<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def map_concepts_to_indicators( self, n: int = 1, min_temporal_res: Optional[str] = None ):
 """ Map each concept node in the AnalysisGraph instance to one or more tangible quantities, known as 'indicators'. Args: n: Number of matches to keep min_temporal_res: Minimum temporal resolution that the indicators must have data for. """


        for node in self.nodes(data=True):
            query_parts = [
                "select Indicator from concept_to_indicator_mapping",
                f"where `Concept` like '{node[0]}'",
            ]

            # TODO May need to delve into SQL/database stuff a bit more deeply
            # for this. Foreign keys perhaps?

            query = "  ".join(query_parts)
            results = engine.execute(query)

            if min_temporal_res is not None:
                if min_temporal_res not in ["month"]:
                    raise ValueError("min_temporal_res must be 'month'")

                vars_with_required_temporal_resolution = [
                    r[0]
                    for r in engine.execute(
                        "select distinct `Variable` from indicator where "
                        f"`{min_temporal_res.capitalize()}` is not null"
                    )
                ]
                results = [
                    r
                    for r in results
                    if r[0] in vars_with_required_temporal_resolution
                ]

            node[1]["indicators"] = {
                x: Indicator(x, "MITRE12")
                for x in [r[0] for r in take(n, results)]
            }