Extensible JSON-RPC library
Project description
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:
framework agnostic
intuitive api
extendability
synchronous and asynchronous client backed
synchronous and asynchronous server support
popular frameworks integration
builtin parameter validation
pytest integration
openapi schema generation support
web ui support (SwaggerUI, RapiDoc, ReDoc)
Installation
You can install pjrpc with pip:
$ pip install pjrpc
Extra requirements
Documentation
Documentation is available at Read the Docs.
Quickstart
Client requests
pjrpc client interface 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.server.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)
Open API specification
pjrpc has built-in OpenAPI and OpenRPC specification generation support and integrated web UI as an extra dependency. Three UI types are supported:
SwaggerUI (https://swagger.io/tools/swagger-ui/)
RapiDoc (https://mrin9.github.io/RapiDoc/)
ReDoc (https://github.com/Redocly/redoc)
Web UI extra dependency can be installed using the following code:
$ pip install pjrpc[openapi-ui-bundles]
The following example illustrates how to configure OpenAPI specification generation and Swagger UI web tool with basic auth:
import uuid
from typing import Any, Optional
import flask
import flask_httpauth
import pydantic
import flask_cors
from werkzeug import security
import pjrpc.server.specs.extractors.pydantic
from pjrpc.server.integration import flask as integration
from pjrpc.server.validators import pydantic as validators
from pjrpc.server.specs import extractors, openapi as specs
app = flask.Flask('myapp')
flask_cors.CORS(app, resources={"/myapp/api/v1/*": {"origins": "*"}})
methods = pjrpc.server.MethodRegistry()
validator = validators.PydanticValidator()
auth = flask_httpauth.HTTPBasicAuth()
credentials = {"admin": security.generate_password_hash("admin")}
@auth.verify_password
def verify_password(username: str, password: str) -> Optional[str]:
if username in credentials and security.check_password_hash(credentials.get(username), password):
return username
class AuthenticatedJsonRPC(integration.JsonRPC):
@auth.login_required
def _rpc_handle(self, dispatcher: pjrpc.server.Dispatcher) -> flask.Response:
return super()._rpc_handle(dispatcher)
class JSONEncoder(pjrpc.JSONEncoder):
def default(self, o: Any) -> Any:
if isinstance(o, pydantic.BaseModel):
return o.dict()
if isinstance(o, uuid.UUID):
return str(o)
return super().default(o)
class UserIn(pydantic.BaseModel):
"""
User registration data.
"""
name: str
surname: str
age: int
class UserOut(UserIn):
"""
Registered user data.
"""
id: uuid.UUID
class AlreadyExistsError(pjrpc.exc.JsonRpcError):
"""
User already registered error.
"""
code = 2001
message = "user already exists"
class NotFoundError(pjrpc.exc.JsonRpcError):
"""
User not found error.
"""
code = 2002
message = "user not found"
@specs.annotate(
tags=['users'],
errors=[AlreadyExistsError],
examples=[
specs.MethodExample(
summary="Simple example",
params=dict(
user={
'name': 'Alex',
'surname': 'Smith',
'age': 25,
},
),
result={
'id': 'c47726c6-a232-45f1-944f-60b98966ff1b',
'name': 'Alex',
'surname': 'Smith',
'age': 25,
},
),
],
)
@methods.add
@validator.validate
def add_user(user: UserIn) -> UserOut:
"""
Creates a user.
:param object user: user data
:return object: registered user
:raise AlreadyExistsError: user already exists
"""
for existing_user in flask.current_app.users_db.values():
if user.name == existing_user.name:
raise AlreadyExistsError()
user_id = uuid.uuid4().hex
flask.current_app.users_db[user_id] = user
return UserOut(id=user_id, **user.dict())
@specs.annotate(
tags=['users'],
errors=[NotFoundError],
examples=[
specs.MethodExample(
summary='Simple example',
params=dict(
user_id='c47726c6-a232-45f1-944f-60b98966ff1b',
),
result={
'id': 'c47726c6-a232-45f1-944f-60b98966ff1b',
'name': 'Alex',
'surname': 'Smith',
'age': 25,
},
),
],
)
@methods.add
@validator.validate
def get_user(user_id: uuid.UUID) -> UserOut:
"""
Returns a user.
:param object user_id: user id
:return object: registered user
:raise NotFoundError: user not found
"""
user = flask.current_app.users_db.get(user_id)
if not user:
raise NotFoundError()
return UserOut(**user.dict())
@specs.annotate(
tags=['users'],
errors=[NotFoundError],
examples=[
specs.MethodExample(
summary='Simple example',
params=dict(
user_id='c47726c6-a232-45f1-944f-60b98966ff1b',
),
result=None,
),
],
)
@methods.add
@validator.validate
def delete_user(user_id: uuid.UUID) -> None:
"""
Deletes a user.
:param object user_id: user id
:raise NotFoundError: user not found
"""
user = flask.current_app.users_db.pop(user_id, None)
if not user:
raise NotFoundError()
json_rpc = AuthenticatedJsonRPC(
'/api/v1',
json_encoder=JSONEncoder,
spec=specs.OpenAPI(
info=specs.Info(version="1.0.0", title="User storage"),
servers=[
specs.Server(
url='http://127.0.0.1:8080',
),
],
security_schemes=dict(
basicAuth=specs.SecurityScheme(
type=specs.SecuritySchemeType.HTTP,
scheme='basic',
),
),
security=[
dict(basicAuth=[])
],
schema_extractor=extractors.pydantic.PydanticSchemaExtractor(),
ui=specs.SwaggerUI(),
# ui=specs.RapiDoc(),
# ui=specs.ReDoc(),
),
)
json_rpc.dispatcher.add_methods(methods)
app.users_db = {}
myapp = flask.Blueprint('myapp', __name__, url_prefix='/myapp')
json_rpc.init_app(myapp)
app.register_blueprint(myapp)
if __name__ == "__main__":
app.run(port=8080)
Specification is available on http://localhost:8080/myapp/api/v1/openapi.json
Web UI is running on http://localhost:8080/myapp/api/v1/ui/
Swagger UI:
RapiDoc:
Redoc:
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