有没有可靠的方法来检查对象的类是否是所需超级的子类?
例如,在我正在编写的迁移脚本中,我必须以给定的方式将给定类型的对象转换为字典,以确保数据的双向兼容性。
最好总结如下:
但是,当我在depickling之后递归检查对象时,我会收到一个Test对象,它会产生以下结果:
测试数据对象类型:
type(data)
{型}< class'_ main.Test'>
测试类类型:
type(Test())
{型}< class'_ main.Test'>
针对类类型测试对象类型:
type(Test()) == type(data)
{BOOL}假
测试对象isinstance()是否为Class:
isinstance(data, Test)
{BOOL}假
测试超类的Class isinstance():
isinstance(Test(), Serializable)
{BOOL}真
测试Super Class ::
的isinstance()isinstance(data, Serializable)
{BOOL}假
有趣的是,它在酸洗之前似乎没有任何这样的问题,因为它处理字典和完整性哈希的创建就好了。 这只会与Pickle和Dill中的去除物体一起出现。
对于Context,这是其本机环境中的代码 - 被pickle的DataCache对象:
class DataCache(object):
_hash=""
_data = None
@staticmethod
def genHash(data):
dataDict = DataCache.dictify(data)
datahash = json.dumps(dataDict, sort_keys=True)
return hashlib.sha256(datahash).digest()
@staticmethod
def dictify(data):
if isinstance(data,list):
datahash = []
for item in data:
datahash.append(DataCache.dictify(item))
elif isinstance(data,(dict, collections.OrderedDict)):
datahash = collections.OrderedDict()
for key,value in datahash.iteritems():
datahash[key]= DataCache.dictify(value)
elif isinstance(data, Serializable):
datahash = data.toDict()
else:
datahash = data
return datahash
def __init__(self, restoreDict = {}):
if restoreDict:
self.__dict__.update(restoreDict)
def __getinitargs__(self):
return (self.__dict__)
def set(self, data):
self._hash = DataCache.genHash(data)
self._data = data
def verify(self):
dataHash = DataCache.genHash(self._data)
return (self._hash == dataHash)
def get(self):
return self._data
最后,我知道在存储中使用JSON的可读性存在争议,我需要Pickle能够直接转换为Object,而不是自己指定对象类型。 (感谢嵌套,这不太可行)
我是否在这里生气或者在课堂定义上做些什么?
修改
最小化实施:
#!/usr/bin/python
# -*- coding: UTF-8 -*-
import requests
from aenum import Enum
import json # _tricks
import base64
import argparse
import os
import sys
import datetime
import dill
import hashlib
import collections
class Serializable(object):
def __init__(self, initDict={}):
if initDict:
self.__dict__.update(initDict)
def __str__(self):
return str(self.sortSelf())
def sortSelf(self):
return collections.OrderedDict(sorted(self.__dict__.items()))
def toDict(self):
return self.__dict__
def fromDict(self, dict):
# Not using __dict__.update(...) to avoid polluting objects with the excess data
varMap = self.__dict__
if dict and varMap:
for key in varMap:
if (key in dict):
varMap[key] = dict[key]
self.__dict__.update(varMap)
return self
return None
class Issue(Serializable):
def __init__(self, initDict={}):
self.id = 0
self.key = ""
self.fields = {}
if initDict:
self.__dict__.update(initDict)
Serializable.__init__(self)
def fieldToDict(self, obj, key, type):
if key in obj:
result = obj[key]
else:
return None
if result is None:
return None
if isinstance(result, type):
return result.toDict()
return result
def fromDict(self, jsonDict):
super(Issue, self).fromDict(jsonDict)
self.fields["issuetype"] = IssueType().fromDict(self.fields["issuetype"])
self.fields["assignee"] = User().fromDict(self.fields["assignee"])
self.fields["creator"] = User().fromDict(self.fields["creator"])
self.fields["reporter"] = User().fromDict(self.fields["reporter"])
return self
def toDict(self):
result = super(Issue, self).toDict()
blankKeys = []
for fieldName, fieldValue in self.fields.iteritems():
if fieldValue is None:
blankKeys.append(fieldName)
if blankKeys:
for key in blankKeys:
self.fields.pop(key, None)
result["fields"]["issuetype"] = self.fieldToDict(result["fields"], "issuetype", IssueType)
result["fields"]["creator"] = self.fieldToDict(result["fields"], "creator", User)
result["fields"]["reporter"] = self.fieldToDict(result["fields"], "reporter", User)
result["fields"]["assignee"] = self.fieldToDict(result["fields"], "assignee", User)
return result
class IssueType(Serializable):
def __init__(self):
self.id = 0
self.name = ""
def toDict(self):
return {"id": str(self.id)}
class Project(Serializable):
def __init__(self):
Serializable.__init__(self)
self.id = 0
self.name = ""
self.key = ""
class Cycle(Serializable):
def __init__(self):
self.id = 0
self.name = ""
self.totalExecutions = 0
self.endDate = ""
self.description = ""
self.totalExecuted = 0
self.started = ""
self.versionName = ""
self.projectKey = ""
self.versionId = 0
self.environment = ""
self.totalCycleExecutions = 0
self.build = ""
self.ended = ""
self.name = ""
self.modifiedBy = ""
self.projectId = 0
self.startDate = ""
self.executionSummaries = {'executionSummary': []}
class Step(Serializable):
def __init__(self):
self.id = ""
self.orderId = 0
self.step = ""
self.data = ""
self.result = ""
self.attachmentsMap = {}
def toDict(self):
dict = {}
dict["step"] = self.step
dict["data"] = self.data
dict["result"] = self.result
dict["attachments"] = []
return dict
class Status(Serializable):
def __init__(self):
self.id = 0
self.name = ""
self.description = ""
self.isFinal = True
self.color = ""
self.isNative = True
self.statusCount = 0
self.statusPercent = 0.0
class User(Serializable):
def __init__(self):
self.displayName = ""
self.name = ""
self.emailAddress = ""
self.key = ""
self.active = False
self.timeZone = ""
class Execution(Serializable):
def __init__(self):
self.id = 0
self.orderId = 0
self.cycleId = -1
self.cycleName = ""
self.issueId = 0
self.issueKey = 0
self.projectKey = ""
self.comment = ""
self.versionId = 0,
self.versionName = "",
self.executedOn = ""
self.creationDate = ""
self.executedByUserName = ""
self.assigneeUserName = ""
self.status = {}
self.executionStatus = ""
def fromDict(self, jsonDict):
super(Execution, self).fromDict(jsonDict)
self.status = Status().fromDict(self.status)
# This is already listed as Execution Status, need to associate and convert!
return self
def toDict(self):
result = super(Execution, self).toDict()
result['status'] = result['status'].toDict()
return result
class ExecutionContainer(Serializable):
def __init__(self):
self.executions = []
def fromDict(self, jsonDict):
super(ExecutionContainer, self).fromDict(jsonDict)
self.executions = []
for executionDict in jsonDict["executions"]:
self.executions.append(Execution().fromDict(executionDict))
return self
class Test(Issue):
def __init__(self, initDict={}):
if initDict:
self.__dict__.update(initDict)
Issue.__init__(self)
def toDict(self):
result = super(Test, self).toDict()
stepField = "CustomField_0001"
if result["fields"][stepField]:
steps = []
for step in result["fields"][stepField]["steps"]:
steps.append(step.toDict())
result["fields"][stepField] = steps
return result
def fromDict(self, jsonDict):
super(Test, self).fromDict(jsonDict)
stepField = "CustomField_0001"
steps = []
if stepField in self.fields:
for step in self.fields[stepField]["steps"]:
steps.append(Step().fromDict(step))
self.fields[stepField] = {"steps": steps}
return self
class Set(Issue):
def __init__(self, initDict={}):
self.__dict__.update(initDict)
Issue.__init__(self)
class DataCache(object):
_hash = ""
_data = None
@staticmethod
def genHash(data):
dataDict = DataCache.dictify(data)
datahash = json.dumps(dataDict, sort_keys=True)
return hashlib.sha256(datahash).digest()
@staticmethod
def dictify(data):
if isinstance(data, list):
datahash = []
for item in data:
datahash.append(DataCache.dictify(item))
elif isinstance(data, (dict, collections.OrderedDict)):
datahash = collections.OrderedDict()
for key, value in datahash.iteritems():
datahash[key] = DataCache.dictify(value)
elif isinstance(data, Serializable):
datahash = data.toDict()
else:
datahash = data
return datahash
def __init__(self, restoreDict={}):
if restoreDict:
self.__dict__.update(restoreDict)
def __getinitargs__(self):
return (self.__dict__)
def set(self, data):
self._hash = DataCache.genHash(data)
self._data = data
def verify(self):
dataHash = DataCache.genHash(self._data)
return (self._hash == dataHash)
def get(self):
return self._data
def saveCache(name, projectKey, object):
filePath = "migration_caches/{projectKey}".format(projectKey=projectKey)
if not os.path.exists(path=filePath):
os.makedirs(filePath)
cache = DataCache()
cache.set(object)
targetFile = open("{path}/{name}".format(name=name, path=filePath), 'wb')
dill.dump(obj=cache, file=targetFile)
targetFile.close()
def loadCache(name, projectKey):
filePath = "migration_caches/{projectKey}/{name}".format(name=name, projectKey=projectKey)
result = False
try:
targetFile = open(filePath, 'rb')
try:
cache = dill.load(targetFile)
if isinstance(cache, DataCache):
if cache.verify():
result = cache.get()
except EOFError:
# except BaseException:
print ("Failed to load cache from file: {filePath}\n".format(filePath=filePath))
except IOError:
("Failed to load cache file at: {filePath}\n".format(filePath=filePath))
targetFile.close()
return result
testIssue = Test().fromDict({"id": 1000,
"key": "TEST",
"fields": {
"issuetype": {
"id": 1,
"name": "TestIssue"
},
"assignee": "Minothor",
"reporter": "Minothor",
"creator": "Minothor",
}
})
saveCache("Test", "TestProj", testIssue)
result = loadCache("Test", "TestProj")
编辑2
它当前形式的脚本现在似乎与vanilla Pickle一起正常工作(由于类似问题,最初切换到Dill,这是由交换机解决的)。
但是,如果您在这里遇到此问题并需要Dill的功能,那么正如Mike在评论中所指出的那样 - 可以更改dill.settings
中的设置,让Dill仅使用{{1}来表示pickle引用的项目模式,有效地反映了泡菜的标准酸洗行为。