我有一本嵌套的字典。是否只有一种方法可以安全地传递价值观?
try:
example_dict['key1']['key2']
except KeyError:
pass
或者python有一个类似get()的方法用于嵌套字典?
我有一本嵌套的字典。是否只有一种方法可以安全地传递价值观?
try:
example_dict['key1']['key2']
except KeyError:
pass
或者python有一个类似get()的方法用于嵌套字典?
你可以使用get两次:
example_dict.get('key1', {}).get('key2')
如果key1或key2不存在,则返回None。
注意,如果example_dict['key1']存在但不是dict(或具有get方法的类dict对象),仍然可能引发AttributeError。如果example_dict['key1']不可下标,你发布的try..except代码将引发TypeError。
另一个区别是try…除非在第一次丢失钥匙后立即发生短路。get调用链则不然。
如果您希望保留语法example_dict['key1']['key2'],但不希望它引发KeyErrors,那么您可以使用哈希recipe:
class Hasher(dict):
# https://stackoverflow.com/a/3405143/190597
def __missing__(self, key):
value = self[key] = type(self)()
return value
example_dict = Hasher()
print(example_dict['key1'])
# {}
print(example_dict['key1']['key2'])
# {}
print(type(example_dict['key1']['key2']))
# <class '__main__.Hasher'>
注意,当缺少一个键时,返回一个空的hash。
因为Hasher是dict的一个子类,你可以像使用dict一样使用Hasher。所有相同的方法和语法都是可用的,哈希器只是以不同的方式对待缺失的键。
你可以像这样把一个普通字典转换成哈希:
hasher = Hasher(example_dict)
并将哈希转换为普通字典一样容易:
regular_dict = dict(hasher)
另一种选择是在helper函数中隐藏丑陋的代码:
def safeget(dct, *keys):
for key in keys:
try:
dct = dct[key]
except KeyError:
return None
return dct
这样你剩下的代码就可以保持相对的可读性:
safeget(example_dict, 'key1', 'key2')
你也可以使用python reduce:
def deep_get(dictionary, *keys):
return reduce(lambda d, key: d.get(key) if d else None, keys, dictionary)
在深入获取属性后,我使用点表示法安全地获得嵌套的dict值。这适用于我,因为我的字典是反序列化的MongoDB对象,所以我知道键名不包含.s。此外,在我的上下文中,我可以指定一个数据中没有的虚假回退值(None),因此在调用函数时可以避免使用try/except模式。
from functools import reduce # Python 3
def deepgetitem(obj, item, fallback=None):
"""Steps through an item chain to get the ultimate value.
If ultimate value or path to value does not exist, does not raise
an exception and instead returns `fallback`.
>>> d = {'snl_final': {'about': {'_icsd': {'icsd_id': 1}}}}
>>> deepgetitem(d, 'snl_final.about._icsd.icsd_id')
1
>>> deepgetitem(d, 'snl_final.about._sandbox.sbx_id')
>>>
"""
def getitem(obj, name):
try:
return obj[name]
except (KeyError, TypeError):
return fallback
return reduce(getitem, item.split('.'), obj)
根据Yoav的回答,一个更安全的方法是:
def deep_get(dictionary, *keys):
return reduce(lambda d, key: d.get(key, None) if isinstance(d, dict) else None, keys, dictionary)
虽然reduce方法简洁而简短,但我认为简单的循环更容易理解。我还包含了一个默认参数。
def deep_get(_dict, keys, default=None):
for key in keys:
if isinstance(_dict, dict):
_dict = _dict.get(key, default)
else:
return default
return _dict
作为理解reduce一行程序如何工作的练习,我执行了以下操作。但最终循环方法对我来说似乎更直观。
def deep_get(_dict, keys, default=None):
def _reducer(d, key):
if isinstance(d, dict):
return d.get(key, default)
return default
return reduce(_reducer, keys, _dict)
使用
nested = {'a': {'b': {'c': 42}}}
print deep_get(nested, ['a', 'b'])
print deep_get(nested, ['a', 'b', 'z', 'z'], default='missing')
一个简单的类,可以包装字典,并根据键进行检索:
class FindKey(dict):
def get(self, path, default=None):
keys = path.split(".")
val = None
for key in keys:
if val:
if isinstance(val, list):
val = [v.get(key, default) if v else None for v in val]
else:
val = val.get(key, default)
else:
val = dict.get(self, key, default)
if not val:
break
return val
例如:
person = {'person':{'name':{'first':'John'}}}
FindDict(person).get('person.name.first') # == 'John'
如果该键不存在,则默认返回None。你可以在FindDict包装器中使用default=键覆盖它,例如':
FindDict(person, default='').get('person.name.last') # == doesn't exist, so ''
通过把所有这些答案和我做的小改变结合起来,我认为这个函数会很有用。安全、快捷、易于维护。
def deep_get(dictionary, keys, default=None):
return reduce(lambda d, key: d.get(key, default) if isinstance(d, dict) else default, keys.split("."), dictionary)
例子:
from functools import reduce
def deep_get(dictionary, keys, default=None):
return reduce(lambda d, key: d.get(key, default) if isinstance(d, dict) else default, keys.split("."), dictionary)
person = {'person':{'name':{'first':'John'}}}
print(deep_get(person, "person.name.first")) # John
print(deep_get(person, "person.name.lastname")) # None
print(deep_get(person, "person.name.lastname", default="No lastname")) # No lastname
unutbu回答的一个改编,我发现在我自己的代码中很有用:
example_dict.setdefaut('key1', {}).get('key2')
如果key1还没有这个键,它会为它生成一个字典条目,以避免出现KeyError。如果您希望像我这样以包含键对的嵌套字典结束,这似乎是最简单的解决方案。
递归解。它不是最有效的,但我发现它比其他示例更具可读性,而且它不依赖于functools。
def deep_get(d, keys):
if not keys or d is None:
return d
return deep_get(d.get(keys[0]), keys[1:])
例子
d = {'meta': {'status': 'OK', 'status_code': 200}}
deep_get(d, ['meta', 'status_code']) # => 200
deep_get(d, ['garbage', 'status_code']) # => None
一个更精致的版本
def deep_get(d, keys, default=None):
"""
Example:
d = {'meta': {'status': 'OK', 'status_code': 200}}
deep_get(d, ['meta', 'status_code']) # => 200
deep_get(d, ['garbage', 'status_code']) # => None
deep_get(d, ['meta', 'garbage'], default='-') # => '-'
"""
assert type(keys) is list
if d is None:
return default
if not keys:
return d
return deep_get(d.get(keys[0]), keys[1:], default)
因为如果缺少一个键就会引发一个键错误是合理的,我们甚至可以不检查它,让它像这样单一:
def get_dict(d, kl):
cur = d[kl[0]]
return get_dict(cur, kl[1:]) if len(kl) > 1 else cur
我建议你试试蟒蛇本尼迪克特。
它是一个dict子类,提供小键盘支持等功能。
安装:pip install python-benedict
from benedict import benedict
example_dict = benedict(example_dict, keypath_separator='.')
现在你可以使用keypath访问嵌套值:
val = example_dict['key1.key2']
# using 'get' method to avoid a possible KeyError:
val = example_dict.get('key1.key2')
或者使用键列表访问嵌套值:
val = example_dict['key1', 'key2']
# using get to avoid a possible KeyError:
val = example_dict.get(['key1', 'key2'])
它在GitHub上经过了很好的测试和开源:
https://github.com/fabiocaccamo/python-benedict
注:我是这个项目的作者
减少方法的改进很少,使其与列表一起工作。也使用数据路径作为字符串除以点,而不是数组。
def deep_get(dictionary, path):
keys = path.split('.')
return reduce(lambda d, key: d[int(key)] if isinstance(d, list) else d.get(key) if d else None, keys, dictionary)
还有一个相同功能的函数,也返回一个布尔值来表示是否找到键,并处理一些意想不到的错误。
'''
json : json to extract value from if exists
path : details.detail.first_name
empty path represents root
returns a tuple (boolean, object)
boolean : True if path exists, otherwise False
object : the object if path exists otherwise None
'''
def get_json_value_at_path(json, path=None, default=None):
if not bool(path):
return True, json
if type(json) is not dict :
raise ValueError(f'json={json}, path={path} not supported, json must be a dict')
if type(path) is not str and type(path) is not list:
raise ValueError(f'path format {path} not supported, path can be a list of strings like [x,y,z] or a string like x.y.z')
if type(path) is str:
path = path.strip('.').split('.')
key = path[0]
if key in json.keys():
return get_json_value_at_path(json[key], path[1:], default)
else:
return False, default
使用示例:
my_json = {'details' : {'first_name' : 'holla', 'last_name' : 'holla'}}
print(get_json_value_at_path(my_json, 'details.first_name', ''))
print(get_json_value_at_path(my_json, 'details.phone', ''))
(真的,大声叫) (假的,”)
我使用的一个解决方案类似于double get,但具有使用if else逻辑避免TypeError的额外能力:
value = example_dict['key1']['key2'] if example_dict.get('key1') and example_dict['key1'].get('key2') else default_value
然而,字典嵌套越多,这就变得越麻烦。
对于嵌套的字典/JSON查找,可以使用dictor
PIP安装指示器
dict对象
{
"characters": {
"Lonestar": {
"id": 55923,
"role": "renegade",
"items": [
"space winnebago",
"leather jacket"
]
},
"Barfolomew": {
"id": 55924,
"role": "mawg",
"items": [
"peanut butter jar",
"waggy tail"
]
},
"Dark Helmet": {
"id": 99999,
"role": "Good is dumb",
"items": [
"Shwartz",
"helmet"
]
},
"Skroob": {
"id": 12345,
"role": "Spaceballs CEO",
"items": [
"luggage"
]
}
}
}
要获得龙星的物品,只需提供一个点分隔的路径,即
import json
from dictor import dictor
with open('test.json') as data:
data = json.load(data)
print dictor(data, 'characters.Lonestar.items')
>> [u'space winnebago', u'leather jacket']
如果键不在路径中,您可以提供回退值
你还有很多选择,比如忽略字母大小写,使用'以外的其他字符。作为路径分隔符,
https://github.com/perfecto25/dictor
我稍微改变了一下答案。我添加了检查,如果我们使用列表与数字。 所以现在我们可以用任何一种方法。deep_get(allTemp,[0],{})或deep_get(getMinimalTemp, [0, minimalTemperatureKey], 26)等
def deep_get(_dict, keys, default=None):
def _reducer(d, key):
if isinstance(d, dict):
return d.get(key, default)
if isinstance(d, list):
return d[key] if len(d) > 0 else default
return default
return reduce(_reducer, keys, _dict)
你可以使用pydash:
import pydash as _ #NOTE require `pip install pydash`
_.get(example_dict, 'key1.key2', default='Default')
https://pydash.readthedocs.io/en/latest/api.html
已经有很多很好的答案,但我已经提出了一个类似于JavaScript领域的lodash get的函数,它也支持通过索引进入列表:
def get(value, keys, default_value = None):
'''
Useful for reaching into nested JSON like data
Inspired by JavaScript lodash get and Clojure get-in etc.
'''
if value is None or keys is None:
return None
path = keys.split('.') if isinstance(keys, str) else keys
result = value
def valid_index(key):
return re.match('^([1-9][0-9]*|[0-9])$', key) and int(key) >= 0
def is_dict_like(v):
return hasattr(v, '__getitem__') and hasattr(v, '__contains__')
for key in path:
if isinstance(result, list) and valid_index(key) and int(key) < len(result):
result = result[int(key)] if int(key) < len(result) else None
elif is_dict_like(result) and key in result:
result = result[key]
else:
result = default_value
break
return result
def test_get():
assert get(None, ['foo']) == None
assert get({'foo': 1}, None) == None
assert get(None, None) == None
assert get({'foo': 1}, []) == {'foo': 1}
assert get({'foo': 1}, ['foo']) == 1
assert get({'foo': 1}, ['bar']) == None
assert get({'foo': 1}, ['bar'], 'the default') == 'the default'
assert get({'foo': {'bar': 'hello'}}, ['foo', 'bar']) == 'hello'
assert get({'foo': {'bar': 'hello'}}, 'foo.bar') == 'hello'
assert get({'foo': [{'bar': 'hello'}]}, 'foo.0.bar') == 'hello'
assert get({'foo': [{'bar': 'hello'}]}, 'foo.1') == None
assert get({'foo': [{'bar': 'hello'}]}, 'foo.1.bar') == None
assert get(['foo', 'bar'], '1') == 'bar'
assert get(['foo', 'bar'], '2') == None
递归法(мб п п и и одитс)
示例dict类型:
foo = [{'feature_name': 'Sample Creator > Contract Details > Elements of the page',
'scenarios': [{'scenario_name': 'SC, CD, Elements of the page',
'scenario_status': 'failed',
'scenario_tags': None,
'steps': [{'duration': 0,
'name': 'I open application Stage and login by '
'SPT_LOGIN and password SPT_PWD',
'status': 'untested'},
{'duration': 0,
'name': 'I open Sample Creator query page',
'status': 'untested'},
{'duration': 7.78166389465332,
'name': 'I open application Stage and login by '
'SPT_LOGIN and password SPT_PWD',
'status': 'passed'},
{'duration': 3.985326051712036,
'name': 'I open Sample Creator query page',
'status': 'passed'},
{'duration': 2.9063704013824463,
'name': 'Enter value: '
'X-2008-CON-007,X-2011-CON-016 in '
'textarea: project_text_area sleep: 1',
'status': 'passed'},
{'duration': 4.4447715282440186,
'name': 'I press on GET DATA',
'status': 'passed'},
{'duration': 1.1209557056427002,
'name': 'Verify the top table on Contract Details',
'status': 'passed'},
{'duration': 3.8173601627349854,
'name': 'I export contract_details table by offset '
'x:100, y:150',
'status': 'passed'},
{'duration': 1.032956600189209,
'name': 'Check data of '
'sc__cd_elements_of_the_page_1 and skip '
'cols None',
'status': 'passed'},
{'duration': 0.04593634605407715,
'name': "Verify 'Number of Substances' column "
'values',
'status': 'passed'},
{'duration': 0.10199904441833496,
'name': 'Substance Sample Details bottom table '
'columns',
'status': 'passed'},
{'duration': 0.0009999275207519531,
'name': 'Verify the Substance Sample Details '
'bottom table',
'status': 'passed'},
{'duration': 3.8558616638183594,
'name': 'I export substance_sample_details table '
'by offset x:100, y:150',
'status': 'passed'},
{'duration': 1.0329277515411377,
'name': 'Check data of '
'sc__cd_elements_of_the_page_2 and skip '
'cols None',
'status': 'passed'},
{'duration': 0.2879970073699951,
'name': 'Click on AG-13369',
'status': 'passed'},
{'duration': 3.800830364227295,
'name': 'I export substance_sample_details table '
'by offset x:100, y:150',
'status': 'passed'},
{'duration': 1.0169551372528076,
'name': 'Check data of '
'sc__cd_elements_of_the_page_3 and skip '
'cols None',
'status': 'passed'},
{'duration': 1.7484464645385742,
'name': 'Select all cells, table: 2',
'status': 'passed'},
{'duration': 3.812828779220581,
'name': 'I export substance_sample_details table '
'by offset x:100, y:150',
'status': 'passed'},
{'duration': 1.0029594898223877,
'name': 'Check data of '
'sc__cd_elements_of_the_page_2 and skip '
'cols None',
'status': 'passed'},
{'duration': 1.6729373931884766,
'name': 'Set window size x:800, y:600',
'status': 'passed'},
{'duration': 30.145705699920654,
'name': 'All scrollers are placed on top 6 and far '
'left 8',
'status': 'failed'}]}]},
{'feature_name': 'Sample Creator > Substance Sample History > Elements of the '
'page',
'scenarios': [{'scenario_name': 'SC, SSH, Elements of the page',
'scenario_status': 'passed',
'scenario_tags': None,
'steps': [{'duration': 0,
'name': 'I open application Stage and login by '
'SPT_LOGIN and password SPT_PWD',
'status': 'untested'},
{'duration': 0,
'name': 'I open Sample Creator query page',
'status': 'untested'},
{'duration': 7.305850505828857,
'name': 'I open application Stage and login by '
'SPT_LOGIN and password SPT_PWD',
'status': 'passed'},
{'duration': 3.500955104827881,
'name': 'I open Sample Creator query page',
'status': 'passed'},
{'duration': 3.0419492721557617,
'name': 'Enter value: NOA401800 SYN-NOA '
'A,S4A482070C SYN-ISN-OLD '
'O,S04A482167T,S04A482190Y,CSAA796564,CSCD106701 '
'in textarea: id_text_area sleep: 1',
'status': 'passed'},
{'duration': 49.567158460617065,
'name': 'I press on GET DATA',
'status': 'passed'},
{'duration': 0.13904356956481934,
'name': 'Open substance_sample_history',
'status': 'passed'},
{'duration': 1.1039845943450928,
'name': 'Columns displayed',
'status': 'passed'},
{'duration': 3.881945848464966,
'name': 'I export export_parent_table table by '
'offset x:100, y:150',
'status': 'passed'},
{'duration': 1.0334820747375488,
'name': 'Check data of '
'sc__ssh_elements_of_the_page_1 and skip '
'cols None',
'status': 'passed'},
{'duration': 0.0319981575012207,
'name': "Title is 'Additional Details for Marked "
"Rows'",
'status': 'passed'},
{'duration': 0.08897256851196289,
'name': 'Columns displayed (the same as in top '
'table)',
'status': 'passed'},
{'duration': 25.192569971084595,
'name': 'Verify the content of the bottom table',
'status': 'passed'},
{'duration': 4.308935880661011,
'name': 'I export '
'additional_details_for_marked_rows table '
'by offset x:100, y:150',
'status': 'passed'},
{'duration': 1.0089836120605469,
'name': 'Check data of '
'sc__ssh_elements_of_the_page_1 and skip '
'cols None',
'status': 'passed'}]}]}]
代码:
def get_keys(_dict: dict, prefix: list):
prefix += list(_dict.keys())
return prefix
def _loop_elements(elems:list, prefix=None, limit=None):
prefix = prefix or []
limit = limit or 9
try:
if len(elems) != 0 and isinstance(elems, list):
for _ in elems:
if isinstance(_, dict):
get_keys(_, prefix)
for item in _.values():
_loop_elements(item, prefix, limit)
return prefix[:limit]
except TypeError:
return
>>>goo = _loop_elements(foo,limit=9)
>>>goo
['feature_name', 'scenarios', 'scenario_name', 'scenario_status', 'scenario_tags', 'steps', 'duration', 'name', 'status']
Glom是一个很好的库,可以进入点查询:
In [1]: from glom import glom
In [2]: data = {'a': {'b': {'c': 'd'}}}
In [3]: glom(data, "a.b.c")
Out[3]: 'd'
查询失败有一个很好的堆栈跟踪,指出确切的故障点:
In [4]: glom(data, "a.b.foo")
---------------------------------------------------------------------------
PathAccessError Traceback (most recent call last)
<ipython-input-4-2a3467493ac4> in <module>
----> 1 glom(data, "a.b.foo")
~/.cache/pypoetry/virtualenvs/neural-knapsack-dE7ihQtM-py3.8/lib/python3.8/site-packages/glom/core.py in glom(target, spec, **kwargs)
2179
2180 if err:
-> 2181 raise err
2182 return ret
2183
PathAccessError: error raised while processing, details below.
Target-spec trace (most recent last):
- Target: {'a': {'b': {'c': 'd'}}}
- Spec: 'a.b.foo'
glom.core.PathAccessError: could not access 'foo', part 2 of Path('a', 'b', 'foo'), got error: KeyError('foo')
默认保护:
In [5]: glom(data, "a.b.foo", default="spam")
Out[5]: 'spam'
格洛姆的魅力在于多功能的规格参数。例如,可以很容易地从以下数据中提取所有的名字:
In [8]: data = {
...: "people": [
...: {"first_name": "Alice", "last_name": "Adams"},
...: {"first_name": "Bob", "last_name": "Barker"}
...: ]
...: }
In [9]: glom(data, ("people", ["first_name"]))
Out[9]: ['Alice', 'Bob']
更多的例子请阅读glom文档。
def safeget(_dct, *_keys):
if not isinstance(_dct, dict): raise TypeError("Is not instance of dict")
def foo(dct, *keys):
if len(keys) == 0: return dct
elif not isinstance(_dct, dict): return None
else: return foo(dct.get(keys[0], None), *keys[1:])
return foo(_dct, *_keys)
assert safeget(dict()) == dict()
assert safeget(dict(), "test") == None
assert safeget(dict([["a", 1],["b", 2]]),"a", "d") == None
assert safeget(dict([["a", 1],["b", 2]]),"a") == 1
assert safeget({"a":{"b":{"c": 2}},"d":1}, "a", "b")["c"] == 2
我已经编写了一个deepextract包,它完全符合您的要求:https://github.com/ya332/deepextract 你可以这样做
from deepextract import deepextract
# Demo: deepextract.extract_key(obj, key)
deeply_nested_dict = {
"items": {
"item": {
"id": {
"type": {
"donut": {
"name": {
"batters": {
"my_target_key": "my_target_value"
}
}
}
}
}
}
}
}
print(deepextract.extract_key(deeply_nested_dict, "my_target_key") == "my_target_value")
返回
True
我改编了GenesRus和unutbu的答案,非常简单:
class new_dict(dict):
def deep_get(self, *args, default=None):
_empty_dict = {}
out = self
for key in args:
out = out.get(key, _empty_dict)
return out if out else default
它适用于:
d = new_dict(some_data)
d.deep_get("key1", "key2", "key3", ..., default=some_value)
从Python 3.4开始,你可以使用suppress (KeyError)来访问嵌套的json对象,而不用担心KeyError
from contextlib import suppress
with suppress(KeyError):
a1 = json_obj['key1']['key2']['key3']
a2 = json_obj['key4']['key5']['key6']
a3 = json_obj['key7']['key8']['key9']
Techdragon提供。看看他的回答,了解更多细节:https://stackoverflow.com/a/45874251/1189659
我的实现下降到子字典,忽略None值,但失败与TypeError如果发现任何其他
def deep_get(d: dict, *keys, default=None):
""" Safely get a nested value from a dict
Example:
config = {'device': None}
deep_get(config, 'device', 'settings', 'light')
# -> None
Example:
config = {'device': True}
deep_get(config, 'device', 'settings', 'light')
# -> TypeError
Example:
config = {'device': {'settings': {'light': 'bright'}}}
deep_get(config, 'device', 'settings', 'light')
# -> 'light'
Note that it returns `default` is a key is missing or when it's None.
It will raise a TypeError if a value is anything else but a dict or None.
Args:
d: The dict to descend into
keys: A sequence of keys to follow
default: Custom default value
"""
# Descend while we can
try:
for k in keys:
d = d[k]
# If at any step a key is missing, return default
except KeyError:
return default
# If at any step the value is not a dict...
except TypeError:
# ... if it's a None, return default. Assume it would be a dict.
if d is None:
return default
# ... if it's something else, raise
else:
raise
# If the value was found, return it
else:
return d
如果您想使用另一个库来解决问题,这是最好的方法
https://github.com/maztohir/dict-path
from dict-path import DictPath
data_dict = {
"foo1": "bar1",
"foo2": "bar2",
"foo3": {
"foo4": "bar4",
"foo5": {
"foo6": "bar6",
"foo7": "bar7",
},
}
}
data_dict_path = DictPath(data_dict)
data_dict_path.get('key1/key2/key3')
下面是一个基于unutbu函数答案的解决方案:
Python命名指南 默认值作为参数 不用try,只是检查key是否在object上
def safe_get(dictionary, *keys, default=None):
for key in keys:
if key not in dictionary:
return default
dictionary = dictionary[key]
return dictionary
你可以用虚线:
PIP安装
from dotted.collection import DottedDict
assert DottedDict(dict(foo=dict(bar="baz")))["foo"]["bar"] == "baz"
assert DottedDict(dict(foo=dict(bar="baz")))["foo.bar"] == "baz"
assert DottedDict(dict(foo=dict(bar="baz"))).get("lorem.ipsum", None) is None
assert DottedDict(dict(foo=dict(bar="baz"))).get("lorem.ipsum", "default") == "default"
你可以使用开源ndicts包中的NestedDict(我是作者),它有一个完全像字典一样的安全get方法。
>>> from ndicts import NestedDict
>>> nd = NestedDict({"key1": {"key2": 0}}
>>> nd.get(("key1", "key2))
0
>>> nd.get("asd")