An easy-to-use and powerful RPC framework. Base WSGI & ASGI.
Project description
rpc.py
An easy-to-use and powerful RPC framework. Base WSGI & ASGI.
Based on WSGI/ASGI, you can deploy the rpc.py server to any server and use http2 to get better performance.
Install
Install from PyPi:
pip install rpc.py
Install from github:
pip install git+https://github.com/abersheeran/rpc.py@setup.py
Usage
Server side:
Use ASGI
mode to register async def
...
import uvicorn
from rpcpy import RPC
app = RPC(mode="ASGI")
@app.register
async def none() -> None:
return
@app.register
async def sayhi(name: str) -> str:
return f"hi {name}"
@app.register
async def yield_data(max_num: int):
for i in range(max_num):
yield i
if __name__ == "__main__":
uvicorn.run(app, interface="asgi3", port=65432)
OR
Use WSGI
mode to register def
...
import uvicorn
from rpcpy import RPC
app = RPC()
@app.register
def none() -> None:
return
@app.register
def sayhi(name: str) -> str:
return f"hi {name}"
@app.register
def yield_data(max_num: int):
for i in range(max_num):
yield i
if __name__ == "__main__":
uvicorn.run(app, interface="wsgi", port=65432)
Client side:
Notice: Regardless of whether the server uses the WSGI mode or the ASGI mode, the client can freely use the asynchronous or synchronous mode.
Use httpx.Client()
mode to register def
...
import httpx
from rpcpy.client import Client
app = Client(httpx.Client(), base_url="http://127.0.0.1:65432/")
@app.remote_call
def none() -> None:
...
@app.remote_call
def sayhi(name: str) -> str:
...
@app.remote_call
def yield_data(max_num: int):
yield
OR
Use httpx.AsyncClient()
mode to register async def
...
import httpx
from rpcpy.client import Client
app = Client(httpx.AsyncClient(), base_url="http://127.0.0.1:65432/")
@app.remote_call
async def none() -> None:
...
@app.remote_call
async def sayhi(name: str) -> str:
...
@app.remote_call
async def yield_data(max_num: int):
yield
Sub-route
If you need to deploy the rpc.py server under example.com/sub-route/*
, you need to set RPC(prefix="/sub-route/")
and modify the Client(base_path=https://example.com/sub-route/)
.
Serialization of results
Currently supports two serializers, JSON and Pickle. JSON is used by default.
from rpcpy.serializers import JSONSerializer, PickleSerializer
RPC(serializer=JSONSerializer())
# or
RPC(serializer=PickleSerializer())
Type hint and OpenAPI Doc
Thanks to the great work of pydantic, which makes rpc.py allow you to use type annotation to annotate the types of function parameters and response values, and perform type verification and JSON serialization . At the same time, it is allowed to generate openapi documents for human reading.
OpenAPI Documents
If you want to open the OpenAPI document, you need to initialize RPC
like this RPC(openapi={"title": "TITLE", "description": "DESCRIPTION", "version": "v1"})
.
Then, visit the "{prefix}openapi-docs"
of RPC and you will be able to see the automatically generated OpenAPI documentation. (If you do not set the prefix
, the prefix
is "/"
)
Limitations
Currently, function parameters must be serializable by json
.
Project details
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