Skip to main content

type of zope vocabularies that dont "forget", like elephants

Project description

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, [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

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_vocab2 = wrap_vocabulary('example-vocab', [2, 3])(context)
>>> [i.value for i in wrapped_vocab2]
[1, 4]

hidden_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_vocab3 = wrap_vocabulary(example_vocab, hidden_terms)(context)
>>> [i.value for i in wrapped_vocab3]
[2, 3]

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

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

>>> example_vocab.hidden_terms = [1, 2]
>>> wrapped_vocab4 = wrap_vocabulary(example_vocab)(context)
>>> [i.value for i in wrapped_vocab4]
[3, 4]

Credits

Generously sponsored by 4teamwork.

Todo

  • provide list of enabled valued (other way around then hidden_terms is working)

  • provide test for custom wrapper class

History

0.1.1 (2010-10-08)

  • add dependencies from where we import (using mr.igor) [garbas]

  • add link to zope.schema which was breaking formating for rst formatting [garbas]

  • initial release was broken (missing README.rst) [garbas]

0.1 (2010-10-08)

  • initial release [garbas]

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

collective.elephantvocabulary-0.1.1.tar.gz (11.1 kB view details)

Uploaded Source

File details

Details for the file collective.elephantvocabulary-0.1.1.tar.gz.

File metadata

File hashes

Hashes for collective.elephantvocabulary-0.1.1.tar.gz
Algorithm Hash digest
SHA256 046217d9d129740c74c2e43f668dfe581ccceae2937f71741492e19d8402586e
MD5 d8cec0ee1bb093ed55332159b8274aa7
BLAKE2b-256 e5c09c8f371ed1f56f4e11936fadb17ecbe4d8efe7f05435ccbe8f4e2ec1bfe6

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page