Summary
-------
This cube implements facets using postgresql text search vectors.
What does this cube offer ?
---------------------------
This cube defines a new CubicWeb AppObject registry: `tsfacets`.
The base class is `cubicweb_tsfacets.views.TSFacets`; it provides
three methods allowing to recover information to use facets in
a CubicWeb application:
* `get_facets_values_with_count`, which recovers all available facets
with how many target entities it filters for each value;
* `get_target_entities_count`, which counts target entities taking into
account the selected facets and possibly a RQL request to restrict
results;
* `get_target_entities_rset`, which builds a CubicWeb ResultSet taking
into account the selected facets and possibly a RQL request to restrict
results.
How to use it ?
---------------
For each group of facets, you have to define a child class of
`cubicweb_tsfacets.views.TSFacets`. Then, you have to complete
the following attributes:
* `key_names_to_rql_definition`: a dictionary linking each facet key
with a RQLRequestFacetDef object. A facet key must only contain
characters, no space, no ".", no "_", etc.
This object represents a RQL request with the information of if we
need a mapping table for the value or not. We need a mapping if we
want to index string with space or other characters like "'";
* `text_search_indexation`: a RQL request returning a list of tuples:
(target entity eid, text to index for full text search). This
attribute is optional, and is only used if you want to add
text search to your result list. Note: this feature will be added in
an upcoming version;
* `target_etypes`: which entity types are targeted by your facet search;
* `table_name`: the name of the specific postgresql table.
Example of implementation:
--------------------------
In this example, we want to add facets to `Performance` entities.
These facets will be the city, country and theater of the representation,
the date of the representation and the director.
```python
from cubicweb_tsfacets.views import TSFacets, RQLRequestFacetDef
class PerformanceTSFacets(TSFacets):
__regid__ = "performance_tsfacets"
table_name = "performance_tsfacets"
key_names_to_rql_definition = {
"city": RQLRequestFacetDef("Any X, R Where X representation_city R", True),
"country": RQLRequestFacetDef("Any X, R Where X representation_country R", True),
"theater": RQLRequestFacetDef("Any X, R Where X representation_theater R", True),
"date": RQLRequestFacetDef("Any X, D Where X formatted_start_date D", False),
"director": RQLRequestFacetDef(
"Any X, D Where X is Performance, C manifestation X, "
"C contributor D, C role R, R code 500",
False
),
}
target_etypes = {"Performance"}
```
Thus, `CubicWeb-TSFacets` will provide the methods we will need to
build our interface.
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"description": "Summary\n-------\nThis cube implements facets using postgresql text search vectors.\n\nWhat does this cube offer ?\n---------------------------\n\nThis cube defines a new CubicWeb AppObject registry: `tsfacets`.\nThe base class is `cubicweb_tsfacets.views.TSFacets`; it provides\nthree methods allowing to recover information to use facets in\na CubicWeb application:\n\n* `get_facets_values_with_count`, which recovers all available facets\n with how many target entities it filters for each value;\n* `get_target_entities_count`, which counts target entities taking into\n account the selected facets and possibly a RQL request to restrict\n results;\n* `get_target_entities_rset`, which builds a CubicWeb ResultSet taking\n into account the selected facets and possibly a RQL request to restrict\n results.\n\nHow to use it ?\n---------------\n\nFor each group of facets, you have to define a child class of\n`cubicweb_tsfacets.views.TSFacets`. Then, you have to complete\nthe following attributes:\n\n* `key_names_to_rql_definition`: a dictionary linking each facet key \n with a RQLRequestFacetDef object. A facet key must only contain\n characters, no space, no \".\", no \"_\", etc.\n This object represents a RQL request with the information of if we\n need a mapping table for the value or not. We need a mapping if we\n want to index string with space or other characters like \"'\";\n* `text_search_indexation`: a RQL request returning a list of tuples:\n (target entity eid, text to index for full text search). This\n attribute is optional, and is only used if you want to add\n text search to your result list. Note: this feature will be added in\n an upcoming version;\n* `target_etypes`: which entity types are targeted by your facet search;\n* `table_name`: the name of the specific postgresql table.\n\nExample of implementation:\n--------------------------\n\nIn this example, we want to add facets to `Performance` entities.\nThese facets will be the city, country and theater of the representation,\nthe date of the representation and the director.\n\n```python\nfrom cubicweb_tsfacets.views import TSFacets, RQLRequestFacetDef\n\n\nclass PerformanceTSFacets(TSFacets):\n __regid__ = \"performance_tsfacets\"\n table_name = \"performance_tsfacets\"\n\n key_names_to_rql_definition = {\n \"city\": RQLRequestFacetDef(\"Any X, R Where X representation_city R\", True),\n \"country\": RQLRequestFacetDef(\"Any X, R Where X representation_country R\", True),\n \"theater\": RQLRequestFacetDef(\"Any X, R Where X representation_theater R\", True),\n \"date\": RQLRequestFacetDef(\"Any X, D Where X formatted_start_date D\", False),\n \"director\": RQLRequestFacetDef(\n \"Any X, D Where X is Performance, C manifestation X, \"\n \"C contributor D, C role R, R code 500\",\n False\n ),\n }\n\n target_etypes = {\"Performance\"}\n```\n\nThus, `CubicWeb-TSFacets` will provide the methods we will need to\nbuild our interface.\n",
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