Skip to main content

A developer centric, performant Python web framework

Project description

Xpresso

Test Coverage Package version Supported Python versions

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:

Swagger UI

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:

See this release on GitHub: v0.4.3

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

xpresso-0.4.3.tar.gz (41.5 kB view details)

Uploaded Source

Built Distribution

xpresso-0.4.3-py3-none-any.whl (70.4 kB view details)

Uploaded Python 3

File details

Details for the file xpresso-0.4.3.tar.gz.

File metadata

  • Download URL: xpresso-0.4.3.tar.gz
  • Upload date:
  • Size: 41.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.12 CPython/3.10.1 Linux/5.11.0-1025-azure

File hashes

Hashes for xpresso-0.4.3.tar.gz
Algorithm Hash digest
SHA256 2139bb6f91431592e00261ace608b789e8c8accdc26ae31dcfff8cd45d4ea156
MD5 9febde35c80b603a1d217b8ad0136063
BLAKE2b-256 d8ca46bb395b78d3d40bd387d411b70fa6120d661b6639a6f324f7b395fb49fd

See more details on using hashes here.

File details

Details for the file xpresso-0.4.3-py3-none-any.whl.

File metadata

  • Download URL: xpresso-0.4.3-py3-none-any.whl
  • Upload date:
  • Size: 70.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.12 CPython/3.10.1 Linux/5.11.0-1025-azure

File hashes

Hashes for xpresso-0.4.3-py3-none-any.whl
Algorithm Hash digest
SHA256 e611622e187a5f7db28728a61692fef4ce8e84217600733252bbfad9d23f7e71
MD5 1d108fb95376fb0f7eda555ed6f8552b
BLAKE2b-256 a20c115f38958f716d3bf8917aa7531f206bac4320f78b48c0fdce6727cd1036

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