python-squall 0.3.0

Squall ASGI REST framework

Squall, API framework which looks ahead

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Navigation

• About
  • Motivation
  • Performance
  • ASAP and batching
• Usage
  • Install
  • Quick start
  • OpenAPI
  • Routing
  • Compression
  • HEAD parameters
    • Path
    • Query
    • Header
    • Cookie
    • Parameters configuration
    • Parameters validation
  • Body processing
    • Response serialization
    • Response deserialization serialization
  • Opentelemetry usage
• Acknowledgments
• Roadmap
• Dependencies
• Versioning
• License

About

Motivation

Initially, it was a library for ASGI frameworks for publishing RBAC routing information to the MTAG API-Gateway. After some research, we have decided that this is the most expensive way and made a decision to create a framework which will deliver the best experience in the development of applications behind the API-Gateway.

Eventually, Squall is a part of the e2e solution for modern high-performance stacks.

Performance

1Kb no schema

30Kb no schema

1Kb schema

30Kb schema

More results and benchmark methodology here

ASAP and batching

Squall following own MTAG/Squall ASAP pattern. The idea of the ASAP pattern is pretty simple to understand. If you have all necessaries to do something you can do in the next steps, you should do it now.

Be careful. This pattern is mind-changing.

The batch operation is always better than a lot of small ones.

Usage

Install

pip3 install python-squall

You also need some ASGI server. Let's install Uvicorn, the most popular one.

pip3 install uvicorn

Quick start

Create example.py with the following content

from typing import List, Optional
from dataclasses import dataclass
from squall import Squall

app = Squall()


@dataclass
class Item:
    name: str
    value: Optional[int] = None


@app.get("/get", response_model=List[Item])
async def handle_get() -> List[Item]:
    return [
        Item(name="null_value"),
        Item(name="int_value", value=8)
    ]


@app.post("/post", response_model=Item)
async def handle_post(data: Item) -> Item:
    return data

And run it

uvicorn example:app

Now, we are able to surf our GET endpoint on: http://127.0.0.1:8000/get

And let's play with curl on POST endpoint

# curl -X 'POST' 'http://127.0.0.1:8000/post' -H 'Content-Type: application/json' -d '{"name": "string", "value": 234}'
{
  "name": "string",
  "value": 234
}

Type checking and validation is done by apischema for both, Request and Response.

# curl -X 'POST' 'http://127.0.0.1:8000/post' -H 'Content-Type: application/json' -d '{"name": "string", "value": "not_an_int"}'
{
  "details": [
    {
      "loc": [
        "value"
      ],
      "msg": "expected type integer, found string"
    },
    {
      "loc": [
        "value"
      ],
      "msg": "expected type null, found string"
    }
  ]
}

OpenAPI generation

OpenAPI for your app generates automatically based on route parameters and schema you have defined.

There are support for ReDoc and Swagger out of the box. You can reach it locally once your application started:

• Swagger: http://127.0.0.1:8000/doc
• ReDoc: http://127.0.0.1:8000/redoc

Routing

Squall provides familiar decorators for any method route registration on both, application itself and on nested routers.

Method	app	router *
GET	@app.get	@router.get
PUT	@app.put	@router.put
POST	@app.post	@router.post
DELETE	@app.delete	@router.delete
OPTIONS	@app.options	@router.options
HEAD	@app.head	@router.head
PATCH	@app.patch	@router.patch
TRACE	@app.trace	@router.trace

* router = squall.Router()

Nested routers supports prefixes and further nesting.

from squall import Router, Squall

animals_router = Router(prefix="/animals")


@animals_router.get("/")
async def get_animals():
    return []


@animals_router.get("/cat")
async def get_cat():
    return []

dogs_router = Router(prefix="/dogs")


@dogs_router.get("/list")
async def get_all_dogs():
    return []


animals_router.include_router(dogs_router)

app = Squall()
app.include_router(animals_router)

Will give us

Nested routing is usually used for splitting applications into files and achieving better project structure.

Compression

Squall provides built-in blazing-fast compression based on Intel® Intelligent Storage Acceleration Library (Intel® ISA-L) using awesome Python's isal library as binding.

Compared to Python's builtins ISA-L can deliver up to 20 times faster compression. Such in-app performance does game-changing opportunities for the entire system set up,

In order to enable compression you have to path compression config to Squall app

from squall import Squall
from squall.compression import Compression

app = Squall(compression=Compression())

For more details check compression settings

Accept-Encoding header also required. Squall supports gzip, deflate options for it.

HEAD parameters

There are four kinds of parameters that developers can get from HTTP headers. Squall offers an interface for their conversion and validation.

Path

"Path" is a dynamic value specified by developers in the route URL.

from squall import Squall, Path

app = Squall()


@app.get("/company/{company_id}/employee/{employee_id}")
async def get_company_employee(company_id: int, employee_id = Path()):
    return {
        "company_id": company_id,
        "employee_id": employee_id,
    }

Squall determinate affiliation of the variable with path by any of following ways:

• Default parameter value is Path instance
• Parameter default name equal to route pattern

Specifics:

• Allows only the following annotations: str, bytes, int, float
• Union, Optional, not allowed. Because a path can't have an undefined value. Also, parameters must have a strong conversion contract.
• If an annotation isn't set parameter will arrive as str

Shares common configuration contract for head entities. Please, read more here.

Query

"Query" is a way get query string parameters value(s).

from typing import List
from squall import Squall, Query

app = Squall()


@app.get("/")
async def get_company_employee(company_id: int = Query(), employee_ids: List[int] = Query()):
    return {
        "company_id": company_id,
        "employee_ids": employee_ids,
    }

Specifics:

• Allowed annotations: str, bytes, int, float, Optional, List
• If it is a getting of multiple values for the same key, at the moment, value validation cannot be applied.

Header

"Header" is a way to get header value(s). Shares common behavior with Query

from typing import List
from squall import Squall, Header

app = Squall()


@app.get("/")
async def get_company_employee(company_id: int = Header(), employee_ids: List[int] = Header()):
    return {
        "company_id": company_id,
        "employee_ids": employee_ids,
    }

Specifics:

• Allowed annotations: str, bytes, int, float, Optional, List
• If it is a getting of multiple values for the same key, at the moment, value validation cannot be applied.

Cookie

"Cookie" is a way get cookie value.

from typing import List
from squall import Squall, Cookie

app = Squall()


@app.get("/")
async def get_company_employee(user_id: int = Cookie()):
    return {
        "user_id": user_id,
    }

Specifics:

• Allowed annotations: str, bytes, int, float, Optional

Parameters configuration

All head fields share common configuration pattern which include the following list of parameters:

• default, default value to assign
• alias, replaces source key where to get the value from
• title, title for schema specification
• description, description for schema specification
• valid, instance of validator, squall.Num or squall.Str
• example, example for schema specification
• examples, multiple examples for schema specification
• deprecated, mark parameter as deprecated, will appear in specification

Parameters validation

At the moment, Squall provides following validators that developer can apply to HEAD parameters values:

• squall.Num - int, float validator. Following conditions are supported: gt, ge, lt, le
• squall.Str - str, bytes validator. Following conditions are supported: min_len, max_len

Please, take a look at the related test suite

Body processing

Schema defined using dataclasses behind the scene validated by awesome apischema. Please follow their documentation for build validation.

There are things strictly important to remember:

Response serialization

If response_model is equal to the handler return annotation Squall expects exactly these types and will not perform mutations to dataclasses, etc. Type checking will be done during serialization.

Handy to save some resources working with ORM. For instance SQL Alchemy dataclass mapping

from typing import List, Optional
from dataclasses import dataclass
from squall import Squall

app = Squall()


@dataclass
class Item:
    name: str
    value: Optional[int] = None


@app.get("/get", response_model=List[Item])
async def handle_get() -> List[Item]:
    return [
        Item(name="null_value"),
        Item(name="int_value", value=8)
    ]

Response deserialization-serialization

The following example demonstrates a different scenario. Where response expects to receive from handler Python primitives and Sequences/Maps only. With this scenario, all response data will be processed through the filling of the relevant model.

from typing import List, Optional
from dataclasses import dataclass
from squall import Squall

app = Squall()


@dataclass
class Item:
    name: str
    value: Optional[int] = None


@app.get("/get", response_model=List[Item])
async def handle_get():
    return [
        {"name": "null_value"},
        {"name": "int_value", "value": 8}
    ]

OpenTelemetry usage

To trace internal actions next packages must be installed:

pip install opentelemetry-api opentelemetry-sdk

Having installed libs initial application and OpenTelemetry configuration should be performed as shown bellow:

from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import (
    BatchSpanProcessor,
    ConsoleSpanExporter,
)
from squall import Squall

trace.set_tracer_provider(TracerProvider())
trace.get_tracer_provider().add_span_processor(BatchSpanProcessor(ConsoleSpanExporter()))

app = Squall(trace_internals=True)

@app.get("/get")
async def handle_get() -> dict:
    return {"Hello": "World"}

For detailed config have a look at Opentelemetry docs

Acknowledgments

Many thanks to @tiangolo and the entire FastAPI community. Squall development started from hard-forking this superior developers-friendly framework.

Roadmap

0.1.x - Initial project publication

0.2.x - Intel® ISA-L based compression

0.3.x - Observability based on OpenTelemetry with switchable Squall internals tracing.

0.4.x - Dependency Injector integration

0.5.x - YARL and aio-MultiDict integration

0.6.x - Fine-tuning for __slots__, LEGB, attribute access.

0.7.x - MTAG integration

0.8.x - Starts new SGI initiative

Dependencies

isal

License: MIT

Faster zlib and gzip compatible compression and decompression by providing python bindings for the ISA-L library.

apischema

License: MIT

JSON (de)serialization, GraphQL and JSON schema generation using Python typing.

apischema makes your life easier when dealing with API data.

orjson

License: MIT or Apache 2.0

orjson is a fast, correct JSON library for Python. It benchmarks as the fastest Python library for JSON and is more correct than the standard json library or other third-party libraries. It serializes dataclass, datetime, numpy, and UUID instances natively.

Starlette

License: BSD 3

Starlette is a lightweight ASGI framework/toolkit, which is ideal for building high performance async services.

Versioning

Squall follows the next versioning contract:

AA.BB.CC

• AA - Major changes, backward compatibility breaks
• BB - Minor changes, new features
• CC - Patch, bug fixes

License

MIT