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It's hard to say without knowing the whole context of the problem, but I would not override __iter__.

I would implement __what_goes_here__ on the class.

as_dict(self:
d = {...whatever you need...}
return d

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最佳答案

There are at least ~~five~~ six ways. The preferred way depends on what your use case is.

Option 1:

Simply add an asdict() method.

Based on the problem description I would very much consider the asdict way of doing things suggested by other answers. This is because it does not appear that your object is really much of a collection:

class Wharrgarbl(object):


...


def asdict(self):
return {'a': self.a, 'b': self.b, 'c': self.c}

Using the other options below could be confusing for others unless it is very obvious exactly which object members would and would not be iterated or specified as key-value pairs.

Option 1a:

Inherit your class from 'typing.NamedTuple' (or the mostly equivalent 'collections.namedtuple'), and use the _asdict method provided for you.

from typing import NamedTuple


class Wharrgarbl(NamedTuple):
a: str
b: str
c: str
sum: int = 6
version: str = 'old'

Using a named tuple is a very convenient way to add lots of functionality to your class with a minimum of effort, including an _asdict method. However, a limitation is that, as shown above, the NT will include all the members in its _asdict.

If there are members you don't want to include in your dictionary, you'll need to specify which members you want the named tuple _asdict result to include. To do this, you could either inherit from a base namedtuple class using the older collections.namedtuple API:

from collections import namedtuple as nt


class Wharrgarbl(nt("Basegarble", "a b c")):
# note that the typing info below isn't needed for the old API
a: str
b: str
c: str
sum: int = 6
version: str = 'old'

...or you could create a base class using the newer API, and inherit from that, using only the dictionary members in the base class:

from typing import NamedTuple


class Basegarbl(NamedTuple):
a: str
b: str
c: str


class Wharrgarbl(Basegarbl):
sum: int = 6
version: str = 'old'

Another limitation is that NT is read-only. This may or may not be desirable.

Option 2:

Implement __iter__.

Like this, for example:

def __iter__(self):
yield 'a', self.a
yield 'b', self.b
yield 'c', self.c

Now you can just do:

dict(my_object)

This works because the dict() constructor accepts an iterable of (key, value) pairs to construct a dictionary. Before doing this, ask yourself the question whether iterating the object as a series of key,value pairs in this manner- while convenient for creating a dict- might actually be surprising behavior in other contexts. E.g., ask yourself the question "what should the behavior of list(my_object) be...?"

Additionally, note that accessing values directly using the get item obj["a"] syntax will not work, and keyword argument unpacking won't work. For those, you'd need to implement the mapping protocol.

Option 3:

Implement the mapping protocol. This allows access-by-key behavior, casting to a dict without using __iter__, and also provides two types of unpacking behavior:

mapping unpacking behavior: {**my_obj}
keyword unpacking behavior, but only if all the keys are strings: dict(**my_obj)

The mapping protocol requires that you provide (at minimum) two methods together: keys() and __getitem__.

class MyKwargUnpackable:
def keys(self):
return list("abc")
def __getitem__(self, key):
return dict(zip("abc", "one two three".split()))[key]

Now you can do things like:

>>> m=MyKwargUnpackable()
>>> m["a"]
'one'
>>> dict(m)  # cast to dict directly
{'a': 'one', 'b': 'two', 'c': 'three'}
>>> dict(**m)  # unpack as kwargs
{'a': 'one', 'b': 'two', 'c': 'three'}

As mentioned above, if you are using a new enough version of python you can also unpack your mapping-protocol object into a dictionary comprehension like so (and in this case it is not required that your keys be strings):

>>> {**m}
{'a': 'one', 'b': 'two', 'c': 'three'}

Note that the mapping protocol takes precedence over the __iter__ method when casting an object to a dict directly (without using kwarg unpacking, i.e. dict(m)). So it is possible- and might be sometimes convenient- to cause the object to have different behavior when used as an iterable (e.g., list(m)) vs. when cast to a dict (dict(m)).

But note also that with regular dictionaries, if you cast to a list, it will give the KEYS back, and not the VALUES as you require. If you implement another nonstandard behavior for __iter__ (returning values instead of keys), it could be surprising for other people using your code unless it is very obvious why this would happen.

EMPHASIZED: Just because you CAN use the mapping protocol, does NOT mean that you SHOULD do so. Does it actually make sense for your object to be passed around as a set of key-value pairs, or as keyword arguments and values? Does accessing it by key- just like a dictionary- really make sense? Would you also expect your object to have other standard mapping methods such as items, values, get? Do you want to support the in keyword and equality checks (==)?

If the answer to these questions is yes, it's probably a good idea to not stop here, and consider the next option instead.

Option 4:

Look into using the 'collections.abc' module.

Inheriting your class from 'collections.abc.Mapping or 'collections.abc.MutableMapping signals to other users that, for all intents and purposes, your class is a mapping * and can be expected to behave that way. It also provides the methods items, values, get and supports the in keyword and equality checks (==) "for free".

You can still cast your object to a dict just as you require, but there would probably be little reason to do so. Because of duck typing, bothering to cast your mapping object to a dict would just be an additional unnecessary step the majority of the time.

This answer from me about how to use ABCs might also be helpful.

As noted in the comments below: it's worth mentioning that doing this the abc way essentially turns your object class into a dict-like class (assuming you use MutableMapping and not the read-only Mapping base class). Everything you would be able to do with dict, you could do with your own class object. This may be, or may not be, desirable.

Also consider looking at the numerical abcs in the numbers module:

https://docs.python.org/3/library/numbers.html

Since you're also casting your object to an int, it might make more sense to essentially turn your class into a full fledged int so that casting isn't necessary.

Option 5:

Look into using the dataclasses module (Python 3.7+ only), which includes a convenient asdict() utility method.

from dataclasses import dataclass, asdict, field, InitVar


@dataclass
class Wharrgarbl(object):
a: int
b: int
c: int
sum: InitVar[int]  # note: InitVar will exclude this from the dict
version: InitVar[str] = "old"


def __post_init__(self, sum, version):
self.sum = 6  # this looks like an OP mistake?
self.version = str(version)

Now you can do this:

    >>> asdict(Wharrgarbl(1,2,3,4,"X"))
{'a': 1, 'b': 2, 'c': 3}

Option 6:

Use typing.TypedDict, which has been added in python 3.8.

NOTE: option 6 is likely NOT what the OP, or other readers based on the title of this question, are looking for. See additional comments below.

class Wharrgarbl(TypedDict):
a: str
b: str
c: str

Using this option, the resulting object is a dict (emphasis: it is not a Wharrgarbl). There is no reason at all to "cast" it to a dict (unless you are making a copy).

And since the object is a dict, the initialization signature is identical to that of dict and as such it only accepts keyword arguments or another dictionary.

    >>> w = Wharrgarbl(a=1,b=2,b=3)
>>> w
{'a': 1, 'b': 2, 'c': 3}
>>> type(w)
<class 'dict'>

Emphasized: the above "class" Wharrgarbl isn't actually a new class at all. It is simply syntactic sugar for creating typed dict objects with specific keys ONLY and value fields of different types for the type checker. At run time, it is still nothing more than a dict.

As such this option can be pretty convenient for signaling to readers of your code (and also to a type checker such as mypy) that such a dict object is expected to have specific keys with specific value types.

But this means you cannot, for example, add other methods, although you can try:

class MyDict(TypedDict):
def my_fancy_method(self):
return "world changing result"

...but it won't work:

>>> MyDict().my_fancy_method()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'dict' object has no attribute 'my_fancy_method'

* "Mapping" has become the standard "name" of the dict-like duck type

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something like this would probably work

class MyClass:
def __init__(self,x,y,z):
self.x = x
self.y = y
self.z = z
def __iter__(self): #overridding this to return tuples of (key,value)
return iter([('x',self.x),('y',self.y),('z',self.z)])


dict(MyClass(5,6,7)) # because dict knows how to deal with tuples of (key,value)

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I think this will work for you.

class A(object):
def __init__(self, a, b, c, sum, version='old'):
self.a = a
self.b = b
self.c = c
self.sum = 6
self.version = version


def __int__(self):
return self.sum + 9000


def __iter__(self):
return self.__dict__.iteritems()


a = A(1,2,3,4,5)
print dict(a)

Output

{'a': 1, 'c': 3, 'b': 2, 'sum': 6, 'version': 5}

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There is no magic method that will do what you want. The answer is simply name it appropriately. asdict is a reasonable choice for a plain conversion to dict, inspired primarily by namedtuple. However, your method will obviously contain special logic that might not be immediately obvious from that name; you are returning only a subset of the class' state. If you can come up with with a slightly more verbose name that communicates the concepts clearly, all the better.

Other answers suggest using __iter__, but unless your object is truly iterable (represents a series of elements), this really makes little sense and constitutes an awkward abuse of the method. The fact that you want to filter out some of the class' state makes this approach even more dubious.

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Like many others, I would suggest implementing a to_dict() function rather than (or in addition to) allowing casting to a dictionary. I think it makes it more obvious that the class supports that kind of functionality. You could easily implement such a method like this:

def to_dict(self):
class_vars = vars(MyClass)  # get any "default" attrs defined at the class level
inst_vars = vars(self)  # get any attrs defined on the instance (self)
all_vars = dict(class_vars)
all_vars.update(inst_vars)
# filter out private attributes
public_vars = {k: v for k, v in all_vars.items() if not k.startswith('_')}
return public_vars

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I am trying to write a class that is "both" a list or a dict. I want the programmer to be able to both "cast" this object to a list (dropping the keys) or dict (with the keys).

Looking at the way Python currently does the dict() cast: It calls Mapping.update() with the object that is passed. This is the code from the Python repo:

def update(self, other=(), /, **kwds):
''' D.update([E, ]**F) -> None.  Update D from mapping/iterable E and F.
If E present and has a .keys() method, does:     for k in E: D[k] = E[k]
If E present and lacks .keys() method, does:     for (k, v) in E: D[k] = v
In either case, this is followed by: for k, v in F.items(): D[k] = v
'''
if isinstance(other, Mapping):
for key in other:
self[key] = other[key]
elif hasattr(other, "keys"):
for key in other.keys():
self[key] = other[key]
else:
for key, value in other:
self[key] = value
for key, value in kwds.items():
self[key] = value

The last subcase of the if statement, where it is iterating over other is the one most people have in mind. However, as you can see, it is also possible to have a keys() property. That, combined with a __getitem__() should make it easy to have a subclass be properly casted to a dictionary:

class Wharrgarbl(object):
def __init__(self, a, b, c, sum, version='old'):
self.a = a
self.b = b
self.c = c
self.sum = 6
self.version = version


def __int__(self):
return self.sum + 9000


def __keys__(self):
return ["a", "b", "c"]


def __getitem__(self, key):
# have obj["a"] -> obj.a
return self.__getattribute__(key)

Then this will work:

>>> w = Wharrgarbl('one', 'two', 'three', 6)
>>> dict(w)
{'a': 'one', 'c': 'three', 'b': 'two'}

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Here is very clean and fast solution I created a function that converts any custom class to dict

def convert_to_dict(args: dict):
json = dict()
for key, value in args.items():
key_vals = str(key).split("_")
last_index = len(key_vals)
json[str(key_vals[last_index-1])] = value
return json

what you need is to supply it object.__dict__ then it will do the job for you to clean it and help you store it in databse.

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Going off of the asdict solution, here's a useful mixin for if you want to add asdict to several different classes.

Adapted from: https://www.pythontutorial.net/python-oop/python-mixin/

class DictMixin:
def asdict(self):
return self._traverse_dict(self._attrs)


def _traverse_dict(self, attributes: dict) -> dict:
result = {}
for key, value in attributes.items():
result[key] = self._traverse(value)


return result


def _traverse(self, value):
if isinstance(value, DictMixin):
return value.asdict()
elif isinstance(value, dict):
return self._traverse_dict(value)
elif isinstance(value, list):
return [self._traverse(v) for v in value]
else:
return value

Which you can then use:

class FooBar(DictMixin):
_attrs = ["foo", "hello"]


def __init__(self):
self.foo = "bar"
self.hello = "world"

>>> a = FooBar()
>>> a.asdict()
{
"foo": "bar",
"hello": "world"
}

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You can create a folder like 'Strategy' then you can use pickle to save and load the objects of your class.

import pickle
import os


# Load object as dictionary ---------------------------------------------------
def load_object():
file_path = 'Strategy\\All_Pickles.hd5'
if not os.path.isfile(file_path):
return {}
with open(file_path, 'rb') as file:
unpickler = pickle.Unpickler(file)
return dict(unpickler.load())




# Save object as dictionary ---------------------------------------------------
def save_object(name, value):
file_path = 'Strategy\\All_Pickles.hd5'
object_dict = load_object()
with open(file_path, 'wb') as file:
object_dict[name] = value
pickle.dump(object_dict, file)
return True




class MyClass:
def __init__(self, name):
self.name = name


def show(self):
print(self.name)




save_object('1', MyClass('Test1'))
save_object('2', MyClass('Test2'))
objects = load_object()
obj1 = objects['1']
obj2 = objects['2']
obj1.show()
obj2.show()

I created two objects of one class and called a method of the class. I hope, it can help you.

In python, how do I cast a class object to a dict