为数据集生成随机的JSON结构排列

Question

我想生成许多不同的JSON结构排列作为相同数据集的表示，最好而不必硬编码实现。例如，给定以下JSON：

{"name": "smith", "occupation": "agent", "enemy": "humanity", "nemesis": "neo"}`

应该产生许多不同的排列，例如：

• 名称更改：{"name":"smith"}- > {"last_name":"smith"}
• 更改顺序：{"name":"...","occupation":"..."} -> {"occupation":"...", "name":"..."}
• 安排更改：{"name":"...","occupation":"..."} -> "smith":{"occupation":"..."}
• 模板中的更改：{"name":"...","occupation":"..."} -> "status": 200, "data":{"name":"...","occupation":"..."}
• 等。

目前，实现如下：

我正在使用itertools.permutations和OrderedDict（）来遍历可能的键和相应的值组合以及它们返回的顺序。

key_permutations = SchemaLike(...).permutate()
all_simulacrums = []
for key_permutation in key_permutations:
   simulacrums = OrderedDict(key_permutation)
   all_simulacrums.append(simulacrums)
for x in itertools.permutations(all_simulacrums.items()):
    test_data = json.dumps(OrderedDict(p))
    print(test_data)
    assert json.loads(test_data) == data, 'Oops! {} != {}'.format(test_data, data)

当我尝试实现安排和模板的排列时，就会发生我的问题。我不知道如何最好地实施此功能？

Answer 1

用于订购，只需使用订购的dicts：

>>> data = OrderedDict(foo='bar', bacon='eggs', bar='foo', eggs='bacon')
>>> for p in itertools.permutations(data.items()):
...     test_data = json.dumps(OrderedDict(p))
...     print(test_data)
...     assert json.loads(test_data) == data, 'Oops! {} != {}'.format(test_data, data)
{"foo": "bar", "bacon": "eggs", "bar": "foo", "eggs": "bacon"}
{"foo": "bar", "bacon": "eggs", "eggs": "bacon", "bar": "foo"}
{"foo": "bar", "bar": "foo", "bacon": "eggs", "eggs": "bacon"}
{"foo": "bar", "bar": "foo", "eggs": "bacon", "bacon": "eggs"}
{"foo": "bar", "eggs": "bacon", "bacon": "eggs", "bar": "foo"}
{"foo": "bar", "eggs": "bacon", "bar": "foo", "bacon": "eggs"}
{"bacon": "eggs", "foo": "bar", "bar": "foo", "eggs": "bacon"}
{"bacon": "eggs", "foo": "bar", "eggs": "bacon", "bar": "foo"}
{"bacon": "eggs", "bar": "foo", "foo": "bar", "eggs": "bacon"}
{"bacon": "eggs", "bar": "foo", "eggs": "bacon", "foo": "bar"}
{"bacon": "eggs", "eggs": "bacon", "foo": "bar", "bar": "foo"}
{"bacon": "eggs", "eggs": "bacon", "bar": "foo", "foo": "bar"}
{"bar": "foo", "foo": "bar", "bacon": "eggs", "eggs": "bacon"}
{"bar": "foo", "foo": "bar", "eggs": "bacon", "bacon": "eggs"}
{"bar": "foo", "bacon": "eggs", "foo": "bar", "eggs": "bacon"}
{"bar": "foo", "bacon": "eggs", "eggs": "bacon", "foo": "bar"}
{"bar": "foo", "eggs": "bacon", "foo": "bar", "bacon": "eggs"}
{"bar": "foo", "eggs": "bacon", "bacon": "eggs", "foo": "bar"}
{"eggs": "bacon", "foo": "bar", "bacon": "eggs", "bar": "foo"}
{"eggs": "bacon", "foo": "bar", "bar": "foo", "bacon": "eggs"}
{"eggs": "bacon", "bacon": "eggs", "foo": "bar", "bar": "foo"}
{"eggs": "bacon", "bacon": "eggs", "bar": "foo", "foo": "bar"}
{"eggs": "bacon", "bar": "foo", "foo": "bar", "bacon": "eggs"}
{"eggs": "bacon", "bar": "foo", "bacon": "eggs", "foo": "bar"}

可以将相同的原理应用于密钥/值排列：

>>> for p in itertools.permutations(data.keys()):
...:     test_data = json.dumps(OrderedDict(zip(p, data.values())))
...:     print(test_data)
...:     
{"foo": "bar", "bacon": "eggs", "bar": "foo", "eggs": "bacon"}
{"foo": "bar", "bacon": "eggs", "eggs": "foo", "bar": "bacon"}
{"foo": "bar", "bar": "eggs", "bacon": "foo", "eggs": "bacon"}
{"foo": "bar", "bar": "eggs", "eggs": "foo", "bacon": "bacon"}
{"foo": "bar", "eggs": "eggs", "bacon": "foo", "bar": "bacon"}
{"foo": "bar", "eggs": "eggs", "bar": "foo", "bacon": "bacon"}
{"bacon": "bar", "foo": "eggs", "bar": "foo", "eggs": "bacon"}
{"bacon": "bar", "foo": "eggs", "eggs": "foo", "bar": "bacon"}
{"bacon": "bar", "bar": "eggs", "foo": "foo", "eggs": "bacon"}
{"bacon": "bar", "bar": "eggs", "eggs": "foo", "foo": "bacon"}
{"bacon": "bar", "eggs": "eggs", "foo": "foo", "bar": "bacon"}
{"bacon": "bar", "eggs": "eggs", "bar": "foo", "foo": "bacon"}
{"bar": "bar", "foo": "eggs", "bacon": "foo", "eggs": "bacon"}
{"bar": "bar", "foo": "eggs", "eggs": "foo", "bacon": "bacon"}
{"bar": "bar", "bacon": "eggs", "foo": "foo", "eggs": "bacon"}
{"bar": "bar", "bacon": "eggs", "eggs": "foo", "foo": "bacon"}
{"bar": "bar", "eggs": "eggs", "foo": "foo", "bacon": "bacon"}
{"bar": "bar", "eggs": "eggs", "bacon": "foo", "foo": "bacon"}
{"eggs": "bar", "foo": "eggs", "bacon": "foo", "bar": "bacon"}
{"eggs": "bar", "foo": "eggs", "bar": "foo", "bacon": "bacon"}
{"eggs": "bar", "bacon": "eggs", "foo": "foo", "bar": "bacon"}
{"eggs": "bar", "bacon": "eggs", "bar": "foo", "foo": "bacon"}
{"eggs": "bar", "bar": "eggs", "foo": "foo", "bacon": "bacon"}
{"eggs": "bar", "bar": "eggs", "bacon": "foo", "foo": "bacon"}

等等...如果您不需要所有组合，则可以使用预定义的键/值集。您也可以使用for循环使用random.choice来翻转硬币以跳过一些组合或使用random.shuffle以重复组合的风险。

对于模板的东西，我猜您必须创建一个不同模板的列表（如果需要嵌套结构的列表），然后在其上迭代以创建数据。为了提出更好的建议，我们需要对您想要的更限制的规范。

请注意，有几个库在Python中生成测试数据：

>>> from faker import Faker
>>> faker = Faker()
>>> faker.credit_card_full().strip().split('n')
['VISA 13 digit', 'Jerry Gutierrez', '4885274641760 04/24', 'CVC: 583']

Faker有多个模式，很容易创建您自己的自定义假数据提供商。

Answer 2

由于已经回答了DICT订单的混音，我会跳过。

我会添加这个答案，因为新事物想到了。

from random import randint
from collections import OrderedDict
#Randomly shuffles the key-value pairs of a dictionary
def random_dict_items(input_dict):
    items = input_dict.items()
    new_dict = OrderedDict()
    for i in items:
        rand = randint(0, 1)
        if rand == 0:
            new_dict[i[0]] = i[1]
        else:
            new_dict[i[1]] = i[0]
    return new_dict