我有两本字典，但为了简化起见，我就选这两本:
>>> x = dict(a=1, b=2)
>>> y = dict(a=2, b=2)
现在，我想比较x中的每个键值对在y中是否有相同的对应值，所以我这样写:
>>> for x_values, y_values in zip(x.iteritems(), y.iteritems()):
if x_values == y_values:
print 'Ok', x_values, y_values
else:
print 'Not', x_values, y_values
它的工作原理是返回一个元组，然后比较是否相等。
我的问题:
这对吗?还有更好的办法吗?最好不是在速度上，我说的是代码优雅。
更新:我忘了提到，我必须检查有多少键，值对是相等的。
当前回答
为什么不只是遍历一个字典，并在过程中检查另一个字典(假设两个字典都有相同的键)?
x = dict(a=1, b=2)
y = dict(a=2, b=2)
for key, val in x.items():
if val == y[key]:
print ('Ok', val, y[key])
else:
print ('Not', val, y[key])
输出:
Not 1 2
Ok 2 2
其他回答
由于似乎没有人提到deepdiff，为了完整起见，我将在这里添加它。我发现它非常方便获得(嵌套)对象的差异:
安装
pip install deepdiff
示例代码
import deepdiff
import json
dict_1 = {
"a": 1,
"nested": {
"b": 1,
}
}
dict_2 = {
"a": 2,
"nested": {
"b": 2,
}
}
diff = deepdiff.DeepDiff(dict_1, dict_2)
print(json.dumps(diff, indent=4))
输出
{
"values_changed": {
"root['a']": {
"new_value": 2,
"old_value": 1
},
"root['nested']['b']": {
"new_value": 2,
"old_value": 1
}
}
}
注意关于检查结果的漂亮打印:如果两个字典具有相同的属性键(可能与示例中的属性值不同)，上面的代码就可以工作。但是，如果存在一个“extra”属性是字典之一，json.dumps()将失败
TypeError: Object of type PrettyOrderedSet is not JSON serializable
解决方案:使用diff.to_json()和json.loads() / json.dumps()来漂亮地打印:
import deepdiff
import json
dict_1 = {
"a": 1,
"nested": {
"b": 1,
},
"extra": 3
}
dict_2 = {
"a": 2,
"nested": {
"b": 2,
}
}
diff = deepdiff.DeepDiff(dict_1, dict_2)
print(json.dumps(json.loads(diff.to_json()), indent=4))
输出:
{
"dictionary_item_removed": [
"root['extra']"
],
"values_changed": {
"root['a']": {
"new_value": 2,
"old_value": 1
},
"root['nested']['b']": {
"new_value": 2,
"old_value": 1
}
}
}
替代方案:使用pprint，结果是不同的格式:
import pprint
# same code as above
pprint.pprint(diff, indent=4)
输出:
{ 'dictionary_item_removed': [root['extra']],
'values_changed': { "root['a']": { 'new_value': 2,
'old_value': 1},
"root['nested']['b']": { 'new_value': 2,
'old_value': 1}}}
在PyUnit中有一个比较字典的方法。我使用以下两个字典对它进行了测试，它完全符合您的要求。
d1 = {1: "value1",
2: [{"subKey1":"subValue1",
"subKey2":"subValue2"}]}
d2 = {1: "value1",
2: [{"subKey2":"subValue2",
"subKey1": "subValue1"}]
}
def assertDictEqual(self, d1, d2, msg=None):
self.assertIsInstance(d1, dict, 'First argument is not a dictionary')
self.assertIsInstance(d2, dict, 'Second argument is not a dictionary')
if d1 != d2:
standardMsg = '%s != %s' % (safe_repr(d1, True), safe_repr(d2, True))
diff = ('\n' + '\n'.join(difflib.ndiff(
pprint.pformat(d1).splitlines(),
pprint.pformat(d2).splitlines())))
standardMsg = self._truncateMessage(standardMsg, diff)
self.fail(self._formatMessage(msg, standardMsg))
我不建议在生产代码中导入unittest。我的想法是，PyUnit中的源代码可以重新配置，以在生产环境中运行。它使用pprint来“漂亮地打印”字典。调整这段代码以使其“适合生产”似乎很容易。
@mouad的答案很好，如果你假设两个字典都只包含简单的值。然而，如果你有包含字典的字典，你会得到一个异常，因为字典是不可哈希的。
在我的脑海中，这样做可能有用:
def compare_dictionaries(dict1, dict2):
if dict1 is None or dict2 is None:
print('Nones')
return False
if (not isinstance(dict1, dict)) or (not isinstance(dict2, dict)):
print('Not dict')
return False
shared_keys = set(dict1.keys()) & set(dict2.keys())
if not ( len(shared_keys) == len(dict1.keys()) and len(shared_keys) == len(dict2.keys())):
print('Not all keys are shared')
return False
dicts_are_equal = True
for key in dict1.keys():
if isinstance(dict1[key], dict) or isinstance(dict2[key], dict):
dicts_are_equal = dicts_are_equal and compare_dictionaries(dict1[key], dict2[key])
else:
dicts_are_equal = dicts_are_equal and all(atleast_1d(dict1[key] == dict2[key]))
return dicts_are_equal
下面的代码将帮助您比较python中的dict列表
def compate_generic_types(object1, object2):
if isinstance(object1, str) and isinstance(object2, str):
return object1 == object2
elif isinstance(object1, unicode) and isinstance(object2, unicode):
return object1 == object2
elif isinstance(object1, bool) and isinstance(object2, bool):
return object1 == object2
elif isinstance(object1, int) and isinstance(object2, int):
return object1 == object2
elif isinstance(object1, float) and isinstance(object2, float):
return object1 == object2
elif isinstance(object1, float) and isinstance(object2, int):
return object1 == float(object2)
elif isinstance(object1, int) and isinstance(object2, float):
return float(object1) == object2
return True
def deep_list_compare(object1, object2):
retval = True
count = len(object1)
object1 = sorted(object1)
object2 = sorted(object2)
for x in range(count):
if isinstance(object1[x], dict) and isinstance(object2[x], dict):
retval = deep_dict_compare(object1[x], object2[x])
if retval is False:
print "Unable to match [{0}] element in list".format(x)
return False
elif isinstance(object1[x], list) and isinstance(object2[x], list):
retval = deep_list_compare(object1[x], object2[x])
if retval is False:
print "Unable to match [{0}] element in list".format(x)
return False
else:
retval = compate_generic_types(object1[x], object2[x])
if retval is False:
print "Unable to match [{0}] element in list".format(x)
return False
return retval
def deep_dict_compare(object1, object2):
retval = True
if len(object1) != len(object2):
return False
for k in object1.iterkeys():
obj1 = object1[k]
obj2 = object2[k]
if isinstance(obj1, list) and isinstance(obj2, list):
retval = deep_list_compare(obj1, obj2)
if retval is False:
print "Unable to match [{0}]".format(k)
return False
elif isinstance(obj1, dict) and isinstance(obj2, dict):
retval = deep_dict_compare(obj1, obj2)
if retval is False:
print "Unable to match [{0}]".format(k)
return False
else:
retval = compate_generic_types(obj1, obj2)
if retval is False:
print "Unable to match [{0}]".format(k)
return False
return retval
只使用:
assert cmp(dict1, dict2) == 0
