//! The operator API is a framework to implement dora operators. //! The implemented operator will be managed by `dora`. //! //! This framework enable us to make optimisation and provide advanced features. //! It is the recommended way of using `dora`. //! //! An operator requires to be registered and implement the `DoraOperator` trait. //! It is composed of an `on_event` method that defines the behaviour //! of the operator when there is an event such as receiving an input for example. //! //! Try it out with: //! //! ```bash //! dora new op --kind operator //! ``` //! #![warn(unsafe_op_in_unsafe_fn)] #![allow(clippy::missing_safety_doc)] pub use dora_arrow_convert::*; pub use dora_operator_api_macros::register_operator; pub use dora_operator_api_types as types; pub use types::DoraStatus; use types::{ arrow::{self, array::Array}, Metadata, Output, SendOutput, }; pub mod raw; #[derive(Debug)] #[non_exhaustive] pub enum Event<'a> { Input { id: &'a str, data: ArrowData }, InputParseError { id: &'a str, error: String }, InputClosed { id: &'a str }, Stop, } pub trait DoraOperator: Default { #[allow(clippy::result_unit_err)] // we use a () error type only for testing fn on_event( &mut self, event: &Event, output_sender: &mut DoraOutputSender, ) -> Result; } pub struct DoraOutputSender<'a>(&'a SendOutput); impl DoraOutputSender<'_> { /// Send an output from the operator: /// - `id` is the `output_id` as defined in your dataflow. /// - `data` is the data that should be sent pub fn send(&mut self, id: String, data: impl Array) -> Result<(), String> { let (data_array, schema) = arrow::ffi::to_ffi(&data.into_data()).map_err(|err| err.to_string())?; let result = self.0.send_output.call(Output { id: id.into(), data_array, schema, metadata: Metadata { open_telemetry_context: String::new().into(), // TODO }, }); result.into_result() } }