import argparse
import os
import json
from typing import Optional
import joblib

from csst_dag import CSST_DAGS, Dispatcher, BaseDAG, dfs


def run_l1_pipeline(
        # data parameters
        dataset:str,
        instrument:Optional[str]=None,
        obs_type:Optional[str]=None,
        obs_group:Optional[str]=None,
        obs_id:Optional[str]=None,
        detector:Optional[str]=None,
        prc_status:Optional[int]=None,
        qc_status:Optional[int]=None,
        # task parameters
        batch_id:Optional[str]="test-batch",
        priority:Optional[str]="1",
        # DAG parameters
        pmapname:Optional[str]="",
        ref_cat:Optional[str]="trilegal_093",
        # submit
        verbose:Optional[bool]=True,
        submit:Optional[bool]=False,
        final_prc_status:Optional[int]=-2,
        force:Optional[bool]=False,
        top_n:Optional[int]=-1,
        # select DAGs
        dags:Optional[list[str]]=None,
        dag_group: Optional[str]="csst-l1-pipeline",
    ):
    """Run a DAG.

    Parameters
    ----------
    dataset : str
        Dataset name
    instrument : Optional[str], optional
        Instrument name, by default None
    obs_type : Optional[str], optional
        Observation type, by default None
    obs_group : Optional[str], optional
        Observation group, by default None
    obs_id : Optional[str], optional
        Observation ID, by default None
    detector : Optional[str], optional
        Detector name, by default None
    prc_status : Optional[int], optional
        Initial processing status, by default None
    qc_status : Optional[int], optional
        Initial QC status, by default None
    batch_id : Optional[str], optional
        Batch ID, by default "test-batch"
    priority : Optional[str], optional
        Task priority, by default "1"
    pmapname : Optional[str], optional
        CCDS pmapname, by default ""
    ref_cat : Optional[str], optional
        Reference catalog, by default "trilegal_093"
    submit : Optional[bool], optional
        Push results, by default False
    final_prc_status : Optional[int], optional
        Final processing status, by default -2
    force : Optional[bool], optional
        Force success, by default False
    verbose : Optional[bool], optional
        Force success, by default False
    top_n : Optional[int], optional
        Submit top N tasks, by default -1
    dags : Optional[list[str]], optional
        DAGs to select, by default None
    dag_group: Optional[str]="csst-l1-pipeline",
        DAG group.
    """

    plan_basis, data_basis = Dispatcher.find_plan_level0_basis(
        dataset=dataset,
        instrument=instrument,
        obs_type=obs_type,
        obs_group=obs_group,
        obs_id=obs_id,
        detector=detector,
        prc_status=prc_status,
        qc_status=qc_status,
    )
    print(f"{len(plan_basis)} plan basis, {len(data_basis)} data basis found")

    # generate DAG group run
    dag_group_run = BaseDAG.gen_dag_group_run(
        dag_group=dag_group,
        batch_id=batch_id,
        priority=priority,
    )

    # generate DAG run list
    print("\n")
    print(">>> Matching DAGs ...")
    dag_run_list = []
    data_id_list = []
    n_dag_run_all = 0
    n_dag_run_success = 0

    DEFAULT_DAGS = {
        "csst-msc-l1-mbi",
        "csst-msc-l1-ast",
        "csst-msc-l1-sls",
        "csst-msc-l1-qc0",
        "csst-msc-l1-ooc",
        "csst-mci-l1-qc0",
        "csst-mci-l1",
        "csst-ifs-l1",
        "csst-cpic-l1-qc0",
        "csst-cpic-l1",
        "csst-hstdm-l1",
    }
    assert dags is None or set(dags).issubset(DEFAULT_DAGS), f"Selected DAGs: {dags}"
    SELECTED_DAGS = DEFAULT_DAGS.intersection(dags) if dags is not None else DEFAULT_DAGS
    print("Selected DAGs: ", SELECTED_DAGS)

    for dag in SELECTED_DAGS:
        this_task_list = CSST_DAGS[dag].schedule(
            dag_group_run=dag_group_run,
            plan_basis=plan_basis,
            data_basis=data_basis,
            pmapname=pmapname,
            ref_cat=ref_cat,
            force_success=force,
        )
        this_dag_run_list = [this_task["dag_run"] for this_task in this_task_list if this_task["dag_run"] is not None]
        this_data_id_list = [this_task["relevant_data_id_list"] for this_task in this_task_list if
                             this_task["dag_run"] is not None]

        dag_run_list.extend(this_dag_run_list)
        data_id_list.extend(this_data_id_list)
        this_n_dag_run_all = len(this_task_list)
        this_n_dag_run_success = len(this_dag_run_list)
        n_dag_run_all += this_n_dag_run_all
        n_dag_run_success += this_n_dag_run_success
        print(f"- `{dag}` : [ {this_n_dag_run_success} / {this_n_dag_run_all} ] dag_runs")

    # print dag_group_run and dag_run_list
    if verbose:
        print("\n")
        print(">>> `dag_group_run` :")
        print(f"\t- {json.dumps(dag_group_run, separators=(',', ':'))}")
        print(f">>> `dag_run_list` : [ {n_dag_run_success} / {n_dag_run_all} ]")
        if len(dag_run_list) > 0:
            for dag_run in dag_run_list:
                try:
                    print(f"\t- {json.dumps(dag_run, separators=(',', ':'))}")
                except:
                    print(f"\t- {dag_run}")

    # dump dag_group_run
    # joblib.dump(
    #     dict(
    #         plan_basis=plan_basis,
    #         data_basis=data_basis,
    #         dag_group_run=dag_group_run,
    #         dag_run_list=dag_run_list,
    #     ),
    #     os.path.join(
    #         os.getenv("HOME"),
    #         "csst_dag",
    #         f"{dag_group_run['dag_group_run']}.joblib",
    #     ),
    # )
    # submit DAG group run
    if submit:
        res = dfs.dag.new_dag_group_run(
            dag_group_run=dag_group_run,
            dag_run_list=dag_run_list,
        )
        print(res)