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Is there a Python 'shortcut' to define a class variable equal to a string version of its own name?

This is a bit of a silly thing, but I want to know if there is concise way in Python to define class variables that contain string representations of their own names. For example, one can define:
class foo(object):
bar = 'bar'
baz = 'baz'
baf = 'baf'
Probably a more concise way to write it in terms of lines consumed is:
class foo(object):
bar, baz, baf = 'bar', 'baz', 'baf'
Even there, though, I still have to type each identifier twice, once on each side of the assignment, and the opportunity for typos is rife.
What I want is something like what sympy provides in its var method:
sympy.var('a,b,c')
The above injects into the namespace the variables a, b, and c, defined as the corresponding sympy symbolic variables.
Is there something comparable that would do this for plain strings?
class foo(object):
[nifty thing]('bar', 'baz', 'baf')
EDIT: To note, I want to be able to access these as separate identifiers in code that uses foo:
>>> f = foo(); print(f.bar)
bar
ADDENDUM: Given the interest in the question, I thought I'd provide more context on why I want to do this. I have two use-cases at present: (1) typecodes for a set of custom exceptions (each Exception subclass has a distinct typecode set); and (2) lightweight enum. My desired feature set is:
Only having to type the typecode / enum name (or value) once in the source definition. class foo(object): bar = 'bar' works fine but means I have to type it out twice in-source, which gets annoying for longer names and exposes a typo risk.
Valid typecodes / enum values exposed for IDE autocomplete.
Values stored internally as comprehensible strings:
For the Exception subclasses, I want to be able to define myError.__str__ as just something like return self.typecode + ": " + self.message + " (" + self.source + ")", without having to do a whole lot of dict-fu to back-reference an int value of self.typecode to a comprehensible and meaningful string.
For the enums, I want to just be able to obtain widget as output from e = myEnum.widget; print(e), again without a lot of dict-fu.
I recognize this will increase overhead. My application is not speed-sensitive (GUI-based tool for driving a separate program), so I don't think this will matter at all.
Straightforward membership testing, by also including (say) a frozenset containing all of the typecodes / enum string values as myError.typecodes/myEnum.E classes. This addresses potential problems from accidental (or intentional.. but why?!) use of an invalid typecode / enum string via simple sanity checks like if not enumVal in myEnum.E: raise(ValueError('Invalid enum value: ' + str(enumVal))).
Ability to import individual enum / exception subclasses via, say, from errmodule import squirrelerror, to avoid cluttering the namespace of the usage environment with non-relevant exception subclasses. I believe this prohibits any solutions requiring post-twiddling on the module level like what Sinux proposed.
For the enum use case, I would rather avoid introducing an additional package dependency since I don't (think I) care about any extra functionality available in the official enum class. In any event, it still wouldn't resolve #1.
I've already figured out implementation I'm satisfied with for all of the above but #1. My interest in a solution to #1 (without breaking the others) is partly a desire to typo-proof entry of the typecode / enum values into source, and partly plain ol' laziness. (Says the guy who just typed up a gigantic SO question on the topic.)

I recommend using collections.namedtuple:
Example:
>>> from collections import namedtuple as nifty_thing
>>> Data = nifty_thing("Data", ["foo", "bar", "baz"])
>>> data = Data(foo=1, bar=2, baz=3)
>>> data.foo
1
>>> data.bar
2
>>> data.baz
3
Side Note: If you are using/on Python 3.x I'd recommend Enum as per #user2357112's comment. This is the standardized approach going forward for Python 3+
Update: Okay so if I understand the OP's exact requirement(s) here I think the only way to do this (and presumably sympy does this too) is to inject the names/variables into the globals() or locals() namespaces. Example:
#!/usr/bin/env python
def nifty_thing(*names):
d = globals()
for name in names:
d[name] = None
nifty_thing("foo", "bar", "baz")
print foo, bar, bar
Output:
$ python foo.py
None None None
NB: I don't really recommend this! :)
Update #2: The other example you showed in your question is implemented like this:
#!/usr/bin/env python
import sys
def nifty_thing(*names):
frame = sys._getframe(1)
locals = frame.f_locals
for name in names:
locals[name] = None
class foo(object):
nifty_thing("foo", "bar", "baz")
f = foo()
print f.foo, f.bar, f.bar
Output:
$ python foo.py
None None None
NB: This is inspired by zope.interface.implements().

current_list = ['bar', 'baz', 'baf']
class foo(object):
"""to be added"""
for i in current_list:
setattr(foo, i, i)
then run this:
>>>f = foo()
>>>print(f.bar)
bar
>>>print(f.baz)
baz

This doesn't work exactly like what you asked for, but it seems like it should do the job:
class AutoNamespace(object):
def __init__(self, names):
try:
# Support space-separated name strings
names = names.split()
except AttributeError:
pass
for name in names:
setattr(self, name, name)
Demo:
>>> x = AutoNamespace('a b c')
>>> x.a
'a'
If you want to do what SymPy does with var, you can, but I would strongly recommend against it. That said, here's a function based on the source code of sympy.var:
def var(names):
from inspect import currentframe
frame = currentframe().f_back
try:
names = names.split()
except AttributeError:
pass
for name in names:
frame.f_globals[name] = name
Demo:
>>> var('foo bar baz')
>>> bar
'bar'
It'll always create global variables, even if you call it from inside a function or class. inspect is used to get at the caller's globals, whereas globals() would get var's own globals.

How about you define the variable as emtpy string and then get their name:
class foo(object):
def __getitem__(self, item):
return item
foo = foo()
print foo['test']

Here's an extension of bman's idea. This has its advantages and disadvantages, but at least it does work with some autocompleters.
class FooMeta(type):
def __getattr__(self, attr):
return attr
def __dir__(self):
return ['bar', 'baz', 'baf']
class foo:
__metaclass__ = FooMeta
This allows access like foo.xxx → 'xxx' for all xxx, but also guides autocomplete through __dir__.

Figured out what I was looking for:
>>> class tester:
... E = frozenset(['this', 'that', 'the', 'other'])
... for s in E:
... exec(str(s) + "='" + str(s) + "'") # <--- THIS
...
>>> tester()
<__main__.tester instance at 0x03018BE8>
>>> t = tester()
>>> t.this
'this'
>>> t.that in tester.E
True
Only have to define the element strings once, and I'm pretty sure it will work for all of my requirements listed in the question. In actual implementation, I plan to encapsulate the str(s) + "='" + str(s) + "'" in a helper function, so that I can just call exec(helper(s)) in the for loop. (I'm pretty sure that the exec has to be placed in the body of the class, not in the helper function, or else the new variables would be injected into the (transitory) scope of the helper function, not that of the class.)
EDIT: Upon detailed testing, this DOES NOT WORK -- the use of exec prevents the introspection of the IDE from knowing of the existence of the created variables.

I think you can achieve a rather beautiful solution using metaclasses, but I'm not fluent enough in using those to present that as an answer, but I do have an option which seems to work rather nicely:
def new_enum(name, *class_members):
"""Builds a class <name> with <class_members> having the name as value."""
return type(name, (object, ), { val : val for val in class_members })
Foo = new_enum('Foo', 'bar', 'baz', 'baf')
This should recreate the class you've given as example, and if you want you can change the inheritance by changing the second parameter of the call to class type(name, bases, dict).

How to use dot notation for dict in python?

I'm very new to python and I wish I could do . notation to access values of a dict.
Lets say I have test like this:
>>> test = dict()
>>> test['name'] = 'value'
>>> print(test['name'])
value
But I wish I could do test.name to get value. Infact I did it by overriding the __getattr__ method in my class like this:
class JuspayObject:
def __init__(self,response):
self.__dict__['_response'] = response
def __getattr__(self,key):
try:
return self._response[key]
except KeyError,err:
sys.stderr.write('Sorry no key matches')
and this works! when I do:
test.name // I get value.
But the problem is when I just print test alone I get the error as:
'Sorry no key matches'
Why is this happening?

This functionality already exists in the standard libraries, so I recommend you just use their class.
>>> from types import SimpleNamespace
>>> d = {'key1': 'value1', 'key2': 'value2'}
>>> n = SimpleNamespace(**d)
>>> print(n)
namespace(key1='value1', key2='value2')
>>> n.key2
'value2'
Adding, modifying and removing values is achieved with regular attribute access, i.e. you can use statements like n.key = val and del n.key.
To go back to a dict again:
>>> vars(n)
{'key1': 'value1', 'key2': 'value2'}
The keys in your dict should be string identifiers for attribute access to work properly.
Simple namespace was added in Python 3.3. For older versions of the language, argparse.Namespace has similar behaviour.

I assume that you are comfortable in Javascript and want to borrow that kind of syntax... I can tell you by personal experience that this is not a great idea.
It sure does look less verbose and neat; but in the long run it is just obscure. Dicts are dicts, and trying to make them behave like objects with attributes will probably lead to (bad) surprises.
If you need to manipulate the fields of an object as if they were a dictionary, you can always resort to use the internal __dict__ attribute when you need it, and then it is explicitly clear what you are doing. Or use getattr(obj, 'key') to have into account the inheritance structure and class attributes too.
But by reading your example it seems that you are trying something different... As the dot operator will already look in the __dict__ attribute without any extra code.

In addition to this answer, one can add support for nested dicts as well:
from types import SimpleNamespace
class NestedNamespace(SimpleNamespace):
def __init__(self, dictionary, **kwargs):
super().__init__(**kwargs)
for key, value in dictionary.items():
if isinstance(value, dict):
self.__setattr__(key, NestedNamespace(value))
else:
self.__setattr__(key, value)
nested_namespace = NestedNamespace({
'parent': {
'child': {
'grandchild': 'value'
}
},
'normal_key': 'normal value',
})
print(nested_namespace.parent.child.grandchild) # value
print(nested_namespace.normal_key) # normal value
Note that this does not support dot notation for dicts that are somewhere inside e.g. lists.

Could you use a named tuple?
from collections import namedtuple
Test = namedtuple('Test', 'name foo bar')
my_test = Test('value', 'foo_val', 'bar_val')
print(my_test)
print(my_test.name)

__getattr__ is used as a fallback when all other attribute lookup rules have failed. When you try to "print" your object, Python look for a __repr__ method, and since you don't implement it in your class it ends up calling __getattr__ (yes, in Python methods are attributes too). You shouldn't assume which key getattr will be called with, and, most important, __getattr__ must raise an AttributeError if it cannot resolve key.
As a side note: don't use self.__dict__ for ordinary attribute access, just use the plain attribute notation:
class JuspayObject:
def __init__(self,response):
# don't use self.__dict__ here
self._response = response
def __getattr__(self,key):
try:
return self._response[key]
except KeyError,err:
raise AttributeError(key)
Now if your class has no other responsability (and your Python version is >= 2.6 and you don't need to support older versions), you may just use a namedtuple : http://docs.python.org/2/library/collections.html#collections.namedtuple

You can use the built-in method argparse.Namespace():
import argparse
args = argparse.Namespace()
args.name = 'value'
print(args.name)
# 'value'
You can also get the original dict via vars(args).

class convert_to_dot_notation(dict):
"""
Access dictionary attributes via dot notation
"""
__getattr__ = dict.get
__setattr__ = dict.__setitem__
__delattr__ = dict.__delitem__
test = {"name": "value"}
data = convert_to_dot_notation(test)
print(data.name)

You have to be careful when using __getattr__, because it's used for a lot of builtin Python functionality.
Try something like this...
class JuspayObject:
def __init__(self,response):
self.__dict__['_response'] = response
def __getattr__(self, key):
# First, try to return from _response
try:
return self.__dict__['_response'][key]
except KeyError:
pass
# If that fails, return default behavior so we don't break Python
try:
return self.__dict__[key]
except KeyError:
raise AttributeError, key
>>> j = JuspayObject({'foo': 'bar'})
>>> j.foo
'bar'
>>> j
<__main__.JuspayObject instance at 0x7fbdd55965f0>

Here is a simple, handy dot notation helper example that is working with nested items:
def dict_get(data:dict, path:str, default = None):
pathList = re.split(r'\.', path, flags=re.IGNORECASE)
result = data
for key in pathList:
try:
key = int(key) if key.isnumeric() else key
result = result[key]
except:
result = default
break
return result
Usage example:
my_dict = {"test1": "str1", "nested_dict": {"test2": "str2"}, "nested_list": ["str3", {"test4": "str4"}]}
print(dict_get(my_dict, "test1"))
# str1
print(dict_get(my_dict, "nested_dict.test2"))
# str2
print(dict_get(my_dict, "nested_list.1.test4"))
# str4

With a small addition to this answer you can support lists as well:
class NestedNamespace(SimpleNamespace):
def __init__(self, dictionary, **kwargs):
super().__init__(**kwargs)
for key, value in dictionary.items():
if isinstance(value, dict):
self.__setattr__(key, NestedNamespace(value))
elif isinstance(value, list):
self.__setattr__(key, map(NestedNamespace, value))
else:
self.__setattr__(key, value)

2022 answer: I've created the dotwiz package -- this is a fast, tiny library that seems to perform really well in most cases.
>>> from dotwiz import DotWiz
>>> test = DotWiz(hello='world')
>>> test.works = True
>>> test
✫(hello='world', works=True)
>>> test.hello
'world'
>>> assert test.works

This feature is baked into OmegaConf:
from omegaconf import OmegaConf
your_dict = {"k" : "v", "list" : [1, {"a": "1", "b": "2", 3: "c"}]}
adot_dict = OmegaConf.create(your_dict)
print(adot_dict.k)
print(adot_dict.list)
Installation is:
pip install omegaconf
This lib comes in handy for configurations, which it is actually made for:
from omegaconf import OmegaConf
cfg = OmegaConf.load('config.yml')
print(cfg.data_path)

I use the dotted_dict package:
>>> from dotted_dict import DottedDict
>>> test = DottedDict()
>>> test.name = 'value'
>>> print(test.name)
value
Advantages over SimpleNamespace
(See #win's answer.) DottedDict is an actual dict:
>>> isinstance(test, dict)
True
This allows, for example, checking for membership:
>>> 'name' in test
True
whereas for SimpleNamespace you need something much less readable like hasattr(test, 'name').
Don't use DotMap
I found this out the hard way. If you reference a non-member it adds it rather than throwing an error. This can lead to hard to find bugs in code:
>>> from dotmap import DotMap
>>> dm = DotMap()
>>> 'a' in dm
False
>>> x = dm.a
>>> 'a' in dm
True

#!/usr/bin/env python3
import json
from sklearn.utils import Bunch
from collections.abc import MutableMapping
def dotted(inpt: MutableMapping,
*args,
**kwargs
) -> Bunch:
"""
Enables recursive dot notation for ``dict``.
"""
return json.loads(json.dumps(inpt),
object_hook=lambda x:
Bunch(**{**Bunch(), **x}))

You can make hacks adding dot notation to Dicts mostly work, but there are always namespace problems. As in, what does this do?
x = DotDict()
x["values"] = 1989
print(x. values)
I use pydash, which is a Python port of JS's lodash, to do these things a different way when the nesting gets too ugly.

Add a __repr__() method to the class so that you can customize the text to be shown on
print text
Learn more here: https://web.archive.org/web/20121022015531/http://diveintopython.net/object_oriented_framework/special_class_methods2.html

What do I do when I need a self referential dictionary?

I'm new to Python, and am sort of surprised I cannot do this.
dictionary = {
'a' : '123',
'b' : dictionary['a'] + '456'
}
I'm wondering what the Pythonic way to correctly do this in my script, because I feel like I'm not the only one that has tried to do this.
EDIT: Enough people were wondering what I'm doing with this, so here are more details for my use cases. Lets say I want to keep dictionary objects to hold file system paths. The paths are relative to other values in the dictionary. For example, this is what one of my dictionaries may look like.
dictionary = {
'user': 'sholsapp',
'home': '/home/' + dictionary['user']
}
It is important that at any point in time I may change dictionary['user'] and have all of the dictionaries values reflect the change. Again, this is an example of what I'm using it for, so I hope that it conveys my goal.
From my own research I think I will need to implement a class to do this.

No fear of creating new classes -
You can take advantage of Python's string formating capabilities
and simply do:
class MyDict(dict):
def __getitem__(self, item):
return dict.__getitem__(self, item) % self
dictionary = MyDict({
'user' : 'gnucom',
'home' : '/home/%(user)s',
'bin' : '%(home)s/bin'
})
print dictionary["home"]
print dictionary["bin"]

Nearest I came up without doing object:
dictionary = {
'user' : 'gnucom',
'home' : lambda:'/home/'+dictionary['user']
}
print dictionary['home']()
dictionary['user']='tony'
print dictionary['home']()

>>> dictionary = {
... 'a':'123'
... }
>>> dictionary['b'] = dictionary['a'] + '456'
>>> dictionary
{'a': '123', 'b': '123456'}
It works fine but when you're trying to use dictionary it hasn't been defined yet (because it has to evaluate that literal dictionary first).
But be careful because this assigns to the key of 'b' the value referenced by the key of 'a' at the time of assignment and is not going to do the lookup every time. If that is what you are looking for, it's possible but with more work.

What you're describing in your edit is how an INI config file works. Python does have a built in library called ConfigParser which should work for what you're describing.

This is an interesting problem. It seems like Greg has a good solution. But that's no fun ;)
jsbueno as a very elegant solution but that only applies to strings (as you requested).
The trick to a 'general' self referential dictionary is to use a surrogate object. It takes a few (understatement) lines of code to pull off, but the usage is about what you want:
S = SurrogateDict(AdditionSurrogateDictEntry)
d = S.resolve({'user': 'gnucom',
'home': '/home/' + S['user'],
'config': [S['home'] + '/.emacs', S['home'] + '/.bashrc']})
The code to make that happen is not nearly so short. It lives in three classes:
import abc
class SurrogateDictEntry(object):
__metaclass__ = abc.ABCMeta
def __init__(self, key):
"""record the key on the real dictionary that this will resolve to a
value for
"""
self.key = key
def resolve(self, d):
""" return the actual value"""
if hasattr(self, 'op'):
# any operation done on self will store it's name in self.op.
# if this is set, resolve it by calling the appropriate method
# now that we can get self.value out of d
self.value = d[self.key]
return getattr(self, self.op + 'resolve__')()
else:
return d[self.key]
#staticmethod
def make_op(opname):
"""A convience class. This will be the form of all op hooks for subclasses
The actual logic for the op is in __op__resolve__ (e.g. __add__resolve__)
"""
def op(self, other):
self.stored_value = other
self.op = opname
return self
op.__name__ = opname
return op
Next, comes the concrete class. simple enough.
class AdditionSurrogateDictEntry(SurrogateDictEntry):
__add__ = SurrogateDictEntry.make_op('__add__')
__radd__ = SurrogateDictEntry.make_op('__radd__')
def __add__resolve__(self):
return self.value + self.stored_value
def __radd__resolve__(self):
return self.stored_value + self.value
Here's the final class
class SurrogateDict(object):
def __init__(self, EntryClass):
self.EntryClass = EntryClass
def __getitem__(self, key):
"""record the key and return"""
return self.EntryClass(key)
#staticmethod
def resolve(d):
"""I eat generators resolve self references"""
stack = [d]
while stack:
cur = stack.pop()
# This just tries to set it to an appropriate iterable
it = xrange(len(cur)) if not hasattr(cur, 'keys') else cur.keys()
for key in it:
# sorry for being a duche. Just register your class with
# SurrogateDictEntry and you can pass whatever.
while isinstance(cur[key], SurrogateDictEntry):
cur[key] = cur[key].resolve(d)
# I'm just going to check for iter but you can add other
# checks here for items that we should loop over.
if hasattr(cur[key], '__iter__'):
stack.append(cur[key])
return d
In response to gnucoms's question about why I named the classes the way that I did.
The word surrogate is generally associated with standing in for something else so it seemed appropriate because that's what the SurrogateDict class does: an instance replaces the 'self' references in a dictionary literal. That being said, (other than just being straight up stupid sometimes) naming is probably one of the hardest things for me about coding. If you (or anyone else) can suggest a better name, I'm all ears.
I'll provide a brief explanation. Throughout S refers to an instance of SurrogateDict and d is the real dictionary.
A reference S[key] triggers S.__getitem__ and SurrogateDictEntry(key) to be placed in the d.
When S[key] = SurrogateDictEntry(key) is constructed, it stores key. This will be the key into d for the value that this entry of SurrogateDictEntry is acting as a surrogate for.
After S[key] is returned, it is either entered into the d, or has some operation(s) performed on it. If an operation is performed on it, it triggers the relative __op__ method which simple stores the value that the operation is performed on and the name of the operation and then returns itself. We can't actually resolve the operation because d hasn't been constructed yet.
After d is constructed, it is passed to S.resolve. This method loops through d finding any instances of SurrogateDictEntry and replacing them with the result of calling the resolve method on the instance.
The SurrogateDictEntry.resolve method receives the now constructed d as an argument and can use the value of key that it stored at construction time to get the value that it is acting as a surrogate for. If an operation was performed on it after creation, the op attribute will have been set with the name of the operation that was performed. If the class has a __op__ method, then it has a __op__resolve__ method with the actual logic that would normally be in the __op__ method. So now we have the logic (self.op__resolve) and all necessary values (self.value, self.stored_value) to finally get the real value of d[key]. So we return that which step 4 places in the dictionary.
finally the SurrogateDict.resolve method returns d with all references resolved.
That'a a rough sketch. If you have any more questions, feel free to ask.

If you, just like me wandering how to make #jsbueno snippet work with {} style substitutions, below is the example code (which is probably not much efficient though):
import string
class MyDict(dict):
def __init__(self, *args, **kw):
super(MyDict,self).__init__(*args, **kw)
self.itemlist = super(MyDict,self).keys()
self.fmt = string.Formatter()
def __getitem__(self, item):
return self.fmt.vformat(dict.__getitem__(self, item), {}, self)
xs = MyDict({
'user' : 'gnucom',
'home' : '/home/{user}',
'bin' : '{home}/bin'
})
>>> xs["home"]
'/home/gnucom'
>>> xs["bin"]
'/home/gnucom/bin'
I tried to make it work with the simple replacement of % self with .format(**self) but it turns out it wouldn't work for nested expressions (like 'bin' in above listing, which references 'home', which has it's own reference to 'user') because of the evaluation order (** expansion is done before actual format call and it's not delayed like in original % version).

Write a class, maybe something with properties:
class PathInfo(object):
def __init__(self, user):
self.user = user
#property
def home(self):
return '/home/' + self.user
p = PathInfo('thc')
print p.home # /home/thc

As sort of an extended version of #Tony's answer, you could build a dictionary subclass that calls its values if they are callables:
class CallingDict(dict):
"""Returns the result rather than the value of referenced callables.
>>> cd = CallingDict({1: "One", 2: "Two", 'fsh': "Fish",
... "rhyme": lambda d: ' '.join((d[1], d['fsh'],
... d[2], d['fsh']))})
>>> cd["rhyme"]
'One Fish Two Fish'
>>> cd[1] = 'Red'
>>> cd[2] = 'Blue'
>>> cd["rhyme"]
'Red Fish Blue Fish'
"""
def __getitem__(self, item):
it = super(CallingDict, self).__getitem__(item)
if callable(it):
return it(self)
else:
return it
Of course this would only be usable if you're not actually going to store callables as values. If you need to be able to do that, you could wrap the lambda declaration in a function that adds some attribute to the resulting lambda, and check for it in CallingDict.__getitem__, but at that point it's getting complex, and long-winded, enough that it might just be easier to use a class for your data in the first place.

This is very easy in a lazily evaluated language (haskell).
Since Python is strictly evaluated, we can do a little trick to turn things lazy:
Y = lambda f: (lambda x: x(x))(lambda y: f(lambda *args: y(y)(*args)))
d1 = lambda self: lambda: {
'a': lambda: 3,
'b': lambda: self()['a']()
}
# fix the d1, and evaluate it
d2 = Y(d1)()
# to get a
d2['a']() # 3
# to get b
d2['b']() # 3
Syntax wise this is not very nice. That's because of us needing to explicitly construct lazy expressions with lambda: ... and explicitly evaluate lazy expression with ...(). It's the opposite problem in lazy languages needing strictness annotations, here in Python we end up needing lazy annotations.
I think with some more meta-programmming and some more tricks, the above could be made more easy to use.
Note that this is basically how let-rec works in some functional languages.

The jsbueno answer in Python 3 :
class MyDict(dict):
def __getitem__(self, item):
return dict.__getitem__(self, item).format(self)
dictionary = MyDict({
'user' : 'gnucom',
'home' : '/home/{0[user]}',
'bin' : '{0[home]}/bin'
})
print(dictionary["home"])
print(dictionary["bin"])
Her ewe use the python 3 string formatting with curly braces {} and the .format() method.
Documentation : https://docs.python.org/3/library/string.html

Accessing the name of an instance in Python for printing

So as part of problem 17.6 in "Think Like a Computer Scientist", I've written a class called Kangaroo:
class Kangaroo(object):
def __init__(self, pouch_contents = []):
self.pouch_contents = pouch_contents
def __str__(self):
'''
>>> kanga = Kangaroo()
>>> kanga.put_in_pouch('olfactory')
>>> kanga.put_in_pouch(7)
>>> kanga.put_in_pouch(8)
>>> kanga.put_in_pouch(9)
>>> print kanga
"In kanga's pouch there is: ['olfactory', 7, 8, 9]"
'''
return "In %s's pouch there is: %s" % (object.__str__(self), self.pouch_contents)
def put_in_pouch(self, other):
'''
>>> kanga = Kangaroo()
>>> kanga.put_in_pouch('olfactory')
>>> kanga.put_in_pouch(7)
>>> kanga.put_in_pouch(8)
>>> kanga.put_in_pouch(9)
>>> kanga.pouch_contents
['olfactory', 7, 8, 9]
'''
self.pouch_contents.append(other)
What's driving me nuts is that I'd like to be able to write a string method that would pass the unit test underneath __str__ as written. What I'm getting now instead is:
In <__main__.Kangaroo object at 0x4dd870>'s pouch there is: ['olfactory', 7, 8, 9]
Bascially, what I'm wondering if there is some function that I can perform on kanga = Kangaroo such that the output of the function is those 5 characters, i.e. function(kanga) -> "kanga".
Any ideas?
Edit:
Reading the first answer has made me realize that there is a more concise way to ask my original question. Is there a way to rewrite __init__ such that the following code is valid as written?
>>> somename = Kangaroo()
>>> somename.name
'somename'

To put your request into perspective, please explain what name you would like attached to the object created by this code:
marsupials = []
marsupials.append(Kangaroo())
This classic essay by the effbot gives an excellent explanation.
To answer the revised question in your edit: No.
Now that you've come clean in a comment and said that the whole purpose of this naming exercise was to distinguish between objects for debugging purposes associated with your mutable default argument:
In CPython implementations of Python at least, at any given time, all existing objects have a unique ID, which may be obtained by id(obj). This may be sufficient for your debugging purposes. Note that if an object is deleted, that ID (which is a memory address) can be re-used by a subsequently created object.

I wasn't going to post this but if you only want this for debugging then here you go:
import sys
class Kangaroo(object):
def __str__(self):
flocals = sys._getframe(1).f_locals
for ident in flocals:
if flocals[ident] is self:
name = ident
break
else:
name = 'roo'
return "in {0}'s pouch, there is {1}".format(name, self.pouch_contents)
kang = Kangaroo()
print kang
This is dependent on CPython (AFAIK) and isn't suitable for production code. It wont work if the instance is in any sort of container and may fail for any reason at any time. It should do the trick for you though.
It works by getting the f_locals dictionary out of the stack frame that represents the namespace where print kang is called. The keys of f_locals are the names of the variables in the frame so we just loop through it and test if each entry is self. If so, we break. If break is not executed, then we didn't find an entry and the loops else clause assigns the value 'roo' as requested.
If you want to get it out of a container of some sort, you need to extend this to look through any containers in f_locals. You could either return the key if it's a dictlike container or the index if it's something like a tuple or list.

class Kangaroo(object):
def __init__(self, pouch_contents=None, name='roo'):
if pouch_contents is None:
self.pouch_contents = [] # this isn't shared with all other instances
else:
self.pouch_contents = pouch_contents
self.name = name
...
kanga = Kangaroo(name='kanga')
Note that it's good style not to put spaces around = in the arguments

What you want is basically impossible in Python, even with the suggested "hacks". For example,
what would the following code print?
>>> kanga1 = kanga2 = kanga3 = Kangaroo()
>>> kanga2.name
???
>>> kanga3.name
???
or
>>> l = [Kangaroo()]
>>> l[0].name
???
If you want "named" objects, just supply a name to your object
def __init__(self, name):
self.name = name
More explicit (which we like with Python) and consistent in all cases. Sure you can do something like
>>> foo = Kangaroo("bar")
>>> foo.name
'bar'
but foo will be just one of the possibly many labels the instance has. The name is explicit and permanent. You can even enforce unique naming if you want (while you can reuse a variable as much as you want for different objects)

I hadn't seen aaronasterling's hackish answer when I started working on this, but in any case here's a hackish answer of my own:
class Kangaroo(object):
def __init__(self, pouch_contents = ()):
self.pouch_contents = list(pouch_contents)
def __str__(self):
if not hasattr(self, 'name'):
for k, v in globals().iteritems():
if id(v) == id(self):
self.name = k
break
else:
self.name = 'roo'
return "In %s's pouch there is: %s" % (self.name, self.pouch_contents)
kanga = Kangaroo()
print kanga
You can break this by looking at it funny (it works as written, but it will fail as part of a doctest), but it works. I'm more concerned with what's possible than with what's practical at this point in my learning experience, so I'm glad to see that there are at least two different ways to do a thing I figured should be possible to do. Even if they're bad ways.

Structure accessible by attribute name or index options

I am very new to Python, and trying to figure out how to create an object that has values that are accessible either by attribute name, or by index. For example, the way os.stat() returns a stat_result or pwd.getpwnam() returns a struct_passwd.
In trying to figure it out, I've only come across C implementations of the above types. Nothing specifically in Python. What is the Python native way to create this kind of object?
I apologize if this has been widely covered already. In searching for an answer, I must be missing some fundamental concept that is excluding me from finding an answer.

Python 2.6 introduced collections.namedtuple to make this easy. With older Python versions you can use the named tuple recipe.
Quoting directly from the docs:
>>> Point = namedtuple('Point', 'x y')
>>> p = Point(11, y=22) # instantiate with positional or keyword arguments
>>> p[0] + p[1] # indexable like the plain tuple (11, 22)
33
>>> x, y = p # unpack like a regular tuple
>>> x, y
(11, 22)
>>> p.x + p.y # fields also accessible by name
33
>>> p # readable __repr__ with a name=value style
Point(x=11, y=22)

You can't use the same implementation as the result object of os.stat() and others. However Python 2.6 has a new factory function that creates a similar datatype called named tuple. A named tuple is a tuple whose slots can also be addressed by name. The named tuple should not require any more memory, according to the documentation, than a regular tuple, since they don't have a per instance dictionary. The factory function signature is:
collections.namedtuple(typename, field_names[, verbose])
The first argument specifies the name of the new type, the second argument is a string (space or comma separated) containing the field names and, finally, if verbose is true, the factory function will also print the class generated.
Example
Suppose you have a tuple containing a username and password. To access the username you get the item at position zero and the password is accessed at position one:
credential = ('joeuser', 'secret123')
print 'Username:', credential[0]
print 'Password:', credential[1]
There's nothing wrong with this code but the tuple isn't self-documenting. You have to find and read the documentation about the positioning of the fields in the tuple. This is where named tuple can come to the rescue. We can recode the previous example as follows:
import collections
# Create a new sub-tuple named Credential
Credential = collections.namedtuple('Credential', 'username, password')
credential = Credential(username='joeuser', password='secret123')
print 'Username:', credential.username
print 'Password:', credential.password
If you are interested of what the code looks like for the newly created Credential-type you can add verbose=True to the argument list when creating the type, in this particular case we get the following output:
import collections
Credential = collections.namedtuple('Credential', 'username, password', verbose=True)
class Credential(tuple):
'Credential(username, password)'
__slots__ = ()
_fields = ('username', 'password')
def __new__(_cls, username, password):
return _tuple.__new__(_cls, (username, password))
#classmethod
def _make(cls, iterable, new=tuple.__new__, len=len):
'Make a new Credential object from a sequence or iterable'
result = new(cls, iterable)
if len(result) != 2:
raise TypeError('Expected 2 arguments, got %d' % len(result))
return result
def __repr__(self):
return 'Credential(username=%r, password=%r)' % self
def _asdict(t):
'Return a new dict which maps field names to their values'
return {'username': t[0], 'password': t[1]}
def _replace(_self, **kwds):
'Return a new Credential object replacing specified fields with new values'
result = _self._make(map(kwds.pop, ('username', 'password'), _self))
if kwds:
raise ValueError('Got unexpected field names: %r' % kwds.keys())
return result
def __getnewargs__(self):
return tuple(self)
username = _property(_itemgetter(0))
password = _property(_itemgetter(1))
The named tuple doesn't only provide access to fields by name but also contains helper functions such as the _make() function which helps creating an Credential instance from a sequence or iterable. For example:
cred_tuple = ('joeuser', 'secret123')
credential = Credential._make(cred_tuple)
The python library documentation for namedtuple has more information and code examples, so I suggest that you take a peek.

an object that has values that are accessible either by attribute name, or by index
I'm not sure what you're finding hard about this.
A collection accessible by index implements __getitem__.
A collection accessible by names implements __getattr__ (or __getattribute__).
You can implement both without any trouble at all. Or, you can use namedtuple.
To make life simpler, you could extend the tuple class so you don't have to implement your own __getitem__. Or you can define an ordinary class that also has __getitem__ so you didn't have to mess with __getattr__.
For example
>>> class Foo( object ):
... def __init__( self, x, y, z ):
... self.x= x
... self.y= y
... self.z= z
... def __getitem__( self, index ):
... return { 0: self.x, 1: self.y, 2: self.z }[index]
...
>>> f= Foo(1,2,3)
>>> f.x
1
>>> f[0]
1
>>> f[1]
2
>>> f[2]
3
>>> f.y
2