Zero is a simple Python framework (RPC like) to build fast and high performance microservices or distributed servers

---

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

For Windows, tornado needs to be installed separately (for async operations). It's not included with zeroapi because for linux and mac-os, tornado is not needed as they have their own event loops.

• Create a server.py

from zero import ZeroServer

app = ZeroServer(port=5559)

@app.register_rpc
def echo(msg: str) -> str:
    return msg

@app.register_rpc
async def hello_world() -> str:
    return "hello world"


if __name__ == "__main__":
    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.

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 😃

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)

Use the client -

from my_client import RpcClient, zero_client

client = RpcClient(zero_client)

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

Currently, the code generation tool supports only ZeroClient and not AsyncZeroClient.

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 🏆

11th Gen Intel® Core™ i7-11800H @ 2.30GHz, 8 cores, 16 threads, 16GB RAM (Docker in Ubuntu 22.04.2 LTS)

(Sorted alphabetically)

Framework	"hello world" (req/s)	99% latency (ms)	redis save (req/s)	99% latency (ms)
aiohttp	14391.38	10.96	9470.74	12.94
aiozmq	15121.86	9.42	5904.84	21.57
fastApi	9590.96	18.31	6669.81	24.41
sanic	18790.49	8.69	12259.29	13.52
zero(sync)	24805.61	4.57	16498.83	7.80
zero(async)	22716.84	5.61	17446.19	7.24

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!