pandagg.tree.query module

class pandagg.tree.query.Query(q: Union[str, Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause, Query, None] = None, mappings: Union[pandagg.types.MappingsDict, pandagg.tree.mappings.Mappings, None] = None, nested_autocorrect: bool = False)

Bases: lighttree.tree.Tree

applied_nested_path_at_node(nid: str) → Optional[str]

Return nested path applied at a clause.

Parameters:nid – clause identifier Returns:None if no nested is applied, else applied path (str)

bool(must: Union[Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause, List[Union[Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause]], None] = None, should: Union[Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause, List[Union[Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause]], None] = None, must_not: Union[Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause, List[Union[Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause]], None] = None, filter: Union[Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause, List[Union[Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause]], None] = None, insert_below: Optional[str] = None, on: Optional[str] = None, mode: typing_extensions.Literal['add', 'replace', 'replace_all'][add, replace, replace_all] = 'add', **body) → pandagg.tree.query.Query

>>> Query().bool(must={"term": {"some_field": "yolo"}})

boosting(positive: Union[Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause, None] = None, negative: Union[Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause, None] = None, insert_below: Optional[str] = None, on: Optional[str] = None, mode: typing_extensions.Literal['add', 'replace', 'replace_all'][add, replace, replace_all] = 'add', **body) → pandagg.tree.query.Query

constant_score(filter: Union[Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause, None] = None, boost: Optional[float] = None, insert_below: Optional[str] = None, on: Optional[str] = None, mode: typing_extensions.Literal['add', 'replace', 'replace_all'][add, replace, replace_all] = 'add', **body) → pandagg.tree.query.Query

dis_max(queries: List[Union[Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause]], insert_below: Optional[str] = None, on: Optional[str] = None, mode: typing_extensions.Literal['add', 'replace', 'replace_all'][add, replace, replace_all] = 'add', **body) → pandagg.tree.query.Query

filter(type_or_query: Union[str, Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause, Query], insert_below: Optional[str] = None, on: Optional[str] = None, mode: typing_extensions.Literal['add', 'replace', 'replace_all'][add, replace, replace_all] = 'add', bool_body: Dict[str, Any] = None, **body) → pandagg.tree.query.Query

function_score(query: Union[Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause, None], insert_below: Optional[str] = None, on: Optional[str] = None, mode: typing_extensions.Literal['add', 'replace', 'replace_all'][add, replace, replace_all] = 'add', **body) → pandagg.tree.query.Query

has_child(query: Union[Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause, None], insert_below: Optional[str] = None, on: Optional[str] = None, mode: typing_extensions.Literal['add', 'replace', 'replace_all'][add, replace, replace_all] = 'add', **body) → pandagg.tree.query.Query

has_parent(query: Union[Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause, None], insert_below: Optional[str] = None, on: Optional[str] = None, mode: typing_extensions.Literal['add', 'replace', 'replace_all'][add, replace, replace_all] = 'add', **body) → pandagg.tree.query.Query

must(type_or_query: Union[str, Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause, Query], insert_below: Optional[str] = None, on: Optional[str] = None, mode: typing_extensions.Literal['add', 'replace', 'replace_all'][add, replace, replace_all] = 'add', bool_body: Optional[Dict[str, Any]] = None, **body) → pandagg.tree.query.Query

Create copy of initial Query and insert provided clause under “bool” query “must”.

>>> Query().must('term', some_field=1)
>>> Query().must({'term': {'some_field': 1}})
>>> from pandagg.query import Term
>>> Query().must(Term(some_field=1))

Keyword Arguments:  

• insert_below (str) – named query clause under which the inserted clauses should be placed.
• compound_param (str) – param under which inserted clause will be placed in compound query
• on (str) – named compound query clause on which the inserted compound clause should be merged.
• mode (str one of ‘add’, ‘replace’, ‘replace_all’) – merging strategy when inserting clauses on a existing compound clause.
  • ‘add’ (default) : adds new clauses keeping initial ones
  • ‘replace’ : for each parameter (for instance in ‘bool’ case : ‘filter’, ‘must’, ‘must_not’, ‘should’), replace existing clauses under this parameter, by new ones only if declared in inserted compound query
  • ‘replace_all’ : existing compound clause is completely replaced by the new one

must_not(type_or_query: Union[str, Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause, Query], insert_below: Optional[str] = None, on: Optional[str] = None, mode: typing_extensions.Literal['add', 'replace', 'replace_all'][add, replace, replace_all] = 'add', bool_body: Dict[str, Any] = None, **body) → pandagg.tree.query.Query

nested(path: str, query: Union[Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause, None] = None, insert_below: Optional[str] = None, on: Optional[str] = None, mode: typing_extensions.Literal['add', 'replace', 'replace_all'][add, replace, replace_all] = 'add', **body) → pandagg.tree.query.Query

pinned_query(organic: Union[Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause, None], insert_below: Optional[str] = None, on: Optional[str] = None, mode: typing_extensions.Literal['add', 'replace', 'replace_all'][add, replace, replace_all] = 'add', **body) → pandagg.tree.query.Query

query(type_or_query: Union[str, Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause, Query], insert_below: Optional[str] = None, on: Optional[str] = None, mode: typing_extensions.Literal['add', 'replace', 'replace_all'][add, replace, replace_all] = 'add', compound_param: str = None, **body) → pandagg.tree.query.Query

Insert provided clause in copy of initial Query.

>>> from pandagg.query import Query
>>> Query().query('term', some_field=23)
{'term': {'some_field': 23}}

>>> from pandagg.query import Term
>>> Query()\
>>> .query({'term': {'some_field': 23})\
>>> .query(Term(other_field=24))\
{'bool': {'must': [{'term': {'some_field': 23}}, {'term': {'other_field': 24}}]}}

Keyword Arguments:  

• insert_below (str) – named query clause under which the inserted clauses should be placed.
• compound_param (str) – param under which inserted clause will be placed in compound query
• on (str) – named compound query clause on which the inserted compound clause should be merged.
• mode (str one of ‘add’, ‘replace’, ‘replace_all’) – merging strategy when inserting clauses on a existing compound clause.
  • ‘add’ (default) : adds new clauses keeping initial ones
  • ‘replace’ : for each parameter (for instance in ‘bool’ case : ‘filter’, ‘must’, ‘must_not’, ‘should’), replace existing clauses under this parameter, by new ones only if declared in inserted compound query
  • ‘replace_all’ : existing compound clause is completely replaced by the new one

script_score(query: Union[Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause, None], insert_below: Optional[str] = None, on: Optional[str] = None, mode: typing_extensions.Literal['add', 'replace', 'replace_all'][add, replace, replace_all] = 'add', **body) → pandagg.tree.query.Query

should(type_or_query: Union[str, Dict[str, Dict[str, Any]], pandagg.node.query.abstract.QueryClause, Query], insert_below: Optional[str] = None, on: Optional[str] = None, mode: typing_extensions.Literal['add', 'replace', 'replace_all'][add, replace, replace_all] = 'add', bool_body: Optional[Dict[str, Any]] = None, **body) → pandagg.tree.query.Query

show(*args, line_max_length: int = 80, **kwargs) → str

Return compact representation of Query.

>>> Query()        >>> .must({"exists": {"field": "some_field"}})        >>> .must({"term": {"other_field": {"value": 5}}})        >>> .show()
<Query>
bool
└── must
    ├── exists                                                  field=some_field
    └── term                                          field=other_field, value=5

All *args and **kwargs are propagated to lighttree.Tree.show method.

to_dict(from_: Optional[str] = None) → Optional[Dict[str, Dict[str, Any]]]