提取参数的 Python json 模式

Question

我需要将请求解析为以 JSON 格式出现的单个 url，但有几种不同的格式。例如，有些时间戳记为timestamp attr，另一些记为unixtime 等。所以我想为所有类型的请求创建json模式，这些模式不仅可以验证传入的JSON，还可以从指定的位置提取它们的参数。有没有图书馆可以做到这一点？

例子：

如果我可以定义一个看起来像这样的模式

schema = {
    "type" : "object",
    "properties" : {
        "price" : {
            "type" : "number",
            "mapped_name": "product_price"
        },
        "name" : {
            "type" : "string",
            "mapped_name": "product_name"

        },
        "added_at":{
            "type" : "int",
            "mapped_name": "timestamp"

        },
    },
}

然后将其应用到字典

request = {
    "name" : "Eggs",
    "price" : 34.99,
    'added_at': 1234567
}

通过一些神奇的功能

params = validate_and_extract(request, schema)

我希望 params 在那里有映射值：

{"mapped_name": "Eggs", "product_price": 34.99, "timestamp": 1234567}

所以这是我正在寻找的模块。它应该支持request 中的嵌套字典，而不仅仅是平面字典。

Answer 1

以下代码可能会有所帮助。它也支持嵌套字典。

import json


def valid_type(type_name, obj):
    if type_name == "number":
        return isinstance(obj, int) or isinstance(obj, float)

    if type_name == "int":
        return isinstance(obj, int)

    if type_name == "float":
        return isinstance(obj, float)

    if type_name == "string":
        return isinstance(obj, str)


def validate_and_extract(request, schema):
    ''' Validate request (dict) against the schema (dict).

        Validation is limited to naming and type information.
        No check is done to ensure all elements in schema
        are present in the request. This could be enhanced by
        specifying mandatory/optional/conditional information
        within the schema and subsequently checking for that.
    '''
    out = {}

    for k, v in request.items():
        if k not in schema['properties'].keys():
            print("Key '{}' not in schema ... skipping.".format(k))
            continue

        if schema['properties'][k]['type'] == 'object':
            v = validate_and_extract(v, schema['properties'][k])

        elif not valid_type(schema['properties'][k]['type'], v):
            print("Wrong type for '{}' ... skipping.".format(k))
            continue

        out[schema['properties'][k]['mapped_name']] = v

    return out


# Sample Data 1
schema1 = {
    "type" : "object",
    "properties" : {
        "price" : {
            "type" : "number",
            "mapped_name": "product_price"
        },
        "name" : {
            "type" : "string",
            "mapped_name": "product_name"

        },
        "added_at":{
            "type" : "int",
            "mapped_name": "timestamp"

        },
    },
}
request1 = {
    "name" : "Eggs",
    "price" : 34.99,
    'added_at': 1234567
}

# Sample Data 2: containing nested dict
schema2 = {
    "type" : "object",
    "properties" : {
        "price" : {
            "type" : "number",
            "mapped_name": "product_price"
        },
        "name" : {
            "type" : "string",
            "mapped_name": "product_name"
        },
        "added_at":{
            "type" : "int",
            "mapped_name": "timestamp"
        },
        "discount":{
            "type" : "object",
            "mapped_name": "offer",
            "properties" : {
                "percent": {
                    "type" : "int",
                    "mapped_name": "percentage"
                },
                "last_date": {
                    "type" : "string",
                    "mapped_name": "end_date"
                },
            }
        },
    },
}
request2 = {
    "name" : "Eggs",
    "price" : 34.99,
    'added_at': 1234567,
    'discount' : {
        'percent' : 40,
        'last_date' : '2016-09-25'
    }
}


params = validate_and_extract(request1, schema1)
print(params)

params = validate_and_extract(request2, schema2)
print(params)

运行的输出：

{'timestamp': 1234567, 'product_name': 'Eggs', 'product_price': 34.99}
{'offer': {'percentage': 40, 'end_date': '2016-09-25'}, 'timestamp': 1234567, 'product_name': 'Eggs', 'product_price': 34.99}

Answer 2

见http://json-schema.org

这看起来不像是 Python 问题。