pjrpc 1.0.0

Extensible JSON-RPC library

pjrpc is an extensible JSON-RPC client/server library with an intuitive interface that can be easily extended and integrated in your project without writing a lot of boilerplate code.

Features:

• intuitive api

• extendability

• synchronous and asynchronous client backed

• popular frameworks integration

• builtin parameter validation

• pytest integration

Installation

You can install pjrpc with pip:

$ pip install pjrpc

Extra requirements

• aiohttp

• aio_pika

• flask

• jsonschema

• kombu

• pydantic

• requests

Documentation

Documentation is available at Read the Docs.

Quickstart

Client requests

The way of using pjrpc clients is very simple and intuitive. Methods may be called by name, using proxy object or by sending handmade pjrpc.common.Request class object. Notification requests can be made using pjrpc.client.AbstractClient.notify method or by sending a pjrpc.common.Request object without id.

import pjrpc
from pjrpc.client.backend import requests as pjrpc_client


client = pjrpc_client.Client('http://localhost/api/v1')

response: pjrpc.Response = client.send(pjrpc.Request('sum', params=[1, 2], id=1))
print(f"1 + 2 = {response.result}")

result = client('sum', a=1, b=2)
print(f"1 + 2 = {result}")

result = client.proxy.sum(1, 2)
print(f"1 + 2 = {result}")

client.notify('tick')

Asynchronous client api looks pretty much the same:

import pjrpc
from pjrpc.client.backend import aiohttp as pjrpc_client


client = pjrpc_client.Client('http://localhost/api/v1')

response = await client.send(pjrpc.Request('sum', params=[1, 2], id=1))
print(f"1 + 2 = {response.result}")

result = await client('sum', a=1, b=2)
print(f"1 + 2 = {result}")

result = await client.proxy.sum(1, 2)
print(f"1 + 2 = {result}")

await client.notify('tick')

Batch requests

Batch requests also supported. You can build pjrpc.common.BatchRequest request by your hand and then send it to the server. The result is a pjrpc.common.BatchResponse instance you can iterate over to get all the results or get each one by index:

import pjrpc
from pjrpc.client.backend import requests as pjrpc_client


client = pjrpc_client.Client('http://localhost/api/v1')

batch_response = await client.batch.send(pjrpc.BatchRequest(
    pjrpc.Request('sum', [2, 2], id=1),
    pjrpc.Request('sub', [2, 2], id=2),
    pjrpc.Request('div', [2, 2], id=3),
    pjrpc.Request('mult', [2, 2], id=4),
))
print(f"2 + 2 = {batch_response[0].result}")
print(f"2 - 2 = {batch_response[1].result}")
print(f"2 / 2 = {batch_response[2].result}")
print(f"2 * 2 = {batch_response[3].result}")

There are also several alternative approaches which are a syntactic sugar for the first one (note that the result is not a pjrpc.common.BatchResponse object anymore but a tuple of “plain” method invocation results):

• using chain call notation:

result = await client.batch('sum', 2, 2)('sub', 2, 2)('div', 2, 2)('mult', 2, 2).call()
print(f"2 + 2 = {result[0]}")
print(f"2 - 2 = {result[1]}")
print(f"2 / 2 = {result[2]}")
print(f"2 * 2 = {result[3]}")

• using subscription operator:

result = await client.batch[
    ('sum', 2, 2),
    ('sub', 2, 2),
    ('div', 2, 2),
    ('mult', 2, 2),
]
print(f"2 + 2 = {result[0]}")
print(f"2 - 2 = {result[1]}")
print(f"2 / 2 = {result[2]}")
print(f"2 * 2 = {result[3]}")

• using proxy chain call:

result = await client.batch.proxy.sum(2, 2).sub(2, 2).div(2, 2).mult(2, 2).call()
print(f"2 + 2 = {result[0]}")
print(f"2 - 2 = {result[1]}")
print(f"2 / 2 = {result[2]}")
print(f"2 * 2 = {result[3]}")

Which one to use is up to you but be aware that if any of the requests returns an error the result of the other ones will be lost. In such case the first approach can be used to iterate over all the responses and get the results of the succeeded ones like this:

import pjrpc
from pjrpc.client.backend import requests as pjrpc_client


client = pjrpc_client.Client('http://localhost/api/v1')

batch_response = client.batch.send(pjrpc.BatchRequest(
    pjrpc.Request('sum', [2, 2], id=1),
    pjrpc.Request('sub', [2, 2], id=2),
    pjrpc.Request('div', [2, 2], id=3),
    pjrpc.Request('mult', [2, 2], id=4),
))

for response in batch_response:
    if response.is_success:
        print(response.result)
    else:
        print(response.error)

Batch notifications:

import pjrpc
from pjrpc.client.backend import requests as pjrpc_client


client = pjrpc_client.Client('http://localhost/api/v1')

client.batch.notify('tick').notify('tack').notify('tick').notify('tack').call()

Server

pjrpc supports popular backend frameworks like aiohttp, flask and message brokers like kombu and aio_pika.

Running of aiohttp based JSON-RPC server is a very simple process. Just define methods, add them to the registry and run the server:

import uuid

from aiohttp import web

import pjrpc.server
from pjrpc.server.integration import aiohttp

methods = pjrpc.server.MethodRegistry()


@methods.add(context='request')
async def add_user(request: web.Request, user: dict):
    user_id = uuid.uuid4().hex
    request.app['users'][user_id] = user

    return {'id': user_id, **user}


jsonrpc_app = aiohttp.Application('/api/v1')
jsonrpc_app.dispatcher.add_methods(methods)
jsonrpc_app.app['users'] = {}

if __name__ == "__main__":
    web.run_app(jsonrpc_app.app, host='localhost', port=8080)

Parameter validation

Very often besides dumb method parameters validation it is necessary to implement more “deep” validation and provide comprehensive errors description to clients. Fortunately pjrpc has builtin parameter validation based on pydantic library which uses python type annotation for validation. Look at the following example: all you need to annotate method parameters (or describe more complex types beforehand if necessary). pjrpc will be validating method parameters and returning informative errors to clients.

import enum
import uuid
from typing import List

import pydantic
from aiohttp import web

import pjrpc.server
from pjrpc.server.validators import pydantic as validators
from pjrpc.server.integration import aiohttp

methods = pjrpc.server.MethodRegistry()
validator = validators.PydanticValidator()


class ContactType(enum.Enum):
    PHONE = 'phone'
    EMAIL = 'email'


class Contact(pydantic.BaseModel):
    type: ContactType
    value: str


class User(pydantic.BaseModel):
    name: str
    surname: str
    age: int
    contacts: List[Contact]


@methods.add(context='request')
@validator.validate
async def add_user(request: web.Request, user: User):
    user_id = uuid.uuid4()
    request.app['users'][user_id] = user

    return {'id': user_id, **user.dict()}


class JSONEncoder(pjrpc.common.JSONEncoder):

    def default(self, o):
        if isinstance(o, uuid.UUID):
            return o.hex
        if isinstance(o, enum.Enum):
            return o.value

        return super().default(o)


jsonrpc_app = aiohttp.Application('/api/v1', json_encoder=JSONEncoder)
jsonrpc_app.dispatcher.add_methods(methods)
jsonrpc_app.app['users'] = {}

if __name__ == "__main__":
    web.run_app(jsonrpc_app.app, host='localhost', port=8080)

Error handling

pjrpc implements all the errors listed in protocol specification which can be found in pjrpc.common.exceptions module so that error handling is very simple and “pythonic-way”:

import pjrpc
from pjrpc.client.backend import requests as pjrpc_client

client = pjrpc_client.Client('http://localhost/api/v1')

try:
    result = client.proxy.sum(1, 2)
except pjrpc.MethodNotFound as e:
    print(e)

Default error list can be easily extended. All you need to create an error class inherited from pjrpc.exc.JsonRpcError and define an error code and a description message. pjrpc will be automatically deserializing custom errors for you:

import pjrpc
from pjrpc.client.backend import requests as pjrpc_client

class UserNotFound(pjrpc.exc.JsonRpcError):
    code = 1
    message = 'user not found'


client = pjrpc_client.Client('http://localhost/api/v1')

try:
    result = client.proxy.get_user(user_id=1)
except UserNotFound as e:
    print(e)

On the server side everything is also pretty straightforward:

import uuid

import flask

import pjrpc
from pjrpc.server import MethodRegistry
from pjrpc.server.integration import flask as integration

app = flask.Flask(__name__)

methods = pjrpc.server.MethodRegistry()


class UserNotFound(pjrpc.exc.JsonRpcError):
    code = 1
    message = 'user not found'


@methods.add
def add_user(user: dict):
    user_id = uuid.uuid4().hex
    flask.current_app.users[user_id] = user

    return {'id': user_id, **user}

@methods.add
 def get_user(self, user_id: str):
    user = flask.current_app.users.get(user_id)
    if not user:
        raise UserNotFound(data=user_id)

    return user


json_rpc = integration.JsonRPC('/api/v1')
json_rpc.dispatcher.add_methods(methods)

app.users = {}

json_rpc.init_app(app)

if __name__ == "__main__":
    app.run(port=80)