apply()

template<typename Executor , ComputeData DataType>

template<typename Func >
requires std::invocable<Func, const DataType&>

auto MayaFlux::Yantra::FluentExecutor< Executor, DataType >::apply ( Func &&  func )

inline

Apply a custom transformation function within the chain.

func receives the raw DataType (not the Datum) and returns a value of any ComputeData type. The result is immediately wrapped in a fresh Datum. Container from the current Datum is not carried forward since the function may change the data type entirely; attach a container explicitly via tap() before apply() if it must survive.

Template Parameters

Func	Callable type: (const DataType&) -> U

Parameters

func	Transformation to apply

Returns

New FluentExecutor whose DataType is the return type of func

Definition at line 224 of file OperationChain.hpp.

    {
        if (!m_successful) {
            error<std::runtime_error>(
                Journal::Component::Yantra, Journal::Context::ComputeMatrix,
                std::source_location::current(),
                "Cannot continue chain after failed operation in apply");
        }
 
        using ResultType = std::invoke_result_t<Func, const DataType&>;
 
        try {
            auto result = std::forward<Func>(func)(m_data.data);
            auto next = FluentExecutor<Executor, ResultType>(
                m_executor, Datum<ResultType>(std::move(result)));
            next.m_operation_history = m_operation_history;
            next.m_operation_history.push_back("custom_function");
            return next;
        } catch (const std::exception& e) {
            m_successful = false;
            record_error(std::string("Custom function failed: ") + e.what());
            error_rethrow(
                Journal::Component::Yantra, Journal::Context::ComputeMatrix,
                std::source_location::current(),
                "Exception in custom function: " + std::string(e.what()));
        }
    }