastAPI-Voyager

you are right, in fact the most valuable part in our backend is 'business mode/logic', with voyager we can have a new choice to better understand them.

tank-34on Visualize FastAPI endpoints with FastAPI-Voyager

the return value in resolve/post method will be automatically validated by the pydantic class defined in field annotation.

tank-34on Visualize FastAPI endpoints with FastAPI-Voyager

it's not bound with pydantic-resolve, for vanilla fastapi user if the business model are well designed and composed, it can benefited from this visualization approach too.

the goal is to make the dependencies clear for developers, and figure out the potential impacts from one node to others.

pydantic-resolve is just another my project to make the process of data composition close to ER model and get rid of glue codes like 'for loops'.

tank-34on Visualize FastAPI endpoints with FastAPI-Voyager

https://github.com/allmonday/composition-oriented-developmen...

those are clusters based on modules, you can swith off by toggle 'show module cluster'

tank-34on Visualize FastAPI endpoints with FastAPI-Voyager

if you double click route / pydantic class and click 'view in vscode', it will lead you to the file in github

and in local env, you can 'really' open it in vscode.

tank-34on Visualize FastAPI endpoints with FastAPI-Voyager

thanks for suggestion. this project is still in early stage, I've listed some ux related Todos but not yet finished. TBH, i dont expected it to be noticed in hacker's news LOL

tank-34on Visualize FastAPI endpoints with FastAPI-Voyager

in swagger, from the definition of schema you are not able to easily figure out the related class, the name is marked as <object> or array<object>

in voyager their relationships are visualized and very close to the source code.

tank-34on Visualize FastAPI endpoints with FastAPI-Voyager

heere is the repo: https://github.com/allmonday/fastapi-voyager

tank-34on Visualize FastAPI endpoints with FastAPI-Voyager

scroll to zoom in/out

pick tag/routes at left panel, and see subgraphs

double click to see field table and source code, click link to see source code in github

click focus to hide other nodes.

...

tank-34on Visualize FastAPI endpoints with FastAPI-Voyager

this project is inspired by https://apis.guru/graphql-voyager/, which visualize the entity relationships based on graphviz and add fancy ui effects.

fastapi-voyager, from left to right, is tag, routes(apis) and response_models, it indicates the internal relationship between routes, which can help developers/PO easily figure out the data structure.