Accessing items in an collections OrderedDict by index

Question

Lets say I have the following code   import collections d   collections OrderedDict   d  foo      python  d  bar      spam    Is there a way I can access the items in a numbered manner  like    d 0   foo s Output d 1   bar s Output

User · Accepted Answer

If its an OrderedDict   you can easily access the elements by indexing by getting the tuples of  key value  pairs as follows   gt  gt  gt  import collections  gt  gt  gt  d   collections OrderedDict    gt  gt  gt  d  foo      python   gt  gt  gt  d  bar      spam   gt  gt  gt  d items      foo    python      bar    spam     gt  gt  gt  d items   0    foo    python    gt  gt  gt  d items   1    bar    spam     Note for Python 3 X  dict items would return an iterable dict view object rather than a list  We need to wrap the call onto a list in order to make the indexing possible   gt  gt  gt  items   list d items     gt  gt  gt  items    foo    python      bar    spam     gt  gt  gt  items 0    foo    python    gt  gt  gt  items 1    bar    spam

User · Answer

Here is a special case if you want the first entry  or close to it  in an OrderedDict  without creating a list    This has been updated to Python 3     gt  gt  gt  from collections import OrderedDict  gt  gt  gt    gt  gt  gt  d   OrderedDict    gt  gt  gt  d  foo      one   gt  gt  gt  d  bar      two   gt  gt  gt  d  baz      three   gt  gt  gt  next iter d items       foo    one    gt  gt  gt  next iter d values      one     The first time you say  next     it really means  first     In my informal test  next iter d items     with a small OrderedDict is only a tiny bit faster than items   0    With an OrderedDict of 10 000 entries  next iter d items     was about 200 times faster than items   0     BUT if you save the items   list once and then use the list a lot  that could be faster   Or if you repeatedly   create an items   iterator and step through it to to the position you want    that could be slower

User · Answer

for OrderedDict   you can access the elements by indexing by getting the tuples of  key value  pairs as follows or using    values      gt  gt  gt  import collections  gt  gt  gt  d   collections OrderedDict    gt  gt  gt  d  foo      python   gt  gt  gt  d  bar      spam   gt  gt  gt  d items      foo    python      bar    spam     gt  gt  gt d values   odict values   python   spam     gt  gt  gt list d values      python   spam

User · Answer

If you re dealing with fixed number of keys that you know in advance  use Python s inbuilt namedtuples instead  A possible use-case is when you want to store some constant data and access it throughout the program by both indexing and specifying keys  import collections ordered keys     foo    bar   D   collections namedtuple  D   ordered keys  d   D foo  python   bar  spam    Access by indexing  d 0    result  python d 1    result  spam  Access by specifying keys  d foo   result  python d bar   result  spam  Or better  getattr d   foo     result  python getattr d   bar     result  spam

User · Answer

It s a new era and with Python 3 6 1 dictionaries now retain their order  These semantics aren t explicit because that would require BDFL approval  But Raymond Hettinger is the next best thing  and funnier  and he makes a pretty strong case that dictionaries will be ordered for a very long time   So now it s easy to create slices of a dictionary   test dict                      first    1                   second   2                   third    3                   fourth   4                list test dict items     2    Note  Dictonary insertion-order preservation is now official in Python 3 7

User · Answer

This community wiki attempts to collect existing answers   Python 2 7  In python 2  the keys    values    and items   functions of OrderedDict return lists  Using values as an example  the simplest way is  d values   0      python  d values   1      spam    For large collections where you only care about a single index  you can avoid creating the full list using the generator versions  iterkeys  itervalues and iteritems   import itertools next itertools islice d itervalues    0  1       python  next itertools islice d itervalues    1  2       spam    The indexed py package provides IndexedOrderedDict  which is designed for this use case and will be the fastest option   from indexed import IndexedOrderedDict d   IndexedOrderedDict   foo   python   bar   spam    d values   0      python  d values   1      spam    Using itervalues can be considerably faster for large dictionaries with random access     python2 -m timeit -s  from collections import OrderedDict  from random import randint  size   1000    d   OrderedDict  i i for i in range size       i   randint 0  size-1   d values   i i 1   1000 loops  best of 3  259 usec per loop   python2 -m timeit -s  from collections import OrderedDict  from random import randint  size   10000   d   OrderedDict  i i for i in range size      i   randint 0  size-1   d values   i i 1   100 loops  best of 3  2 3 msec per loop   python2 -m timeit -s  from collections import OrderedDict  from random import randint  size   100000  d   OrderedDict  i i for i in range size      i   randint 0  size-1   d values   i i 1   10 loops  best of 3  24 5 msec per loop    python2 -m timeit -s  from collections import OrderedDict  from random import randint  size   1000    d   OrderedDict  i i for i in range size      i   randint 0  size-1   next itertools islice d itervalues    i  i 1    10000 loops  best of 3  118 usec per loop   python2 -m timeit -s  from collections import OrderedDict  from random import randint  size   10000   d   OrderedDict  i i for i in range size      i   randint 0  size-1   next itertools islice d itervalues    i  i 1    1000 loops  best of 3  1 26 msec per loop   python2 -m timeit -s  from collections import OrderedDict  from random import randint  size   100000  d   OrderedDict  i i for i in range size      i   randint 0  size-1   next itertools islice d itervalues    i  i 1    100 loops  best of 3  10 9 msec per loop    python2 -m timeit -s  from indexed import IndexedOrderedDict  from random import randint  size   1000    d   IndexedOrderedDict  i i for i in range size      i   randint 0  size-1   d values   i   100000 loops  best of 3  2 19 usec per loop   python2 -m timeit -s  from indexed import IndexedOrderedDict  from random import randint  size   10000   d   IndexedOrderedDict  i i for i in range size      i   randint 0  size-1   d values   i   100000 loops  best of 3  2 24 usec per loop   python2 -m timeit -s  from indexed import IndexedOrderedDict  from random import randint  size   100000  d   IndexedOrderedDict  i i for i in range size      i   randint 0  size-1   d values   i   100000 loops  best of 3  2 61 usec per loop   -------- ----------- ---------------- ---------     size    list  ms    generator  ms    indexed    -------- ----------- ---------------- ---------      1000    259         118              00219       10000   2 3         1 26              00224      100000   24 5        10 9              00261     -------- ----------- ---------------- ---------    Python 3 6  Python 3 has the same two basic options  list vs generator   but the dict methods return generators by default   List method   list d values    0      python  list d values    1      spam    Generator method   import itertools next itertools islice d values    0  1       python  next itertools islice d values    1  2       spam    Python 3 dictionaries are an order of magnitude faster than python 2 and have similar speedups for using generators    -------- ----------- ---------------- ---------     size    list  ms    generator  ms    indexed    -------- ----------- ---------------- ---------      1000    0316        0165             00262       10000    288         166              00294      100000   3 53        1 48              00332     -------- ----------- ---------------- ---------

User · Answer

If you have pandas installed  you can convert the ordered dict to a pandas Series  This will allow random access to the dictionary elements   gt  gt  gt  import collections  gt  gt  gt  import pandas as pd  gt  gt  gt  d   collections OrderedDict    gt  gt  gt  d  foo      python   gt  gt  gt  d  bar      spam    gt  gt  gt  s   pd Series d    gt  gt  gt  s  bar   spam  gt  gt  gt  s iloc 1  spam  gt  gt  gt  s index 1  bar

User · Answer

Do you have to use an OrderedDict or do you specifically want a map-like type that s ordered in some way with fast positional indexing  If the latter  then consider one of Python s many sorted dict types  which orders key-value pairs based on key sort order   Some implementations also support fast indexing  For example  the sortedcontainers project has a SortedDict type for just this purpose    gt  gt  gt  from sortedcontainers import SortedDict  gt  gt  gt  sd   SortedDict    gt  gt  gt  sd  foo      python   gt  gt  gt  sd  bar      spam   gt  gt  gt  print sd iloc 0    Note that  bar  comes before  foo  in sort order   bar   gt  gt  gt    If you want the value  then simple do a key lookup   gt  gt  gt  print sd sd iloc 1    python

User · Answer

It is dramatically more efficient to use IndexedOrderedDict from the indexed package   Following Niklas s comment  I have done a benchmark on OrderedDict and IndexedOrderedDict with 1000 entries   In  1   from numpy import   In  2   from indexed import IndexedOrderedDict In  3   id IndexedOrderedDict zip arange 1000  random random 1000    In  4   timeit id keys   56  1000000 loops  best of 3  969 ns per loop  In  8   from collections import OrderedDict In  9   od OrderedDict zip arange 1000  random random 1000    In  10   timeit od keys   56  10000 loops  best of 3  104   s per loop   IndexedOrderedDict is  100 times faster in indexing elements at specific position in this specific case

[python] Accessing items in an collections.OrderedDict by index

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