xpresso 0.30.0

A developer centric, performant Python web framework

Xpresso is an ASGI web framework built on top of Starlette, Pydantic and di, with heavy inspiration from FastAPI.

Some of the standout features are:

• ASGI support for high performance (within the context of Python web frameworks)
• OpenAPI documentation generation
• Automatic parsing and validation of request bodies and parameters, with hooks for custom extractors
• Full support for OpenAPI parameter serialization
• Highly typed and tested codebase with great IDE support
• A powerful dependency injection system, backed by di

Requirements

Python 3.7+

Installation

pip install xpresso

You'll also want to install an ASGI server, such as Uvicorn.

pip install uvicorn

Example

Create a file named example.py:

from pydantic import BaseModel
from xpresso import App, Path, FromPath, FromQuery

class Item(BaseModel):
    item_id: int
    name: str

async def read_item(item_id: FromPath[int], name: FromQuery[str]) -> Item:
    return Item(item_id=item_id, name=name)

app = App(
    routes=[
        Path(
            "/items/{item_id}",
            get=read_item,
        )
    ]
)

Run the application:

uvicorn example:app

Navigate to http://127.0.0.1:8000/items/123?name=foobarbaz in your browser. You will get the following JSON response:

{"item_id":123,"name":"foobarbaz"}

Now navigate to http://127.0.0.1:8000/docs to poke around the interactive Swagger UI documentation:

For more examples, tutorials and reference materials, see our documentation.

Inspiration and relationship to other frameworks

Xpresso is mainly inspired by FastAPI. FastAPI pioneered several ideas that are core to Xpresso's approach:

• Leverage Pydantic for JSON parsing, validation and schema generation.
• Leverage Starlette for routing and other low level web framework functionality.
• Provide a simple but powerful dependency injection system.
• Use that dependency injection system to provide extraction of request bodies, forms, query parameters, etc.

Xpresso takes these ideas and refines them by:

• Decoupling the dependency injection system from the request/response cycle, leading to an overall much more flexible and powerful dependency injection system, packaged up as the standalone di library.
• Decoupling the framework from Pydantic by using Annotated (PEP 593) instead of default values (param: FromQuery[str] instead of param: str = Query(...)).
• Middleware on Routers so that you can use generic ASGI middleware in a routing-aware manner (for example, installing profiling middleware on only some paths without using regex matching).
• Support for lifespans on any Router or mounted App (this silently fails in FastAPI and Starlette)
• dependency injection into the application lifespan and support for multiple dependency scopes.
• Formalizing the framework for extracting parameters and bodies from requests into the Binder API so that 3rd party extensions can do anything the framework does.
• Support for customizing parameter and form serialization.
• Better performance by implementing dependency resolution in Rust, executing dependencies concurrently and controlling threading of sync dependencies on a per-dependency basis.

Current state

This project is under active development. It should not be considered "stable" or ready to be used in production. It is however ready for experimentation and learning!

What is implemented and mostly stable?

1. Extraction and OpenAPI documentation of parameters (query, headers, etc.) and request bodies (including multipart requests).
2. Parameter serialization.
3. Routing, including applications, routers and routes.
4. Dependency injection and testing utilities (dependency overrides).

Most of this APIs will be generally stable going forward, although some minor aspects like argument names will probably change at some point.

What is not implemented or unstable?

1. Low-level API for binders (stuff in xpresso.binders): this is public, but should be considered experimental and is likely to change. The high level APIs (FromPath[str] and Annotated[str, PathParam(...)]) are likely to be stable.
2. Security dependencies and OpenAPI integration. This part used to exist, but needed some work. It is planned for the future, but we need to think about the scope of these features and the API.
3. Specification of reponse models / metadata. This currently works, but there is no deep merging with the automatic inference of models, and the API is overal quite klunky. Expect this to be completely re-writing.

See this release on GitHub: v0.30.0