Update PEP based on latest version of recipe, based on integration testing, and based on newsgroup feedback.
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pep-0372.txt
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pep-0372.txt
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@ -143,22 +143,19 @@ constructor?
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This behavior is consistent with existing implementations in
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Python, the PHP array and the hashmap in Ruby 1.9.
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Why is there no ``odict.insert()``?
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There are few situations where you really want to insert a key at
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a specified index. To avoid API complication, the proposed
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solution for this situation is creating a list of items,
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manipulating that and converting it back into an odict:
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>>> d = odict([('a', 42), ('b', 23), ('c', 19)])
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>>> l = d.items()
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>>> l.insert(1, ('x', 0))
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>>> odict(l)
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collections.odict([('a', 42), ('x', 0), ('b', 23), ('c', 19)])
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Is the ordered dict a dict subclass?
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Is the ordered dict a dict subclass? Why?
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Yes. Like ``defaultdict``, ``odict`` subclasses ``dict``.
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Being a dict subclass confers speed upon methods that aren't overridden
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like ``__getitem__`` and ``__len__``. Also, being a dict gives the
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most utility with tools that were expecting regular dicts (like the
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json module).
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Do any limitations arise from subclassing dict?
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Yes. Since the API for dicts is different in Py2.x and Py3.x, the
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odict API must also be different (i.e. Py2.6 needs to override
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iterkeys, itervalues, and iteritems).
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Does ``odict.popitem()`` return a particular key/value pair?
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@ -166,8 +163,8 @@ Does ``odict.popitem()`` return a particular key/value pair?
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corresponding value. This corresponds to the usual LIFO behavior
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exhibited by traditional push/pop pairs. It is semantically
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equivalent to ``k=list(od)[-1]; v=od[k]; del od[k]; return (k,v)``.
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The actual implementation is more efficient. It is O(n log n)
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on the first call, any successive calls are O(1).
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The actual implementation is more efficient and pops directly
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off of a sorted list of keys.
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Does odict support indexing, slicing, and whatnot?
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@ -184,6 +181,50 @@ Does odict support alternate sort orders such as alphabetical?
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dbm) is likely a better fit. It would be a mistake to try to be all
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things to all users.
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How well does odict work with the json module and PyYAML?
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For json, the good news is that json's encoder respects odict's iteration order:
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>>> items = [('one', 1), ('two', 2), ('three',3), ('four',4), ('five',5)]
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>>> json.dumps(OrderedDict(items))
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'{"one": 1, "two": 2, "three": 3, "four": 4, "five": 5}'
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The bad news is that the object_hook for json decoders will pass in an
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already built dictionary so that the order is lost before the object
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hook sees it:
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>>> jtext = '{"one": 1, "two": 2, "three": 3, "four": 4, "five": 5}'
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>>> json.loads(jtext, object_hook=OrderedDict)
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OrderedDict({u'four': 4, u'three': 3, u'five': 5, u'two': 2, u'one': 1})
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For PyYAML, a full round-trip is problem free:
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>>> ytext = yaml.dump(OrderedDict(items))
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>>> print ytext
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!!python/object/apply:collections.OrderedDict
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- - [one, 1]
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- [two, 2]
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- [three, 3]
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- [four, 4]
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- [five, 5]
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>>> yaml.load(ytext)
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OrderedDict({'one': 1, 'two': 2, 'three': 3, 'four': 4, 'five': 5})
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How does odict handle equality testing?
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Being a dict, one might expect equality tests to not care about order. For
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an odict to dict comparison, this would be a necessity and it's probably
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not wise to silently switch comparison modes based on the input types.
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Also, some third-party tools that expect dict inputs may also expect the
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comparison to not care about order. Accordingly, we decided to punt and
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let the usual dict equality testing run without reference to internal
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ordering. This should be documented clearly since different people will
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have different expectations. If a use case does arise, it's not hard to
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explicitly craft an order based comparison:
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``list(od1.items())==list(od2.items())``.
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Reference Implementation
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========================
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