我今天遇到了这个问题，我发现了一种叫做泡菜的东西。它是一个用于序列化python对象的内置库，也可以从pickle文件加载它。

我发现pickle和json之间唯一的区别是pickle文件是二进制文件，而json是通常的文本文件。

它不会对datetime对象造成任何问题。

在其他答案的基础上，一个简单的解决方案基于只转换datetime的特定序列化器。Datetime和Datetime。将对象日期指定为字符串。

from datetime import date, datetime

def json_serial(obj):
    """JSON serializer for objects not serializable by default json code"""

    if isinstance(obj, (datetime, date)):
        return obj.isoformat()
    raise TypeError ("Type %s not serializable" % type(obj))

As seen, the code just checks to find out if object is of class datetime.datetime or datetime.date, and then uses .isoformat() to produce a serialized version of it, according to ISO 8601 format, YYYY-MM-DDTHH:MM:SS (which is easily decoded by JavaScript). If more complex serialized representations are sought, other code could be used instead of str() (see other answers to this question for examples). The code ends by raising an exception, to deal with the case it is called with a non-serializable type.

这个json_serial函数可以这样使用:

from datetime import datetime
from json import dumps

print dumps(datetime.now(), default=json_serial)

详细说明如何将默认参数设置为json。可以在json模块文档的基本用法章节中找到dump作品。

Another approach is to adopt a concept from FEEL (the Friendly Enough Expression Language) defined in DMN (Decision Model Notation) - namely @strings. Any string starting with @" and ending with " is decoded separately with FEEL decoding. Of course the sender and the receiver have to agree to this convention, but ... the code below lets you encode lots of other things as well as dates, times, date/times, timedeltas. You can encode year/month durations and ranges (so long as you except a 4 element tuple of chr, expr, expr, chr as being a good representation of a range - where the two chrs are open/close brackets). So, @"P4Y2M" is a duration of 4 years and 2 months. @"P2DT5H" is a timedelta of 2 days and 4 hours, @"(2021-01-02 .. 2021-12-31)" is a year range.

下面的代码可用于序列化和反序列化@strings。

import datetime
import pySFeel

parser = pySFeel.SFeelParser()


def convertAtString(thisString):
    # Convert an @string
    (status, newValue) = parser.sFeelParse(thisString[2:-1])
    if 'errors' in status:
        return thisString
    else:
        return newValue


def convertIn(newValue):
    if isinstance(newValue, dict):
        for key in newValue:
            if isinstance(newValue[key], int):
                newValue[key] = float(newValue[key])
            elif isinstance(newValue[key], str) and (newValue[key][0:2] == '@"') and (newValue[key][-1] == '"'):
                newValue[key] = convertAtString(newValue[key])
            elif isinstance(newValue[key], dict) or isinstance(newValue[key], list):
                newValue[key] = convertIn(newValue[key])
    elif isinstance(newValue, list):
        for i in range(len(newValue)):
            if isinstance(newValue[i], int):
                newValue[i] = float(newValue[i])
            elif isinstance(newValue[i], str) and (newValue[i][0:2] == '@"') and (newValue[i][-1] == '"'):
                newValue[i] = convertAtString(newValue[i])
            elif isinstance(newValue[i], dict) or isinstance(newValue[i], list):
                newValue[i] = convertIn(newValue[i])
    elif isinstance(newValue, str) and (newValue[0:2] == '@"') and (newValue[-1] == '"'):
        newValue = convertAtString(newValue)
    return newValue


  def convertOut(thisValue):
      if isinstance(thisValue, datetime.date):
          return '@"' + thisValue.isoformat() + '"'
      elif isinstance(thisValue, datetime.datetime):
          return '@"' + thisValue.isoformat(sep='T') + '"'
      elif isinstance(thisValue, datetime.time):
          return '@"' + thisValue.isoformat() + '"'
      elif isinstance(thisValue, datetime.timedelta):
          sign = ''
          duration = thisValue.total_seconds()
          if duration < 0:
              duration = -duration
              sign = '-'
          secs = duration % 60
          duration = int(duration / 60)
          mins = duration % 60
          duration = int(duration / 60)
          hours = duration % 24
          days = int(duration / 24)
          return '@"%sP%dDT%dH%dM%fS"' % (sign, days, hours, mins, secs)
      elif isinstance(thisValue, bool):
          return thisValue:
      elif thisValue is None:
          return thisValue:
      elif isinstance(thisValue, int):
          sign = ''
          if thisValue < 0:
              thisValue = -thisValue
              sign = '-'
          years = int(thisValue / 12)
          months = (thisValue % 12)
          return '@"%sP%dY%dM"' % (sign, years, months)
      elif isinstance(thisValue, tuple) and (len(thisValue) == 4):
          (lowEnd, lowVal, highVal, highEnd) = thisValue
          return '@"' + lowEnd + str(lowVal) + ' .. ' + str(highVal) + highEnd
      elif thisValue is None:
          return 'null'
      elif isinstance(thisValue, dict):
          for item in thisValue:
              thisValue[item] = convertOut(thisValue[item])
          return thisValue
      elif isinstance(thisValue, list):
          for i in range(len(thisValue)):
              thisValue[i] = convertOut(thisValue[i])
          return thisValue
      else:
          return thisValue

其实很简单。 如果您需要经常序列化日期，那么可以将它们作为字符串使用。如果需要，您可以轻松地将它们转换回datetime对象。

如果您主要需要作为datetime对象工作，那么在序列化之前将它们转换为字符串。

import json, datetime

date = str(datetime.datetime.now())
print(json.dumps(date))
"2018-12-01 15:44:34.409085"
print(type(date))
<class 'str'>

datetime_obj = datetime.datetime.strptime(date, '%Y-%m-%d %H:%M:%S.%f')
print(datetime_obj)
2018-12-01 15:44:34.409085
print(type(datetime_obj))
<class 'datetime.datetime'>

如您所见，两种情况下的输出是相同的。只是类型不同。

这里有一个简单的解决方案来克服“datetime不可JSON序列化” 问题。

enco = lambda obj: (
    obj.isoformat()
    if isinstance(obj, datetime.datetime)
    or isinstance(obj, datetime.date)
    else None
)

json.dumps({'date': datetime.datetime.now()}, default=enco)

输出:-> {"date": "2015-12-16T04:48:20.024609"}

我的快速和肮脏的JSON转储吃日期和一切:

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

Default是一个应用于不可序列化对象的函数。 在这种情况下，它是str，所以它只是把所有它不知道的东西转换成字符串。这对于序列化很好，但在反序列化时就不太好了(因此是“快速和肮脏”)，因为任何东西都可能在没有警告的情况下被字符串化，例如函数或numpy数组。