def SF()

in opensearch_dsl/function.py [0:0]

• 26 lines of code
• 11 McCabe index (conditional complexity)

def SF(name_or_sf, **params):
    # {"script_score": {"script": "_score"}, "filter": {}}
    if isinstance(name_or_sf, collections_abc.Mapping):
        if params:
            raise ValueError("SF() cannot accept parameters when passing in a dict.")
        kwargs = {}
        sf = name_or_sf.copy()
        for k in ScoreFunction._param_defs:
            if k in name_or_sf:
                kwargs[k] = sf.pop(k)

        # not sf, so just filter+weight, which used to be boost factor
        if not sf:
            name = "boost_factor"
        # {'FUNCTION': {...}}
        elif len(sf) == 1:
            name, params = sf.popitem()
        else:
            raise ValueError("SF() got an unexpected fields in the dictionary: %r" % sf)

        # boost factor special case, see https://github.com/elastic/elasticsearch/issues/6343
        if not isinstance(params, collections_abc.Mapping):
            params = {"value": params}

        # mix known params (from _param_defs) and from inside the function
        kwargs.update(params)
        return ScoreFunction.get_dsl_class(name)(**kwargs)

    # ScriptScore(script="_score", filter=Q())
    if isinstance(name_or_sf, ScoreFunction):
        if params:
            raise ValueError(
                "SF() cannot accept parameters when passing in a ScoreFunction object."
            )
        return name_or_sf

    # "script_score", script="_score", filter=Q()
    return ScoreFunction.get_dsl_class(name_or_sf)(**params)