I’m a bit confused about what can/can’t be used as a key for a python dict.

dicked = {}
dicked[None] = 'foo'     # None ok
dicked[(1,3)] = 'baz'    # tuple ok
import sys
dicked[sys] = 'bar'      # wow, even a module is ok !
dicked[(1,[3])] = 'qux'  # oops, not allowed

So a tuple is an immutable type but if I hide a list inside of it, then it can’t be a key.. couldn’t I just as easily hide a list inside a module?

I had some vague idea that that the key has to be “hashable” but I’m just going to admit my own ignorance about the technical details; I don’t know what’s really going on here. What would go wrong if you tried to use lists as keys, with the hash as, say, their memory location?

There’s a good article on the topic in the Python wiki: Why Lists Can’t Be Dictionary Keys. As explained there:

What would go wrong if you tried to use lists as keys, with the hash as, say, their memory location?

It can be done without really breaking any of the requirements, but it leads to unexpected behavior. Lists are generally treated as if their value was derived from their content’s values, for instance when checking (in-)equality. Many would – understandably – expect that you can use any list [1, 2] to get the same key, where you’d have to keep around exactly the same list object. But lookup by value breaks as soon as a list used as key is modified, and for lookup by identity requires you to keep around exactly the same list – which isn’t requires for any other common list operation (at least none I can think of).

Other objects such as modules and object make a much bigger deal out of their object identity anyway (when was the last time you had two distinct module objects called sys?), and are compared by that anyway. Therefore, it’s less surprising – or even expected – that they, when used as dict keys, compare by identity in that case as well.

Why can’t I use a list as a dict key in python?

>>> d = {repr([1,2,3]): 'value'}
{'[1, 2, 3]': 'value'}

(for anybody who stumbles on this question looking for a way around it)

as explained by others here, indeed you cannot. You can however use its string representation instead if you really want to use your list.

Just found you can change List into tuple, then use it as keys.

d = {tuple([1,2,3]): 'value'}

The issue is that tuples are immutable, and lists are not. Consider the following

d = {}
li = [1,2,3]
d[li] = 5
li.append(4)

What should d[li] return? Is it the same list? How about d[[1,2,3]]? It has the same values, but is a different list?

Ultimately, there is no satisfactory answer. For example, if the only key that works is the original key, then if you have no reference to that key, you can never again access the value. With every other allowed key, you can construct a key without a reference to the original.

If both of my suggestions work, then you have very different keys that return the same value, which is more than a little surprising. If only the original contents work, then your key will quickly go bad, since lists are made to be modified.

Here’s an answer http://wiki.python.org/moin/DictionaryKeys

What would go wrong if you tried to use lists as keys, with the hash as, say, their memory location?

Looking up different lists with the same contents would produce different results, even though comparing lists with the same contents would indicate them as equivalent.

What about Using a list literal in a dictionary lookup?

Your awnser can be found here:

Why Lists Can’t Be Dictionary Keys

Newcomers to Python often wonder why, while the language includes both a tuple and a list type, tuples are usable as a dictionary keys, while lists are not. This was a deliberate design decision, and can best be explained by first understanding how Python dictionaries work.

Source & more info: http://wiki.python.org/moin/DictionaryKeys

Because lists are mutable, dict keys (and set members) need to be hashable, and hashing mutable objects is a bad idea because hash values should be computed on the basis of instance attributes.

In this answer, I will give some concrete examples, hopefully adding value on top of the existing answers. Every insight applies to the elements of the set datastructure as well.

Example 1: hashing a mutable object where the hash value is based on a mutable characteristic of the object.

>>> class stupidlist(list):
...     def __hash__(self):
...         return len(self)
... 
>>> stupid = stupidlist([1, 2, 3])
>>> d = {stupid: 0}
>>> stupid.append(4)
>>> stupid
[1, 2, 3, 4]
>>> d
{[1, 2, 3, 4]: 0}
>>> stupid in d
False
>>> stupid in d.keys()
False
>>> stupid in list(d.keys())
True

After mutating stupid, it cannot be found in the dict any longer because the hash changed. Only a linear scan over the list of the dict’s keys finds stupid.

Example 2: … but why not just a constant hash value?

>>> class stupidlist2(list):
...     def __hash__(self):
...         return id(self)
... 
>>> stupidA = stupidlist2([1, 2, 3])
>>> stupidB = stupidlist2([1, 2, 3])
>>> 
>>> stupidA == stupidB
True
>>> stupidA in {stupidB: 0}
False

That’s not a good idea as well because equal objects should hash identically such that you can find them in a dict or set.

Example 3: … ok, what about constant hashes across all instances?!

>>> class stupidlist3(list):
...     def __hash__(self):
...         return 1
... 
>>> stupidC = stupidlist3([1, 2, 3])
>>> stupidD = stupidlist3([1, 2, 3])
>>> stupidE = stupidlist3([1, 2, 3, 4])
>>> 
>>> stupidC in {stupidD: 0}
True
>>> stupidC in {stupidE: 0}
False
>>> d = {stupidC: 0}
>>> stupidC.append(5)
>>> stupidC in d
True

Things seem to work as expected, but think about what’s happening: when all instances of your class produce the same hash value, you will have a hash collision whenever there are more than two instances as keys in a dict or present in a set.

Finding the right instance with my_dict[key] or key in my_dict (or item in my_set) needs to perform as many equality checks as there are instances of stupidlist3 in the dict’s keys (in the worst case). At this point, the purpose of the dictionary – O(1) lookup – is completely defeated. This is demonstrated in the following timings (done with IPython).

Some Timings for Example 3

>>> lists_list = [[i]  for i in range(1000)]
>>> stupidlists_set = {stupidlist3([i]) for i in range(1000)}
>>> tuples_set = {(i,) for i in range(1000)}
>>> l = [999]
>>> s = stupidlist3([999])
>>> t = (999,)
>>> 
>>> %timeit l in lists_list
25.5 µs ± 442 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)
>>> %timeit s in stupidlists_set
38.5 µs ± 61.2 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)
>>> %timeit t in tuples_set
77.6 ns ± 1.5 ns per loop (mean ± std. dev. of 7 runs, 10000000 loops each)

As you can see, the membership test in our stupidlists_set is even slower than a linear scan over the whole lists_list, while you have the expected super fast lookup time (factor 500) in a set without loads of hash collisions.

TL; DR: you can use tuple(yourlist) as dict keys, because tuples are immutable and hashable.

The simple answer to your question is that the class list does not implement the method hash which is required for any object which wishes to be used as a key in a dictionary. However the reason why hash is not implemented the same way it is in say the tuple class (based on the content of the container) is because a list is mutable so editing the list would require the hash to be recalculated which may mean the list in now located in the wrong bucket within the underling hash table. Note that since you cannot modify a tuple (immutable) it doesn’t run into this problem.

As a side note, the actual implementation of the dictobjects lookup is based on Algorithm D from Knuth Vol. 3, Sec. 6.4. If you have that book available to you it might be a worthwhile read, in addition if you’re really, really interested you may like to take a peek at the developer comments on the actual implementation of dictobject here. It goes into great detail as to exactly how it works. There is also a python lecture on the implementation of dictionaries which you may be interested in. They go through the definition of a key and what a hash is in the first few minutes.

According to the Python 2.7.2 documentation:

An object is hashable if it has a hash value which never changes during its lifetime (it needs a hash() method), and can be compared to other objects (it needs an eq() or cmp() method). Hashable objects which compare equal must have the same hash value.

Hashability makes an object usable as a dictionary key and a set member, because these data structures use the hash value internally.

All of Python’s immutable built-in objects are hashable, while no mutable containers (such as lists or dictionaries) are. Objects which are instances of user-defined classes are hashable by default; they all compare unequal, and their hash value is their id().

A tuple is immutable in the sense that you cannot add, remove or replace its elements, but the elements themselves may be mutable. List’s hash value depends on the hash values of its elements, and so it changes when you change the elements.

Using id’s for list hashes would imply that all lists compare differently, which would be surprising and inconvenient.

A Dictionary is a HashMap it stores map of your keys, value converted to a hashed new key and value mapping.

something like (psuedo code):

{key : val}  
hash(key) = val

If you are wondering which are available options that can be used as key for your dictionary. Then

anything which is hashable(can be converted to hash, and hold static value i.e immutable so as to make a hashed key as stated above) is eligible but as list or set objects can be vary on the go so hash(key) should also needs to vary just to be in sync with your list or set.

You can try :

hash(<your key here>)

If it works fine it can be used as key for your dictionary or else convert it to something hashable.

Inshort :

1. Convert that list to tuple(<your list>).
2. Convert that list to str(<your list>).

dict keys need to be hashable. Lists are Mutable and they do not provide a valid hash method.