python-jsonrpc-lib 0.3.2

Simple, yet solid - Type-safe JSON-RPC 1.0/2.0 with OpenAPI support

python-jsonrpc-lib

Simple, yet solid. JSON-RPC 1.0/2.0 for Python.

JSON-RPC is a small protocol: a method name, some parameters, a result. python-jsonrpc-lib keeps it that way. You write ordinary Python functions and dataclasses; the library handles validation, routing, error responses, and API documentation. No framework lock-in, no external dependencies, no boilerplate.

Install

pip install python-jsonrpc-lib

Quickstart

Define methods as classes with typed parameters. The library validates inputs, routes calls, and builds responses automatically.

from dataclasses import dataclass
from jsonrpc import JSONRPC, Method, MethodGroup

@dataclass
class AddParams:
    a: int
    b: int

class Add(Method):
    def execute(self, params: AddParams) -> int:
        return params.a + params.b

@dataclass
class GreetParams:
    name: str
    greeting: str = 'Hello'

class Greet(Method):
    def execute(self, params: GreetParams) -> str:
        return f'{params.greeting}, {params.name}!'

rpc = JSONRPC(version='2.0')
rpc.register('add', Add())
rpc.register('greet', Greet())

response = rpc.handle('{"jsonrpc": "2.0", "method": "add", "params": {"a": 5, "b": 3}, "id": 1}')
# '{"jsonrpc": "2.0", "result": 8, "id": 1}'

Pass in a JSON string, get a JSON string back. What carries it over the wire is up to you.

If a is "five" instead of 5, the caller receives a -32602 Invalid params error immediately — no exception handling on your end.

The same AddParams dataclass drives validation, IDE autocomplete, and the OpenAPI schema.

Why python-jsonrpc-lib?

• Zero dependencies — pure Python 3.11+. Nothing to pin, nothing to audit beyond the library itself.
• Type validation from dataclasses — declare parameters as a dataclass, get automatic validation and clear error messages for free.
• OpenAPI docs auto-generated — type hints and docstrings you already wrote become a full OpenAPI 3.0 spec. Point any Swagger-compatible UI at it and your API is self-documented.
• Transport-agnostic — rpc.handle(json_string) returns a string. HTTP, WebSocket, TCP, message queue: your choice.
• Spec-compliant by default — v1.0 and v2.0 rules enforced out of the box, configurable when you need to support legacy clients.

Namespacing and Middleware

Use MethodGroup to organize methods into namespaces and add cross-cutting concerns:

math = MethodGroup()
math.register('add', Add())

rpc = JSONRPC(version='2.0')
rpc.register('math', math)

# "math.add" is now available

Quick Prototyping

For scripts and throwaway code, the @rpc.method decorator registers functions directly (v2.0 only):

rpc = JSONRPC(version='2.0')

@rpc.method
def add(a: int, b: int) -> int:
    return a + b

For production use, prefer Method classes — they support context, middleware, and groups.

Documentation

Full documentation with tutorials, integration guides, and API reference:

• Tutorial: Hello World — first method, explained
• Tutorial: Parameters — dataclass validation in detail
• Tutorial: Context — authentication and per-request data
• Tutorial: OpenAPI — interactive API documentation
• Flask integration
• FastAPI integration
• Philosophy — design decisions and trade-offs
• API Reference

Claude Code Integration

If you use Claude Code, a skill for this library is available. It gives Claude built-in knowledge of jsonrpc-lib's API: creating methods, registering them, organizing with groups, handling errors, and adding context and middleware — without having to look up docs.

To use it, add the skill file to your project's .claude/skills/ directory.

License

MIT