How to use the omegaml.store.query.Filter function in omegaml

def __and__(self, other):
        return Filter(self.coll, self.q & other.q)

def _get_filter_criteria(self, *args, **kwargs):
        """ 
        return mongo query from filter specs

        this uses a Filter to produce the query from the kwargs.

        :param args: a Q object or logical combination of Q objects
           (optional)
        :param kwargs: all AND filter criteria 
        """
        if len(args) > 0:
            q = args[0]
            if isinstance(q, MongoQ):
                filter_criteria = Filter(self.collection, q).query
            elif isinstance(q, Filter):
                filter_criteria = Filter(self.collection, q.q).query
        else:
            filter_criteria = Filter(self.collection, **kwargs).query
        return filter_criteria

return mongo query from filter specs

        this uses a Filter to produce the query from the kwargs.

        :param args: a Q object or logical combination of Q objects
           (optional)
        :param kwargs: all AND filter criteria 
        """
        if len(args) > 0:
            q = args[0]
            if isinstance(q, MongoQ):
                filter_criteria = Filter(self.collection, q).query
            elif isinstance(q, Filter):
                filter_criteria = Filter(self.collection, q.q).query
        else:
            filter_criteria = Filter(self.collection, **kwargs).query
        return filter_criteria

"""
        collection = self.collection(name)
        if lazy:
            from ..mdataframe import MDataFrame
            filter = filter or kwargs
            df = MDataFrame(collection, columns=columns).query(**filter)
            if is_series:
                df = df[0]
        else:
            # TODO ensure the same processing is applied in MDataFrame
            # TODO this method should always use a MDataFrame disregarding lazy
            filter = filter or kwargs
            if filter:
                from .query import Filter
                query = Filter(collection, **filter).query
                cursor = collection.find(filter=query, projection=columns)
            else:
                cursor = collection.find(projection=columns)
            # restore dataframe
            df = cursor_to_dataframe(cursor)
            if '_id' in df.columns:
                del df['_id']
            meta = self.metadata(name)
            if hasattr(meta, 'kind_meta'):
                df = convert_dtypes(df, meta.kind_meta.get('dtypes', {}))
            # -- restore columns
            meta_columns = dict(meta.kind_meta.get('columns'))
            if meta_columns:
                # apply projection, if any
                if columns:
                    # get only projected columns

def __iter__(self):
        """ for each group returns the key and a Filter object"""
        groups = self._count()
        for group in groups:
            keys = group.get('_id')
            data = Filter(self.collection, **keys)
            yield keys, data

def _get_filter_criteria(self, *args, **kwargs):
        """ 
        return mongo query from filter specs

        this uses a Filter to produce the query from the kwargs.

        :param args: a Q object or logical combination of Q objects
           (optional)
        :param kwargs: all AND filter criteria 
        """
        if len(args) > 0:
            q = args[0]
            if isinstance(q, MongoQ):
                filter_criteria = Filter(self.collection, q).query
            elif isinstance(q, Filter):
                filter_criteria = Filter(self.collection, q.q).query
        else:
            filter_criteria = Filter(self.collection, **kwargs).query
        return filter_criteria