example: datadog_api_client.v2 query_timeseries_data does not work

[bellondr]

Describe the bug
A clear and concise description of what the bug is.
when I run test in
https://github.com/DataDog/datadog-api-client-python/blob/master/examples/v2/metrics/QueryTimeseriesData.py

"""
Query timeseries data across multiple products returns "OK" response
"""

from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.metrics_api import MetricsApi
from datadog_api_client.v2.model.formula_limit import FormulaLimit
from datadog_api_client.v2.model.metrics_data_source import MetricsDataSource
from datadog_api_client.v2.model.metrics_timeseries_query import MetricsTimeseriesQuery
from datadog_api_client.v2.model.query_formula import QueryFormula
from datadog_api_client.v2.model.query_sort_order import QuerySortOrder
from datadog_api_client.v2.model.timeseries_formula_query_request import TimeseriesFormulaQueryRequest
from datadog_api_client.v2.model.timeseries_formula_request import TimeseriesFormulaRequest
from datadog_api_client.v2.model.timeseries_formula_request_attributes import TimeseriesFormulaRequestAttributes
from datadog_api_client.v2.model.timeseries_formula_request_queries import TimeseriesFormulaRequestQueries
from datadog_api_client.v2.model.timeseries_formula_request_type import TimeseriesFormulaRequestType


body = TimeseriesFormulaQueryRequest(
    data=TimeseriesFormulaRequest(
        attributes=TimeseriesFormulaRequestAttributes(
            formulas=[
                QueryFormula(
                    formula="a+b",
                    limit=FormulaLimit(
                        count=10,
                        order=QuerySortOrder.DESC,
                    ),
                ),
            ],
            _from=1730518188595,
            interval=5000,
            queries=TimeseriesFormulaRequestQueries(
                [
                    MetricsTimeseriesQuery(
                        data_source=MetricsDataSource.METRICS,
                        query="avg:system.cpu.user{*}",
                    ),
                ]
            ),
            to=1730604588595,
        ),
        type=TimeseriesFormulaRequestType.TIMESERIES_REQUEST,
    ),
)

API_KEY= 'XXX'
APP_KEY = 'XXX'
configuration = Configuration()
configuration.api_key["apiKeyAuth"] = API_KEY
configuration.api_key["appKeyAuth"] = APP_KEY
configuration.unstable_operations["query_timeseries_data"] = True
with ApiClient(configuration) as api_client:
    api_instance = MetricsApi(api_client)
    response = api_instance.query_timeseries_data(body=body)

    print(response)

return error: {'errors': ['Invalid query input']}

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[wycmiko]

I faced the similar issue while concating a list and pass it :

metric_query_list = []
        for metric_query in metric_queries_list:
            metric_query_list.append(MetricsTimeseriesQuery(
                data_source=MetricsDataSource.METRICS,
                query=metric_query['query'],
                name=metric_query['name'],
            ))

TimeseriesFormulaQueryRequest(
            data=TimeseriesFormulaRequest(
                attributes=TimeseriesFormulaRequestAttributes(
                    formulas=[
                        QueryFormula(
                            formula=fo_expr,
                            limit=FormulaLimit(
                                count=10,
                                order=QuerySortOrder.DESC,
                            ),
                        )
                    ],
                    _from=start_time_ms,
                    interval=864000000,
                    queries=TimeseriesFormulaRequestQueries(metric_query_list), # this line can not correct handle
                    to=current_time_ms,
                ),
                type=TimeseriesFormulaRequestType.TIMESERIES_REQUEST,
            ),
        )

If use code above and submitting the query will get empty response.

If I hard code the list will get the correct response(all query conditions are the same):

      queries=TimeseriesFormulaRequestQueries(
                [
                    MetricsTimeseriesQuery(
                        data_source=MetricsDataSource.METRICS,
                        query="sum:langflow_rag_infer_api_total{http_return_code:200} by {xxx}.as_count().rollup(sum, 60)",
                        name="query3",
                    ),
                    MetricsTimeseriesQuery(
                        data_source=MetricsDataSource.METRICS,
                        query="sum:langflow_rag_infer_api_total{*} by {xxx}.as_count().rollup(sum, 60)",
                        name="query4",
                    ),
                    MetricsTimeseriesQuery(
                        data_source=MetricsDataSource.METRICS,
                        query="sum:langflow_infer_api_total{$xxx, http_return_code:200} by {xxx}.as_count().rollup(sum, 60)",
                        name="query1",
                    ),
                    MetricsTimeseriesQuery(
                        data_source=MetricsDataSource.METRICS,
                        query="sum:xxx{$xxx} by {byoa_app}.as_count().rollup(sum, 60)",
                        name="query2",
                    ),
                ]
            ),

python client version: 2.30.0