如何根据json方案转换字典,Python3

w41d8nur  于 2022-11-26  发布在  Python
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我有一个json方案,它指定了Python 3中字典的格式。

INPUT_SCHEME = {
    "type": "object",
    "properties": {
        "a1": {
            "type": "object",
            "properties": {
                "a1_1": {"type": ["string", "null"]},
                "a1_2": {"type": ["number", "null"]},
            },
            "additionalProperties": False,
            "minProperties": 2,
        },
        "a2": {
            "type": "array",
            "items": {"type": ["number", "null"]},
        },
        "a3": {
            "type": ["number", "null"],
        },
        "a4": {
            "type": "object",
            "properties": {
                "a4_1": {"type": ["string", "null"]},
                "a4_2": {
                    "type": "object",
                    "properties": {
                        "a4_2_1": {"type": ["string", "null"]},
                        "a4_2_2": {"type": ["number", "null"]},
                    },
                    "additionalProperties": False,
                    "minProperties": 2,
                },
            },
            "additionalProperties": False,
            "minProperties": 2,
        },
        "a5": {
            "type": "array",
            "items": {
                "type": "object",
                "properties": {
                    "a5_1": {"type": ["string", "null"]},
                    "a5_2": {"type": ["number", "null"]},
                },
                "additionalProperties": False,
                "minProperties": 2,
            },
        },
    },
    "additionalProperties": False,
    "minProperties": 5,
}

我想写一个函数,它可以把任意的输入字典转换成INPUT_SCHEME定义的格式。
规则是:
1.如果输入指令缺少一个文件,则在输出指令中用None或空列表填充该文件。
1.如果输入dict有一个没有在INPUT_SCHEME中定义的关键字,则在输出dict中删除它。
例如,假设我有a_input,其中只有'a1'是正确的。缺少'a2', 'a3', and 'a4''a5'中的每个元素缺少一个属性。并且'a6'是未定义的字段。我想写的函数应该将a_input转换为a_output。并且您可以使用jsonschema.validate进行检查。

a_input = {
    'a1': {'a1_1': 'apple', 'a1_2': 20.5},
    'a5': [{'a5_1': 'pear'}, {'a5_2': 18.5}],
    'a6': [1, 2, 3, 4],
}

a_output = {
    'a1': {'a1_1': 'apple', 'a1_2': 20.5},
    'a2': [],
    'a3': None,
    'a4': {
        'a4_1': None,
        'a4_2': {
            'a4_2_1': None,
            'a4_2_2': None,
        }
    },
    'a5': [
        {
            'a5_1': 'pear',
            'a5_2': None,
        },
        {
            'a5_1': None,
            'a5_2': 18.5,
        }
    ]
}

jsonschema.validate(a_output, schema=INPUT_SCHEME)

我试着写函数,但是写不出来。主要是因为if-else检查太多,再加上嵌套结构,我迷路了。你能帮帮我吗?

  • 谢谢-谢谢
def my_func(a_from):
    a_to = dict()
    for key_1 in INPUT_SCHEME['properties'].keys():
        if key_1 not in a_from:
            a_to[key_1] = None  # This is incorrect, since the structure of a_to[key_1] depends on INPUT_SCHEME.
            continue

        layer_1 = INPUT_SCHEME['properties'][key_1]
        if 'properties' in layer_1:  # like a1, a4
            for key_2 in layer_1['properties'].keys():
                layer_2 = layer_1['properties'][key_2]
                ...

                # but it can be a nest of layers. Like a4, there are 3 layers. In real case, it can have more layers.

        elif 'items' in layer_1:
            if 'properties' in layer_1['items']:  # like a5
                ...
            else:  # like a2
                ...
        else:  # like 3
            ...
    return a_to
ef1yzkbh

ef1yzkbh1#

递归算法适合这种情况。
我把它分成了两个不同的功能,从模式中删除未定义的属性和填充不存在的属性是两个不同的任务。如果你愿意,你可以把它们合并成一个。
为了填充不存在的属性,我只创建数组、对象和None,然后向内递归。
为了删除未定义的属性,我比较模式键并删除不匹配的键,再次向内递归。
您可能会在代码中看到注解和类型检查:

def fill_nonexistent_properties(input_dictionary, schema):
    """
    Fill missing properties in input_dictionary according to the schema.
    """
    properties = schema['properties']
    missing_properties = set(properties).difference(input_dictionary)

    # Fill all missing properties.
    for key in missing_properties:
        value = properties[key]
        if value['type'] == 'array':
            input_dictionary[key] = []
        elif value['type'] == 'object':
            input_dictionary[key] = {}
        else:
            input_dictionary[key] = None
    
    # Recurse inside all properties.
    for key, value in properties.items():
        
        # If it's an array of objects, recurse inside each item.
        if value['type'] == 'array' and value['items']['type'] == 'object':
            object_list = input_dictionary[key]

            if not isinstance(object_list, list):
                raise ValueError(
                    f"Invalid JSON object: {key} is not a list.")

            for item in object_list:
                if not isinstance(item, dict):
                    raise ValueError(
                        f"Invalid JSON object: {key} is not a list of objects.")
                fill_nonexistent_properties(item, value['items'])

        # If it's an object, recurse inside it.
        elif value['type'] == 'object':
            obj = input_dictionary[key]
            if not isinstance(obj, dict):
                raise ValueError(
                    f"Invalid JSON object: {key} is not a dictionary.")
            fill_nonexistent_properties(obj, value)

def remove_undefined_properties(input_dictionary, schema):
    """
    Remove properties in input_dictionary that are not defined in the schema.
    """
    properties = schema['properties']
    undefined_properties = set(input_dictionary).difference(properties)

    # Remove all undefined properties.
    for key in undefined_properties:
        del input_dictionary[key]
    
    # Recurse inside all existing sproperties.
    for key, value in input_dictionary.items():
        property_shcema = properties[key]

        # If it's an array of objects, recurse inside each item.
        if isinstance(value, list):
            if not property_shcema['type'] == 'array':
                raise ValueError(
                    f"Invalid JSON object: {key} is not a list.")

            # We're only dealing with objects inside arrays.
            if not property_shcema['items']['type'] == 'object':
                continue
            
            for item in value:
                # Make sure each item is an object.
                if not isinstance(item, dict):
                    raise ValueError(
                        f"Invalid JSON object: {key} is not a list of objects.")
                remove_undefined_properties(item, property_shcema['items'])
        
        # If it's an object, recurse inside it.
        elif isinstance(value, dict):
            # Make sure the object is supposed to be an object.
            if not property_shcema['type'] == 'object':
                raise ValueError(
                    f"Invalid JSON object: {key} is not an object.")

            remove_undefined_properties(value, property_shcema)

import pprint
pprint.pprint(a_input)
fill_nonexistent_properties(a_input, INPUT_SCHEME)
remove_undefined_properties(a_input, INPUT_SCHEME)
print("-"*10, "OUTPUT", "-"*10)
pprint.pprint(a_input)

输出量:

{'a1': {'a1_1': 'apple', 'a1_2': 20.5},
 'a5': [{'a5_1': 'pear'}, {'a5_2': 18.5}],
 'a6': [1, 2, 3, 4]}
---------- OUTPUT ----------
{'a1': {'a1_1': 'apple', 'a1_2': 20.5},
 'a2': [],
 'a3': None,
 'a4': {'a4_1': None, 'a4_2': {'a4_2_1': None, 'a4_2_2': None}},
 'a5': [{'a5_1': 'pear', 'a5_2': None}, {'a5_1': None, 'a5_2': 18.5}]}

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