通过这种方式，你可以打印在漂亮的方式，例如你的字典名字是yasin

import json

print (json.dumps(yasin, indent=2))

或者,更安全:

print (json.dumps(yasin, indent=2, default=str))

我把sth的答案稍微修改一下，以适应我的嵌套字典和列表的需要:

def pretty(d, indent=0):
    if isinstance(d, dict):
        for key, value in d.iteritems():
            print '\t' * indent + str(key)
            if isinstance(value, dict) or isinstance(value, list):
                pretty(value, indent+1)
            else:
                print '\t' * (indent+1) + str(value)
    elif isinstance(d, list):
        for item in d:
            if isinstance(item, dict) or isinstance(item, list):
                pretty(item, indent+1)
            else:
                print '\t' * (indent+1) + str(item)
    else:
        pass

然后输出如下:

>>> 
xs:schema
    @xmlns:xs
        http://www.w3.org/2001/XMLSchema
    xs:redefine
        @schemaLocation
            base.xsd
        xs:complexType
            @name
                Extension
            xs:complexContent
                xs:restriction
                    @base
                        Extension
                    xs:sequence
                        xs:element
                            @name
                                Policy
                            @minOccurs
                                1
                            xs:complexType
                                xs:sequence
                                    xs:element
                                            ...

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]]),
}

最简单的方法是安装IPython并使用如下所示的方法

from IPython.lib.pretty import pretty


class MyClass:
    __repr__(self):
       return pretty(data)  # replace data with what makes sense

在你的情况下

print(pretty(mydict))

我必须传递默认参数，就像这样:

print(json.dumps(my_dictionary, indent=4, default=str))

如果你想要键排序，你可以这样做:

print(json.dumps(my_dictionary, sort_keys=True, indent=4, default=str))

为了修复此类型错误:

TypeError: Object of type 'datetime' is not JSON serializable

这是由于datetimes是字典中的一些值。

最python化的方法之一是使用已经构建的pprint模块。

定义打印深度所需的参数与您预期的深度相同

import pprint
pp = pprint.PrettyPrinter(depth=4)
pp.pprint(mydict)

就是这样!