晚了，但是这个答案不需要任何额外的库。类似于STH的答案，但在格式上更健壮一点，并返回一个完整的字符串，然后可以打印:

def pretty_print_dict(
        input_dictionary,
        indent=1,
        depth=0
):
    # Bool flag to add comma's after first item in dict.
    needs_comma = False
    # String for any dict will start with a '{'
    return_string = '\t' * depth + '{\n'
    # Iterate over keys and values, building the full string out.
    for key, value in input_dictionary.items():
        # Start with key. If key follows a previous item, add comma.
        if needs_comma:
            return_string = return_string + ',\n' + '\t' * (depth + 1) + str(key) + ': '
        else:
            return_string = return_string + '\t' * (depth + 1) + str(key) + ': '
        # If the value is a dict, recursively call function.
        if isinstance(value, dict):
            return_string = return_string + '\n' + pretty_print_dict(value, depth=depth+2)
        else:
            return_string = return_string + '\t' * indent + str(value)
        # After first line, flip bool to True to make sure commas make it.
        needs_comma = True
    # Complete the dict with a '}'
    return_string = return_string + '\n' + '\t' * depth + '}'
    # Return dict string.
    return return_string

让我们看看它如何处理像test_dict={1,2,3:{4:{5:6}， 7:8}， 9:10}这样的字典。

字符串的样子:“{\ n \ t1: \ t2, t3: \ n \ \ n \ t \ {\ n \ t \ \ t4: \ n \ t \ t \ \ {\ n \ t \ t \ \ \ t5: \ t6 \ n \ t \ t \ \ t}, \ n \ t \ \ t7: \ t8 \ n \ t \ t}, \ n \ t9: \ t10 \ n}”。

打印该字符串会得到:

{
    1:  2,
    3: 
        {
            4: 
                {
                    5:  6
                },
            7:  8
        },
    9:  10
}

我写了这段简单的代码，用Python打印json对象的一般结构。

def getstructure(data, tab = 0):
    if type(data) is dict:
        print ' '*tab + '{' 
        for key in data:
            print ' '*tab + '  ' + key + ':'
            getstructure(data[key], tab+4)
        print ' '*tab + '}'         
    elif type(data) is list and len(data) > 0:
        print ' '*tab + '['
        getstructure(data[0], tab+4)
        print ' '*tab + '  ...'
        print ' '*tab + ']'

以下数据的结果

a = {'list':['a','b',1,2],'dict':{'a':1,2:'b'},'tuple':('a','b',1,2),'function':'p','unicode':u'\xa7',("tuple","key"):"valid"}
getstructure(a)

非常紧凑，看起来像这样:

{
  function:
  tuple:
  list:
    [
      ...
    ]
  dict:
    {
      a:
      2:
    }
  unicode:
  ('tuple', 'key'):
}

例如，Pout可以漂亮地打印你扔给它的任何东西(借用另一个答案的数据):

data = {'a':2, 'b':{'x':3, 'y':{'t1': 4, 't2':5}}}
pout.vs(data)

将导致输出打印到屏幕上:

{
    'a': 2,
    'b':
    {
        'y':
        {
            't2': 5,
            't1': 4
        },
        'x': 3
    }
}

或者你可以返回对象的格式化字符串输出:

v = pout.s(data)

它的主要用途是调试，因此它不会阻塞对象实例或任何东西，它处理unicode输出，如你所期望的，在python 2.7和3中工作。

披露:我是撅嘴的作者和维护者。

yapf的另一个选择:

from pprint import pformat
from yapf.yapflib.yapf_api import FormatCode

dict_example = {'1': '1', '2': '2', '3': [1, 2, 3, 4, 5], '4': {'1': '1', '2': '2', '3': [1, 2, 3, 4, 5]}}
dict_string = pformat(dict_example)
formatted_code, _ = FormatCode(dict_string)

print(formatted_code)

输出:

{
    '1': '1',
    '2': '2',
    '3': [1, 2, 3, 4, 5],
    '4': {
        '1': '1',
        '2': '2',
        '3': [1, 2, 3, 4, 5]
    }
}

prettyformatter

免责声明:我是该软件包的作者。

有关与其他格式化程序的比较，请参阅其他格式化程序。

---

格式化

不像pprint。Pprint, prettyformatter更多地垂直传播，并尝试更多地对齐项目。

与json。转储，prettyformatter通常更紧凑，并尝试在合理的地方对齐字典值。

from prettyformatter import pprint

batters = [
    {"id": "1001", "type": "Regular"},
    {"id": "1002", "type": "Chocolate"},
    {"id": "1003", "type": "Blueberry"},
    {"id": "1004", "type": "Devil's Food"},
]

toppings = [
    {"id": "5001", "type": None},
    {"id": "5002", "type": "Glazed"},
    {"id": "5005", "type": "Sugar"},
    {"id": "5007", "type": "Powdered Sugar"},
    {"id": "5006", "type": "Chocolate with Sprinkles"},
    {"id": "5003", "type": "Chocolate"},
    {"id": "5004", "type": "Maple"},
]

data = {"id": "0001", "type": "donut", "name": "Cake", "ppu": 0.55, "batters": batters, "topping": toppings}

pprint(data)

输出:

{
    "id"    : "0001",
    "type"  : "donut",
    "name"  : "Cake",
    "ppu"   : 0.55,
    "batters":
        [
            {"id": "1001", "type": "Regular"},
            {"id": "1002", "type": "Chocolate"},
            {"id": "1003", "type": "Blueberry"},
            {"id": "1004", "type": "Devil's Food"},
        ],
    "topping":
        [
            {"id": "5001", "type": None},
            {"id": "5002", "type": "Glazed"},
            {"id": "5005", "type": "Sugar"},
            {"id": "5007", "type": "Powdered Sugar"},
            {"id": "5006", "type": "Chocolate with Sprinkles"},
            {"id": "5003", "type": "Chocolate"},
            {"id": "5004", "type": "Maple"},
        ],
}

---

特性

请在这里查看完整的文档。

JSON

不像pprint。pprint, prettyformatter通过JSON =True参数支持JSON转换。这包括将None更改为null, True更改为True, False更改为False，以及正确使用引号。

与json。转储，prettyformatter支持更多数据类型的JSON强制。这包括将任何数据类或映射更改为字典，将任何可迭代对象更改为列表。

from dataclasses import dataclass

from prettyformatter import PrettyDataclass, pprint


@dataclass(unsafe_hash=True)
class Point(PrettyDataclass):
    x: int
    y: int


pprint((Point(1, 2), Point(3, 4)), json=True)

输出:

[{"x": 1, "y": 2}, {"x": 3, "y": 4}]

定制

不像pprint。Pprint或json。转储，prettyformatter支持轻松定制附加类型。

为一个prettyformatter实现__pargs__和/或__pkwargs__方法。PrettyClass子类允许用户以“cls_name(*args， **kwargs)”的形式轻松地自定义类。

from prettyformatter import PrettyClass


class Dog(PrettyClass):

    def __init__(self, name, **kwargs):
        self.name = name

    def __pkwargs__(self):
        return {"name": self.name}


print(Dog("Fido"))
"""
Dog(name="Fido")
"""

print(Dog("Fido"), json=True)
"""
{"name": "Fido"}
"""

实现__pformat__方法可以实现更具体的pformat函数。

实现@prettyformatter。Register函数还允许以与实现__pformat__相同的方式自定义已经存在的类。

import numpy as np
from prettyformatter import pprint, register

@register(np.ndarray)
def pformat_ndarray(obj, specifier, depth, indent, shorten, json):
    if json:
        return pformat(obj.tolist(), specifier, depth, indent, shorten, json)
    with np.printoptions(formatter=dict(all=lambda x: format(x, specifier))):
        return repr(obj).replace("\n", "\n" + " " * depth)

pprint(dict.fromkeys("ABC", np.arange(9).reshape(3, 3)))

输出:

{
    "A":
        array([[0, 1, 2],
               [3, 4, 5],
               [6, 7, 8]]),
    "B":
        array([[0, 1, 2],
               [3, 4, 5],
               [6, 7, 8]]),
    "C":
        array([[0, 1, 2],
               [3, 4, 5],
               [6, 7, 8]]),
}

你可以使用打印字典

from print_dict import pd

dict1 = {
    'key': 'value'
} 

pd(dict1)

输出:

{
    'key': 'value'
}

---

此Python代码的输出:

{
    'one': 'value-one',
    'two': 'value-two',
    'three': 'value-three',
    'four': {
        '1': '1',
        '2': '2',
        '3': [1, 2, 3, 4, 5],
        '4': {
            'method': <function custom_method at 0x7ff6ecd03e18>,
            'tuple': (1, 2),
            'unicode': '✓',
            'ten': 'value-ten',
            'eleven': 'value-eleven',
            '3': [1, 2, 3, 4]
        }
    },
    'object1': <__main__.Object1 object at 0x7ff6ecc588d0>,
    'object2': <Object2 info>,
    'class': <class '__main__.Object1'>
}

---

安装:

$ pip install print-dict

---

披露:我是print-dict的作者