Python dictionary - binary search for a key?

Question

I want to write a container class that acts like a dictionary (actually derives from a dict), The keys for this structure will be dates.

When a key (i.e. date) is used to retrieve a value from the class, if the date does not exist then the next available date that preceeds the key is used to return the value.

The following data should help explain the concept further:

Date (key)      Value
2001/01/01      123
2001/01/02       42
2001/01/03      100
2001/01/04      314
2001/01/07      312
2001/01/09      321

If I try to fetch the value associated with key (date) '2001/01/05' I should get the value stored under the key 2001/01/04 since that key occurs before where the key '2001/01/05' would be if it existed in the dictionary.

In order to do this, I need to be able to do a search (ideally binary, rather than naively looping through every key in the dictionary). I have searched for bsearch dictionary key lookups in Python dictionaries - but have not found anything useful.

Anyway, I want to write a class like that encapsulates this behavior.

This is what I have so far (not much):

#
class NearestNeighborDict(dict):
#
"""
#
a dictionary which returns value of nearest neighbor 
if specified key not found
#
"""

def __init__(self, items={}):
    dict.__init__(self, items)


def get_item(self, key):
    # returns the item stored with the key (if key exists)
    # else it returns the item stored with the key

Answer 1

You really don't want to subclass dict because you can't really reuse any of its functionality. Rather, subclass the abstract base class collections.Mapping (or MutableMapping if you want to also be able to modify an instance after creation), implement the indispensable special methods for the purpose, and you'll get other dict-like methods "for free" from the ABC.

The methods you need to code are __getitem__ (and __setitem__ and __delitem__ if you want mutability), __len__, __iter__, and __contains__.

The bisect module of the standard library gives you all you need to implement these efficiently on top of a sorted list. For example...:

import collections
import bisect

class MyDict(collections.Mapping):
  def __init__(self, contents):
    "contents must be a sequence of key/value pairs"
    self._list = sorted(contents)
  def __iter__(self):
    return (k for (k, _) in self._list)
  def __contains__(self, k):
    i = bisect.bisect_left(self._list, (k, None))
    return i < len(self._list) and self._list[i][0] == k
  def __len__(self):
    return len(self._list)
  def __getitem__(self, k):
    i = bisect.bisect_left(self._list, (k, None))
    if i >= len(self._list): raise KeyError(k)
    return self._list[i][1]

You'll probably want to fiddle __getitem__ depending on what you want to return (or whether you want to raise) for various corner cases such as "k greater than all keys in self".

Answer 2

I'd extend a dict, and override the __getitem__ and __setitem__ method to store a sorted list of keys.

from bisect import bisect

class NearestNeighborDict(dict):
    def __init__(self):
        dict.__init__(self)
        self._keylist = []

    def __getitem__(self, x):
        if x in self:
            return dict.__getitem__(self, x)

        index = bisect(self._keylist, x)
        if index == len(self._keylist):
            raise KeyError('No next date')

        return dict.__getitem__(self, self._keylist[index])

    def __setitem__(self, x, value):
        if x not in self:
            index = bisect(self._keylist, x)
            self._keylist.insert(index, value)

        dict.__setitem__(self, x, value)

It's true you're better off inheriting from MutableMapping, but the principle is the same, and the above code can be easily adapted.

Answer 3

Why not just maintain a sorted list from dict.keys() and search that? If you're subclassing dict you may even devise an opportunity to do a binary insert on that list when values are added.