Corpus objects are validated in the database when they are saved. However, not every requirement for a working corpus can be mandated when it is intially created.
A corpus has two additional checks for different stages of its creation: ready to index and ready to publish. More details on each of these below.
A corpus that does not meet this check cannot be indexed in Elasticsearch. This can mean that it's missing essential fields, has no source data directory configured, etc.
A corpus must pass this check when you use the index command.
A corpus that does not meet this check cannot be searched in the frontend. This usually means the interface configuration is incomplete or invalid.
A corpus must pass this check to be set to active - which enables the corpus in the search interface.
The ready_to_publish validation is not executed when handling views, because it can include some non-trivial checks. Instead, we check whether active is True, which implies that the corpus passed this validation.
For Python corpora, active is automatically set by running ready_to_publish() after importing the corpus definition. Database-only corpora are inactive by default, and have to be activated manually, which will trigger the validation.
These checks are available as methods on a Corpus object. The corpus has two methods for this: corpus.validate_ready_to_index() and corpus.validate_ready_to_publish(). These methods return no value but raise errors if they run into problems.
In addition, the following methods wrap these validation functions in a try/except block and return a boolean value: corpus.ready_to_index() and corpus.ready_to_publish().
The first two methods are useful if you want feedback, the latter two methods are useful if you just need a binary state.