I'm searching for an elegant way to get data using attribute access on a dict with some nested dicts and lists (i.e. javascript-style object syntax).
For example:
>>> d = {'a': 1, 'b': {'c': 2}, 'd': ["hi", {'foo': "bar"}]}
Should be accessible in this way:
>>> x = dict2obj(d)
>>> x.a
1
>>> x.b.c
2
>>> x.d[1].foo
bar
I think, this is not possible without recursion, but what would be a nice way to get an object style for dicts?
Update: In Python 2.6 and onwards, consider whether the namedtuple data structure suits your needs:
>>> from collections import namedtuple
>>> MyStruct = namedtuple('MyStruct', 'a b d')
>>> s = MyStruct(a=1, b={'c': 2}, d=['hi'])
>>> s
MyStruct(a=1, b={'c': 2}, d=['hi'])
>>> s.a
1
>>> s.b
{'c': 2}
>>> s.c
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'MyStruct' object has no attribute 'c'
>>> s.d
['hi']
The alternative (original answer contents) is:
class Struct:
def __init__(self, **entries):
self.__dict__.update(entries)
Then, you can use:
>>> args = {'a': 1, 'b': 2}
>>> s = Struct(**args)
>>> s
<__main__.Struct instance at 0x01D6A738>
>>> s.a
1
>>> s.b
2
Structs from nested dictionaries, but in general the type of the value can be anything. Key is restricted to being suitable for an object slot –
Tuning argparse.Namespace (which has also defined __eq__, __ne__, __contains__). –
Shopping def __repr__(self): return '<%s>' % str('\n '.join('%s : %s' % (k, repr(v)) for (k, v) in self.__dict__.iteritems())) –
Salangi Surprisingly no one has mentioned Bunch. This library is exclusively meant to provide attribute style access to dict objects and does exactly what the OP wants. A demonstration:
>>> from bunch import bunchify
>>> d = {'a': 1, 'b': {'c': 2}, 'd': ["hi", {'foo': "bar"}]}
>>> x = bunchify(d)
>>> x.a
1
>>> x.b.c
2
>>> x.d[1].foo
'bar'
A Python 3 library is available at https://github.com/Infinidat/munch - Credit goes to codyzu
>>> from munch import DefaultMunch
>>> d = {'a': 1, 'b': {'c': 2}, 'd': ["hi", {'foo': "bar"}]}
>>> obj = DefaultMunch.fromDict(d)
>>> obj.b.c
2
>>> obj.a
1
>>> obj.d[1].foo
'bar'
class obj(object):
def __init__(self, d):
for k, v in d.items():
if isinstance(k, (list, tuple)):
setattr(self, k, [obj(x) if isinstance(x, dict) else x for x in v])
else:
setattr(self, k, obj(v) if isinstance(v, dict) else v)
>>> d = {'a': 1, 'b': {'c': 2}, 'd': ["hi", {'foo': "bar"}]}
>>> x = obj(d)
>>> x.b.c
2
>>> x.d[1].foo
'bar'
if isinstance(b, (list, tuple)): –
Shopping obj class inherit from argparse.Namespace for additional features like readable string representation. –
Casuistry collections module would you use to replace isinstance(b, (list, tuple))? –
Geriatrics if isinstance(k, (list, tuple)):: k is the key, you should test v instead! –
Passementerie x = type('new_dict', (object,), d)
then add recursion to this and you're done.
edit this is how I'd implement it:
>>> d
{'a': 1, 'b': {'c': 2}, 'd': ['hi', {'foo': 'bar'}]}
>>> def obj_dic(d):
top = type('new', (object,), d)
seqs = tuple, list, set, frozenset
for i, j in d.items():
if isinstance(j, dict):
setattr(top, i, obj_dic(j))
elif isinstance(j, seqs):
setattr(top, i,
type(j)(obj_dic(sj) if isinstance(sj, dict) else sj for sj in j))
else:
setattr(top, i, j)
return top
>>> x = obj_dic(d)
>>> x.a
1
>>> x.b.c
2
>>> x.d[1].foo
'bar'
top_instance = top() and returning that where you return top? –
Bluefarb x and x.b which return ugly <class '__main__.new'> –
Dracaena # Applies to Python-3 Standard Library
class Struct(object):
def __init__(self, data):
for name, value in data.items():
setattr(self, name, self._wrap(value))
def _wrap(self, value):
if isinstance(value, (tuple, list, set, frozenset)):
return type(value)([self._wrap(v) for v in value])
else:
return Struct(value) if isinstance(value, dict) else value
# Applies to Python-2 Standard Library
class Struct(object):
def __init__(self, data):
for name, value in data.iteritems():
setattr(self, name, self._wrap(value))
def _wrap(self, value):
if isinstance(value, (tuple, list, set, frozenset)):
return type(value)([self._wrap(v) for v in value])
else:
return Struct(value) if isinstance(value, dict) else value
Can be used with any sequence/dict/value structure of any depth.
def __repr__(self): return '{%s}' % str(', '.join("'%s': %s" % (k, repr(v)) for (k, v) in self.__dict__.iteritems())) –
Dracaena .items() instead of .iteritems() in line 4. (The function was renamed, but does essentialy the same) –
Quotidian def __repr__(self): return ("{ " + str(", ".join([f"'{k}': {v}" for k, v in [(k, repr(v)) for (k, v) in self.__dict__.items()]])) + " }") –
Mauricemauricio There's a
collection helper called namedtuple, that can do this for you:
from collections import namedtuple
d_named = namedtuple('Struct', d.keys())(*d.values())
In [7]: d_named
Out[7]: Struct(a=1, b={'c': 2}, d=['hi', {'foo': 'bar'}])
In [8]: d_named.a
Out[8]: 1
d_named = namedtuple('Struct', d)(**d) –
Brandeebranden If your dict is coming from json.loads(), you can turn it into an object instead (rather than a dict) in one line:
import json
from collections import namedtuple
json.loads(data, object_hook=lambda d: namedtuple('X', d.keys())(*d.values()))
.loads if you have a huge JSON object –
Fogel You can leverage the json module of the standard library with a custom object hook:
import json
class obj(object):
def __init__(self, dict_):
self.__dict__.update(dict_)
def dict2obj(d):
return json.loads(json.dumps(d), object_hook=obj)
Example usage:
>>> d = {'a': 1, 'b': {'c': 2}, 'd': ['hi', {'foo': 'bar'}]}
>>> o = dict2obj(d)
>>> o.a
1
>>> o.b.c
2
>>> o.d[0]
u'hi'
>>> o.d[1].foo
u'bar'
And it is not strictly read-only as it is with namedtuple, i.e. you can change values – not structure:
>>> o.b.c = 3
>>> o.b.c
3
json.JSONEncoder and object_hook. –
Termitarium Taking what I feel are the best aspects of the previous examples, here's what I came up with:
class Struct:
"""The recursive class for building and representing objects with."""
def __init__(self, obj):
for k, v in obj.items():
if isinstance(v, dict):
setattr(self, k, Struct(v))
else:
setattr(self, k, v)
def __getitem__(self, val):
return self.__dict__[val]
def __repr__(self):
return '{%s}' % str(', '.join('%s : %s' % (k, repr(v)) for (k, v) in self.__dict__.items()))
def __init__(self, dct): for k, v in dct.iteritems(): setattr(self, k, isinstance(v, dict) and self.__class__(v) or v) which also removes the explicit call to Struct –
Conciseness isinstance(v, dict) check would be better as isinstance(v, collections.Mapping) so it can handle future dict-like things –
Vision I ended up trying BOTH the AttrDict and the Bunch libraries and found them to be way too slow for my uses. After a friend and I looked into it, we found that the main method for writing these libraries results in the library aggressively recursing through a nested object and making copies of the dictionary object throughout. With this in mind, we made two key changes. 1) We made attributes lazy-loaded 2) instead of creating copies of a dictionary object, we create copies of a light-weight proxy object. This is the final implementation. The performance increase of using this code is incredible. When using AttrDict or Bunch, these two libraries alone consumed 1/2 and 1/3 respectively of my request time(what!?). This code reduced that time to almost nothing(somewhere in the range of 0.5ms). This of course depends on your needs, but if you are using this functionality quite a bit in your code, definitely go with something simple like this.
class DictProxy(object):
def __init__(self, obj):
self.obj = obj
def __getitem__(self, key):
return wrap(self.obj[key])
def __getattr__(self, key):
try:
return wrap(getattr(self.obj, key))
except AttributeError:
try:
return self[key]
except KeyError:
raise AttributeError(key)
# you probably also want to proxy important list properties along like
# items(), iteritems() and __len__
class ListProxy(object):
def __init__(self, obj):
self.obj = obj
def __getitem__(self, key):
return wrap(self.obj[key])
# you probably also want to proxy important list properties along like
# __iter__ and __len__
def wrap(value):
if isinstance(value, dict):
return DictProxy(value)
if isinstance(value, (tuple, list)):
return ListProxy(value)
return value
See the original implementation here by https://stackoverflow.com/users/704327/michael-merickel.
The other thing to note, is that this implementation is pretty simple and doesn't implement all of the methods you might need. You'll need to write those as required on the DictProxy or ListProxy objects.
Mapping and Sequence from collections.abc instead of collections –
Codicil If you want to access dict keys as an object (or as a dict for difficult keys), do it recursively, and also be able to update the original dict, you could do:
class Dictate(object):
"""Object view of a dict, updating the passed in dict when values are set
or deleted. "Dictate" the contents of a dict...: """
def __init__(self, d):
# since __setattr__ is overridden, self.__dict = d doesn't work
object.__setattr__(self, '_Dictate__dict', d)
# Dictionary-like access / updates
def __getitem__(self, name):
value = self.__dict[name]
if isinstance(value, dict): # recursively view sub-dicts as objects
value = Dictate(value)
return value
def __setitem__(self, name, value):
self.__dict[name] = value
def __delitem__(self, name):
del self.__dict[name]
# Object-like access / updates
def __getattr__(self, name):
return self[name]
def __setattr__(self, name, value):
self[name] = value
def __delattr__(self, name):
del self[name]
def __repr__(self):
return "%s(%r)" % (type(self).__name__, self.__dict)
def __str__(self):
return str(self.__dict)
Example usage:
d = {'a': 'b', 1: 2}
dd = Dictate(d)
assert dd.a == 'b' # Access like an object
assert dd[1] == 2 # Access like a dict
# Updates affect d
dd.c = 'd'
assert d['c'] == 'd'
del dd.a
del dd[1]
# Inner dicts are mapped
dd.e = {}
dd.e.f = 'g'
assert dd['e'].f == 'g'
assert d == {'c': 'd', 'e': {'f': 'g'}}
>>> def dict2obj(d):
if isinstance(d, list):
d = [dict2obj(x) for x in d]
if not isinstance(d, dict):
return d
class C(object):
pass
o = C()
for k in d:
o.__dict__[k] = dict2obj(d[k])
return o
>>> d = {'a': 1, 'b': {'c': 2}, 'd': ["hi", {'foo': "bar"}]}
>>> x = dict2obj(d)
>>> x.a
1
>>> x.b.c
2
>>> x.d[1].foo
'bar'
In 2021, use pydantic BaseModel - will convert nested dicts and nested json objects to python objects and vice versa:
https://pydantic-docs.helpmanual.io/usage/models/
>>> class Foo(BaseModel):
... count: int
... size: float = None
...
>>>
>>> class Bar(BaseModel):
... apple = 'x'
... banana = 'y'
...
>>>
>>> class Spam(BaseModel):
... foo: Foo
... bars: List[Bar]
...
>>>
>>> m = Spam(foo={'count': 4}, bars=[{'apple': 'x1'}, {'apple': 'x2'}])
Object to dict
>>> print(m.dict())
{'foo': {'count': 4, 'size': None}, 'bars': [{'apple': 'x1', 'banana': 'y'}, {'apple': 'x2', 'banana': 'y'}]}
Object to JSON
>>> print(m.json())
{"foo": {"count": 4, "size": null}, "bars": [{"apple": "x1", "banana": "y"}, {"apple": "x2", "banana": "y"}]}
Dict to object
>>> spam = Spam.parse_obj({'foo': {'count': 4, 'size': None}, 'bars': [{'apple': 'x1', 'banana': 'y'}, {'apple': 'x2', 'banana': 'y2'}]})
>>> spam
Spam(foo=Foo(count=4, size=None), bars=[Bar(apple='x1', banana='y'), Bar(apple='x2', banana='y2')])
JSON to object
>>> spam = Spam.parse_raw('{"foo": {"count": 4, "size": null}, "bars": [{"apple": "x1", "banana": "y"}, {"apple": "x2", "banana": "y"}]}')
>>> spam
Spam(foo=Foo(count=4, size=None), bars=[Bar(apple='x1', banana='y'), Bar(apple='x2', banana='y')])
create_model(__model_name="ModelName", **some_dict). This however only works with the top level, so you have to make it generate pydantic model recursively.. But creating pydantic models is slower than other modules such as named_tuples or dataclasses. –
Clovis x.__dict__.update(d) should do fine.
__dict__: try object().__dict__ and you'll get AttributeError: 'object' object has no attribute '__dict__' –
Catcall __slots__. –
Jenevajeni Typically you want to mirror dict hierarchy into your object but not list or tuples which are typically at lowest level. So this is how I did this:
class defDictToObject(object):
def __init__(self, myDict):
for key, value in myDict.items():
if type(value) == dict:
setattr(self, key, defDictToObject(value))
else:
setattr(self, key, value)
So we do:
myDict = { 'a': 1,
'b': {
'b1': {'x': 1,
'y': 2} },
'c': ['hi', 'bar']
}
and get:
x.b.b1.x 1
x.c ['hi', 'bar']
This should get your started:
class dict2obj(object):
def __init__(self, d):
self.__dict__['d'] = d
def __getattr__(self, key):
value = self.__dict__['d'][key]
if type(value) == type({}):
return dict2obj(value)
return value
d = {'a': 1, 'b': {'c': 2}, 'd': ["hi", {'foo': "bar"}]}
x = dict2obj(d)
print x.a
print x.b.c
print x.d[1].foo
It doesn't work for lists, yet. You'll have to wrap the lists in a UserList and overload __getitem__ to wrap dicts.
if isinstance(d, list) clause from Anon's answer. –
Malebranche I know there's already a lot of answers here already and I'm late to the party but this method will recursively and 'in place' convert a dictionary to an object-like structure... Works in 3.x.x
def dictToObject(d):
for k,v in d.items():
if isinstance(v, dict):
d[k] = dictToObject(v)
return namedtuple('object', d.keys())(*d.values())
# Dictionary created from JSON file
d = {
'primaryKey': 'id',
'metadata':
{
'rows': 0,
'lastID': 0
},
'columns':
{
'col2': {
'dataType': 'string',
'name': 'addressLine1'
},
'col1': {
'datatype': 'string',
'name': 'postcode'
},
'col3': {
'dataType': 'string',
'name': 'addressLine2'
},
'col0': {
'datatype': 'integer',
'name': 'id'
},
'col4': {
'dataType': 'string',
'name': 'contactNumber'
}
},
'secondaryKeys': {}
}
d1 = dictToObject(d)
d1.columns.col1 # == object(datatype='string', name='postcode')
d1.metadata.rows # == 0
from mock import Mock
d = {'a': 1, 'b': {'c': 2}, 'd': ["hi", {'foo': "bar"}]}
my_data = Mock(**d)
# We got
# my_data.a == 1
ModuleNotFoundError: No module named 'mock'. –
Jenevajeni mock was a third party package, now incorporated into unittest. from unittest.mock import Mock should work. One downside is, if your code is production code, it now depends on what should theoretically be just test code. Another is, this only works for shallow dictionaries. But, at the top level, a nested dictionary gets returned correctly, unlike many of the answers above. –
Codicil This also works well too
class DObj(object):
pass
dobj = Dobj()
dobj.__dict__ = {'a': 'aaa', 'b': 'bbb'}
print dobj.a
>>> aaa
print dobj.b
>>> bbb
TypeError: 'DObj' object is not subscriptable , do you know a fix for this? :) –
Cucurbit The simplest way would be using collections.namedtuple.
I find the following 4-liner the most beautiful, which supports nested dictionaries:
def dict_to_namedtuple(typename, data):
return namedtuple(typename, data.keys())(
*(dict_to_namedtuple(typename + '_' + k, v) if isinstance(v, dict) else v for k, v in data.items())
)
The output will look good as well:
>>> nt = dict_to_namedtuple('config', {
... 'path': '/app',
... 'debug': {'level': 'error', 'stream': 'stdout'}
... })
>>> print(nt)
config(path='/app', debug=config_debug(level='error', stream='stdout'))
>>> print(nt.debug.level)
'error'
Let me explain a solution I almost used some time ago. But first, the reason I did not is illustrated by the fact that the following code:
d = {'from': 1}
x = dict2obj(d)
print x.from
gives this error:
File "test.py", line 20
print x.from == 1
^
SyntaxError: invalid syntax
Because "from" is a Python keyword there are certain dictionary keys you cannot allow.
Now my solution allows access to the dictionary items by using their names directly. But it also allows you to use "dictionary semantics". Here is the code with example usage:
class dict2obj(dict):
def __init__(self, dict_):
super(dict2obj, self).__init__(dict_)
for key in self:
item = self[key]
if isinstance(item, list):
for idx, it in enumerate(item):
if isinstance(it, dict):
item[idx] = dict2obj(it)
elif isinstance(item, dict):
self[key] = dict2obj(item)
def __getattr__(self, key):
return self[key]
d = {'a': 1, 'b': {'c': 2}, 'd': ["hi", {'foo': "bar"}]}
x = dict2obj(d)
assert x.a == x['a'] == 1
assert x.b.c == x['b']['c'] == 2
assert x.d[1].foo == x['d'][1]['foo'] == "bar"
Old Q&A, but I get something more to talk. Seems no one talk about recursive dict. This is my code:
#!/usr/bin/env python
class Object( dict ):
def __init__( self, data = None ):
super( Object, self ).__init__()
if data:
self.__update( data, {} )
def __update( self, data, did ):
dataid = id(data)
did[ dataid ] = self
for k in data:
dkid = id(data[k])
if did.has_key(dkid):
self[k] = did[dkid]
elif isinstance( data[k], Object ):
self[k] = data[k]
elif isinstance( data[k], dict ):
obj = Object()
obj.__update( data[k], did )
self[k] = obj
obj = None
else:
self[k] = data[k]
def __getattr__( self, key ):
return self.get( key, None )
def __setattr__( self, key, value ):
if isinstance(value,dict):
self[key] = Object( value )
else:
self[key] = value
def update( self, *args ):
for obj in args:
for k in obj:
if isinstance(obj[k],dict):
self[k] = Object( obj[k] )
else:
self[k] = obj[k]
return self
def merge( self, *args ):
for obj in args:
for k in obj:
if self.has_key(k):
if isinstance(self[k],list) and isinstance(obj[k],list):
self[k] += obj[k]
elif isinstance(self[k],list):
self[k].append( obj[k] )
elif isinstance(obj[k],list):
self[k] = [self[k]] + obj[k]
elif isinstance(self[k],Object) and isinstance(obj[k],Object):
self[k].merge( obj[k] )
elif isinstance(self[k],Object) and isinstance(obj[k],dict):
self[k].merge( obj[k] )
else:
self[k] = [ self[k], obj[k] ]
else:
if isinstance(obj[k],dict):
self[k] = Object( obj[k] )
else:
self[k] = obj[k]
return self
def test01():
class UObject( Object ):
pass
obj = Object({1:2})
d = {}
d.update({
"a": 1,
"b": {
"c": 2,
"d": [ 3, 4, 5 ],
"e": [ [6,7], (8,9) ],
"self": d,
},
1: 10,
"1": 11,
"obj": obj,
})
x = UObject(d)
assert x.a == x["a"] == 1
assert x.b.c == x["b"]["c"] == 2
assert x.b.d[0] == 3
assert x.b.d[1] == 4
assert x.b.e[0][0] == 6
assert x.b.e[1][0] == 8
assert x[1] == 10
assert x["1"] == 11
assert x[1] != x["1"]
assert id(x) == id(x.b.self.b.self) == id(x.b.self)
assert x.b.self.a == x.b.self.b.self.a == 1
x.x = 12
assert x.x == x["x"] == 12
x.y = {"a":13,"b":[14,15]}
assert x.y.a == 13
assert x.y.b[0] == 14
def test02():
x = Object({
"a": {
"b": 1,
"c": [ 2, 3 ]
},
1: 6,
2: [ 8, 9 ],
3: 11,
})
y = Object({
"a": {
"b": 4,
"c": [ 5 ]
},
1: 7,
2: 10,
3: [ 12 , 13 ],
})
z = {
3: 14,
2: 15,
"a": {
"b": 16,
"c": 17,
}
}
x.merge( y, z )
assert 2 in x.a.c
assert 3 in x.a.c
assert 5 in x.a.c
assert 1 in x.a.b
assert 4 in x.a.b
assert 8 in x[2]
assert 9 in x[2]
assert 10 in x[2]
assert 11 in x[3]
assert 12 in x[3]
assert 13 in x[3]
assert 14 in x[3]
assert 15 in x[2]
assert 16 in x.a.b
assert 17 in x.a.c
if __name__ == '__main__':
test01()
test02()
Wanted to upload my version of this little paradigm.
class Struct(dict):
def __init__(self,data):
for key, value in data.items():
if isinstance(value, dict):
setattr(self, key, Struct(value))
else:
setattr(self, key, type(value).__init__(value))
dict.__init__(self,data)
It preserves the attributes for the type that's imported into the class. My only concern would be overwriting methods from within the dictionary your parsing. But otherwise seems solid!
df.a doesn't even work. –
Stillbirth Here is another way to implement SilentGhost's original suggestion:
def dict2obj(d):
if isinstance(d, dict):
n = {}
for item in d:
if isinstance(d[item], dict):
n[item] = dict2obj(d[item])
elif isinstance(d[item], (list, tuple)):
n[item] = [dict2obj(elem) for elem in d[item]]
else:
n[item] = d[item]
return type('obj_from_dict', (object,), n)
else:
return d
I stumbled upon the case I needed to recursively convert a list of dicts to list of objects, so based on Roberto's snippet here what did the work for me:
def dict2obj(d):
if isinstance(d, dict):
n = {}
for item in d:
if isinstance(d[item], dict):
n[item] = dict2obj(d[item])
elif isinstance(d[item], (list, tuple)):
n[item] = [dict2obj(elem) for elem in d[item]]
else:
n[item] = d[item]
return type('obj_from_dict', (object,), n)
elif isinstance(d, (list, tuple,)):
l = []
for item in d:
l.append(dict2obj(item))
return l
else:
return d
Note that any tuple will be converted to its list equivalent, for obvious reasons.
Hope this helps someone as much as all your answers did for me, guys.
What about just assigning your dict to the __dict__ of an empty object?
class Object:
"""If your dict is "flat", this is a simple way to create an object from a dict
>>> obj = Object()
>>> obj.__dict__ = d
>>> d.a
1
"""
pass
Of course this fails on your nested dict example unless you walk the dict recursively:
# For a nested dict, you need to recursively update __dict__
def dict2obj(d):
"""Convert a dict to an object
>>> d = {'a': 1, 'b': {'c': 2}, 'd': ["hi", {'foo': "bar"}]}
>>> obj = dict2obj(d)
>>> obj.b.c
2
>>> obj.d
["hi", {'foo': "bar"}]
"""
try:
d = dict(d)
except (TypeError, ValueError):
return d
obj = Object()
for k, v in d.iteritems():
obj.__dict__[k] = dict2obj(v)
return obj
And your example list element was probably meant to be a Mapping, a list of (key, value) pairs like this:
>>> d = {'a': 1, 'b': {'c': 2}, 'd': [("hi", {'foo': "bar"})]}
>>> obj = dict2obj(d)
>>> obj.d.hi.foo
"bar"
Here's another implementation:
class DictObj(object):
def __init__(self, d):
self.__dict__ = d
def dict_to_obj(d):
if isinstance(d, (list, tuple)): return map(dict_to_obj, d)
elif not isinstance(d, dict): return d
return DictObj(dict((k, dict_to_obj(v)) for (k,v) in d.iteritems()))
[Edit] Missed bit about also handling dicts within lists, not just other dicts. Added fix.
class Struct(dict):
def __getattr__(self, name):
try:
return self[name]
except KeyError:
raise AttributeError(name)
def __setattr__(self, name, value):
self[name] = value
def copy(self):
return Struct(dict.copy(self))
Usage:
points = Struct(x=1, y=2)
# Changing
points['x'] = 2
points.y = 1
# Accessing
points['x'], points.x, points.get('x') # 2 2 2
points['y'], points.y, points.get('y') # 1 1 1
# Accessing inexistent keys/attrs
points['z'] # KeyError: z
points.z # AttributeError: z
# Copying
points_copy = points.copy()
points.x = 2
points_copy.x # 1
How about this:
from functools import partial
d2o=partial(type, "d2o", ())
This can then be used like this:
>>> o=d2o({"a" : 5, "b" : 3})
>>> print o.a
5
>>> print o.b
3
I think a dict consists of number, string and dict is enough most time. So I ignore the situation that tuples, lists and other types not appearing in the final dimension of a dict.
Considering inheritance, combined with recursion, it solves the print problem conveniently and also provides two ways to query a data,one way to edit a data.
See the example below, a dict that describes some information about students:
group=["class1","class2","class3","class4",]
rank=["rank1","rank2","rank3","rank4","rank5",]
data=["name","sex","height","weight","score"]
#build a dict based on the lists above
student_dic=dict([(g,dict([(r,dict([(d,'') for d in data])) for r in rank ]))for g in group])
#this is the solution
class dic2class(dict):
def __init__(self, dic):
for key,val in dic.items():
self.__dict__[key]=self[key]=dic2class(val) if isinstance(val,dict) else val
student_class=dic2class(student_dic)
#one way to edit:
student_class.class1.rank1['sex']='male'
student_class.class1.rank1['name']='Nan Xiang'
#two ways to query:
print student_class.class1.rank1
print student_class.class1['rank1']
print '-'*50
for rank in student_class.class1:
print getattr(student_class.class1,rank)
Results:
{'score': '', 'sex': 'male', 'name': 'Nan Xiang', 'weight': '', 'height': ''}
{'score': '', 'sex': 'male', 'name': 'Nan Xiang', 'weight': '', 'height': ''}
--------------------------------------------------
{'score': '', 'sex': '', 'name': '', 'weight': '', 'height': ''}
{'score': '', 'sex': '', 'name': '', 'weight': '', 'height': ''}
{'score': '', 'sex': 'male', 'name': 'Nan Xiang', 'weight': '', 'height': ''}
{'score': '', 'sex': '', 'name': '', 'weight': '', 'height': ''}
{'score': '', 'sex': '', 'name': '', 'weight': '', 'height': ''}
class Dict2Obj:
def __init__(self, json_data):
self.convert(json_data)
def convert(self, json_data):
if not isinstance(json_data, dict):
return
for key in json_data:
if not isinstance(json_data[key], dict):
self.__dict__.update({key: json_data[key]})
else:
self.__dict__.update({ key: Dict2Obj(json_data[key])})
I could not find the implementation of nested dictionary to object, so wrote one.
Usage:
>>> json_data = {"a": {"b": 2}, "c": 3}
>>> out_obj = Dict2Obj(json_data)
>>> out_obj.a
<Dict2Obj object at 0x7f3dc22c2d68>
>>> out_obj.a.b
2
>>> out_obj.a.c
3
Looking for a simple wrapper class for dict enabling attribute-style key access/assignment (dot notation) I was not satisfied with the existing options for the reasons below.
dataclasses, pydantic, etc. are great but require a static definition of the content. Also, they cannot replace dict in code which relied on dict since they don't share the same methods and __getitem__() syntax is not supported.
Hence, I developed MetaDict. It behaves exactly like dict but enables dot notation and IDE autocompletion (if the object is loaded in the RAM) without the shortcomings and potential namespace conflicts of other solutions. All features and usage examples can be found on GitHub (see link above).
Full disclosure: I am the author of MetaDict.
Shortcomings/limitations I encountered when trying out other solutions:
dict objects are not converted to support attribute-style key accessDictdataclass)dict objects when embedded in list or other inbuilt iterableslist objects to tuple behind the scenesitems(), update(), etc. can be overwritten with obj.items = [1, 2, 3]dict objects when embedded in list or other inbuilt iterablesdict accepts all hashable objects as keysitems(), update(), etc. can be overwritten with obj.items = [1, 2, 3]obj.pop('unknown_key', None) raises an AttributeErrorNote: I wrote a similar answer in this stackoverflow, which is related.
Building off my answer to "python: How to add property to a class dynamically?":
class data(object):
def __init__(self,*args,**argd):
self.__dict__.update(dict(*args,**argd))
def makedata(d):
d2 = {}
for n in d:
d2[n] = trydata(d[n])
return data(d2)
def trydata(o):
if isinstance(o,dict):
return makedata(o)
elif isinstance(o,list):
return [trydata(i) for i in o]
else:
return o
You call makedata on the dictionary you want converted, or maybe trydata depending on what you expect as input, and it spits out a data object.
Notes:
trydata if you need more functionality.x.a = {} or similar.My dictionary is of this format:
addr_bk = {
'person': [
{'name': 'Andrew', 'id': 123, 'email': '[email protected]',
'phone': [{'type': 2, 'number': '633311122'},
{'type': 0, 'number': '97788665'}]
},
{'name': 'Tom', 'id': 456,
'phone': [{'type': 0, 'number': '91122334'}]},
{'name': 'Jack', 'id': 7788, 'email': '[email protected]'}
]
}
As can be seen, I have nested dictionaries and list of dicts. This is because the addr_bk was decoded from protocol buffer data that converted to a python dict using lwpb.codec. There are optional field (e.g. email => where key may be unavailable) and repeated field (e.g. phone => converted to list of dict).
I tried all the above proposed solutions. Some doesn't handle the nested dictionaries well. Others cannot print the object details easily.
Only the solution, dict2obj(dict) by Dawie Strauss, works best.
I have enhanced it a little to handle when the key cannot be found:
# Work the best, with nested dictionaries & lists! :)
# Able to print out all items.
class dict2obj_new(dict):
def __init__(self, dict_):
super(dict2obj_new, self).__init__(dict_)
for key in self:
item = self[key]
if isinstance(item, list):
for idx, it in enumerate(item):
if isinstance(it, dict):
item[idx] = dict2obj_new(it)
elif isinstance(item, dict):
self[key] = dict2obj_new(item)
def __getattr__(self, key):
# Enhanced to handle key not found.
if self.has_key(key):
return self[key]
else:
return None
Then, I tested it with:
# Testing...
ab = dict2obj_new(addr_bk)
for person in ab.person:
print "Person ID:", person.id
print " Name:", person.name
# Check if optional field is available before printing.
if person.email:
print " E-mail address:", person.email
# Check if optional field is available before printing.
if person.phone:
for phone_number in person.phone:
if phone_number.type == codec.enums.PhoneType.MOBILE:
print " Mobile phone #:",
elif phone_number.type == codec.enums.PhoneType.HOME:
print " Home phone #:",
else:
print " Work phone #:",
print phone_number.number
Here is a nested-ready version with namedtuple:
from collections import namedtuple
class Struct(object):
def __new__(cls, data):
if isinstance(data, dict):
return namedtuple(
'Struct', data.iterkeys()
)(
*(Struct(val) for val in data.values())
)
elif isinstance(data, (tuple, list, set, frozenset)):
return type(data)(Struct(_) for _ in data)
else:
return data
=>
>>> d = {'a': 1, 'b': {'c': 2}, 'd': ["hi", {'foo': "bar"}]}
>>> s = Struct(d)
>>> s.d
['hi', Struct(foo='bar')]
>>> s.d[0]
'hi'
>>> s.d[1].foo
'bar'
Convert dict to object
from types import SimpleNamespace
def dict2obj(data):
"""将字典对象转换为可访问的对象属性"""
if not isinstance(data, dict):
raise ValueError('data must be dict object.')
def _d2o(d):
_d = {}
for key, item in d.items():
if isinstance(item, dict):
_d[key] = _d2o(item)
else:
_d[key] = item
return SimpleNamespace(**_d)
return _d2o(data)
I wasn't satisfied with the marked and upvoted answers, so here is a simple and general solution for transforming JSON-style nested datastructures (made of dicts and lists) into hierachies of plain objects:
# tested in: Python 3.8
from collections import abc
from typings import Any, Iterable, Mapping, Union
class DataObject:
def __repr__(self):
return str({k: v for k, v in vars(self).items()})
def data_to_object(data: Union[Mapping[str, Any], Iterable]) -> object:
"""
Example
-------
>>> data = {
... "name": "Bob Howard",
... "positions": [{"department": "ER", "manager_id": 13}],
... }
... data_to_object(data).positions[0].manager_id
13
"""
if isinstance(data, abc.Mapping):
r = DataObject()
for k, v in data.items():
if type(v) is dict or type(v) is list:
setattr(r, k, data_to_object(v))
else:
setattr(r, k, v)
return r
elif isinstance(data, abc.Iterable):
return [data_to_object(e) for e in data]
else:
return data
Building on what was done earlier by the accepted answer, if you would like to have it recursive.
class FullStruct:
def __init__(self, **kwargs):
for key, value in kwargs.items():
if isinstance(value, dict):
f = FullStruct(**value)
self.__dict__.update({key: f})
else:
self.__dict__.update({key: value})
You can use my way to handle it.
somedict= {"person": {"name": "daniel"}}
class convertor:
def __init__(self, dic: dict) -> object:
self.dict = dic
def recursive_check(obj):
for key, value in dic.items():
if isinstance(value, dict):
value= convertor(value)
setattr(obj, key, value)
recursive_check(self)
my_object= convertor(somedict)
print(my_object.person.name)
The following code from here, works on nested dictionaries and IDEs such as VS Code are able to hint the existing attributes:
class Struct:
def __init__(self, **kwargs):
for key, value in kwargs.items():
if isinstance(value, dict):
self.__dict__[key] = Struct(**value)
else:
self.__dict__[key] = value
my_dict = {
'name': 'bobbyhadz',
'address': {
'country': 'Country A',
'city': 'City A',
'codes': [1, 2, 3]
},
}
obj = Struct(**my_dict)
If you want to see how to load a YAML file and covert it to a Python object, see this gist.
my_dict.address is no longer a dictionary, but an instance of Struct). –
Codicil I had some problems with __getattr__ not being called so I constructed a new style class version:
class Struct(object):
'''The recursive class for building and representing objects with.'''
class NoneStruct(object):
def __getattribute__(*args):
return Struct.NoneStruct()
def __eq__(self, obj):
return obj == None
def __init__(self, obj):
for k, v in obj.iteritems():
if isinstance(v, dict):
setattr(self, k, Struct(v))
else:
setattr(self, k, v)
def __getattribute__(*args):
try:
return object.__getattribute__(*args)
except:
return Struct.NoneStruct()
def __repr__(self):
return '{%s}' % str(', '.join('%s : %s' % (k, repr(v)) for
(k, v) in self.__dict__.iteritems()))
This version also has the addition of NoneStruct that is returned when an attribute is called that is not set. This allows for None testing to see if an attribute is present. Very usefull when the exact dict input is not known (settings etc.).
bla = Struct({'a':{'b':1}})
print(bla.a.b)
>> 1
print(bla.a.c == None)
>> True
This is another, alternative, way to convert a list of dictionaries to an object:
def dict2object(in_dict):
class Struct(object):
def __init__(self, in_dict):
for key, value in in_dict.items():
if isinstance(value, (list, tuple)):
setattr(
self, key,
[Struct(sub_dict) if isinstance(sub_dict, dict)
else sub_dict for sub_dict in value])
else:
setattr(
self, key,
Struct(value) if isinstance(value, dict)
else value)
return [Struct(sub_dict) for sub_dict in in_dict] \
if isinstance(in_dict, list) else Struct(in_dict)
This little class never gives me any problem, just extend it and use the copy() method:
import simplejson as json
class BlindCopy(object):
def copy(self, json_str):
dic = json.loads(json_str)
for k, v in dic.iteritems():
if hasattr(self, k):
setattr(self, k, v);
Updated with recursive array expansion on @max-sirwa 's code
class Objectify:
def __init__(self, **kwargs):
for key, value in kwargs.items():
if isinstance(value, dict):
f = Objectify(**value)
self.__dict__.update({key: f})
elif isinstance(value, list):
t = []
for i in value:
t.append(Objectify(**i)) if isinstance(i, dict) else t.append(i)
self.__dict__.update({key: t})
else:
self.__dict__.update({key: value})
The exact solution of the question can be achieved easily by PyPI package named attrdict. The interesting fact about this package is that the dict can be accessed either as keys or as attributes. Here is the solution -
from attrdict import AttrDict
d = {'a': 1, 'b': {'c': 2}, 'd': ["hi", {'foo': "bar"}]}
x = AttrDict(d)
print(x.a, x['a'])
print(x.b.c, x['b']['c'])
print(x.d[1].foo, x['d'][1]['foo'])
And output is as follows (obviously with no error) -
1 1
2 2
bar bar
N.B. It was first released in Feb 2, 2019 which means at the time of asking this question, this third party pypi package didn't exist. But if someone now wants to access dict value either by key or by attribute, this package surely can help as magic with only one line of code.
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from_rather than_fromaccording to PEP 8. – Coriandergetattr(x, 'from')instead of renaming the attribute. – Concisenessd1.b.c), I think it's clear you should be using something from a library, e.g. namedtuple from collections, as this answer suggests, ... – Stillbirth