def run_after_optimization_chord()

in src/backend/entrypoints/llm_backend/tasks.py [0:0]

• 37 lines of code
• 5 McCabe index (conditional complexity)

def run_after_optimization_chord(self, results, pipeline_start_time: int, account_for_dividends: bool):
    current_user = user.get()

    session = session_manager_singleton.get(current_user.email, self.session_id)

    try:
        list_trading_stats_by_symbol, list_strategy_stats = [], []
        for result in results:
            trading_stats_by_symbol, strategy_stats = pickle.loads(result)
            list_trading_stats_by_symbol.append(trading_stats_by_symbol)
            list_strategy_stats.append(strategy_stats)

        trading_statistics = get_combined_trading_statistics(
            session, list_trading_stats_by_symbol, list_strategy_stats, apply_dividends=account_for_dividends
        )

        session.update(trading_statistics)

        session.flow_status.promote_backtesting_step(
            {
                # TODO: safe only if running processes are within the same machine/pod, fine for one celery pod
                "execution_time": time.time()
                - pipeline_start_time,
            }
        )

        session_manager_singleton.save(current_user.email, session)

        payload = {"progress": PUBSUB_END_OF_DATA}
        _safe_progress_publish(
            pubsub=sync_redis_client,
            channel=f"task-{self.request.id}-progress",
            message=json.dumps(payload),
            error_flag=False,
        )

        return FlowStatusResponseModel(
            flow_status=session.flow_status.to_dict(),
        ).model_dump()
    # TODO: handle only specific exceptions in prod
    except (SoftTimeLimitExceeded, LLMBadResponseError, Exception) as e:
        _handle_error(
            session_id=session.session_id,
            email=current_user.email,
            step=Steps.OPTIMIZE,
            exc_to_raise=e,
        )