BForest Doc Tests

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bforests are dictionary-like objects that use multiple BTrees for a backend and
support rotation of the composite trees.  This supports various implementations 
of timed member expirations, enabling caches and semi-persistent storage.  A
useful and simple subclass would be to promote a key-value pair to the
first (newest) bucket whenever the key is accessed, for instance.

Like btrees, bforests come in four flavors: Integer-Integer (IIBForest), 
Integer-Object (IOBForest), Object-Integer (OIBForest), and Object-Object
(OOBForest).  The examples here will deal with them in the abstract: we will
create classes from the imaginary and representative BForest class, and
generate keys from KeyGenerator and values from ValueGenerator.  From the 
examples you should be able to extrapolate usage of all four types.

First let's instantiate a bforest and look at an empty example.  By default,
a new bforest creates two composite btree buckets.

>>> d = BForest()
>>> list(d.keys())
[]
>>> list(d.values())
[]
>>> len(d.buckets)
2
>>> dummy_key = KeyGenerator()
>>> d.get(dummy_key)
>>> d.get(dummy_key, 42)
42

Now we'll populate it.  We'll first create a dictionary we'll use to compare.

>>> original = {}
>>> for i in range(10):
...     original[KeyGenerator()] = ValueGenerator()
... 
>>> d.update(original)
>>> d == original
True
>>> d_keys = list(d.keys())
>>> d_keys.sort()
>>> o_keys = original.keys()
>>> o_keys.sort()
>>> d_keys == o_keys
True
>>> d_values = list(d.values())
>>> d_values.sort()
>>> o_values = original.values()
>>> o_values.sort()
>>> o_values == d_values
True
>>> d_items = list(d.items())
>>> d_items.sort()
>>> o_items = original.items()
>>> o_items.sort()
>>> o_items == d_items
True
>>> key, value = d.popitem()
>>> value == original.pop(key)
True
>>> key, value = original.popitem()
>>> value == d.pop(key)
True
>>> len(d) == len(original)
True

Now let's rotate the buckets.

>>> d.rotateBucket()

...and we'll do the exact same test as above, first.

>>> d == original
True
>>> d_keys = list(d.keys())
>>> d_keys.sort()
>>> o_keys = original.keys()
>>> o_keys.sort()
>>> d_keys == o_keys
True
>>> d_values = list(d.values())
>>> d_values.sort()
>>> o_values = original.values()
>>> o_values.sort()
>>> o_values == d_values
True
>>> d_items = list(d.items())
>>> d_items.sort()
>>> o_items = original.items()
>>> o_items.sort()
>>> o_items == d_items
True
>>> key, value = d.popitem()
>>> value == original.pop(key)
True
>>> key, value = original.popitem()
>>> value == d.pop(key)
True
>>> len(d) == len(original)
True

Now we'll make a new dictionary to represent changes made after the bucket
rotation.

>>> second = {}
>>> for i in range(10):
...     key = KeyGenerator()
...     value = ValueGenerator()
...     second[key] = value
...     d[key] = value
... 
>>> original.update(second)

...and we'll do almost the exact same test as above, first.

>>> d == original
True
>>> d_keys = list(d.keys())
>>> d_keys.sort()
>>> o_keys = original.keys()
>>> o_keys.sort()
>>> d_keys == o_keys
True
>>> d_values = list(d.values())
>>> d_values.sort()
>>> o_values = original.values()
>>> o_values.sort()
>>> o_values == d_values
True
>>> d_items = list(d.items())
>>> d_items.sort()
>>> o_items = original.items()
>>> o_items.sort()
>>> o_items == d_items
True
>>> key, value = d.popitem()
>>> ignore = second.pop(key, None) # keep second up-to-date
>>> value == original.pop(key)
True
>>> key, value = original.popitem()
>>> ignore = second.pop(key, None) # keep second up-to-date
>>> value == d.pop(key)
True
>>> len(d) == len(original)
True

Now if we rotate the buckets, the first set of items will be gone, but the 
second will remain.

>>> d.rotateBucket()
>>> d == original
False
>>> d == second
True

Let's set a value, check the copy behavior,  and then rotate it one more time.

>>> third = {KeyGenerator(): ValueGenerator()}
>>> d.update(third)
>>> copy = d.copy()
>>> copy == d
True
>>> copy != second # because second doesn't have the values of third
True
>>> list(copy.buckets[0].items()) == list(d.buckets[0].items())
True
>>> list(copy.buckets[1].items()) == list(d.buckets[1].items())
True
>>> copy[KeyGenerator()] = ValueGenerator()
>>> copy == d
False
>>> d.rotateBucket()
>>> d == third
True
>>> d.clear()
>>> d == BForest() == {}
True

>>> d.update(second)

We'll make a value in one bucket that we'll override in another.

>>> d[third.keys()[0]] = ValueGenerator()
>>> d.rotateBucket()
>>> d.update(third)
>>> second.update(third)
>>> d == second
True

Notice this unpleasant bit: a bforest and dict with the same contents will 
return True if the comparison is bforest == dict (above) but false if the
comparison is dict == bforest.  This might be fixable if we could use rich
comparisons, but we can't do that with the old-style ExtensionClass used in 
pre-Zope 2.8.

>>> second == d
False

The tree method converts the bforest to a btree as efficiently as I know how
for a common case of more items in buckets than buckets.

>>> tree = d.tree()
>>> d_items = list(d.items())
>>> d_items.sort()
>>> t_items = list(tree.items())
>>> t_items.sort()
>>> t_items == d_items
True