zeroapi 0.3.2

Zero is a RPC framework to build fast and high performance Python microservices

Zero is a RPC framework to build fast and high performance Python microservices

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Zero is actually a RPC like framework that passes message between client server like architecture. Also supports Pub-Sub.

Features:

• Zero provides faster communication (see benchmarks) between the microservices using zeromq under the hood.
• Zero uses messages for communication and traditional client-server or request-reply pattern is supported.
• Support for both Async and sync.
• The base server (ZeroServer) utilizes all cpu cores.
• Code generation! See example 👇

Philosophy behind Zero:

• Zero learning curve: The learning curve is tends to zero. You just add your functions and spin up a server, literally that's it! The framework hides the complexity of messaging pattern that enables faster communication.
• ZeroMQ: An awesome messaging library enables the power of Zero.

Let's get started!

Getting started 🚀

Ensure Python 3.8+

pip install zeroapi

• Create a server.py

from zero import ZeroServer

def echo(msg: str) -> str:
    return msg

async def hello_world() -> str:
    return "hello world"


if __name__ == "__main__":
    app = ZeroServer(port=5559)
    app.register_rpc(echo)
    app.register_rpc(hello_world)
    app.run()

Please note that server RPC methods are type hinted. Type hint is must in Zero server.

See the method type async or sync, doesn't matter. 😃

• Run it

python -m server

• Call the rpc methods

from zero import ZeroClient

zero_client = ZeroClient("localhost", 5559)

def echo():
    resp = zero_client.call("echo", "Hi there!")
    print(resp)

def hello():
    resp = zero_client.call("hello_world", None)
    print(resp)


if __name__ == "__main__":
    echo()
    hello()

Or using async client -

import asyncio

from zero import AsyncZeroClient

zero_client = AsyncZeroClient("localhost", 5559)

async def echo():
    resp = await zero_client.call("echo", "Hi there!")
    print(resp)

async def hello():
    resp = await zero_client.call("hello_world", None)
    print(resp)


if __name__ == "__main__":
    loop = asyncio.get_event_loop()
    loop.run_until_complete(echo())
    loop.run_until_complete(hello())

Code Generation! 🙌

You can also use our code generation tool to generate Python client code!

After running the server, like above, you can call the server to get the client code.

python -m zero.generate_client --host localhost --port 5559 --overwrite-dir ./my_client

It will generate client like this -

import typing  # remove this if not needed
from typing import List, Dict, Union, Optional, Tuple  # remove this if not needed
from zero import ZeroClient


zero_client = ZeroClient("localhost", 5559)


class RpcClient:
    def __init__(self, zero_client: ZeroClient):
        self._zero_client = zero_client

    def echo(self, msg: str) -> str:
        return self._zero_client.call("echo", msg)

    def hello_world(self, msg: str) -> str:
        return self._zero_client.call("hello_world", msg)

You can just use this -

from my_client import RpcClient, zero_client

client = RpcClient(zero_client)

if __name__ == "__main__":
    client.echo("Hi there!")
    client.hello_world(None)

Using zero.generate_client you can generate client code for even remote servers using the --host and --port options. You don't need access to the code 😃

Important notes 📝

• ZeroServer should always be run under if __name__ == "__main__":, as it uses multiprocessing.
• The methods which are under register_rpc() in ZeroServer should have type hinting, like def echo(msg: str):

Let's do some benchmarking 🤘

Zero is talking about inter service communication. In most real life scenarios, we need to call another microservice.

So we will be testing a gateway calling another server for some data. Check the benchmark/dockerize folder for details.

There are two endpoints in every tests,

• /hello: Just call for a hello world response 😅
• /order: Save a Order object in redis

Compare the results! 👇

Benchmarks 🏆

On my pc, core i3-10100 CPU @ 3.60GHz, 16GB ram with docker limits, cpu 40% and memory 256m, I got the following results -

Framework	"hello world" example	redis save example
aiohttp	1,424.24 req/s	256.15 req/s
fastApi	980.42 req/s	252.08 req/s
sanic	3,085.80 req/s	547.02 req/s
zero	5,000.77 req/s	784.51 req/s

Here is the result on MacBook Pro (13-inch, M1, 2020), Apple M1, 8 cores (4 performance and 4 efficiency), 8 GB RAM

Framework	"hello world" example	redis save example
aiohttp	12,409.50 req/s	6,161.43 req/s
fastApi	8,653.16 req/s	5,727.53 req/s
sanic	22,644.41 req/s	7,750.49 req/s
zero	15,853.92 req/s	11,167.89 req/s

More about MacBook benchmarks here

Todo list 📃

• Add pydantic support
• Code generation for pydantic models
• Improve error handling
• Fault tolerance

Contribution

Contributors are welcomed 🙏

Please leave a star ⭐ if you like Zero!