collective.elephantvocabulary 0.2

Introduction

Like elephants don’t forget anything, so does’t collective.elephantvocabulary. It provides a wrapper around for existing zope.schema vocabularies and make them not forget anything.

Example usecase would be a vocabulary (source) of users which from certain point in time wants to hide / deactivate some users for form or listing. But at the same time you want keep old references to user term working. This is when collective.elephantvocabulary comes into the picture. With it you wrap existing vocabulary of users and provide set of hidden list of users (term values).

Usage

Some example content and vocabularies

>>> context = layer.context
>>> example_vocab = layer.example_vocab
>>> example_source = layer.example_source

>>> [i.value for i in example_vocab]
[1, 2, 3, 4]

Bellow is out wraper method we use to make our existing vocab more elephant-like.

>>> from collective.elephantvocabulary import wrap_vocabulary

In first exampe we pass to our wrap_vocabulary a vocabulary of [1, 2, 3, 4] and we set terms 2 and 3 to hidden. wrap_vocabulary returns VocabularyFactory which needs to be called with context (you could also register it with as utility).

>>> wrapped_vocab_factory = wrap_vocabulary(example_vocab, hidden_terms=[2, 3])
>>> print wrapped_vocab_factory
<collective.elephantvocabulary.vocabulary.VocabularyFactory object at ...>

>>> wrapped_vocab = wrapped_vocab_factory(context)
>>> [i.value for i in wrapped_vocab]
[1, 4]

>>> len(wrapped_vocab) == len(example_vocab)
True

>>> 2 in wrapped_vocab
True

>>> 5 in wrapped_vocab
False

>>> wrapped_vocab.getTerm(3).value
3

Similar we can to to limit items shown only to the set we want (via visible_terms)

>>> wrapped_vocab = wrap_vocabulary(example_vocab,
...                                 visible_terms=[2, 3])(context)
>>> [i.value for i in wrapped_vocab]
[2, 3]

>>> len(wrapped_vocab) == len(example_vocab)
True

>>> 2 in wrapped_vocab
True

>>> 5 in wrapped_vocab
False

>>> wrapped_vocab.getTerm(1).value
1

Above we see what collective.elephantvocabulary is all about. When listing vocabulary hidden terms are not listed. But when item is requested with its term value then term is also returned. Also length of vocabulary is unchanged. It still shows original lenght of vocabulary.

We can also call vocabulary by name it was register with ZCA machinery..

>>> wrapped_vocab = wrap_vocabulary('example-vocab',
...                                  hidden_terms=[2, 3])(context)
>>> [i.value for i in wrapped_vocab]
[1, 4]

hidden_terms or visible_terms parameter (second argument we pass to wrap_vocabulary) can also be callable which expects 2 parameters, context and original vocabulary.

>>> def hidden_terms(context, vocab):
...     return [1, 4]

>>> wrapped_vocab = wrap_vocabulary(example_vocab,
...                                 hidden_terms=hidden_terms)(context)
>>> [i.value for i in wrapped_vocab]
[2, 3]

>>> def visible_terms(context, vocab):
...     return [1, 4]

>>> wrapped_vocab = wrap_vocabulary(example_vocab,
...                                 visible_terms=hidden_terms)(context)
>>> [i.value for i in wrapped_vocab]
[1, 4]

collective.elephantvocabulary also works with sources.

>>> [i.value for i in example_source]
[1, 2, 3, 4]

>>> [i.value for i in example_source.search()]
[1, 2]

>>> wrapped_source = wrap_vocabulary(example_source, hidden_terms=[1, 4])(context)
>>> [i.value for i in wrapped_source.search()]
[2]

>>> wrapped_source = wrap_vocabulary(example_source, visible_terms=[1, 4])(context)
>>> [i.value for i in wrapped_source.search()]
[1]

If vocabulary already provides set of hidden terms they are passed to wrapped vocabulary.

>>> example_vocab.hidden_terms = [1, 2]
>>> wrapped_vocab = wrap_vocabulary(example_vocab)(context)
>>> [i.value for i in wrapped_vocab]
[3, 4]

>>> del example_vocab.hidden_terms

>>> example_vocab.visible_terms= [1, 2]
>>> wrapped_vocab = wrap_vocabulary(example_vocab)(context)
>>> [i.value for i in wrapped_vocab]
[1, 2]

>>> del example_vocab.visible_terms

Vocabulary will ass to the list of passed visible_terms or hidden_terms.

>>> example_vocab.hidden_terms = [1, 2]
>>> wrapped_vocab = wrap_vocabulary(example_vocab,
...                                 hidden_terms=[2, 3])(context)
>>> [i.value for i in wrapped_vocab]
[4]

>>> del example_vocab.hidden_terms

>>> example_vocab.visible_terms= [1]
>>> wrapped_vocab = wrap_vocabulary(example_vocab,
...                                 visible_terms=[1, 2, 3])(context)
>>> [i.value for i in wrapped_vocab]
[1, 2, 3]

>>> del example_vocab.visible_terms

hidden_terms and visible_terms can also work together.

>>> wrapped_vocab = wrap_vocabulary(example_vocab,
...                                 visible_terms=[1, 2, 3],
...                                 hidden_terms=[2])(context)
>>> [i.value for i in wrapped_vocab]
[1, 3]

And if we don’t pass anything to wrap_vocabulary then it should ack as normal vocabulary.

>>> wrapped_vocab5 = wrap_vocabulary(example_vocab)(context)
>>> [i.value for i in wrapped_vocab5]
[1, 2, 3, 4]

Credits

Generously sponsored by 4teamwork.

• Rok Garbas, author

Todo

• provide test / documentation for custom wrapper class

• coverage should show 100%, but its failing on method and import lines, weird.

History