python json-rpc client/server without boilerplate
… image:: https://static.pepy.tech/personalized-badge/pjrpc?period=month&units=international_system&left_color=grey&right_color=orange&left_text=Downloads/month
:target: https://pepy.tech/project/pjrpc
:alt: Downloads/month
… image:: https://github.com/dapper91/pjrpc/actions/workflows/test.yml/badge.svg?branch=master
:target: https://github.com/dapper91/pjrpc/actions/workflows/test.yml
:alt: Build status
… image:: https://img.shields.io/pypi/l/pjrpc.svg
:target: https://pypi.org/project/pjrpc
:alt: License
… image:: https://img.shields.io/pypi/pyversions/pjrpc.svg
:target: https://pypi.org/project/pjrpc
:alt: Supported Python versions
… image:: https://codecov.io/gh/dapper91/pjrpc/branch/master/graph/badge.svg
:target: https://codecov.io/gh/dapper91/pjrpc
:alt: Code coverage
… image:: https://readthedocs.org/projects/pjrpc/badge/?version=stable&style=flat
:alt: ReadTheDocs status
:target: https://pjrpc.readthedocs.io/en/stable/
pjrpc
is an extensible JSON-RPC <https://www.jsonrpc.org>
_ 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:
You can install pjrpc with pip:
… code-block:: console
$ pip install pjrpc
aiohttp <https://aiohttp.readthedocs.io>
_aio_pika <https://aio-pika.readthedocs.io>
_flask <https://flask.palletsprojects.com>
_jsonschema <https://python-jsonschema.readthedocs.io>
_kombu <https://kombu.readthedocs.io/en/stable/>
_pydantic <https://pydantic-docs.helpmanual.io/>
_requests <https://requests.readthedocs.io>
_httpx <https://www.python-httpx.org/>
_openapi-ui-bundles <https://github.com/dapper91/python-openapi-ui-bundles>
_starlette <https://www.starlette.io/>
_django <https://www.djangoproject.com>
_Documentation is available at Read the Docs <https://pjrpc.readthedocs.io>
_.
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.
… code-block:: python
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:
… code-block:: python
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:
… code-block:: python
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):
… code-block:: python
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]}")
… code-block:: python
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]}")
… code-block:: python
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:
… code-block:: python
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:
… code-block:: python
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 <https://aiohttp.readthedocs.io>
,
flask <https://flask.palletsprojects.com>
and message brokers like kombu <https://kombu.readthedocs.io/en/stable/>
_
and aio_pika <https://aio-pika.readthedocs.io>
_.
Running of aiohttp based JSON-RPC server is a very simple process. Just define methods, add them to the
registry and run the server:
… code-block:: python
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 <https://pydantic-docs.helpmanual.io/>
_ 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.
… code-block:: python
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 <https://www.jsonrpc.org/specification#error_object>
_
which can be found in pjrpc.common.exceptions
module so that error handling is very simple and “pythonic-way”:
… code-block:: python
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:
… code-block:: python
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:
… code-block:: python
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 <https://swagger.io/specification/>
_ and OpenRPC <https://spec.open-rpc.org/#introduction>
_
specification generation support and integrated web UI as an extra dependency. Three UI types are supported:
<https://swagger.io/tools/swagger-ui/>
_)<https://mrin9.github.io/RapiDoc/>
_)<https://github.com/Redocly/redoc>
_)Web UI extra dependency can be installed using the following code:
… code-block:: console
$ pip install pjrpc[openapi-ui-bundles]
The following example illustrates how to configure OpenAPI specification generation
and Swagger UI web tool with basic auth:
… code-block:: python
import uuid
from typing import Annotated, Any, Optional
import flask
import flask_cors
import flask_httpauth
import pydantic as pd
from werkzeug import security
import pjrpc.server.specs.extractors.pydantic
from pjrpc.server.integration import flask as integration
from pjrpc.server.specs import extractors
from pjrpc.server.specs import openapi as specs
from pjrpc.server.validators import pydantic as validators
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, pd.BaseModel):
return o.model_dump()
if isinstance(o, uuid.UUID):
return str(o)
return super().default(o)
UserName = Annotated[
str,
pd.Field(description="User name", examples=["John"]),
]
UserSurname = Annotated[
str,
pd.Field(description="User surname", examples=['Doe']),
]
UserAge = Annotated[
int,
pd.Field(description="User age", examples=[25]),
]
UserId = Annotated[
uuid.UUID,
pd.Field(description="User identifier", examples=["c47726c6-a232-45f1-944f-60b98966ff1b"]),
]
class UserIn(pd.BaseModel):
"""
User registration data.
"""
name: UserName
surname: UserSurname
age: UserAge
class UserOut(UserIn):
"""
Registered user data.
"""
id: UserId
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(
summary='Creates a user',
tags=['users'],
errors=[AlreadyExistsError],
)
@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.model_dump())
@specs.annotate(
summary='Returns a user',
tags=['users'],
errors=[NotFoundError],
)
@methods.add
@validator.validate
def get_user(user_id: UserId) -> 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.hex)
if not user:
raise NotFoundError()
return UserOut(id=user_id, **user.model_dump())
@specs.annotate(
summary='Deletes a user',
tags=['users'],
errors=[NotFoundError],
)
@methods.add
@validator.validate
def delete_user(user_id: UserId) -> None:
"""
Deletes a user.
:param object user_id: user id
:raise NotFoundError: user not found
"""
user = flask.current_app.users_db.pop(user_id.hex, 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(),
),
)
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:
.. image:: docs/source/_static/swagger-ui-screenshot.png
:width: 1024
:alt: Open API full example
RapiDoc:
~~~~~~~~
.. image:: docs/source/_static/rapidoc-screenshot.png
:width: 1024
:alt: Open API cli example
Redoc:
~~~~~~
.. image:: docs/source/_static/redoc-screenshot.png
:width: 1024
:alt: Open API method example