GitLocker: The Coding Marketplace

Description:

pythonsquall 0.3.0

Squall, API framework which looks ahead

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