use std::sync::Arc;

use super::analytic_unit::types::{AnalyticUnitConfig, PatchConfig};
use super::detection_runner::DetectionRunner;
use super::types::{
    self, AnalyticUnitRF, DetectionRunnerConfig, DetectionRunnerTask, LearningWaiter, HSR,
};
use super::{
    analytic_client::AnalyticClient,
    types::{AnalyticServiceMessage, LearningStatus, RequestType, ResponseType},
};

use crate::config::{AlertingConfig, AlertingType};

use crate::services::analytic_unit_service::AnalyticUnitService;
use crate::services::{
    metric_service::MetricService,
    segments_service::{self, Segment, SegmentType, SegmentsService, ID_LENGTH},
};
use crate::utils::{self};

use crate::services::analytic_service::analytic_unit::types::{AnalyticUnit, LearningResult};

use anyhow;

use chrono::{DateTime, Utc};
use tokio::sync::{mpsc, oneshot};

// TODO: now it's basically single analytic unit, service will operate on many AU
// TODO: trigger anomaly unit model update in runner
pub struct AnalyticService {
    metric_service: MetricService,
    segments_service: SegmentsService,
    analytic_unit_service: AnalyticUnitService,

    alerting: Option<AlertingConfig>,

    analytic_unit: Option<AnalyticUnitRF>,
    analytic_unit_config: AnalyticUnitConfig,
    analytic_unit_learning_status: LearningStatus,

    // TODO: add comment about how it's used
    tx: mpsc::Sender<AnalyticServiceMessage>,
    rx: mpsc::Receiver<AnalyticServiceMessage>,

    // handlers
    learning_handler: Option<tokio::task::JoinHandle<()>>,

    // awaiters
    learning_waiters: Vec<LearningWaiter>,

    detection_runner: Option<DetectionRunner>,
}

impl AnalyticService {
    pub fn new(
        analytic_unit_service: AnalyticUnitService,
        metric_service: MetricService,
        segments_service: segments_service::SegmentsService,
        alerting: Option<AlertingConfig>,
    ) -> AnalyticService {

        // TODO: move buffer size to config
        let (tx, rx) = mpsc::channel::<AnalyticServiceMessage>(32);

        let aus = analytic_unit_service.clone();

        AnalyticService {
            analytic_unit_service: aus,
            metric_service,
            segments_service,

            alerting,

            analytic_unit: None,
            analytic_unit_config: analytic_unit_service.get_active_config().unwrap(),

            analytic_unit_learning_status: LearningStatus::Initialization,
            tx,
            rx,

            // handlers
            learning_handler: None,

            // awaiters
            learning_waiters: Vec::new(),

            detection_runner: None,
        }
    }

    pub fn get_client(&self) -> AnalyticClient {
        AnalyticClient::new(self.tx.clone())
    }

    fn run_learning_waiter(&mut self, learning_waiter: LearningWaiter) {
        // TODO: save handler of the task
        match learning_waiter {
            LearningWaiter::Detection(task) => {
                tokio::spawn({
                    let ms = self.metric_service.clone();
                    let au = self.analytic_unit.as_ref().unwrap().clone();
                    async move {
                        AnalyticService::get_detections(task.sender, au, ms, task.from, task.to)
                            .await
                    }
                });
            }
            LearningWaiter::HSR(task) => {
                tokio::spawn({
                    let ms = self.metric_service.clone();
                    let au = self.analytic_unit.as_ref().unwrap().clone();
                    async move {
                        AnalyticService::get_hsr(task.sender, au, ms, task.from, task.to).await
                    }
                });
            }
            LearningWaiter::DetectionRunner(task) => {
                self.run_detection_runner(task.from);
            }
        }
    }

    fn run_detection_runner(&mut self, from: u64) {
        // TODO: handle case or make it impossible to run_detection_runner second time

        if self.analytic_unit_learning_status != LearningStatus::Ready {
            let task = DetectionRunnerTask { from };
            self.learning_waiters
                .push(LearningWaiter::DetectionRunner(task));
            return;
        }

        let AlertingType::Webhook(acfg) = self.alerting.as_ref().unwrap().alerting_type.clone();
        let drcfg = DetectionRunnerConfig {
            endpoint: acfg.endpoint.clone(),
            interval: self.alerting.as_ref().unwrap().interval,
        };
        let tx = self.tx.clone();
        let au = self.analytic_unit.as_ref().unwrap().clone();
        let dr = DetectionRunner::new(self.metric_service.clone(), tx, drcfg, au);
        self.detection_runner = Some(dr);
        self.detection_runner.as_mut().unwrap().run(from);

        // TODO: rerun detection runner on analytic unit change (by setting analytic unit)
        // if self.runner_handler.is_some() {
        //     self.runner_handler.as_mut().unwrap().abort();
        // }
        // // TODO: save handler of the task
        // self.runner_handler = Some(tokio::spawn({
        //     let au = self.analytic_unit.unwrap();
        //     let ms = self.metric_service.clone();
        //     async move {
        //         // TODO: implement
        //     }
        // }));
    }

    // TODO: maybe make `consume_request` async
    fn consume_request(&mut self, req: types::RequestType) -> () {
        match req {
            RequestType::RunLearning => {
                // TODO: if detection_runner then add it to learning_waiters
                if self.learning_handler.is_some() {
                    self.learning_handler.as_ref().unwrap().abort();
                    self.learning_handler = None;
                }
                self.learning_handler = Some(tokio::spawn({
                    self.analytic_unit_learning_status = LearningStatus::Starting;
                    let tx = self.tx.clone();
                    let aus = self.analytic_unit_service.clone();
                    let ms = self.metric_service.clone();
                    let ss = self.segments_service.clone();
                    let cfg = self.analytic_unit_config.clone();
                    async move {
                        AnalyticService::run_learning(tx, cfg, aus, ms, ss).await;
                    }
                }));
            }
            RequestType::RunDetection(task) => {
                // TODO: signle source of truth: Option<AnalyticUnit> vs LearningStatus
                if self.analytic_unit_learning_status == LearningStatus::Initialization {
                    match task
                        .sender
                        .send(Err(anyhow::format_err!("Analytics in initialization")))
                    {
                        Ok(_) => {}
                        Err(e) => {
                            println!("failed to send error about initialization");
                            println!("{:?}", e);
                        }
                    }
                    return;
                }
                if self.analytic_unit_learning_status == LearningStatus::Ready {
                    self.run_learning_waiter(LearningWaiter::Detection(task));
                } else {
                    self.learning_waiters.push(LearningWaiter::Detection(task));
                }
            }
            RequestType::GetStatus(tx) => {
                tx.send(self.analytic_unit_learning_status.clone()).unwrap();
            }

            // TODO: do it in abstract way for all analytic units
            // RequestType::GetLearningTrain(tx) => {
            //     if self.analytic_unit_learning_results.is_none() {
            //         tx.send(LearningTrain::default()).unwrap();
            //     } else {
            //         tx.send(
            //             self.analytic_unit_learning_results
            //                 .as_ref()
            //                 .unwrap()
            //                 .learning_train
            //                 .clone(),
            //         )
            //         .unwrap();
            //     }
            // }
            RequestType::GetConfig(tx) => {
                tx.send(self.analytic_unit_config.clone()).unwrap();
            }
            RequestType::PatchConfig(patch_obj, tx) => {
                self.patch_config(patch_obj, tx);
            }
            RequestType::GetHSR(task) => {
                if self.analytic_unit.is_some() {
                    self.run_learning_waiter(LearningWaiter::HSR(task));
                } else {
                    self.learning_waiters.push(LearningWaiter::HSR(task));
                }
            }
        };
    }

    // TODO: maybe make `consume_response` async
    fn consume_response(&mut self, res: anyhow::Result<types::ResponseType>) {
        match res {
            Ok(response_type) => {
                match response_type {
                    ResponseType::DetectionRunnerStarted(from) => {
                        println!("Detection runner started from {}", from)
                    }
                    ResponseType::DetectionRunnerUpdate(id, timestamp) => {
                        self.analytic_unit_service.set_last_detection(id, timestamp).unwrap();
                    }
                    ResponseType::LearningStarted => {
                        self.analytic_unit_learning_status = LearningStatus::Learning
                    }
                    ResponseType::LearningFinished(results) => {
                        self.learning_handler = None;
                        self.analytic_unit = Some(Arc::new(tokio::sync::RwLock::new(results)));
                        self.analytic_unit_learning_status = LearningStatus::Ready;

                        // TODO: run tasks from self.learning_waiter
                        while self.learning_waiters.len() > 0 {
                            let task = self.learning_waiters.pop().unwrap();
                            self.run_learning_waiter(task);
                        }
                    }
                    ResponseType::LearningFinishedEmpty => {
                        // TODO: drop all learning_waiters with empty results
                        self.analytic_unit = None;
                        self.analytic_unit_learning_status = LearningStatus::Initialization;
                    }
                }
            }
            // TODO: create custom DatasourceError error type
            Err(err) => {
                self.analytic_unit = None;
                self.analytic_unit_learning_status = LearningStatus::Error(err.to_string());
            }
        }
    }

    fn patch_config(&mut self, patch: PatchConfig, tx: oneshot::Sender<()>) {

        let my_id = self.analytic_unit_service.get_config_id(&self.analytic_unit_config);
        let patch_id = patch.get_type_id();

        println!("my id: {}", my_id);
        println!("patch id: {}", patch_id);

        println!("equals: {}", my_id == patch_id);

        // TODO: update analytic_unit config if some
        // TODO: save updated
        // TODO: run learning when different
        // TODO: run learning when it's necessary
    

        match tx.send(()) {
            Ok(_) => {}
            Err(_e) => {
                println!("Can`t send patch config notification");
            }
        }


        
    }

    pub async fn serve(&mut self) {
        // TODO: remove this hack
        self.consume_request(RequestType::RunLearning);
        if self.alerting.is_some() {
            // TODO: get it from persistance
            let now: DateTime<Utc> = Utc::now();
            let from = now.timestamp() as u64;
            self.run_detection_runner(from);
        }

        while let Some(message) = self.rx.recv().await {
            match message {
                AnalyticServiceMessage::Request(req) => self.consume_request(req),
                AnalyticServiceMessage::Response(res) => self.consume_response(res),
            }
        }
    }

    async fn run_learning(
        tx: mpsc::Sender<AnalyticServiceMessage>,
        aucfg: AnalyticUnitConfig,
        aus: AnalyticUnitService,
        ms: MetricService,
        ss: SegmentsService,
    ) {
        let mut au = match aus.resolve(&aucfg) {
            Ok(a) => a,
            Err(e) => { panic!("{}", e); }
        };

        match tx
            .send(AnalyticServiceMessage::Response(Ok(
                ResponseType::LearningStarted,
            )))
            .await
        {
            Ok(_) => {}
            Err(_e) => println!("Fail to send learning started notification"),
        }

        // TODO: maybe to spawn_blocking here
        let lr = match au.learn(ms, ss).await {
            Ok(res) => match res {
                LearningResult::Finished => Ok(ResponseType::LearningFinished(au)),
                LearningResult::FinishedEmpty => Ok(ResponseType::LearningFinishedEmpty),
            },
            Err(e) => Err(e),
        };

        match tx.send(AnalyticServiceMessage::Response(lr)).await {
            Ok(_) => {}
            Err(_e) => println!("Fail to send learning results"),
        }
    }

    async fn get_detections(
        tx: oneshot::Sender<anyhow::Result<Vec<Segment>>>,
        analytic_unit: AnalyticUnitRF,
        ms: MetricService,
        from: u64,
        to: u64,
    ) {
        // It's important that we don't drop read() lock until end
        // because there mght be attempt to make .write() with setting new config
        let result = analytic_unit
            .read()
            .await
            .detect(ms, from, to)
            .await
            .unwrap();

        let result_segments: Vec<Segment> = result
            .iter()
            .map(|(p, q)| Segment {
                from: *p,
                to: *q,
                id: Some(utils::get_random_str(ID_LENGTH)),
                segment_type: SegmentType::Detection,
            })
            .collect();

        match tx.send(Ok(result_segments)) {
            Ok(_) => {}
            Err(_e) => {
                println!("failed to send results");
            }
        }
        return;
    }

    async fn get_hsr(
        tx: oneshot::Sender<anyhow::Result<HSR>>,
        analytic_unit: AnalyticUnitRF,
        ms: MetricService,
        from: u64,
        to: u64,
    ) {
        let hsr = analytic_unit
            .read()
            .await
            .get_hsr(ms, from, to)
            .await
            .unwrap();

        match tx.send(Ok(hsr)) {
            Ok(_) => {}
            Err(_e) => {
                println!("failed to send results");
            }
        }
    }
}