天天热头条丨python json-rpc 规范源码阅读
来源:脚本之家    时间:2022-10-18 06:07:36
目录
json-rpc 源码阅读JSON-RPC规范jsonrpcclient的实现jsonrpcserver的实现小结小技巧

json-rpc 源码阅读

JSON-RPC是一个无状态且轻量级的远程过程调用(RPC)协议。JSON-RPC应用很广泛,比如以太坊的API。JSON-RPC的python实现较多,我选择了Exploding Labs 提供的python版本。主要是其它库都比较古老,而e-labs的实现采用最新版本python,支持类型系统,还有一些函数式编程的范式,代码也很简洁,值得学习。

e-labs的JSON-RPC分成客户端和服务端两个库,分别是jsonrpcclient和jsonrpcserver, 代码版本如下表:


【资料图】

名称版本
jsonrpcclient4.0.2
jsonrpcserver5.0.9

准备好代码后,我们可以开始json-rpc的源码阅读,本文包括下面几个部分:

JSON-RPC规范jsonrpcclient的实现jsonrpcserver的实现小结小技巧

JSON-RPC规范

JSON-RPC规范,我这里借用jsonrpcserver中的验证规则文件简单介绍一下,文件如下:

# request-schema.json
{
    "$schema": "http://json-schema.org/draft-04/schema#",
    "description": "A JSON RPC 2.0 request",
    "oneOf": [
        {
            "description": "An individual request",
            "$ref": "#/definitions/request"
        },
        {
            "description": "An array of requests",
            "type": "array",
            "items": { "$ref": "#/definitions/request" },
            "minItems": 1
        }
    ],
    "definitions": {
        "request": {
            "type": "object",
            "required": [ "jsonrpc", "method" ],
            "properties": {
                "jsonrpc": { "enum": [ "2.0" ] },
                "method": {
                    "type": "string"
                },
                "id": {
                    "type": [ "string", "number", "null" ],
                    "note": [
                        "While allowed, null should be avoided: http://www.jsonrpc.org/specification#id1",
                        "While allowed, a number with a fractional part should be avoided: http://www.jsonrpc.org/specification#id2"
                    ]
                },
                "params": {
                    "type": [ "array", "object" ]
                }
            },
            "additionalProperties": false
        }
    }
}

文件描述了JSON-RPC的规则,如下:

json-rpc请求可以是单个的request对象,也是是批量的request对象数组每个request对象需要符合:必填字段jsonrpc,值枚举类型。目前2.0,其实就是版本号。(之前有1.0版本)必填字段method, 字符串类型。远程函数的名称。id字段,支持字符串,数字或者空。为空表示通知无需回应(result)。id确保响应可以一一对应到请求上。params字段,支持数组或者字典。

JSON-RPC响应部分的规则是:

jsonrpc字段,值为2.0result字段,值为调用结果error字段,值为异常信息,包括code,message和data三个字段,规范定义了详细的错误清单。id同请求的idresult和error二选一

强烈建议大家阅读参考链接中的规范原文,介绍的非常清晰,中文翻译也很到位,有助于对JSON-RPC规范完全理解。

jsonrpcclient的实现

模块文件功能描述
id_generators.pyid生成器
requests.py请求信息封装
response.py响应信息封装
sentinels.py定义NOID,用于通知类请求
utils.py一些工具函数
examples一些示例

从示例可以知道JSON-RPC,可以使用不同的底层协议比如http,websocket和tcp(zeromq实现)等。我们看最简单的基于http实现的实例:

from jsonrpcclient import request, parse, Ok
import logging
import requests
response = requests.post("http://localhost:5000/", json=request("ping"))
parsed = parse(response.json())
if isinstance(parsed, Ok):
    print(parsed.result)
else:
    logging.error(parsed.message)

这段api展示了:

jsonrpcclient只是封装请求request和响应Ok,数据请求的发送由不同协议提供,这里使用requests,另外还有aiohttp的实现等。resquest函数封装请求,parse解析响应正常的结果展示result信息,错误的结果展示message信息

request代码很简单, 封装请求成符合JSON-RPC规范的字符串:

# requests.py
def request_pure(
    id_generator: Iterator[Any],
    method: str,
    params: Union[Dict[str, Any], Tuple[Any, ...]],
    id: Any,
) -> Dict[str, Any]:
    return {
        "jsonrpc": "2.0",
        "method": method,
        **(
            {"params": list(params) if isinstance(params, tuple) else params}
            if params
            else {}
        ),
        "id": id if id is not NOID else next(id_generator),
    }
def request_impure(
    id_generator: Iterator[Any],
    method: str,
    params: Union[Dict[str, Any], Tuple[Any, ...], None] = None,
    id: Any = NOID,
) -> Dict[str, Any]:
    return request_pure(
        id_generator or id_generators.decimal(), method, params or (), id
    )
request_natural = partial(request_impure, id_generators.decimal())
...
request = request_natural

所以示例中的请求,可以等价下面的curl命令:

$ curl -X POST http://localhost:5001 -d "{"jsonrpc": "2.0", "method": "ping", "params": {}, "id": 1}"

response处理也很简单:

# response.py
class Ok(NamedTuple):
    result: Any
    id: Any
    def __repr__(self) -> str:
        return f"Ok(result={self.result!r}, id={self.id!r})"
class Error(NamedTuple):
    code: int
    message: str
    data: Any
    id: Any
    def __repr__(self) -> str:
        return f"Error(code={self.code!r}, message={self.message!r}, data={self.data!r}, id={self.id!r})"
Response = Union[Ok, Error]

定义Response类型,是Ok或者Error。Ok和Error是两个可命名元祖。

parse就是将结果json字典解析成对应的Response:

def to_result(response: Dict[str, Any]) -> Response:
    return (
        Ok(response["result"], response["id"])
        if "result" in response
        else Error(
            response["error"]["code"],
            response["error"]["message"],
            response["error"].get("data"),
            response["id"],
        )
    )
def parse(response: Deserialized) -> Union[Response, Iterable[Response]]:
    return (
        map(to_result, response) if isinstance(response, list) else to_result(response)
    )

也可以直接使用parse_json函数,从json字符串生成结果:

parse_json = compose(parse, json.loads)

这里的map,componse等都是函数式编程。在server中函数式编程使用的更多,可见作者非常喜欢函数式编程的思想

jsonrpcserver的实现

jsonrpcclient实现非常简单,jsonrpcserver的实现会略微复杂点,但是还是可以很好的理解的,我们一起继续。jsonrpcserver的主要模块如下:

模块描述
main.py/async_main.pymain文件,分别是同步和异步版本
dispatcher.py/async_dispatcher.pyrpc服务的分配器实现
methods.pyrpc函数的装饰器
request.py请求处理
response.py响应处理
result.py结果处理
examplse一些示例

通用,我们先从示例入手,看看api的使用。下面是flask版本:

# flask_server.py
from flask import Flask, Response, request
from jsonrpcserver import method, Result, Success, dispatch
app = Flask(__name__)
@method
def ping() -> Result:
    return Success("pong")
@app.route("/", methods=["POST"])
def index():
    return Response(
        dispatch(request.get_data().decode()), content_type="application/json"
    )
if __name__ == "__main__":
    app.run()

从示例我们可以知道,rpc服务其实就2大步骤:

使用method装饰ping函数,使它支持rpc调用,ping函数返回的是一个特点的Result数据结构所有rpc调用的http-url都是根目录,服务使用dispatch调度rpc请求

先看第一步rpc装饰器:

# methods.py
Method = Callable[..., Result]
Methods = Dict[str, Method]
global_methods = dict()
def method(
    f: Optional[Method] = None, name: Optional[str] = None
) -> Callable[..., Any]:
    """A decorator to add a function into jsonrpcserver"s internal global_methods dict.
    The global_methods dict will be used by default unless a methods argument is passed
    to `dispatch`.
    Functions can be renamed by passing a name argument:
        @method(name=bar)
        def foo():
            ...
    """
    def decorator(func: Method) -> Method:
        nonlocal name
        global_methods[name or func.__name__] = func
        return func
    return decorator(f) if callable(f) else cast(Method, decorator)
将所有的rpc函数都封装到global_methods字典中函数需要返回Result类型

第2步中,main模块提供了dispatch的api,主要就是下面的函数:

# main.py
def dispatch_to_response(
    request: str,
    methods: Optional[Methods] = None,
    *,
    context: Any = NOCONTEXT,
    deserializer: Callable[[str], Deserialized] = json.loads,
    validator: Callable[[Deserialized], Deserialized] = default_validator,
    post_process: Callable[[Response], Any] = identity,
) -> Union[Response, List[Response], None]:
    """Takes a JSON-RPC request string and dispatches it to method(s), giving Response
    namedtuple(s) or None.
    This is a public wrapper around dispatch_to_response_pure, adding globals and
    default values to be nicer for end users.
    Args:
        request: The JSON-RPC request string.
        methods: Dictionary of methods that can be called - mapping of function names to
            functions. If not passed, uses the internal global_methods dict which is
            populated with the @method decorator.
        context: If given, will be passed as the first argument to methods.
        deserializer: Function that deserializes the request string.
        validator: Function that validates the JSON-RPC request. The function should
            raise an exception if the request is invalid. To disable validation, pass
            lambda _: None.
        post_process: Function that will be applied to Responses.
    Returns:
        A Response, list of Responses or None.
    Examples:
       >>> dispatch("{"jsonrpc": "2.0", "method": "ping", "id": 1}")
       "{"jsonrpc": "2.0", "result": "pong", "id": 1}"
    """
    return dispatch_to_response_pure(
        deserializer=deserializer,
        validator=validator,
        post_process=post_process,
        context=context,
        methods=global_methods if methods is None else methods,
        request=request,
    )
request 请求的函数名称methods 可供调用的函数集合,默认就是之前rpc装饰器中存储的global_methodsdeserializer 请求的反序列化函数,validator请求验证器post_process响应处理函数

post_process主要就是根据结果类型,分别取不同的字段并序列化:

def to_serializable_one(response: ResponseType) -> Union[Deserialized, None]:
    return (
        serialize_error(response._error)
        if isinstance(response, Left)
        else serialize_success(response._value)
    )

dispatch的实现,主要是下面2个函数dispatch_request和call,前者查找rpc函数,后者执行rpc函数。dispatch_request内容如下:

def dispatch_request(
    methods: Methods, context: Any, request: Request
) -> Tuple[Request, Result]:
    """Get the method, validates the arguments and calls the method.
    Returns: A tuple containing the Result of the method, along with the original
        Request. We need the ids from the original request to remove notifications
        before responding, and  create a Response.
    """
    return (
        request,
        get_method(methods, request.method)
        .bind(partial(validate_args, request, context))
        .bind(partial(call, request, context)),
    )

这里使用了oslash这个函数式编程库,我们可以简单的使用unix的管道思想去理解:

使用get_method查找rpc响应函数使用validate_args验证rpc请求使用call执行rpc调用3个步骤依次执行,前者的返回值会作为后缀的参数

重中之重是call函数,原理非常简单:

def call(request: Request, context: Any, method: Method) -> Result:
    """Call the method.
    Handles any exceptions raised in the method, being sure to return an Error response.
    Returns: A Result.
    """
    try:
        result = method(*extract_args(request, context), **extract_kwargs(request))
        # validate_result raises AssertionError if the return value is not a valid
        # Result, which should respond with Internal Error because its a problem in the
        # method.
        validate_result(result)
    # Raising JsonRpcError inside the method is an alternative way of returning an error
    # response.
    except JsonRpcError as exc:
        return Left(ErrorResult(code=exc.code, message=exc.message, data=exc.data))
    # Any other uncaught exception inside method - internal error.
    except Exception as exc:
        logger.exception(exc)
        return Left(InternalErrorResult(str(exc)))
    return result
使用args和kwargs动态执行rpc函数,并将结果进行返回捕获异常,返回标准错误

这里的Left是函数式编程中的概念,我们可以从response的实现,简单了解一下:

# response.py
class SuccessResult(NamedTuple):
    result: Any = None
class ErrorResult(NamedTuple):
    code: int
    message: str
    data: Any = NODATA  # The spec says this value may be omitted
# Union of the two valid result types
Result = Either[ErrorResult, SuccessResult]
def Success(*args: Any, **kwargs: Any) -> Either[ErrorResult, SuccessResult]:
    return Right(SuccessResult(*args, **kwargs))
def Error(*args: Any, **kwargs: Any) -> Either[ErrorResult, SuccessResult]:
    return Left(ErrorResult(*args, **kwargs))

SuccessResult和ErrorResult是python的两个标准对象;Result是oslash中定义的联合对象,在ErrorResult, SuccessResult中二选一,有些类似rust中的Option;Right封装了正确的结果,Left封装了错误的结果。

这一部分需要一些函数式编程的基础,如果不太理解,推荐阅读参考链接。

小结

我们一起学习了JSON-RPC规范,并且了解了Exploding Labs如何使用 现代python实现该规范,也接触了一些函数式编程的方式。

小技巧

业务有时候需要自己实现一个简单的自增id,我们也许会用全局变量来做:

start = 0
def gen1():
    start +=1
    return count
# 调用
id = gen1()

全局变量会形成一些污染,利用闭包的特性,我们可以优化成这样:

def gen2():
    start = 0 
    def incr():
        start +=1
        return count
    return incr
gen = gen2()
# 调用
id = gen()

json-rpc里提供了使用yeild关键字实现的版本:

def hexadecimal(start: int = 1) -> Iterator[str]:
    """
    Incremental hexadecimal numbers.
    e.g. 1, 2, 3, .. 9, a, b, etc.
    Args:
        start: The first value to start with.
    """
    while True:
        yield "%x" % start
        start += 1

参考链接

www.jsonrpc.org/specificati…

ethereum.org/en/develope…

www.wallarm.com/what/what-i…

github.com/dbrattli/OS…

以上就是python json-rpc 规范源码阅读的详细内容,更多关于python json-rpc 规范的资料请关注脚本之家其它相关文章!

关键词: 全局变量 数据请求 一一对应 捕获异常

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