How to use the pydruid.utils.filters.Dimension function in pydruid

"direction": "descending",
                }],
            }
            client.groupby(**pre_qry)
            query_str += "// Two phase query\n// Phase 1\n"
            query_str += json.dumps(
                client.query_builder.last_query.query_dict, indent=2) + "\n"
            query_str += "//\nPhase 2 (built based on phase one's results)\n"
            df = client.export_pandas()
            if df is not None and not df.empty:
                dims = qry['dimensions']
                filters = []
                for unused, row in df.iterrows():
                    fields = []
                    for dim in dims:
                        f = Dimension(dim) == row[dim]
                        fields.append(f)
                    if len(fields) > 1:
                        filt = Filter(type="and", fields=fields)
                        filters.append(filt)
                    elif fields:
                        filters.append(fields[0])

                if filters:
                    ff = Filter(type="or", fields=filters)
                    if not orig_filters:
                        qry['filter'] = ff
                    else:
                        qry['filter'] = Filter(type="and", fields=[
                            ff,
                            orig_filters])
                qry['limit_spec'] = None

granularity = {"type": "duration", "duration": granularity}

        qry = dict(
            datasource=self.datasource_name,
            dimensions=groupby,
            aggregations=aggregations,
            granularity=granularity,
            intervals=from_dttm.isoformat() + '/' + to_dttm.isoformat(),
        )
        filters = None
        for col, op, eq in filter:
            cond = None
            if op == '==':
                cond = Dimension(col) == eq
            elif op == '!=':
                cond = ~(Dimension(col) == eq)
            elif op in ('in', 'not in'):
                fields = []
                splitted = eq.split(',')
                if len(splitted) > 1:
                    for s in eq.split(','):
                        s = s.strip()
                        fields.append(Filter.build_filter(Dimension(col) == s))
                    cond = Filter(type="or", fields=fields)
                else:
                    cond = Dimension(col) == eq
                if op == 'not in':
                    cond = ~cond
            if filters:
                filters = Filter(type="and", fields=[
                    Filter.build_filter(cond),
                    Filter.build_filter(filters)

if op == '==':
                cond = Dimension(col) == eq
            elif op == '!=':
                cond = ~(Dimension(col) == eq)
            elif op in ('in', 'not in'):
                fields = []
                # Distinguish quoted values with regular value types
                splitted = FillterPattern.split(eq)[1::2]
                values = [types.replace("'", '') for types in splitted]
                if len(values) > 1:
                    for s in values:
                        s = s.strip()
                        fields.append(Dimension(col) == s)
                    cond = Filter(type="or", fields=fields)
                else:
                    cond = Dimension(col) == eq
                if op == 'not in':
                    cond = ~cond
            elif op == 'regex':
                cond = Filter(type="regex", pattern=eq, dimension=col)
            if filters:
                filters = Filter(type="and", fields=[
                    cond,
                    filters
                ])
            else:
                filters = cond
        return filters

if op == '==':
                cond = Dimension(col) == eq
            elif op == '!=':
                cond = ~(Dimension(col) == eq)
            elif op in ('in', 'not in'):
                fields = []
                # Distinguish quoted values with regular value types
                splitted = FillterPattern.split(eq)[1::2]
                values = [types.replace("'", '') for types in splitted]
                if len(values) > 1:
                    for s in values:
                        s = s.strip()
                        fields.append(Dimension(col) == s)
                    cond = Filter(type="or", fields=fields)
                else:
                    cond = Dimension(col) == eq
                if op == 'not in':
                    cond = ~cond
            elif op == 'regex':
                cond = Filter(type="regex", pattern=eq, dimension=col)
            if filters:
                filters = Filter(type="and", fields=[
                    cond,
                    filters
                ])
            else:
                filters = cond
        return filters

def get_filters(raw_filters):
        filters = None
        for col, op, eq in raw_filters:
            cond = None
            if op == '==':
                cond = Dimension(col) == eq
            elif op == '!=':
                cond = ~(Dimension(col) == eq)
            elif op in ('in', 'not in'):
                fields = []
                # Distinguish quoted values with regular value types
                splitted = FillterPattern.split(eq)[1::2]
                values = [types.replace("'", '') for types in splitted]
                if len(values) > 1:
                    for s in values:
                        s = s.strip()
                        fields.append(Dimension(col) == s)
                    cond = Filter(type="or", fields=fields)
                else:
                    cond = Dimension(col) == eq
                if op == 'not in':
                    cond = ~cond

elif op in ("in", "not in"):
                fields = []
                # ignore the filter if it has no value
                if not len(eq):
                    continue
                # if it uses an extraction fn, use the "in" operator
                # as Dimension isn't supported
                elif extraction_fn is not None:
                    cond = Filter(
                        dimension=col,
                        values=eq,
                        type="in",
                        extraction_function=extraction_fn,
                    )
                elif len(eq) == 1:
                    cond = Dimension(col) == eq[0]
                else:
                    for s in eq:
                        fields.append(Dimension(col) == s)
                    cond = Filter(type="or", fields=fields)
                if op == "not in":
                    cond = ~cond
            elif op == "regex":
                cond = Filter(
                    extraction_function=extraction_fn,
                    type="regex",
                    pattern=eq,
                    dimension=col,
                )

            # For the ops below, could have used pydruid's Bound,
            # but it doesn't support extraction functions

# Check if this dimension uses an extraction function
                    # If so, create the appropriate pydruid extraction object
                    if isinstance(dim, dict) and "extractionFn" in dim:
                        (col, extraction_fn) = DruidDatasource._create_extraction_fn(
                            dim
                        )
                        dim_val = dim["outputName"]
                        f = Filter(
                            dimension=col,
                            value=row[dim_val],
                            extraction_function=extraction_fn,
                        )
                    elif isinstance(dim, dict):
                        dim_val = dim["outputName"]
                        if dim_val:
                            f = Dimension(dim_val) == row[dim_val]
                    else:
                        f = Dimension(dim) == row[dim]
                    if f:
                        fields.append(f)
                if len(fields) > 1:
                    term = Filter(type="and", fields=fields)
                    new_filters.append(term)
                elif fields:
                    new_filters.append(fields[0])
            if new_filters:
                ff = Filter(type="or", fields=new_filters)
                if not dim_filter:
                    ret = ff
                else:
                    ret = Filter(type="and", fields=[ff, dim_filter])
        return ret

if not len(eq):
                    continue
                # if it uses an extraction fn, use the "in" operator
                # as Dimension isn't supported
                elif extraction_fn is not None:
                    cond = Filter(
                        dimension=col,
                        values=eq,
                        type="in",
                        extraction_function=extraction_fn,
                    )
                elif len(eq) == 1:
                    cond = Dimension(col) == eq[0]
                else:
                    for s in eq:
                        fields.append(Dimension(col) == s)
                    cond = Filter(type="or", fields=fields)
                if op == "not in":
                    cond = ~cond
            elif op == "regex":
                cond = Filter(
                    extraction_function=extraction_fn,
                    type="regex",
                    pattern=eq,
                    dimension=col,
                )

            # For the ops below, could have used pydruid's Bound,
            # but it doesn't support extraction functions
            elif op == ">=":
                cond = Bound(
                    extraction_function=extraction_fn,

if op in ('in', 'not in'):
                    eq = [utils.js_string_to_num(v) for v in eq]
                else:
                    eq = utils.js_string_to_num(eq)
            if op == '==':
                cond = Dimension(col) == eq
            elif op == '!=':
                cond = ~(Dimension(col) == eq)
            elif op in ('in', 'not in'):
                fields = []
                if len(eq) > 1:
                    for s in eq:
                        fields.append(Dimension(col) == s)
                    cond = Filter(type="or", fields=fields)
                elif len(eq) == 1:
                    cond = Dimension(col) == eq[0]
                if op == 'not in':
                    cond = ~cond
            elif op == 'regex':
                cond = Filter(type="regex", pattern=eq, dimension=col)
            if filters:
                filters = Filter(type="and", fields=[
                    cond,
                    filters
                ])
            else:
                filters = cond
        return filters

continue
            col = flt['col']
            op = flt['op']
            eq = flt['val']
            cond = None
            if op in ('in', 'not in'):
                eq = [types.replace("'", '').strip() for types in eq]
            elif not isinstance(flt['val'], basestring):
                eq = eq[0] if len(eq) > 0 else ''
            if col in self.num_cols:
                if op in ('in', 'not in'):
                    eq = [utils.js_string_to_num(v) for v in eq]
                else:
                    eq = utils.js_string_to_num(eq)
            if op == '==':
                cond = Dimension(col) == eq
            elif op == '!=':
                cond = ~(Dimension(col) == eq)
            elif op in ('in', 'not in'):
                fields = []
                if len(eq) > 1:
                    for s in eq:
                        fields.append(Dimension(col) == s)
                    cond = Filter(type="or", fields=fields)
                elif len(eq) == 1:
                    cond = Dimension(col) == eq[0]
                if op == 'not in':
                    cond = ~cond
            elif op == 'regex':
                cond = Filter(type="regex", pattern=eq, dimension=col)
            if filters:
                filters = Filter(type="and", fields=[