On 01/20/2014 08:14 PM, Dan Stromberg wrote:
On Mon, Jan 20, 2014 at 12:09 PM, Charles Hixson
<charleshi...@earthlink.net> wrote:
class RODict:
#Instance Variable Doc
## @var _ddict
# This variable holds the reference to the dict.
## Class initializer.
# @param ddict The data dictionary to which this is a read only
# access.
# @throws TypeError if ddict is not a dict.
def __init__ (self, ddict = {}):
if not isinstance(ddict, dict):
raise TypeError("ddict must be a dict. It is " +
repr(ddict))
self._ddict = ddict
When I see this isinstance, I think "Gee, that means none of the
dict-like-objects I recently compared would work with this class."
The comparison is at the URL below; all the things compared are trees
that provide a dictionary-like interface, but also find_min, find_max
and can iterate in key order. I don't think any of them inherit from
dict, but they are all dict-like in a duck-typed sense:
http://stromberg.dnsalias.org/~strombrg/python-tree-and-heap-comparison/2014-01/
HTH
Well, it would mean you couldn't create instances of this class from
them. I haven't yet specified the eq and ne methods, but they'd
probably be something like:
def ne(self, key):
return self._ddict.ne(key)
(I'd need to look up the precise names of the comparison routines.
Perhaps it would be "__ne__" rather than "ne".)
So if they'd work with a normal dict, they should work with this, for
comparison.
Note that this is a dict-alike, and therefore not in a predictable
order. If the items were to be ordered, however, they would be in order
by the value rather than by the key, as my use-case is most likely to
want to access the items with the highest value most often. I may even
decide to use a list of lists, but a dict yields simpler code, even if I
suspect that lists might be more efficient. But the choice of list would
mean I could use a tuple, which because it is standard would also tend
to make things simpler. (It wouldn't, however, allow background
updating, as dictviews do, and also RODict does, so I'd need to find
some way to manage that...probably meaning that I'd need to regenerate
them more often.)
-- Charles Hixson
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